Oblique line scanner system and method for high-throughput single-molecule tracking in living cells

Abstract

A high-throughput single-molecule tracking (htSMT) system and method is described, and the htSMT workflow is adapted to characterize the contributions of both known and novel pathways to interaction networks in living cells, such as protein signaling interaction networks.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Application No. 63 / 476,953, filed December 22, 2022, and U.S. Provisional Application No. 63 / 476,942, filed December 22, 2022, the entire contents of each of which are incorporated herein by reference.

[0002] The subject matter described herein relates to a platform for tracking single molecules in complex systems. [Background technology]

[0003] Protein movement within the dense environment of living cells is strongly influenced by interactions with its surroundings. Single-molecule tracking (SMT) is one method for capturing protein movement as a reporter of activity. In SMT, fluorescent proteins of interest are imaged with high spatiotemporal resolution to track their movement within complex systems, such as living cells. The information embedded in these traces has been used to investigate diverse cellular phenomena, including protein-protein interactions, such as those mediating signal transduction, interorganelle communication, nuclear organization, and transcriptional regulation. However, the application of SMT technology is limited in scale and has primarily been used to address specific mechanistic hypotheses. For example, SMT is not amenable to throughput settings that enable systems-level screening or drug discovery. Summary of the Invention

[0004] In a first aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being capable of inducing a change in the K of the target fluorescent protein. offthe method further comprises (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of view in the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method adapted to selectively detect localized fluorescence; and (c) determining a change in the movement of the target fluorescent protein in the presence of the compound, wherein an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound reduces the K of the target fluorescent protein. off This indicates that it induces a decrease in

[0005] In a related aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being a compound that induces a change in binding of the target fluorescent protein. offThe present invention is directed to a method for determining whether a compound reduces a target fluorescent protein in a plurality of cells, the method comprising: (a) contacting a sample comprising a population of living cells with a compound, the living cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam so as to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells, the subset of target fluorescent proteins generating and tracking up to about 1,000,000 molecular trajectories within a single detection field. further comprising (ii) detecting, via the detector device, fluorescence from one or more of the target fluorescent proteins within a detection field at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence, the method further comprising (c) determining a change in the movement of the target fluorescent protein in the presence of a compound, wherein an increase in the signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K off This indicates that it induces a decrease in

[0006] In a related aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being a compound that induces a change in binding of the target fluorescent protein. offthe method further comprises (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of view in the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method adapted to selectively detect localized fluorescence compared to dynamic fluorescence, the method further comprising: (c) determining a change in the movement of the target fluorescent protein in the presence of the compound, wherein an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound reduces the K of the target fluorescent protein. off This indicates that it induces a decrease in

[0007] In a related aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being a compound that induces a change in binding of the target fluorescent protein. offThe present invention is directed to a method for determining whether a compound reduces the activity of one or more of the target fluorescent proteins in a sample, the method comprising: (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to induce fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of the sample plane. and detecting the target fluorescent protein, wherein the detection field has a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and 95% or more of the detection field achieves sufficient laser illumination to track protein movement; the method is adapted to selectively detect localized fluorescence; and the method further includes (c) determining a change in movement of the target fluorescent protein in the presence of a compound, wherein an increase in the signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K off This indicates that it induces a decrease in

[0008] In certain instances of the above embodiment, the detected change in motion is indicative of the binding state (f bound) is an increase in immobile trajectories, indicating an increase in occupancy or duration of the target fluorescent protein. In certain cases of the above aspects, the detected change in motion is a change in (a) the median of the jump length distribution, (b) the third quartile of the jump length distribution, (c) the median radius of gyration, (d) the mean posterior diffusion coefficient, (e) the geometric mean posterior diffusion coefficient, (f) the mean squared displacement, (g) the median bond angle, (h) the maximum likelihood estimator of the diffusion coefficient, and / or (i) the inferred state occupancy. In certain cases of the above aspects, the target fluorescent protein interacts within a larger molecular assembly. In certain cases of the above aspects, the target fluorescent protein is a ligand. In certain cases of the above aspects, the target fluorescent protein is a receptor. In certain cases of the above aspects, the biological interaction is a direct interaction. In certain cases of the above aspects, the direct interaction includes binding of a compound to the target fluorescent protein. In certain cases of the above aspects, the biological interaction is an indirect interaction. In certain instances of the above embodiments, the indirect interaction involves the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

[0009] In a related aspect, the present disclosure provides a method for determining the dose of a compound that induces a change in binding of a target fluorescent protein in a living cell, based on the K offthe compound determines a dose by determining whether the compound reduces the K of the target fluorescent protein, the method comprising: (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of view in the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm). The method is adapted to selectively detect localized fluorescence. The method further comprises: (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound; and determining whether the compound reduces the K of the target fluorescent protein by determining whether the compound reduces the K of the target fluorescent protein by determining whether the compound reduces the K of the target fluorescent protein. off This indicates that it induces a decrease in

[0010] In a related aspect, the present disclosure provides a method for determining the dose of a compound that induces a change in binding of a target fluorescent protein in a living cell, based on the K offThe present invention is directed to a method for determining whether a compound reduces the activity of a living cell, the method comprising: (a) contacting a sample comprising a population of living cells with a compound, the living cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam so as to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells, the subset of target fluorescent proteins generating up to about 1,000,000 molecular trajectories within a single detection field; and (ii) detecting, via the detector device, fluorescence from one or more of the target fluorescent proteins within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence. The method further includes (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound, wherein an increase in the signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K off This indicates that it induces a decrease in

[0011] In a related aspect, the present disclosure provides a method for determining the dose of a compound that induces a change in binding of a target fluorescent protein in a living cell, based on the K offthe compound determines a dose by determining whether the compound reduces the K of the target fluorescent protein, the method comprising: (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of view in the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm). The method is adapted to selectively detect localized fluorescence. The method further comprises: (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound; and determining whether the compound reduces the K of the target fluorescent protein by determining whether the compound reduces the K of the target fluorescent protein by determining whether the compound reduces the K of the target fluorescent protein. off This indicates that it induces a decrease in

[0012] In a related aspect, the present disclosure provides a method for determining the dose of a compound that induces a change in binding of a target fluorescent protein in a living cell, based on the K offthe living cells comprise a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of the sample plane. and (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of a compound, wherein an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K of the target fluorescent protein. off This indicates that it induces a decrease in

[0013] In certain instances of the above embodiment, the detected change in motion is determined by the coupling (f bound) an increase in immobile trajectories indicative of an increase in the target fluorescent protein. In certain cases of the above aspects, the detected change in motion is a change in (a) the median of the jump length distribution, (b) the third quartile of the jump length distribution, (c) the median radius of gyration, (d) the mean posterior diffusion coefficient, (e) the geometric mean posterior diffusion coefficient, (f) the mean squared displacement, (g) the median bond angle, (h) the maximum likelihood estimator of the diffusion coefficient, and / or (i) the inferred state occupancy. In certain cases of the above aspects, the target fluorescent protein interacts within a larger molecular assembly. In certain cases of the above aspects, the target fluorescent protein is a ligand. In certain cases of the above aspects, the target fluorescent protein is a receptor. In certain cases of the above aspects, the biological interaction is a direct interaction. In certain cases of the above aspects, the direct interaction includes binding of a compound to the target fluorescent protein. In certain cases of the above aspects, the biological interaction is an indirect interaction. In certain instances of the above embodiments, the indirect interaction involves the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

[0014] In a related aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being a compound that induces a change in binding of the target fluorescent protein. offThe present invention relates to a microscope system configured to determine whether a compound reduces the movement of the target fluorescent proteins, the microscope system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a target fluorescent protein; the microscope system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, wherein a subset of the target fluorescent proteins in the sample are positioned within a detection field of view at the plane of the sample, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm); the microscope system further including: (d) a detector device for monitoring the light-based response from the target fluorescent proteins in the presence of a compound; (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound.

[0015] In a related aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being a compound that induces a change in binding of the target fluorescent protein. off The present invention relates to a microscope system configured to determine whether a compound reduces the movement of a target fluorescent protein, the microscope system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a target fluorescent protein; the microscope system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a sample plane, wherein a subset of the target fluorescent proteins in the sample are positioned within a detection field of view at the sample plane, the subset of target fluorescent proteins generating up to about 1,000,000 molecular trajectories within a single detection field of view, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm); the microscope system further including: (d) a detector device for monitoring the light-based response from the target fluorescent proteins in the presence of a compound; (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound.

[0016] In a related aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being a compound that induces a change in binding of the target fluorescent protein. off The present invention relates to a microscope system configured to determine whether a compound reduces the movement of the target fluorescent proteins, the microscope system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a target fluorescent protein; the microscope system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, wherein a subset of the target fluorescent proteins in the sample are positioned within a detection field of view at the plane of the sample, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm); the microscope system further including: (d) a detector device for monitoring the light-based response from the target fluorescent proteins in the presence of a compound; (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound compared to the absence of the compound.

[0017] In a related aspect, the present disclosure provides a compound that induces a change in binding of a target fluorescent protein in a living cell, the compound being a compound that induces a change in binding of the target fluorescent protein. offThe present invention relates to a microscope system configured to determine whether a compound reduces the activity of a target fluorescent protein, the microscope system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a target fluorescent protein; the microscope system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a sample plane, wherein a subset of the target fluorescent proteins in the sample are positioned within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and 95% or more of the detection field achieves laser illumination sufficient to track protein movement; and the microscope system further includes: (d) a detector device for monitoring the light-based response from the target fluorescent proteins in the presence of a compound; (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound.

[0018] In certain instances of the above embodiment, the detected change in motion is determined by the coupling (f bound) an increase in immobile trajectories indicative of an increase in the target fluorescent protein. In certain cases of the above aspects, the detected change in motion is a change in (a) the median of the jump length distribution, (b) the third quartile of the jump length distribution, (c) the median radius of gyration, (d) the mean posterior diffusion coefficient, (e) the geometric mean posterior diffusion coefficient, (f) the mean squared displacement, (g) the median bond angle, (h) the maximum likelihood estimator of the diffusion coefficient, and / or (i) the inferred state occupancy. In certain cases of the above aspects, the target fluorescent protein interacts within a larger molecular assembly. In certain cases of the above aspects, the target fluorescent protein is a ligand. In certain cases of the above aspects, the target fluorescent protein is a receptor. In certain cases of the above aspects, the biological interaction is a direct interaction. In certain cases of the above aspects, the direct interaction includes binding of a compound to the target fluorescent protein. In certain cases of the above aspects, the biological interaction is an indirect interaction. In certain instances of the above embodiments, the indirect interaction involves the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

[0019] This patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. [Brief explanation of the drawings]

[0020] [Figure 1] A schematic diagram of the htSMT workflow is shown. [Figure 2A] 1 illustrates an exemplary image acquisition system of the present disclosure, showing the XZ sample plane. [Figure 2B] 1 illustrates an exemplary image acquisition system of the present disclosure, with the YZ sample plane visible. [Figure 2C] 1 illustrates an exemplary image acquisition system of the present disclosure, showing the XZ sample plane. [Figure 2D] 1 illustrates an exemplary image acquisition system of the present disclosure, with the YZ sample plane visible. [Figure 2E]Details of the light beam compared to the HILO-based approach (OLS on the left, HILO on the right). [Figure 2F] An example of incorporating a camera roll shutter is shown below. [Figure 3A] Figure 1 shows various measurements demonstrating that the disclosed image acquisition system and workflow are suitable for robust htSMT analysis. A laser titration experiment showing the relationship between laser power (mW) at the sample and signal-to-noise ratio (SNR) (left panel) and the average SNR at the well level across four image acquisition systems measuring six different 384-well plates per system (right panel). [Figure 3B] Figure 1 shows various measurements demonstrating the suitability of the disclosed image acquisition system and workflow for robust htSMT analysis. The difference in spatial SNR heterogeneity between the disclosed OLS system and a HILO-based approach is shown. The top panel compares the spatial standard deviation observed with OLS to a HILO-based approach. The bottom panel shows the difference in FOV between the HILO-based and OLS-based approaches (left image) and a comparison of spatial heterogeneity across the FOV for the HILO-based approach (center image) and the OLS-based approach (right image). [Figure 3C] Figure 1 shows various measurements demonstrating that the disclosed image acquisition system and workflow are suitable for robust htSMT analysis. Dose-response experiments performed on Halo-tagged proteins using established and well-characterized compounds to assess plate-to-plate and day-to-day reproducibility are shown (top panel) with the respective EC50s presented (bottom panel). [Figure 3D] Various measurements are shown demonstrating that the image acquisition system and workflow of the present disclosure are suitable for robust htSMT analysis. The system described herein is configured to capture comparable protein diffusion coefficients per FOV per well, with each point representing an individual FOV position averaged per plot for each concentration (top panel), and both EC50 and Z-factor are presented (bottom panel). [Figure 3E]Various measurements are shown demonstrating that the disclosed image acquisition system and workflow are suitable for robust htSMT analysis. Data consistency across multiple wells and multiple experiments is demonstrated, with each point representing one FOV from 14 independently generated dose-response curves. [Figure 4] A comparison of the Z-factors associated with the data presented in Figures 3D and 3E and data collected using a HILO-based approach is shown. [Figure 5] 1 shows a schematic diagram of an exemplary sample handling system of the present disclosure. [Figure 6] An exemplary system for a high-throughput single-molecule imaging platform for measuring protein movement in live cells is shown. [Figure 7] FIG. 1 illustrates data flow through an exemplary system for a high-throughput single-molecule imaging platform that measures protein movement in living cells. [Figure 8] 1 shows a number of images illustrating the difference between a mask category and an instance mask or a semantic mask. [Figure 9] 1 illustrates an exemplary computer-implemented environment relevant to the subject matter described herein. [Figure 10] FIG. 1 illustrates a sample computing device architecture for implementing various aspects described herein. [Figure 11A] We demonstrate that OLS provides uniform illumination over nearly the entire field of view, enabling extended SMT. A simplified schematic illustrating an embodiment of an OLS is shown. Briefly, a collimated beam is shaped into an optical light sheet, which is directed into a water immersion objective, and the emitted light is projected onto a high-speed sCMOS camera. [Figure 11B]We demonstrate that OLS provides uniform illumination across nearly the entire field of view, enabling extended SMT. We demonstrate an exemplary SMT workflow that relies on Halo tagging of protein targets of interest. Using JF549 or JF646 organic fluorophores, we detected individual emitters with the appropriate signal, performed interframe stitching, and tracked generation. From these coordinates and trajectories, various metrics can be extracted, including protein diffusion and spatial localization, among others. [Figure 11C] This demonstrates that OLS provides uniform illumination across nearly the entire field of view, enabling extended SMT. The results of HIF ablation on rod and cone cell survival and function are shown. This shows 20-point dose-response curves from six to seven different 384-well plates per microscope, imaged on Eikon's high-throughput SMT platform. 72 FOV from 12 wells were captured for each concentration on randomized plates, and error bars indicate standard deviation. [Figure 11D] This shows that OLS provides uniform illumination across nearly the entire field of view, enabling extended SMT. Representative sampling areas in HILO and OLS for illumination from Halo-Keap1 containing U2OS cells are shown. Trajectories were plotted over a 1.5-second acquisition and color-coded based on the measured diffusion coefficients, with the nuclear mask outline overlaid with a black dotted line. [Figure 11E] We show that OLS provides uniform illumination across almost the entire field of view, enabling extended SMT. We show quantification of the number of trajectories captured per FOV using HILO and OLS, with OLS capturing a 6x improvement. [Figure 11F] We demonstrate that OLS provides uniform illumination across nearly the entire field of view, enabling extended SMT. Representative average spatial SNR maps per pixel calculated across a 1,232 FOV are shown for plates imaged with HILO or OLS. OLS provides a 6x larger FOV while improving illumination uniformity. [Figure 11G]Figure 1 shows that the OLS provides uniform illumination across nearly the entire field of view, enabling extended SMT. Figure 2 provides the standard deviation of the mean FOV level in SNR sampled across 308 wells. [Figure 12]Figures A-F show exemplary schematics of an OLS microscope for single-molecule tracking. Figure A shows an exemplary schematic of an OLS microscope based on scanning a tilted excitation light sheet using a galvanometric scanning mirror across a sample placed inside an inverted microscope. The OLS microscope is based on multiwavelength optical excitation provided by a laser engine module (LEM) and coupled to a beam shaper by a collimator-coupled single-mode fiber. The beam shaper converts the incident Gaussian-shaped optical excitation into an optical light sheet, which is focused along the line axis of the light sheet onto the back focal plane of the microscope objective and scanned along the scan axis using a galvanometric mirror. The resulting oblique light sheet is immersion-coupled and delivered to an environmentally controlled sample-holding plate, while the relative position of the microscope's focal plane is controlled by an autofocus unit. The excitation fluorescence is spectrally filtered from the excitation light by a dichroic filter and an absorption filter and projected onto a high-speed sCMOS camera. Synchronization of optical excitation, scanning, and acquisition is achieved by a custom-built control unit (MIC). Figure 1B shows an example schematic of an autofocus unit based on detecting the 780 nm LED reflection on the top surface of the sample-holding glass bottom and repositioning the objective lens to ensure proper focal plane positioning within the sample. Figure 1C shows an example schematic of an optical confocal scanning mode achieved by scanning a tilted and focused light sheet through the focal plane of the objective lens. Background suppression is achieved by confocal placement of the tilted light sheet (green), the depth of field of the objective lens, and synchronous rolling shutter detection (orange). Figure 1D shows an example schematic of a beam-shaping subassembly that shapes the collimated optical excitation into a light sheet by a series of Powell, cylindrical, spherical, and plano-convex lenses projected along the line axis (x) and scan axis (y) before encountering a galvanometric scanning mirror. The inset shows the optical beam profile at each position.(E) shows an exemplary schematic of an optical line-scanning framework based on a tilted light sheet in the sample plane, achieved by focusing the optical excitation along the line axis of the back focal plane of the objective and positioning the optical excitation along the scan axis at an offset position relative to the optical axis of the objective. Corresponding detections of the optically aligned fluorescence are projected onto the camera sensor. (F) shows an exemplary schematic of an OLS acquisition mode that relies on detecting fluorescence by matching the area of ​​the camera's exposure pixels and synchronizing the camera's rolling shutter to the optically projected intensity line of the fluorescence excited by the tilted light sheet. [Figure 13A] Characterization of motion-induced blur and confocality between OLS and HILO illumination is shown. A bar graph comparing the measured diffusion coefficients of Halo-KEAP1 treated with DMSO or 1 mM KI-696 across 72 FOVs from 12 individual wells for HILO and OLS. Despite extensive sampling, the standard deviation of the measurements is still larger for HILO. [Figure 13B] Characterization of motion-induced blur and confocality between OLS and HILO illumination is shown. Estimated point spread functions (PSFs) were determined by averaging all detections over a representative 150-frame acquisition. For each condition, the following numbers of PSFs were detected: n = 123,596 (OLS-DMSO), n = 3,897 (HILO-DMSO), n = 113,276 (OLS 0.33 mM KI-696), and n = 13,620 (HILO 0.33 mM KI-696) from one representative FOV. [Figure 13C] Characterization of motion-induced blur and confocality between OLS and HILO illumination. PSF detection is shown as a function of integration time. HILO required five times longer integration time to achieve comparable PSF detection and spot density as OLS, resulting in more pronounced motion-induced blur with HILO. [Figure 13D]Figure 1 shows characterization of motion-induced blur and confocality between OLS and HILO illumination. Figure 2 shows PSF width measurements as a function of JF549 measured in Halo-KEAP1 cells treated with 1 mM KI-696. [Figure 13E] Figure 1 shows the characterization of motion-induced blur and confocality between OLS and HILO illumination. Figure 2 shows the average SNR plotted as a function of JF549 measured in Halo-KEAP1 cells treated with 1 mM KI-696. [Figure 13F] Figure 1 shows the characterization of motion-induced blurring and confocality between OLS and HILO illumination. Figure 2 shows the number of spot detections plotted as a function of JF549 measured at increasing concentrations of Halo-JF549 in solution. [Figure 14A] This demonstrates that OLS enables reproducible and robust SMT measurements. EC50 values ​​calculated from each dose-response curve averaged per plate per microscope are shown. The black line represents the median EC50. [Figure 14B] We demonstrate that OLS enables reproducible and robust SMT measurements. Figure 1 shows violin plots of signal-to-noise ratio (SNR) for each microscope, with the thick dashed line representing the median. [Figure 14C] Figure 1 shows that OLS enables reproducible and robust SMT measurements. Violin plot of SNR as a function of FOV position within an acquired well. [Figure 14D] This demonstrates that OLS enables reproducible and robust SMT measurements. A 20-point dose-response curve for Halo-KEAP1U2OS sampled in a full OLS FOV (purple) and a cropped 768 x 768 pixel FOV (black) representing a HILO-sized FOV. Error bars indicate standard deviation across FOVs. [Figure 15A]We demonstrate that OLS enables the capture of fast protein diffusion in live cells. Representative images of different FOV sizes for each of five frame rates ranging from 100 to 1250 Hz are shown. Trajectories are superimposed on the average projection of the Hoechst channel (blue) and colored by their maximum likelihood diffusion coefficient. [Figure 15B] We demonstrate that OLS enables the capture of fast protein diffusion in live cells. Figure 1 shows the fraction of trajectories with diffusion coefficients greater than 10 mm / s as a function of frame rate for DMSO- and KI-696-treated cells, calculated from the posterior mean occupancy of state sequences. [Figure 15C] We demonstrate that OLS enables the capture of fast protein diffusion in live cells. We demonstrate the accuracy of state profile recovery from optical dynamic simulations of SMT across several frame rates for three different state mixtures. Error bars indicate standard deviation. [Figure 16] A-E show that the frame rate determines the dynamic range of SMT. A shows a schematic illustrating the role of localization and tracking errors for a hypothetical fast-moving protein. The rolling shutter of the OLS captures the position of a dye molecule at separate time points. If these time points are too close, the apparent motion is dominated by localization errors. If the time points are too far apart, the trajectory becomes difficult to reconstruct and is dominated by incorrect connections. B shows that the frame rate determines the dynamic range of SMT. A shows a schematic illustrating the dynamic range of SMT, which is limited on the one hand by localization errors and on the other by tracking errors. An approximation of this range for Brownian motion is

number

[0021] The subject matter of this disclosure relates to industrial-scale high-throughput SMT (htSMT) techniques using oblique line scanning (OLS) illumination, systems incorporating such OLS htSMT techniques, hardware and software developments related to such OLS htSMT techniques, and methods of using such OLS htSMT techniques. For example, the OLS htSMT techniques described herein are capable of measuring protein motion in millions of cells per day. In addition to the ability to capture a large number of cells per field of view, OLS offers advantages such as improved spatial uniformity of the signal-to-noise ratio (SNR) across the camera chip, improved confocality (fewer out-of-focus signals and reduced motion blur), and improved temporal resolution, as shown, for example, in Table 1 (each "+" represents a 2x improvement). [Table 1]

[0022] The OLS htSMT technology described herein can be used for a variety of applications, including, but not limited to, drug discovery activities such as screening compound libraries and elucidating structure-activity relationships (SAR). Importantly, the OLS htSMT technology described herein can be used to characterize the contributions of both known and novel pathways to larger molecular assemblies that contain targets, such as protein signaling interaction networks.

[0023] 1 , aspects of the present subject matter can be implemented using an OLS htSMT workflow, which can include various stages, such as (i) sample preparation, including reagent handling, (ii) image acquisition using imaging of the sample to generate a series of images and / or videos, (iii) image analysis, for example, using various analytics, single emitter detection and sub-pixel localization (i.e., "super-resolution imaging"), tracking, computer vision, and machine learning algorithms to process these images and videos, (iv) storage of information extracted from or characterizing or constituting the images and videos (i.e., features, raw images, modified images, etc.), and (v) providing insights using the stored information, including biological interpretations (which can additionally or alternatively be provided using various analytics, tracking, computer vision, and machine learning algorithms), as described in more detail below.

[0024] The subject matter of the present disclosure will be described with reference to the figures, wherein reference numerals are used to denote like or equivalent elements throughout. The figures are not drawn to scale and are provided solely to illustrate aspects disclosed herein. Certain disclosed aspects are described below with reference to illustrative example hardware, software, and applications. It should be understood that numerous specific details, relationships, and methods are set forth to provide a more thorough understanding of the subject matter disclosed herein. For clarity of disclosure, and not for purposes of limitation, the detailed description is divided into the following subsections. 1.Definition 2.OLS htSMT hardware 3.OLS htSMT software 4. Specific OLS htSMT Applications 5. Exemplary Embodiments 6. Working Example

[0025] 1.Definition Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. In the case of conflict, the present document, including definitions, will control. Preferred methods and materials are described below; however, methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the subject matter of this disclosure. All publications, patent applications, patents, and other references mentioned herein are incorporated herein by reference in their entirety. The materials, methods, and examples disclosed herein are illustrative only and are not intended to be limiting.

[0026] The terms "comprise," "include," "having," "has," "can," "contain," and variations thereof, as used herein, are intended to be open-ended transitional phrases, terms, or phrases that do not exclude the possibility of additional acts or structures. The singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. The present disclosure also contemplates other instances of "comprising," "consisting of," and "consisting essentially of" the instances or elements presented herein, whether explicitly stated or not.

[0027] In reciting numerical ranges herein, each intervening number in the range is expressly contemplated with the same precision. For example, in the range 6 to 9, the numbers 7 and 8 are contemplated in addition to 6 and 9, and in the range 6.0 to 7.0, the numbers 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, and 7.0 are expressly contemplated.

[0028] As used herein, the term "about" or "approximately" means within an acceptable error range for a particular value as determined by those skilled in the art, which depends in part on the method of measuring or determining the value, i.e., the limitations of the measurement system. For example, "about" can mean within 3 or more standard deviations, according to the practice in the art. Alternatively, "about" can mean a range of up to 20%, preferably up to 10%, more preferably up to 5%, and even more preferably up to 1% of a given value. Alternatively, particularly with respect to biological systems or processes, this term can mean within an order of magnitude, preferably within 5 times, more preferably within 2 times of a value.

[0029] As used herein, the term "trajectory" refers to a set of spatial coordinates corresponding to the observed positions of fluorescent proteins linked in time. In certain cases, multiple trajectories can be constructed algorithmically by linking multiple fluorescent proteins whose positions have been determined at successive time points. In certain cases, multiple trajectories can be constructed conservatively by linking only spots within a fixed search radius when other links are not valid. In certain cases, multiple trajectories can be constructed probabilistically.

[0030] As defined herein, protein motion refers to changes in the positions of multiple fluorescent proteins. In certain cases, protein motion can be quantified by analyzing changes in spatial coordinates at successive time points. Motion characterized in this way can include, but is not limited to, measuring the distribution of jump lengths. That is, given a set of protein displacements between one time point and a subsequent time point, a histogram of the probability of each displacement length ("jump length") can be constructed. Quantiles of this distribution can be used to describe protein motion. In certain cases, the quantile used is the median of the jump length distribution. In certain cases, the quantile used is the third quartile of the jump length distribution. In certain cases, protein motion can be quantified by analyzing trajectories. Motion characterized in this way can include, but is not limited to, measurements of mean square displacement, defined as the mean value of the squares of all displacements within a trajectory, averaged over multiple trajectories. Motion characterized in this way can also include, but is not limited to, measurements of trajectory length or measurements of the distribution of trajectory lengths. Such characterized motion may include, but is not limited to, measurements of the average radius of gyration, defined by the root-mean-square distance of all coordinates on a trajectory from the center of mass of the set of points included in the trajectory, averaged over multiple trajectories. Such characterized motion may also include, but is not limited to, measurements of the average bond angle, defined by the angle formed from three consecutive spatial coordinates averaged over multiple trajectories. Such characterized motion may also include, but is not limited to, measurements of the maximum likelihood diffusion coefficient estimate, defined as the maximum likelihood diffusion coefficient estimate for multiple trajectories under a single-state diffusion model with a constant localization error. In certain cases, protein motion may be measured through analysis of the products of a link generation algorithm. Such characterized motion may include, but is not limited to, the mean posterior diffusion coefficient, the average of the posterior probability distribution of coefficients from a probabilistic linkage algorithm. Such characterized motion may include, but is not limited to, the geometric mean posterior diffusion coefficient, the average of the log-scaled posterior probability distribution of coefficients from a probabilistic linkage algorithm.In certain cases, protein motion can be measured through model-dependent analysis of multiple trajectories. Motion characterized in this way is the fraction of immobile molecules ("f") defined by two-state model fitting. bound ") may include, but is not limited to:

[0031] As used herein, the term "motion" encompasses not only changes in the direction in which a target moves, but also both increases and decreases in the speed of movement. Thus, tracking motion may, in certain cases, include determining that a target is not moving, e.g., determining that the target is in a statically constrained state or an essentially statically constrained state. Motion can be characterized in various ways, including, but not limited to, quantifying (a) the median of the jump length distribution (where the jump length corresponds to the observed distance traveled by the target's fluorescent protein in successive frames), (b) the third quartile of the jump length distribution, (c) the median radius of gyration, (d) the mean posterior diffusion coefficient, (e) the geometric mean posterior diffusion coefficient, (f) the mean squared displacement, (g) the median bond angle, (h) the maximum likelihood estimator of the diffusion coefficient, (i) the trajectory length, and / or (j) the inferred state occupancy.

[0032] As used herein, detected movement includes, but is not limited to, any change in movement, which may occur in response to any environmental or other factor. For example, but not limited to, movement, or lack thereof, may be caused by (A) the addition of a compound, (B) a change in temperature, (C) a change in oxygen concentration, e.g., the introduction of hypoxia, (D) mechanical stress, (E) a change in pH, and / or (F) a change in light exposure (e.g., an increase or decrease in intensity).

[0033] As used herein, the term "fluorescent protein" refers to any protein that emits a fluorescent signal. In certain cases, the fluorescent emission occurs in response to irradiation with light of a specific wavelength. An example of a naturally occurring fluorescent protein is green fluorescent protein (GFP). However, in certain cases, a protein of interest can be adapted to emit a fluorescent signal through the introduction of an encoded fluorescent tag. That is, a protein sequence is fused to the protein of interest to make it fluorescent. In certain cases, a protein of interest can be adapted to emit a fluorescent signal through the binding of a fluorescent ligand. Non-limiting examples of such encoded fluorescent tags include Halo tag, SNAP tag, CLIP tag, TMP tag, and SunTag. Additionally or alternatively, a protein of interest can be adapted to emit a fluorescent signal by binding to a fluorescent dye molecule, such as an amine-reactive dye or a sulfhydryl-reactive dye.

[0034] As used herein, the term "compound" refers to any chemically defined entity. In certain cases, a compound may be a molecule less than 1000 Da, i.e., a "small molecule." In certain cases, a compound may be a macromolecule, such as a nucleic acid. In certain cases, a nucleic acid may have a defined sequence. In certain cases, a nucleic acid includes (A) ribonucleic acid (RNA) (e.g., including modified RNA), (B) deoxyribonucleic acid (DNA) (e.g., including modified DNA), and (C) a combination of (A) and (B). In certain cases, a nucleic acid is a single- or double-stranded small interfering nucleic acid (e.g., double-stranded siRNA), an antisense oligonucleotide, a ribozyme, a microRNA, or an aptamer. In certain cases, a compound may be a protein. For example, and not by way of limitation, protein compounds of the present disclosure include signaling proteins, such as protein hormones, cytokines, kinases, phosphatases, and other enzymes and transcription factors, as well as antibodies, contractile proteins, structural proteins, storage proteins, and transport proteins. In certain cases, a compound can refer to a mixture of molecules, for example, a mixture of defined composition.

[0035] As used herein, the term "uniform intensity" refers to light that has an intensity difference of 5% or less, sometimes 10% or less, or sometimes 15% or less relative to the intensity of the light, e.g., the intensity of the light directed at the sample surface.

[0036] The term "uniform intensity" as used herein, in relation to signal-to-noise ratio (SNR), refers to the SNR per pixel within the field of view (FOV) where the range of possible values ​​falls between 0.5 and 1 standard deviation from the mean SNR.

[0037] 2.OLS htSMT hardware 2.1.Image Acquisition System With reference to Figure 1, aspects of the present subject matter can be implemented using an htSMT workflow incorporating a system for image acquisition. For example, such image acquisition can incorporate imaging of a sample to generate a series of images and / or video. Figure 2A shows a schematic diagram of an exemplary image acquisition system of the present disclosure, with the XZ sample plane visible. Figure 2B shows the same exemplary image acquisition system, but with the YZ sample plane visible. An exemplary image acquisition system (2-001) includes a light source (2-005) configured to emit light that is relayed by one or more optical elements in an optical relay (2-010), the optical relay configured to shape the light emitted from the light source to form a shaped beam (2-065) such that the shaped beam has a uniform intensity across the long dimension of the linear shape, the system further including optical elements, such as a galvo mirror (2-085), configured to translate the shaped beam, and one or more optical elements, such as a dichroic mirror (2-100), configured to direct the shaped beam to an objective lens (2-120) so that a portion of the sample surface (2-130) is illuminated by an oblique beam (2-125) to produce light emission from the sample, such as fluorescent emission, which is focused by the objective lens (2-120) through a series of optical elements, such as a lens (2-155) and an absorption filter (2-160), onto an image collection system (2-165).

[0038] 2.1.1.Light source Referring to the exemplary image acquisition system of FIG. 2A, the system includes a light source (2-005) configured to emit light. The light source (2-005), in certain embodiments of the image acquisition systems disclosed herein, can be configured to emit light at a single wavelength. In certain embodiments of the image acquisition systems disclosed herein, the light source (2-005) can be configured to emit light at two, three, four, five, or more distinct wavelengths. In certain embodiments, the wavelength(s) of light emitted by the light source are predetermined. For example, but not by way of limitation, the wavelength(s) can be predetermined such that, when irradiated onto a sample, e.g., a sample containing a fluorescent protein, the emitted light induces fluorescence. In certain instances, the wavelength(s) used in connection with the methods described herein will fall within the range of 400 nm to 650 nm. In certain instances, the light source (2-005) emits light having a wavelength of 400 nm to 408 nm, 550 nm to 565 nm, or 638 nm to 650 nm. In certain non-limiting embodiments, the light source (2-005) is configured to include three lasers with nominal center wavelengths of 405 nm, 560 nm, and 640 nm, which can vary within the absorption band of the fluorophore used. In certain cases, the 405 nm wavelength is used to excite Hoechst dyes. In certain cases, the 560 nm wavelength is used to excite dyes attached to HaloTags (e.g., JF549). In certain cases, the 642 or 646 nm wavelength is used to excite dyes attached to HaloTags (e.g., JF646).

[0039] In certain non-limiting embodiments, the light source (2-005) is used to catalyze a photochemical reaction. For example, but not by way of limitation, the wavelength(s) and irradiation intensity can be such that cleavage of a chemical bond occurs. As a further example, but not by way of limitation, the wavelength(s) and irradiation intensity can induce the adoption of a non-radiative dark state (i.e., "photobleaching molecules"). As a further example, but not by way of limitation, the wavelength(s) and irradiation intensity can induce radiative or non-radiative energy transfer between fluorophores within the sample.

[0040] In certain embodiments of the image acquisition system described herein, the light source (2-005) can be configured to deliver a predetermined amount of power to the back focal plane of the objective lens (2-105). For example, and without limitation, the light source (2-005) can deliver more than 10 mW of power at a particular wavelength, such as 405 nm, and / or more than 150 mW of power at another wavelength, such as 640 nm. Additionally or alternatively, if the light source (2-005) includes three lasers emitting at wavelengths of 405 nm, 560 nm, and 640 nm, respectively, the light source (2-005) can be configured to deliver a predetermined amount of power to the back focal plane of the objective lens (2-105). For example, and without limitation, 405 nm can be configured to deliver more than 10 mW, 560 nm can be configured to deliver more than 150 mW, and 640 nm can be configured to deliver more than 50 mW.

[0041] In certain embodiments of the image acquisition system described herein, the light source (2-005) is configured to emit pulsed light. For example, but not by way of limitation, the light source (2-005) can be configured to emit strobe pulsed light. In certain embodiments of the image acquisition system described herein, the light source (2-005) is configured to emit pulsed light synchronized with the start of image acquisition. In certain non-limiting embodiments, the light source (2-005) pulses at specific time intervals depending on the number of frames per second being captured. For example, but not by way of limitation, if 100 frames per second (FPS) are being captured by the detector (2-165), the laser will be on for 9 ms and off for 1 ms. In contrast, in a 200 FPS mode, the laser will be on for 4 ms and off for 1 ms. In certain embodiments of the OLS htSMT workflow, the light source is configured to transition from 90% to 10% power in less than about 0.4 ms. In a particular embodiment of the OLS htSMT workflow, the light source is configured to transition from 90% to 10% power in less than about 0.2 ms.

[0042] The emission of light by the light source (2-005) and the directing of that light to the optical relay (2-010) may be facilitated using a single mode fiber in certain embodiments of the image acquisition systems disclosed herein. Alternatively, multimode fiber may be used in certain embodiments of the image acquisition systems disclosed herein. For example, but not by way of limitation, the multimode fiber may be configured in a predetermined shape for sample illumination.

[0043] In certain embodiments of the image acquisition systems described herein, for example, with respect to systems configured for high-throughput sample analysis, the light source (2-005) can be configured to exhibit low drift in output. In certain embodiments, such low-drift configurations increase the consistency of sample processing and facilitate high-throughput analysis. For example, and not by way of limitation, such low-drift output configurations maintain output within about 0% to about 15% variation, about 0% to about 10% variation, about 10% variation, about 9% variation, about 8% variation, about 7% variation, about 6% variation, about 5% variation, about 4% variation, about 3% variation, about 2% variation, or about 1% variation.

[0044] In certain instances, such a low-drift output configuration maintains output power within about 0% to about 15% variation, about 0% to about 10% variation, about 10% variation, about 9% variation, about 8% variation, about 7% variation, about 6% variation, about 5% variation, about 4% variation, about 3% variation, about 2% variation, or about 1% variation across ambient (room) temperature variations of, for example, 17°C + / - 5°C. In certain instances, this is achieved by using a temperature sensor and / or a closed-loop heater to stabilize the temperature of the internal light source (e.g., laser engine) and thereby reduce output power drift. For example, but not by way of limitation, the light source may be thermally isolated from ambient temperature variations using an insulated enclosure design. Additionally or alternatively, closed-loop heaters can be strategically placed in specific locations within the system, such as at the fiber coupler, to reduce output power drift. Additionally or alternatively, a water jacket and / or cooling device can be used to reduce heat buildup from the laser head. Additionally, these thermal controls, used individually or in combination, reduce the warm-up time to reach a steady state of operation and maintain a more stable internal operating temperature as the laser is powered off and on.

[0045] 2.1.2. Optical Elements and Sample Illumination Referring to the exemplary image acquisition system of Figure 2A, the system includes a light source (2-005) configured to emit light, which is relayed by one or more optical elements in an optical relay (2-010) configured to shape the light emitted from the light source to form a shaped beam (2-065). The particular optical elements of any particular optical relay (2-010) embodiment can be selected and configured to not only generate a beam (2-065) of an appropriate shape, but also to provide appropriate translation of that beam.

[0046] In certain non-limiting embodiments of the optical relay (2-010) of the image acquisition system of the present disclosure, the optical relay (2-010) comprises one or more lenses and / or other optical elements. For example, but not by way of limitation, the selection and orientation of the lenses and other optical elements in the optical relay (2-010) are configured to appropriately shape the light beam directed at the sample. In certain non-limiting embodiments, the optical relay (2-010) includes an optical element, such as a collimator (2-020), for collimating the light emitted from the light source (2-005). Additionally or alternatively, the optical relay (2-010) may include additional optical elements, such as a Powell lens (2-025) or other element adapted to create a beam fan, one or more cylindrical lenses (2-045 and 2-055), one or more slits (2-050 and 2-095) for adjusting the size of the light sheet, one or more achromatic lenses (2-060 and 2-080), and / or one or more mirrors (2-070, 2-075, and 2-085), one or more of which may be galvo mirrors (2-085) that can translate the light. The specific attributes of the optical elements are predetermined to produce an appropriately shaped light beam. For example, but not by way of limitation, the OLS htSMT system of the present disclosure may achieve a uniform horizontal FOV and a uniform vertical FOV. Such uniformity of horizontal and vertical FOV is in contrast to other strategies that provide non-uniform horizontal and / or non-uniform vertical FOV (see Table 2). [Table 2]

[0047] To achieve a uniform horizontal FOV and a uniform vertical FOV, the optical relay (2-010) of the OLS htSMT system described herein includes an optical element or assembly capable of generating a beam that is elongated along the X-plane and narrow along the Y-plane, where the light beam has a uniform intensity across the long dimension of the linear shape. In a specific, non-limiting embodiment, the optical relay (2-010) of the OLS htSMT system described herein includes a Powell lens (2-025) that shapes the light beam to have a uniform intensity across the long dimension of the linear shape (2-065). The optical relay (2-010) of the OLS htSMT system described herein can include additional or alternative optical elements or assemblies that shape the light beam to have a uniform intensity across the long dimension of the linear shape (2-065). For example, but not by way of limitation, the optical relay (2-010) of the OLS htSMT system described herein can include a diffractive element or assembly configured to shape the light beam to have a uniform intensity across the long dimension of the linear shape.

[0048] In certain non-limiting embodiments of the optical relay (2-010) of the image acquisition system of the present disclosure, the optical relay (2-010) comprises one or more optical elements or assemblies configured to translate the light beam relative to the sample surface of the sample being analyzed, e.g., in a direction perpendicular to the long dimension of the light beam. For example, and without limitation, such optical elements or assemblies configured to translate the light beam relative to the sample surface of the sample being analyzed can include a galvo mirror (2-085) or a piezoelectric element configured to translate the light beam. Additionally or alternatively, such optical elements or assemblies configured to translate the light beam relative to the sample surface of the sample being analyzed can comprise a computer-controlled motor.

[0049] Referring to the exemplary image acquisition system of FIG. 2A, the system includes an optical relay (2-010) configured to shape light emitted from a light source to form a shaped beam (2-065), which is directed by an optical element (2-100), such as a dichroic mirror, and directed toward an objective lens (2-120), thereby illuminating a sample plane (2-130) with an oblique beam (2-125).

[0050] In certain non-limiting embodiments of the image acquisition system of the present disclosure, the objective lens (2-120) directs an inclined beam (2-125) onto the sample plane (2-130) to be analyzed. In certain non-limiting embodiments of the image acquisition system of the present disclosure, the objective lens (2-120) is a water-immersion objective lens. The use of a water-immersion objective lens facilitates high-throughput sample analysis by eliminating the oil present in conjunction with the use of an oil-immersion objective lens, thereby enabling higher quality and less distortion. In the context of automated systems, the presence of oil can be problematic, as well as the potential for oil to spread to components such as optical elements that may be exposed to oil and become contaminated. However, water-immersion objective lenses have a refractive index more suited to cellular imaging, resulting in less distortion and improved image quality than oil-immersion objective lenses. In certain non-limiting embodiments, the objective lens is a 60x 1.27 NA water-immersion objective lens (Nikon). In certain embodiments of the workflow described herein, the water-immersion objective lens (2-120) is heated by a heating element. For example, such a heating element maintains the water immersion objective (2-120) at a temperature sufficient to avoid inducing temperature changes in the sample contained in the sample plate (2-021).

[0051] 2.1.3.Image Acquisition In certain non-limiting embodiments of the image acquisition system of the present disclosure, the objective lens (2-0120) is also used to focus the fluorescence emitted by the sample (2-145) in response to the illumination provided by the oblique beam (2-125). In certain non-limiting embodiments, the fluorescence emission (2-145) focused on the objective lens passes through absorption filters (2-150 and 2-160), e.g., bandpass absorption filters that match the spectrum of the fluorophore under observation and are mounted on a high-speed filter wheel (Finger Lakes Instruments), and is collected by a detector device (2-165). In certain non-limiting embodiments, the fluorescence emission focused on the objective lens is directed to an optical relay before collection by the detector device (2-165). For example, but not by way of limitation, such an optical relay can include one or more lenses (2-155) and one or more additional optical elements, e.g., elements configured to reject additional scattered light before collection by the detector device (2-165). In certain non-limiting embodiments, the fluorescent emission focused onto the objective is directed through another dichroic mirror to split the emission across multiple regions of the detector (2-165). In certain non-limiting embodiments, the fluorescent emission focused onto the objective is directed through another dichroic mirror to split the emission across multiple detectors (2-165).

[0052] In certain non-limiting embodiments of the image acquisition system of the present disclosure, the detector device is configured to synchronize detection of the tilted beam (2-125) across the sample plane (2-130) with the movement of the beam. Such synchronization is shown schematically in FIG. 2F. For example, but not by way of limitation, the detector device can be a CMOS camera, such as a back-illuminated CMOS camera (the Hamamatsu Fusion BT).

[0053] In certain embodiments of the image acquisition system of the present disclosure, the CMOS camera can be operated to collect a series of SMT frames for each field of view. For example, and without limitation, 1-20,000 SMT frames, 1-15,000 SMT frames, 1-10,000 SMT frames, 1-5,000 SMT frames, 1-1,000 SMT frames, 2-500 SMT frames, 5-250 SMT frames, 10-200 SMT frames, 100-200 SMT frames, or 200 SMT frames can be collected per field of view. In certain embodiments, the CMOS camera can be configured to operate at a frame rate of about 0.5 to about 2000 Hz. In certain embodiments, the CMOS camera can be configured to operate at a frame rate of 0.5 to 1000 Hz, although in certain embodiments, it can be configured to operate at 100 Hz. In certain embodiments, the CMOS camera may be configured to operate at a frame rate between 100 Hz and 1250 Hz, as shown in FIGS. 15, 17, 18, and 19. For example, and without limitation, certain cell SMT implementations may be performed at 100 Hz. In certain embodiments, certain cell SMT implementations may be performed at 200 Hz. In certain embodiments, certain cell SMT implementations may be performed at 400 Hz. In certain embodiments, certain cell SMT implementations may be performed at 800 Hz. In certain embodiments, certain cell SMT implementations may be performed at 1000 Hz. In certain embodiments, certain cell SMT implementations may be performed at 1200 Hz. In certain embodiments, certain cell SMT implementations may be performed at 1250 Hz. In certain embodiments, certain cell SMT implementations may be performed at 1400 Hz. In certain embodiments, certain cell SMT implementations may be performed at 1600 Hz. In certain embodiments, certain cell SMT implementations may be performed at 1800 Hz. In certain embodiments, certain cellular SMT implementations can run at 2000 Hz.In certain embodiments, certain cell SMT implementations can be performed at frame rates of about 100 Hz or greater, about 200 Hz or greater, about 400 Hz or greater, about 600 Hz or greater, about 800 Hz or greater, about 1000 Hz or greater, about 1200 Hz or greater, about 1400 Hz or greater, about 1600 Hz or greater, or about 1800 Hz or greater. In certain embodiments, certain cell SMT implementations can be performed at frame rates of up to about 1200 Hz. In certain embodiments, certain cell SMT implementations can be performed at frame rates of up to about 1400 Hz. In certain embodiments, certain cell SMT implementations can be performed at frame rates of up to about 1600 Hz. In certain embodiments, certain cell SMT implementations can be performed at frame rates of up to about 1800 Hz. In certain embodiments, certain cell SMT implementations can be performed at frame rates of up to about 2000 Hz.

[0054] In certain non-limiting embodiments of the image acquisition system of the present disclosure, the detector device is configured to transmit a signal with each frame to trigger other elements of the imaging system. For example, but not by way of limitation, the detector device can trigger illumination from the light source (2-005) to collect fluorescence emission associated with a strobe laser pulse. For example, but not by way of limitation, such fluorescence emission collection is associated with a 10-100 millisecond frame and a 2 millisecond strobe laser pulse. In certain embodiments, the fluorescence emission collection is associated with a strobe laser pulse of about 0.1 to about 1 millisecond. In certain embodiments, fluorescence emission collection is associated with a strobe laser pulse of about 0.2 to about 1 millisecond, about 0.3 to about 1 millisecond, about 0.4 to about 1 millisecond, about 0.1 to about 0.9 millisecond, about 0.1 to about 0.8 millisecond, about 0.1 to about 0.7 millisecond, about 0.1 to about 0.6 millisecond, about 0.1 to about 0.5 millisecond, about 0.1 to about 0.4 millisecond, about 0.2 to about 0.6 millisecond, about 0.2 to about 0.5 millisecond, about 0.2 to about 0.4 millisecond, or about 0.3 to about 0.5 millisecond. In certain embodiments, fluorescence emission collection is associated with a strobe laser pulse of about 0.1 to about 0.6 millisecond. In certain embodiments, fluorescence emission collection is associated with a strobe laser pulse of about 0.1 to about 0.5 millisecond. In certain embodiments, fluorescence emission collection is associated with a strobe laser pulse of about 0.2 to about 0.4 millisecond. In certain embodiments, the fluorescence emission collection is associated with a strobe laser pulse of about 0.2 milliseconds. In certain embodiments, the fluorescence emission collection is associated with a strobe laser pulse of about 0.4 milliseconds, as shown in FIG. 13C.

[0055] In certain embodiments, the imaging acquisition system can be configured to acquire a predetermined field of view (FOV), e.g., a detected FOV. In certain embodiments, the FOV, e.g., the detected FOV, can have a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm). In certain embodiments, the FOV, e.g., the detected FOV, can have a size of a first dimension (about 200 μm to about 250 μm) by a second dimension (about 150 μm to about 210 μm), or the FOV, e.g., the detected FOV, can have a size of a first dimension (about 225 μm to about 250 μm) by a second dimension (about 175 μm to about 210 μm). For example, and not by way of limitation, an FOV, e.g., a detected FOV, may have a size of a first dimension (approximately 250 μm) by a second dimension (approximately 190 μm), e.g., as disclosed in Example 1.

[0056] In certain embodiments, a certain percentage of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 75% of the FOV, at least 80% of the FOV, at least 85% of the FOV, at least 90% of the FOV, at least 95% of the FOV, at least 96% of the FOV, at least 97% of the FOV, at least 98% of the FOV, at least 99% of the FOV, or 100% of the FOV provides usable data. In certain embodiments, at least 75% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 80% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 85% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 90% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 95% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 96% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 97% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 98% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, at least 99% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, 100% of the FOV, e.g., the detected FOV, provides usable data. In certain embodiments, about 75% or more of the FOV, e.g., about 80% or more of the FOV, about 85% or more of the FOV, about 90% or more of the FOV, about 95% or more of the FOV, about 96% or more of the FOV, about 97% or more of the FOV, about 98% or more of the FOV, or about 99% or more of the FOV, provides usable data. In certain embodiments, a certain percentage of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion.For example, without limitation, at least 75% of the FOV, at least 80% of the FOV, at least 85% of the FOV, at least 90% of the FOV, at least 95% of the FOV, at least 96% of the FOV, at least 97% of the FOV, at least 98% of the FOV, at least 99% of the FOV, or 100% of the FOV achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 75% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 80% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 85% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 90% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 95% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 96% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 97% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 98% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 99% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, 100% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion.In certain embodiments, about 75% or more of the FOV achieves sufficient laser illumination to track protein motion, e.g., about 80% or more of the FOV, about 85% or more of the FOV, about 90% or more of the FOV, about 95% or more of the FOV, about 96% or more of the FOV, about 97% or more of the FOV, about 98% or more of the FOV, or about 99% or more of the FOV provides sufficient laser illumination to track protein motion.

[0057] In certain embodiments, the imaging acquisition system can be configured to acquire a predetermined image dimension per frame, referred to herein as a region of interest (ROI). In certain embodiments, the ROI varies depending on the frame rate employed. For example, at 100 FPS, 2304 x 1728 pixels define an ROI that is 248.832 x 186.624 microns in the sample plane. In contrast, at 200 FPS, 2304 x 768 pixels define an ROI that is 248.832 x 82.944 microns in the sample plane.

[0058] In certain embodiments, the imaging acquisition system can be configured to perform a predetermined sweep speed at a predetermined frame rate. For example, and not by way of limitation, at 100 FPS, the sweep speed may be 186.624 microns / 9 ms, which corresponds to 20.8 microns / ms, which corresponds to 2.08 cm / s. In contrast, at 200 FPS, the sweep speed may be 82.94 microns / 4 ms, which corresponds to 20.7 microns / ms, which corresponds to 2.07 cm / s.

[0059] In certain embodiments, a detector device can be used to collect fluorescent emissions at multiple wavelengths. For example, but not by way of limitation, fluorescent emissions of additional fluorophores can be collected at the same frame rate or at different frame rates for the same field of view to provide downstream registration of SMT tracks to other cellular components, such as nuclei. Additional channels of the detector device can be used as needed to expand the number of fluorescent emissions simultaneously captured for the same field of view to provide downstream registration of SMT tracks to other cellular components, such as nuclei.

[0060] 2.2. Sample handling Referring to FIG. 1 , embodiments of the present subject matter can be implemented using an htSMT workflow incorporating a system for sample preparation, including reagent processing. For example, and not by way of limitation, FIG. 5 provides a schematic diagram of a sample plate (2-021) containing multiple wells (2-016) in which sample preparation and analysis can occur. FIG. 5 also provides a schematic diagram of the components of a sample, e.g., cells (2-018) and fluorescent target proteins (2-017) within the cells. However, as noted herein, FIG. 5 is not intended to convey scale; for example, each sample present in well (2-016) may contain thousands of cells, each cell containing numerous fluorescent target proteins. FIG. 5 also schematically illustrates the ability of the sample processing system of the present disclosure to add additional reagents to the sample (2-019). The addition of such reagents can be handled by robotic manipulation, including, but not limited to, translation of a robotic fluid handling system relative to the individual wells (2-016) of the sample plate (2-021), translation of the sample plate (2-021) itself, or a combination of both. In certain embodiments of the image acquisition system, the sample plate (2-021) can be maintained in a temperature-controlled environment via the environmental control area (2-020). For example, but not limited to, the sample may be maintained at 22-50°C. In certain embodiments of the image acquisition system, the sample plate (2-021) can be maintained in a humidity-controlled environment via the environmental control area (2-020). For example, but not limited to, the sample may be maintained at 20%-95% humidity. In certain embodiments of the image acquisition system, the sample plate (2-021) can be maintained in a defined gas environment via the environmental control area (2-020). For example, but not limited to, the sample may be maintained at 5% CO2.

[0061] 2.2.1. Cell Lines and Cell Culture Referring to FIG. 5, a particular advantage of the htSMT system described herein is its ability to assay live cells (2-016), facilitating tracking of protein activity, mobility, and diffusion behavior within a dense, live-cell environment. As shown in FIG. 11B, the htSMT system of the present disclosure can be used to track fluorescently labeled proteins in a sample containing multiple cells. Exemplary cells (e.g., cell lines) for use in conjunction with the htSMT system described herein are considered if the sample (e.g., containing such cells) can be focused by the objective lens (2-120) for a sufficient period of time so that the fluorescent emission of the fluorophore can be directed toward the detector (2-165). For example, but not by way of limitation, cells can be directly attached to a coverslip. As a further example, but not by way of limitation, the coverslip can be treated with an extracellular matrix material (e.g., fibronectin, collagen, poly-D-lysine, laminin, Matrigel, vitronectin, etc.) before inducing cells to attach to the coverslip.

[0062] Exemplary cells, e.g., cell lines, can be selected to minimize non-fluorophore emissions reaching the detector. In certain embodiments, cells for use in the present disclosure can be mammalian cells, bacterial cells, or fungal cells. In certain embodiments, the cells are mammalian cells. In certain embodiments, the cells can be obtained from preserved tissue, e.g., fixed tissue, frozen tissue, e.g., frozen tissue samples, or fresh tissue, e.g., fresh tissue samples. In certain embodiments, the cells and / or samples comprising cells can be obtained from a subject. In certain embodiments, the cells can be obtained from a tissue malignancy or tumor, e.g., the cells can be present within a tumor sample (e.g., a portion of a tumor). In certain embodiments, the cells can be obtained from a cell line. For example, but not by way of limitation, certain cell lines that can be used in connection with the htSMT system described herein include U2OS cells (ATCC Catalog No. HTB-96), T47d cells (ATCC Catalog No. HTB-133), and SK-BR-3 cells (ATCC Catalog No. HTB-30), including MCF7 cells (ATCC Catalog No. HTB-22).In certain embodiments, cells can be present in a three-dimensional structure, such as organoid or spheroid.In certain embodiments, cells can be present in organoid.

[0063] In certain embodiments of the htSMT system of the present disclosure, cells used are cultured as needed to provide sufficient cell numbers to achieve the desired high-throughput analysis. For example, but not limited to, cells such as U2OS cells (ATCC Catalog No. HTB-96), MCF7 cells (ATCC Catalog No. HTB-22), T47d cells (ATCC Catalog No. HTB-133), and SK-BR-3 cells (ATCC Catalog No. HTB-30) can be grown in DMEM (Cat. No. 1056601, Gibco DMEM, High Glucose, GlutaMAX Supplement, Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (Cat. No. 16000044, Thermo Fisher Scientific) and 1% penicillin-strep (Cat. No. 15140122, Thermo Fisher Scientific), maintained in a humidified 37°C incubator with 5% CO2, and subcultured approximately every 2-3 days. Additional culture strategies that may be suitable for use with the cell lines outlined herein will be known to those of skill in the relevant art.

[0064] In certain embodiments of the htSMT system of the present disclosure, cells contain one or more fluorescent target proteins. The choice of the specific protein(s) to be labeled and the specific labeling approach can vary depending on the particularities of a particular investigation. For example, but not by way of limitation, one approach for labeling proteins used in connection with the htSMT system described herein is the HaloTag fusion strategy. For example, but not by way of limitation, one approach for labeling proteins is SNAPtag fusion. For example, but not by way of limitation, one approach for labeling proteins is to use a fluorophore ligase system. For example, but not by way of limitation, one approach for labeling proteins is to use a tetracysteine ​​motif such as FlAsH or ReAsH. For example, but not by way of limitation, one approach for labeling proteins is by strain-promoted alkyne-azide cycloaddition of a fluorophore. For example, but not by way of limitation, one approach for labeling proteins is by inducing cellular uptake of a separately produced fluorescent target protein. In certain embodiments of the htSMT system of the present disclosure, the cells contain one or more fluorescently labeled glycoproteins. In certain embodiments, one approach to labeling proteins uses a gene editing system, such as a CRISPR-based editing system. For example, but not limited to, a nucleic acid encoding a fluorescent protein (e.g., a fluorescent tag such as HaloTag) can be inserted into a gene encoding the protein to be labeled, or upstream or downstream of the gene, to generate a protein fluorescently labeled with HaloTag (e.g., at its C-terminus or N-terminus), as described, for example, in Example 2.

[0065] While those skilled in the art can implement the HaloTag fusion approach in a variety of ways, one exemplary approach is to transfect a mammalian expression vector containing a fusion gene (i.e., a protein of interest fused in frame with the HaloTag sequence) under the control of a weak L30 promoter and containing a neomycin resistance marker into a cell line of interest (e.g., U2OS cells). In certain embodiments, such transfection can be achieved when cells are at 70% confluence using FuGENE6 (Cat. No. E2691, Promega). In certain embodiments, transfected cells can then be selected using an appropriate selection agent, e.g., G418 (Cat. No. 10131027, ThermoFisher), at an appropriate concentration, e.g., 500 μg / mL. In certain embodiments, cells can then be clonally isolated. Clones expressing the desired fusion gene can be initially transfected using 100 nM JF 549 -HTL (Cat. No. GA1110, Promega) and 50 nM Hoechst 33342 staining, JF 549 The distribution of signals can be determined by identifying expected clones. An alternative exemplary approach is to transfect cells with a ribonucleoprotein (RNP) complex containing a target protein and an sgRNA targeting a genomic sequence encoding the N- or C-terminal region of the Cas9 protein, combined with one or more linear dsDNA donors. In certain embodiments, each donor consists of 200-300 bp of homology arms specific for each target, a codon-optimized HaloTag sequence, and a TEV linker (ENLYFQG) between the target and the HaloTag. In certain embodiments, 3-6 clones can be subsequently tested for response to control compounds using SMT conditions, and the most homogeneous clones can then be expanded for further testing.

[0066] Although the htSMT workflow of the present application is generally described with respect to an embodiment tracking the effects of compounds on a target fluorescent protein, the htSMT workflow described herein is equally applicable to tracking and analyzing fluorescent target compounds. For example, but not by way of limitation, the compounds described herein may themselves be fluorescent or may be modified to facilitate fluorescent detection. Furthermore, changes in the motion of fluorescent compounds can be used to determine the SMT profile of the compound itself. Thus, all analytical strategies described herein for tracking a target fluorescent protein are also applicable to results obtained by tracking the compound itself.

[0067] 2.2.2. Single Molecule Tracking Sample Preparation Referring to FIG. 5, embodiments of the present subject matter can be implemented using an htSMT workflow whereby cells (2-018) are seeded onto plates (2-021), e.g., tissue culture-treated 384-well glass-bottom plates, although other plate types, including but not limited to single chamber, 9-well glass-bottom plates, 24-well glass-bottom plates, 96-well glass-bottom plates, 1536-well glass-bottom plates, and 3456-well glass-bottom plates, as well as plates made of alternative materials, e.g., plates made partially or entirely of plastic, can also be used in conjunction with the approach outlined herein. In certain embodiments, cells (2-018) are seeded at 1 to 20,000 cells per well (2-016), e.g., 50 to 10,000 cells, 100 to 9,000 cells, 250 to 8,500 cells, 500 to 7,500 cells, 750 to 7,000 cells, 2,500 to 6,500 cells, or 6,000 cells. The seeded cells can then be incubated under conditions desirable for attachment, e.g., overnight at 37°C and 5% CO2. To allow for fluorescence, the cells can be incubated with a sufficient amount of label, e.g., one or more cell-permeable fluorophores. For example, but not by way of limitation, in the case of HaloTag fusions, cells can be incubated with about 0.1 to about 100 pM of JF 549 , J.F. 646or other equivalent cell-permeable fluorophores. In certain embodiments, cells are incubated with about 0.1-100 pM JF 549 -HTL (catalog no. GA1110, Promega), or approximately 0.1–100 pM JF 646 and / or 50 nM Hoechst 33342 (for labeling nuclei) in complete medium for, for example, 1 hour to achieve the desired results.

[0068] In certain embodiments of the htSMT strategy described herein, the cells are then washed, for example, three times in DPBS and twice in imaging medium. In certain embodiments, the imaging medium is prepared to facilitate fluorescence, for example, fluoroBrite DMEM medium (catalog number A1896701, Thermo Fisher), which can be supplemented with GlutaMAX (catalog number 35050079, Thermo Fisher) and the same serum and antibiotics as the growth medium.

[0069] Where appropriate, compounds can be added to samples to test their effect on specific target proteins via SMT. In certain embodiments, compounds can be serially diluted in an Echo-certified 384-well low-dead-volume source microplate (product number 0018544, Beckman Coulter) to generate source material for dose titration. Compounds can then be administered to cell culture media at a final dilution of, for example, 1:1000. In certain embodiments of the htSMT strategy described herein, each dose of compound has at least two replicates per plate and three plate replicates. Additionally, in certain embodiments of the htSMT strategy described herein, 20 DMSO control wells and two no-dye control wells can be randomized across each sample plate (2-020). In certain embodiments, compounds can be incubated for 0-48 hours, for example, 1 hour at 37°C, before acquiring images.

[0070] 3.OLS htSMT software FIG. 6 illustrates an exemplary system 600 for a high-throughput single-molecule imaging platform for measuring molecular movement in live cells. An experiment 602 can be performed to collect large amounts of data from multiple live cells (e.g., using an imaging system 624 to identify compounds 626 and / or targets 622). The experiment 602 can include applying various identifiers, such as labels that can subsequently fluoresce or otherwise be detected, to molecules of interest (e.g., using a laser or other light source). Biological samples forming part of such an experiment 602 can be organized in a plate 604 having multiple wells 606. Each well 606 can have one or more associated fields of view (FOVs) 610. The FOVs 610 can be positions within or corresponding to a single well 606. Image sequences can be generated for the FOVs 610 to generate one or more movies 612, which can include SMT movies and non-SMT movies. SMT movies can be used to track the paths of individual labeled molecules, such as proteins, generating multiple trajectories. Each trajectory may consist of multiple spots 614 containing spatiotemporal coordinates of labeled molecules at a particular time (as described in more detail in FIG. 7). Separately from, and in some examples in parallel with, tracking, the video 612 can be used to identify molecules by using machine learning and / or computer vision-based image segmentation to generate masks 618. Masks 618 are spatial regions within the FOV 610 generated by segmentation. Each mask 618 can belong to a mask category, which is described in more detail in FIGS. 8 and 20B.

[0071] Data associated with the two channels (e.g., the tracking channel and the segmentation / masking channel) can be combined to generate multiple metrics 620 associated with various aspects of the sample. In other words, the trajectories 616 (e.g., trajectory data) can be combined with the machine learning processed image segmentation data and further analyzed using statistical / machine learning techniques. Processing of the combined data can be used to generate metrics 620, such as hit scores, associated with compounds and / or targets within the biological sample, which may be stored in a database structure, as further described in FIG. 9.

[0072] FIG. 7 illustrates data flow through an exemplary system 700 for a high-throughput single-molecule imaging platform for measuring protein movement in live cells. An experiment specification 704 defining an experiment 602 can be provided as data input via one or more clients 702. For example, each experiment 602 can be collected along with an accompanying stain (e.g., Hoechst or Promac Red) used for downstream analysis, including segmentation 618. The experiment specification 704 can define various parameters for the experiment 602, such as stains, dyes, compounds, and treatments. As previously described in FIG. 6, the imaging system 706 (e.g., imaging system 624) can capture a sequence of images to generate one or more SMT movies 711 and / or non-SMT or segmented movies 708 (e.g., movie 612) that characterize the movement of molecules. The SMT movie 711 can characterize the movement of individual fluorescent molecules and / or can include images of individual fluorescent molecules. The segmented movie 708 can include a sequence of images that characterize the movement of a labeled molecule and / or its components. It will be understood that Hoechst staining is only one technique that may be used to label molecules, and / or multiple labeling techniques, such as Potomoc Red, may be utilized depending on the desired configuration. For example, MitoTracker Deep Red may be used to label mitochondria, Concanavalin A-dye conjugates may be used to label endoplasmic reticulum, SYTO14 may be used to label nucleoli, phalloidin may be used to label actin, etc.

[0073] The SMT movie 711 can be analyzed to perform operations related to molecule tracking 710, which can include detecting 712, sub-pixel localizing 713, and linking 714 to identify trajectories 715 of molecules across various images in the SMT movie 711. More specifically, during detecting 712, one or more spots can be detected or recovered in the SMT movie 711. Each spot can be provided with spatiotemporal coordinates. These spatiotemporal coordinates can be estimated by using sub-pixel localizing techniques 713. Linking 714 can be performed on the spots to ultimately identify trajectories 715.

[0074] As used herein, a link is a potential connection between two spots. Each link is directed, starting at one spot and ending at another. A "correct link" connects two spots generated by the same emitter in different frames. Otherwise, the link is "incorrect." One goal of the linking algorithm is to estimate which link is correct. In this specification, links are referred to in the form a:i→j, which is interpreted to mean link α starting at spot i and ending at spot j. A link satisfies at least three of the following constraints: (a) the link moves forward in time; (b) the link cannot connect two spots that are more distant than a certain limit (hereinafter referred to as the "search radius"); and (c) the link cannot connect two spots that are more distant in time than a certain limit (hereinafter referred to as the "gap limit"). A spot-link graph is a graph of the spots and links of a single SMT video 711. In this graph, spots are vertices and links are edges. Because links move forward in time, the spot-link graph is a directed acyclic graph. A matching is a subset of links in the spot-link graph, such that no two links in this subset start or end at the same spot. Trajectory 715 is used herein to refer to a sequence of consecutive (end-to-end) links in the same matching. Dynamic metrics 730 can be determined using multiple trajectories. Such parameters can include spot attributes that characterize the spot's motion. Such parameters can include one or more of the velocity, diffusion coefficient, or anomaly parameter(s) of each spot. The dynamic parameter(s) of spot i are defined herein as θ i Herein, the set of dynamic parameters of all spots in the spot-link graph is called Θ.

[0075] Separately from, and in some variations in parallel with, the processing of the SMT video 711, the segmented video 708 can undergo segmentation to generate one or more masks 720. The masks can be classified into various categories, including, but not limited to, cell nucleus, cytoplasm, and / or extraneous masks, which are further described in FIG. 8 . Instance masks are individually segmented objects (e.g., one cell, one nucleus, one mitochondrion, M phase, G1 phase, early S phase, mid-S phase, late S phase, G2 phase). The FOV 610 can include any number of instance masks for one mask category. A semantic mask is the union of all instance masks corresponding to one type of mask category for one FOV (e.g., all cells, all nuclei, or all mitochondria for one FOV). Extraneous masks can include portions of the non-SMT video 708 that are excluded from any downstream data analysis. For example, these extraneous masks may correspond to portions of the non-SMT movie 708 that are out of focus or contain autofluorescent cellular debris that prevents accurate tracking. During segmentation, molecules in the segmented movie 708 can be assigned to one or more masks. Image metrics 740 can be assessed from the masked molecules, such as cell health, focus quality, etc.

[0076] Experiment information, such as dynamic metrics 730, image metrics 740, and any data from which any metrics are derived (e.g., segmentation information), may be provided to a data repository 770 for storage. Such a data repository 770 may store any results of the experiment 602, such as, for example, dynamic metrics 730, image metrics 740, and / or any data from which any metrics are derived. The data repository may include a local persistence server and / or a dedicated server accessed locally or via the cloud. The data repository 770 may also store metadata associated therewith and / or associated with the experiment specification 704. Experiment information (e.g., results and metadata from past experiments, etc.) may be provided to the data repository 770 via a repository application program interface (API) 750. The repository API 750 may also interface with a web-based graphical user interface front end 760 that provides such information for display on the client 702.

[0077] In some variations, the segmentation information can be used to identify subcellular compartments such as the nucleus, nucleolus, cytoplasm, etc. The segmentation information may also be used to distinguish one cell from another. The segmentation information may be stored in a particular format (e.g., a multi-image file format such as TIFF, etc.).

[0078] The exemplary dynamics metrics 730 can also include a state array. The state array is a framework for learning interpretable dynamic models from SMT trajectories and can be used to gain additional insight into the motion of a target protein and where that motion occurs within the cell. In some variations, the state array can be generated / added using segmentation information. The state array output can be returned at the subcellular compartment level, allowing researchers to distinguish between dynamics in different subcellular compartments. Additionally, the state array can be calculated for each individual subcellular compartment (e.g., for each nucleus).

[0079] To facilitate data access by applications, including but not limited to state arrays, processed SMT data may be stored in a format that allows for (a) representation of processed trajectories and associated attributes, such as SNR and spot shape characteristics, for each SMT video; (b) representation of mask objects, including mask categories (e.g., the subcellular organelles associated with each mask object, the cell cycle stage for each mask object, etc.); (c) association of trajectories with mask objects (e.g., the cell nuclei in which each trajectory was observed, the cell cycle stage in which each trajectory was observed, etc.); and (d) association of all SMT videos with metadata related to the original experiment, such as compound treatment, acquisition time, and imaging system name. Formats (a) and (c) may be protocol buffer schemas that define the storage format for trajectories and associated mask objects. Format (b) may be a specialized image file format containing the mask object to which each pixel in the FOV belongs. Format (d) may be a PostgreSQL database that records all captured experiments / videos. As a client of the processed SMT data, state arrays can reference these data schemas to report the dynamic properties of trajectories by mask category or by mask object.

[0080] FIG. 8 illustrates a plurality of images 800 illustrating the distinction between mask categories and instance or semantic masks. As previously described, a non-SMT video or segmented video can be assigned to multiple categories. Such categories may include cell nuclei (e.g., Category A), cytoplasm (e.g., Category B), and / or extraneous masks (e.g., Category C). Unique, individual masks can be applied to a biological sample. For example, image 810 illustrates a unique, individual instance mask applied to a cell nucleus (e.g., Category A). Image 812 illustrates a unique, individual instance mask applied to a cell cytoplasm (e.g., Category B). Image 820 illustrates multiple instance masks applied to one or more nuclei, each with a different, unique, individual instance mask. Image 822 illustrates multiple masks applied to one or more cytoplasms, each with a different, unique, individual instance mask. Image 830 illustrates a semantic mask that is the union of all instance masks applied to one or more nuclei. Image 832 illustrates a semantic mask applied to one or more cytoplasms. 20B further illustrates the use of mask categories. As shown in FIG. 20B, an individual instance mask can be applied to cells in M ​​phase, an individual instance mask can be applied to cells in G1 phase, an individual instance mask can be applied to cells in early S phase, an individual instance mask can be applied to cells in mid S phase, an individual instance mask can be applied to cells in late S phase, and / or an individual instance mask can be applied to cells in G2 phase.

[0081] FIG. 9 illustrates an exemplary computer-implemented environment 900 in which an imaging system 910 can interact with a computing architecture to execute various algorithms described herein. As shown in FIG. 9 , the imaging system 910 can interface with one or more clients 950 (e.g., client 702 via a web application having a graphical user interface). The one or more clients 950 can interface with one or more servers 920 accessible via network(s) 930. The one or more clients 950 can host a frame grabber that captures images (e.g., video 612) from a camera. These images can be temporarily stored on the one or more clients 950 and periodically transferred via the network 930 to the one or more servers 920 for remote storage. The one or more servers 920 also include or have access to one or more data stores 940 for storing data collected and / or extracted from the sample by the imaging system 910. In some variations, the network 930 may include or interface with one or more network storage arrays 960 for storing data such as captured images (e.g., video 612).

[0082] FIG. 10 is a diagram 1000 illustrating a sample computing device architecture for implementing various aspects described herein. In some variations, the sample computing device architecture may be that of a client(s) 950 and / or a server(s) 920, and some components described in connection with diagram 1000 may be optional for the client(s) 950 and / or the server(s) 920. A bus 1004 may function as an information highway interconnecting the other illustrated components of hardware. A processing system 1008 (e.g., one or more computer processors / data processors in a given computer or in multiple computers), labeled CPU (Central Processing Unit), may perform the computational and logical operations required to execute a program. Optionally, or additionally, a processing system 1012 (e.g., one or more computer processors / data processors in a given computer or in multiple computers), labeled GPU (Graphics Processing Unit), may perform the computational and logical operations required to execute a program. Non-transitory processor-readable storage media, such as read-only memory (ROM) 1016 and random access memory (RAM) 1020, may be in communication with processing system 1008 and / or processing system 1012 and may contain one or more programming instructions for the operations specified herein. Optionally, the program instructions may be stored on a non-transitory computer-readable storage medium, such as a magnetic disk, optical disk, recordable memory device, flash memory, solid-state drive, or other physical storage medium.

[0083] In one example, the disk controller 1048 can interface with one or more optional removable storage 1056 or local storage 1052 via the system bus 1004. The removable storage 1056 can be an external or internal disk drive, a solid-state drive, or an external hard drive. The local storage 1052 can be an internal hard drive and / or memory. As mentioned above, these various examples of the removable storage 1056, the local storage 1052, and the disk controller 1048 are optional devices. The system bus 1004 may also include at least one communication interface 1024 to enable communication with external devices either physically connected to the computing system or externally available via a wired or wireless network, such as cloud storage or a remote service. In some cases, the at least one communication interface 1024 includes or otherwise comprises a network interface.

[0084] In some variations, e.g., client(s) 950, to provide for interaction with a user, the subject matter described herein can be implemented on a computing device having a display device 1044 (e.g., an LCD (liquid crystal display) or LED (light emitting diode) monitor) for displaying information retrieved from bus 1004 to a user via display interface 1040, and input devices 1032, such as a keyboard and / or pointing device (e.g., a mouse or trackball) and / or a touch screen, for a user to provide input to the computer. Other types of input devices 1032 can also be used to provide interaction with a user. For example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback via microphone 1036, or tactile feedback), and input from the user can be received in any form, including acoustic, voice, or tactile input. The input devices 1032 and microphone 1036 can be connected to bus 1004 via input device interface 1028 to communicate information. As an example, the input device 1032 may be the imaging system 910 configured with the capability to capture a sequence of images, as described herein. The frame grabber 1058 may capture or grab individual frames from analog or digital data encapsulating the sequence of images acquired from the bus 1004. The frame grabber 1058 may include memory capable of storing single or multiple frames. The frame grabber 1058 may also provide individual frames or multiple frames to the bus 1004 for further storage, for example, in the local storage 1052 and / or the removable storage 1056. Other computing devices, such as dedicated servers, may omit one or more of the components described in connection with FIG. 10 .

[0085] One or more aspects or features of the subject matter described herein may be implemented in digital electronic circuitry, integrated circuits, specially designed application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. These various aspects or features may include implementation in one or more computer programs executable and / or interpretable by a programmable system including at least one programmable processor, which may be special or general-purpose, coupled to receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device. The programmable system or computing system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and by virtue of the client-server relationship they have to each other.

[0086] These computer programs, which may also be referred to as programs, software, software applications, applications, components, or code, contain machine instructions for a programmable processor and may be implemented in high-level procedural languages, object-oriented programming languages, functional programming languages, logic programming languages, and / or assembly / machine languages. As used herein, a "machine-readable medium" refers to any computer program product, apparatus, and / or device (e.g., magnetic disk, optical disk, memory, programmable logic device (PLD), etc.) used to provide machine instructions and / or data to a programmable processor, including a machine-readable medium that receives the machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and / or data to a programmable processor. A machine-readable medium may non-transitory store such machine instructions, such as, for example, a non-transitory solid-state memory, a magnetic hard drive, or any equivalent storage medium. Alternatively or additionally, a machine-readable medium may temporarily store such machine instructions, such as, for example, a processor cache or other random access memory associated with one or more physical processor cores.

[0087] 4. Specific OLS htSMT Applications Many, perhaps most, pathways that regulate fundamental cellular biochemistry rely on the interaction of protein sensors and protein effectors that transiently engage and trigger changes in cellular physiology. While the fundamentals of this process have long been recognized, biochemical investigation of these protein interactions has typically required in vitro reconstitution or been investigated through pull-down assays after cell permeabilization. The htSMT workflow described herein provides a means to visualize protein movement in large numbers of live cells, and also in contexts where the effects of additive compounds, such as small molecule inhibitors, can be quantitatively assessed.

[0088] 1 , aspects of the OLS htSMT workflow of the present disclosure include, but are not limited to, (i) sample preparation, including reagent handling, (ii) image acquisition, imaging the sample to generate a series of images and / or video, (iii) image analysis, processing these images and videos, (iv) information storage, and (v) providing insights using the stored information, including biological interpretation. With respect to biological interpretation, the htSMT workflows described herein provide the ability to provide specific insights, as outlined below, depending on the particular workflow employed, e.g., (i) OLS htSMT screening, (ii) OLS htSMT binding, and / or (iii) OLS kinetic SMT.

[0089] In certain embodiments, a workflow of the present disclosure can include detecting fluorescence from multiple target fluorescent proteins within a field of view at a sample plane, where the field of view (e.g., a detection field of view) has a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm). In certain embodiments, the FOV, e.g., the detected FOV, can have a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm). In certain embodiments, the FOV, e.g., the detected FOV, can have a size of a first dimension (about 200 μm to about 250 μm) by a second dimension (about 150 μm to about 210 μm), or the FOV, e.g., the detected FOV, can have a size of a first dimension (about 225 μm to about 250 μm) by a second dimension (about 175 μm to about 210 μm). For example, and not by way of limitation, an FOV, e.g., a detected FOV, may have a size of a first dimension (approximately 250 μm) by a second dimension (approximately 190 μm), e.g., as disclosed in Example 1.

[0090] In certain embodiments, a certain percentage of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. For example, without limitation, at least 75% of the FOV, at least 80% of the FOV, at least 85% of the FOV, at least 90% of the FOV, at least 95% of the FOV, at least 96% of the FOV, at least 97% of the FOV, at least 98% of the FOV, at least 99% of the FOV, or 100% of the FOV achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 75% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 80% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 85% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 90% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 95% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 96% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 97% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 98% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, at least 99% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion. In certain embodiments, 100% of the FOV, e.g., the detected FOV, achieves sufficient laser illumination to track protein motion.In certain embodiments, about 75% or more of the FOV achieves sufficient laser illumination to track protein motion, e.g., about 80% or more of the FOV, about 85% or more of the FOV, about 90% or more of the FOV, about 95% or more of the FOV, about 96% or more of the FOV, about 97% or more of the FOV, about 98% or more of the FOV, or about 99% or more of the FOV provides sufficient laser illumination to track protein motion. In certain embodiments, about 90% or more of the FOV achieves sufficient laser illumination to track protein motion. In certain embodiments, about 95% or more of the FOV achieves sufficient laser illumination to track protein motion.

[0091] In certain embodiments, the disclosed workflow includes detecting a field of view at a frame rate of up to about 2000 Hz. In certain embodiments, the disclosed workflow includes detecting a field of view at a frame rate of about 100 Hz or more, about 200 Hz or more, about 400 Hz or more, about 600 Hz or more, about 800 Hz or more, about 1000 Hz or more, about 1200 Hz or more, about 1400 Hz or more, about 1600 Hz or more, or about 1800 Hz or more. In certain embodiments, the disclosed workflow includes detecting a field of view at a frame rate of up to about 1200 Hz. In certain embodiments, the disclosed workflow includes detecting a field of view at a frame rate of up to about 1400 Hz. In certain embodiments, the disclosed workflow includes detecting a field of view at a frame rate of up to about 1600 Hz. In certain embodiments, the disclosed workflow includes detecting a field of view at a frame rate of up to about 1800 Hz.

[0092] In certain embodiments, the disclosed workflow includes illuminating the field of view using a strobe laser pulse of about 0.1 to about 1 millisecond. In certain embodiments, the disclosed workflow includes illuminating the field of view using a strobe laser pulse of about 0.2 to about 1 millisecond, about 0.3 to about 1 millisecond, about 0.4 to about 1 millisecond, about 0.1 to about 0.9 millisecond, about 0.1 to about 0.8 millisecond, about 0.1 to about 0.7 millisecond, about 0.1 to about 0.6 millisecond, about 0.1 to about 0.5 millisecond, about 0.1 to about 0.4 millisecond, about 0.2 to about 0.6 millisecond, about 0.2 to about 0.5 millisecond, about 0.2 to about 0.4 millisecond, or about 0.3 to about 0.5 millisecond. In certain embodiments, the disclosed workflow includes illuminating the field of view using a strobe laser pulse of about 0.1 to about 0.6 millisecond. In certain embodiments, the disclosed workflow includes illuminating the field of view using a strobe laser pulse of about 0.1 to about 0.5 milliseconds. In certain embodiments, the disclosed workflow includes illuminating the field of view using a strobe laser pulse of about 0.2 to about 0.4 milliseconds. In certain embodiments, the disclosed workflow includes illuminating the field of view using a strobe laser pulse of about 0.2 milliseconds.

[0093] In certain embodiments, the disclosed workflow includes illuminating a field of view of a sample surface disposed within the sample with a light beam to induce fluorescence by a subset of fluorescent target proteins in live cells, thereby imaging multiple molecular trajectories. In certain embodiments, up to about 1,000,000 molecular trajectories can be imaged within a single detection field, e.g., up to about 900,000, up to about 800,000, up to about 700,000, up to about 600,000, up to about 500,000, up to about 400,000, up to about 300,000, up to about 200,000, or up to about 100,000 molecular trajectories. In certain embodiments, the number of trajectories imaged within a single detection field can be between about 30,000 and about 1,000,000, e.g., between about 30,000 and about 250,000. For example, and without limitation, the number of trajectories imaged within a single detection field of view may be about 50,000 to about 200,000, about 100,000 to about 200,000, about 100,000 to about 500,000, or about 100,000 to about 150,000. In certain embodiments, the number of trajectories imaged within a single detection field of view may be up to about 1,000,000. In certain embodiments, the number of trajectories imaged within a single detection field of view may be about 100,000 to about 1,000,000. In certain embodiments, the number of trajectories imaged within a single detection field of view may be about 200,000 to about 1,000,000. In certain embodiments, the number of trajectories imaged within a single detection field of view may be about 100,000 to about 500,000. In certain embodiments, the number of trajectories imaged within a single detection field of view can be from about 200,000 to about 500,000.

[0094] In certain embodiments, a field of view can include multiple cells. In certain embodiments, the number of cells imaged within a field of view is related to the size of the cells being imaged. For example, but not by way of limitation, the smaller the cell size, the greater the number of cells that can be imaged within the field of view. In certain embodiments, depending on the size of the cells being imaged, a field of view can include about 30 to about 200 live cells, e.g., about 30 to about 80 cells or about 50 to about 80 cells. In certain embodiments, depending on the size of the cells being imaged, a field of view can include up to about 80 live cells, e.g., mammalian cells. In certain embodiments, for U2OS cells, the range is about 30 to about 40 cells per field, while for HCT116 cells, the range is about 50 to about 80 cells per field, taking into account differences in area. In certain embodiments, a field of view can include 30 to about 80 live cells, e.g., mammalian cells. In certain embodiments, a field of view can include 50 to about 80 live cells, e.g., mammalian cells. In certain embodiments, the field of view can include between 55 and about 80 viable cells, e.g., mammalian cells. In certain embodiments, the field of view can include between 60 and about 80 viable cells, e.g., mammalian cells.

[0095] In certain embodiments, the disclosed workflows may include analyzing a subset (e.g., a subpopulation) of cells present within a field of view, e.g., analyzing and / or tracking the trajectory of a fluorescent target protein within a subset (e.g., a subpopulation) of cells present within a field of view. For example, and without limitation, the disclosed workflows may include analyzing between about 1% and about 99% of the cells present within a field of view, e.g., between about 1% and about 50% of the cells present within a field of view.

[0096] In certain embodiments, the disclosed workflow can include illuminating a field of view of a sample surface disposed within the sample with a light beam to induce fluorescence of multiple fluorescent target proteins within the live cells. In certain embodiments, the multiple fluorescent target proteins can include about 1,000 to about 1,000,000, e.g., about 10,000 to about 1,000,000, or about 100,000 to about 1,000,000 fluorescent target proteins.

[0097] In certain embodiments, the disclosed workflows can include detecting fluorescence from multiple fluorescent target proteins within a field of view at the sample plane at a rate of greater than about 100,000 detection fields per day. For example, and without limitation, fields of view can be detected at a rate of about 100,000 to about 1,000,000 per day. In certain embodiments, the disclosed workflows can include detecting fluorescence from multiple fluorescent target proteins within a field of view at the sample plane at a rate of about 100,000 to about 500,000 detection fields per day.

[0098] In certain embodiments, the workflow of the present disclosure can include determining a change in the movement of a fluorescently labeled target protein in the presence of a compound. For example, but not by way of limitation, the average change in the movement of the fluorescent target protein in the presence of the compound is about 1% to about 5%, or about 10%, relative to baseline movement in the absence of the compound. In certain embodiments, the average change in the movement of the fluorescent target protein in the presence of the compound is about 1% to about 5%. In certain embodiments, the average change in the movement of the fluorescent target protein in the presence of the compound is about 1% to about 10%.

[0099] In certain embodiments, an exemplary OLS htSMT workflow includes the individual strategies described above, as well as combinations of these strategies where two or more of the strategic requirements are combined.

[0100] 4.1OLS htSMT screening In certain embodiments of the OLS htSMT workflow described herein, the systems and methods are adapted to examine the ability of one or more compositions (e.g., "test" compounds) to affect the SMT profile associated with a labeled protein. For example, such htSMT workflows screen for changes in the SMT profile, e.g., either an increase or decrease in the movement of the protein of interest, in the presence of a composition compared to the SMT profile in the absence of the composition, such as when the addition of the composition is replaced with a control, such as, but not limited to, DMSO. It will also be appreciated that higher-order comparisons can be performed when compounds are multiplexed, including when multiple proteins are fluorescent. Furthermore, as outlined above, the htSMT screening strategies described herein are equally applicable to screening SMT profiles associated with fluorescent compounds, e.g., compounds that are naturally fluorescent or compounds that have been modified to fluoresce or linked to a fluorophore.

[0101] Fundamental to such an htSMT screening strategy is the ability of the htSMT workflow described herein to extract large-scale, accurate molecular trajectories. Exemplary OLS htSMT workflows include the following individual strategies and combinations of the following strategies, combining two or more strategic requirements. For example, without limitation, the disclosed workflow includes both illuminating a field of view in a sample plane disposed within a sample with a light beam to induce fluorescence by a subset of fluorescent target proteins in live cells, the subset of fluorescent target proteins being present in about 30 to about 80 live cells illuminated within the field of view in the sample plane, and illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by a subset of fluorescent target proteins in live cells, the subset of fluorescent target proteins comprising a range of about 1,000 to about 1,000,000 proteins. Similarly, illuminating the sample plane to illuminate about 30 to about 80 live cells per FOV and / or generating fluorescence from about 1,000 to about 1,000,000 proteins can be combined with any of the other strategic requirements disclosed herein, such as determining that the average change in the motion of a fluorescent target protein in the presence of a compound is about 1% to about 5% or about 1% to about 10% compared to the absence of the compound, detecting fluorescence from multiple fluorescent target proteins within the field of view of the sample plane at a rate of about 10,000 to about 18,000 per day per system, and achieving a Z-factor greater than 0.5 based on a single field of view.

[0102] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include identifying biological interactions between a compound and a fluorescent target protein in live cells, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells including the fluorescent target protein, the workflow further including (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample, the tracking including (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to cause fluorescence by a subset of the target fluorescent proteins in the live cells, the subset of fluorescent target proteins being selected depending on the particular cell type being used. Depending on the method, there are approximately 30 to approximately 80 live cells illuminated within the field of view of the sample plane. For example, for U2OS cells, the range is approximately 30 to approximately 40 cells per FOV, while for HCT116 cells, the range is approximately 50 to approximately 80 cells, taking into account the difference in area. The tracking further includes (ii) detecting fluorescence from multiple fluorescent target proteins within the field of view of the sample plane via a detector device. The workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound. The change in the movement of the fluorescent target proteins in the presence of the compound compared to the movement of the fluorescent target proteins in the absence of the compound identifies a biological interaction between the compound and the fluorescent target proteins.

[0103] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include identifying biological interactions between a compound and a fluorescent target protein in live cells, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells including the fluorescent target protein, and the workflow further including (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample, the tracking including (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to induce fluorescence by a subset of target fluorescent proteins in the live cells, the subset of fluorescent target proteins including a range of about 1,000 to about 1,000,000 proteins, and The number of proteins in the set depends on the expression level of the protein of interest and the dye concentration deemed appropriate for labeling a subset of proteins for robust SMT, both of which can be calculated and / or configured by one of skill in the art based on the disclosure of the present application; the tracking further includes (ii) detecting fluorescence from multiple fluorescent target proteins within a field of view of the sample plane via a detector device; the workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound; a change in the movement of the fluorescent target proteins in the presence of the compound compared to the movement of the fluorescent target proteins in the absence of the compound identifies a biological interaction between the compound and the fluorescent target proteins.

[0104] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include identifying a biological interaction between a compound and a fluorescent target protein in live cells, the workflow including: (a) contacting a sample including a population of live cells with a compound, the live cells including the fluorescent target protein; and (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample, the tracking including: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to cause fluorescence by a subset of the target fluorescent proteins in the live cells; and (ii) detecting fluorescence from the plurality of fluorescent target proteins in the field of view in the sample plane via a detector device; and (c) determining a change in the movement of the fluorescent target protein in the presence of the compound, wherein the average change in the movement of the fluorescent target protein in the presence of the compound is about 1% to about 5% or about 1% to about 10% compared to the movement of the fluorescent target protein in the presence of the compound compared to the movement of the fluorescent target protein in the absence of the compound, identifying a biological interaction between the compound and the fluorescent target protein.

[0105] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include identifying biological interactions between a compound and a fluorescent target protein in live cells, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells including the fluorescent target protein, and the workflow further including (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample, the tracking including (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to cause fluorescence by a subset of the target fluorescent proteins in the live cells, and (ii) detecting fluorescence from the plurality of fluorescent target proteins in the field of view in the sample plane using a detector device. (iii) the tracking includes detecting fluorescence from multiple fluorescent target proteins within a field of view of the sample plane at a rate of about 10,000 to about 18,000 per day per system, and the workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound, wherein the average change in the movement of the fluorescent target proteins in the presence of the compound is about 1% to about 5% or about 1% to about 10% compared to baseline movement in the absence of the compound, and the change in the movement of the fluorescent target proteins in the presence of the compound compared to the movement of the fluorescent target proteins in the absence of the compound identifies a biological interaction between the compound and the fluorescent target proteins.

[0106] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include identifying biological interactions between a compound and a fluorescent target protein in live cells, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells including the fluorescent target protein, and the workflow further including (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample, the tracking including (i) illuminating with a light beam a field of view in a sample plane located within the sample to cause fluorescence by a subset of the target fluorescent proteins in the live cells; and (ii) illuminating with a light beam a field of view in a sample plane located within the sample to cause fluorescence by a subset of the target fluorescent proteins in the live cells. (iii) detecting fluorescence from the fluorescent target protein via a detector device; and (iv) achieving a Z-factor of greater than 0.5 based on a single field of view, the workflow further comprising (c) determining a change in the movement of the fluorescent target protein in the presence of the compound, wherein the average change in the movement of the fluorescent target protein in the presence of the compound is about 1% to about 5% or about 1% to about 10% compared to baseline movement in the absence of the compound, wherein a change in the movement of the fluorescent target protein in the presence of the compound compared to the movement of the fluorescent target protein in the absence of the compound identifies a biological interaction between the compound and the fluorescent target protein.

[0107] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include determining a dose response of a compound to induce a change in the movement of a fluorescent target protein in a live cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells, (ii) the live cells including a fluorescent target protein, and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; and (b) tracking the movement of individual target fluorescent proteins in the plurality of live cells of the sample, the tracking including: (i) illuminating with a light beam a field of view in a sample plane located within the sample to induce fluorescence by at least a subset of the fluorescent target proteins in the live cells; The protein subset is present in approximately 30 to approximately 80 live cells illuminated within a field of view of the sample plane, depending on the particular cell type used. For example, for U2OS cells, the range is approximately 30 to approximately 40 per FOV, while for HCT116 cells, the range is approximately 50 to approximately 80 per FOV, taking into account differences in area. The tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins within the sample plane via a detector device. The workflow further includes (c) determining a change in the movement of the fluorescent target protein in the presence of a compound; and (d) repeating steps (b) to (c) for each of a plurality of samples across a range of compound concentrations, wherein the change in the movement of the fluorescent target protein across a range of concentrations in the presence of the compound indicates a dose response of the compound.

[0108] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include determining a dose response of a compound that induces a change in the movement of a fluorescent target protein in a live cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells; (ii) the live cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; the workflow further including: (b) tracking the movement of individual target fluorescent proteins in the plurality of live cells of the sample, the tracking including: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to induce fluorescence by at least a subset of the fluorescent target proteins in the live cells; The subset includes proteins ranging from 0 to approximately 1,000,000, where the number of proteins in the subset depends on the expression level of the protein of interest and the dye concentration deemed appropriate for labeling the subset proteins for robust SMT, both of which can be calculated and / or configured by one of ordinary skill in the art based on the disclosure of the present application. The tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, where the workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound; and (d) repeating steps (b)-(c) for each of a plurality of samples across a range of compound concentrations, where the change in the movement of the fluorescent target proteins in the presence of the compound across the concentration range indicates a dose response of the compound.

[0109] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include determining a dose response of a compound to induce a change in the movement of a fluorescent target protein in a live cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells; (ii) the live cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; the workflow further including: (b) tracking the movement of individual target fluorescent proteins in the plurality of live cells of the samples, the tracking including: (i) determining whether the compound induces fluorescence by at least a subset of the fluorescent target proteins in the live cells; (ii) illuminating with a light beam a field of view in a sample plane disposed within the sample; and (ii) detecting fluorescence from one or more fluorescent target proteins in the sample plane via a detector device; the workflow further includes (c) determining a change in movement of the fluorescent target protein in the presence of the compound, wherein the average change in movement of the fluorescent target protein in the presence of the compound is about 1% to about 5% or about 1% to about 10% compared to the absence of the compound; and (d) repeating steps (b)-(c) for each of a plurality of samples across a range of compound concentrations, wherein the change in movement of the fluorescent target protein across the concentration range in the presence of the compound indicates a dose response of the compound.

[0110] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include determining a dose response of a compound to induce a change in the movement of a fluorescent target protein in a living cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of living cells; (ii) the living cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; the workflow further including: (b) tracking the movement of individual target fluorescent proteins in a plurality of living cells of the samples, the tracking including: (i) detecting changes in the movement of individual target fluorescent proteins in the samples so as to cause fluorescence by at least a subset of the fluorescent target proteins in the cells. (ii) illuminating with a light beam a field of view in the plane of the sample disposed in the sample; and (ii) detecting via a detector device fluorescence from one or more of the fluorescent target proteins in the plane of the sample; (iii) said tracking includes detecting fluorescence from a plurality of fluorescent target proteins in the field of view in the plane of the sample at a rate of about 10,000 to about 18,000 per day per system; the workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound; and (d) repeating steps (b)-(c) for each of a plurality of samples across a range of compound concentrations, wherein the change in the movement of the fluorescent target proteins in the presence of the compound across the range of concentrations indicates a dose response of the compound.

[0111] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include determining a dose response of a compound to induce a change in the movement of a fluorescent target protein in a living cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of living cells; (ii) the living cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; and the workflow further including: (b) tracking the movement of individual target fluorescent proteins in a plurality of living cells of the samples, the tracking including: (i) determining a dose response of at least one fluorescent target protein in the cells; (ii) illuminating a field of view in a sample plane located within the sample with a light beam to cause fluorescence by a subset of the fluorescent target proteins; (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device; and (iii) achieving a Z-factor of greater than 0.5 based on the single field of view, the workflow further including (c) determining a change in the movement of the fluorescent target proteins in the presence of the compound; and (d) repeating steps (b)-(c) for each of a plurality of samples across a range of compound concentrations, wherein the change in the movement of the fluorescent target proteins in the presence of the compound across the concentration range indicates a dose response of the compound.

[0112] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include the use of a microscopy system configured to identify biological interactions between compounds and fluorescent target proteins in live cells, the system including: (a) a stage for supporting a sample, the sample including a population of live cells, the live cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, wherein a subset of the fluorescent target proteins in the sample is positioned within a field of view in the plane of the sample, the subset of fluorescent target proteins being present in about 30 to about 80 live cells illuminated within the field of view in the plane of the sample, depending on the particular cell type used, e.g., For U2OS cells, the range is about 30 to about 40 cells per FOV, while for HCT116 cells, the range is about 50 to about 80 cells, taking into account differences in area. The system further includes (d) a detector device that monitors a light-based response from the fluorescent target protein in the presence of a compound, the detector device being configured to (i) block light received from a light source other than the sample plane where the fluorescent target protein is located, thereby tracking the position of the fluorescent target protein, and (ii) track the movement of individual fluorescent target proteins. The system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, the processor being capable of determining a change in the movement of the fluorescent target protein in the presence of the compound compared to the absence of the compound.

[0113] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include use of a microscope system configured to identify biological interactions between compounds and fluorescent target proteins in live cells, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample; a subset of the fluorescent target proteins in the sample is positioned within a field of view in the plane of the sample; the subset of fluorescent target proteins includes proteins in a range of about 1,000 to about 1,000,000; and the number of proteins in the subset is determined based on the expression level of the protein of interest and the number of proteins in the subset to identify a robust SMT. and a dye concentration deemed appropriate for labeling the subset proteins for the compound, both of which can be calculated and / or configured by one of ordinary skill in the art based on the disclosure of the present application; the system further includes (d) a detector device that monitors a light-based response from the fluorescent target proteins in the presence of the compound, the detector device being configured to (i) block light received from a light source other than the sample plane where the fluorescent target proteins are located, thereby tracking the positions of the fluorescent target proteins, and (ii) track the movement of individual fluorescent target proteins; the system further includes (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the fluorescent target proteins in the presence of the compound compared to the absence of the compound.

[0114] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include the use of a microscope system configured to identify biological interactions between compounds and fluorescent target proteins in live cells, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, wherein a subset of the fluorescent target proteins in the sample are positioned within a field of view of the sample plane; and the system further including: (d) detecting a light-based response from the fluorescent target proteins in the presence of a compound. the detector device is configured to (i) block light received from a light source other than the sample plane on which the fluorescent target proteins are disposed, thereby tracking the positions of the fluorescent target proteins, and (ii) track the movement of individual fluorescent target proteins, wherein an average change in the movement of the fluorescent target proteins in the presence of the compound compared to the absence of the compound is about 1% to about 5% or about 1% to about 10%, and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining the change in the movement of the fluorescent target proteins in the presence of the compound compared to the absence of the compound.

[0115] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include the use of a microscope system configured to identify biological interactions between a compound and a fluorescent target protein in living cells, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, the plurality of fluorescent target proteins in the sample being disposed in the plane of the sample; and (d) monitoring the light-based response from the fluorescent target proteins in the presence of the compound. the detector device is configured to (i) block light received from a light source other than the sample plane where the fluorescent target proteins are located, thereby tracking the positions of the fluorescent target proteins, and (ii) track the movement of individual fluorescent target proteins, wherein the tracking includes detecting fluorescence from a plurality of fluorescent target proteins within a field of view of the sample plane at a rate of about 10,000 to about 18,000 per day per system, and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the fluorescent target proteins in the presence of a compound compared to the absence of the compound.

[0116] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow can include the use of a microscope system configured to identify biological interactions between a compound and a fluorescent target protein in living cells, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, the plurality of fluorescent target proteins in the sample being disposed in the plane of the sample; and (d) an objective lens for focusing the light beam onto the sample in a plane of the sample, the plurality of fluorescent target proteins in the sample being disposed in the plane of the sample. The system includes a detector device that monitors a light-based response from the fluorescent target proteins, the detector device being configured to (i) block light received from a light source other than the sample plane where the fluorescent target proteins are located, thereby tracking the position of the fluorescent target proteins, (ii) track the movement of individual fluorescent target proteins, and (iii) achieve a Z-factor of greater than 0.5 based on a single field of view, and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the fluorescent target proteins in the presence of a compound compared to the absence of the compound.

[0117] OLS htSMT binding In certain embodiments of the OLS htSMT workflow described herein, the system and method utilizes the f seen in htSMT screening assays. bound Increase in residence time (k* off Importantly, both FRAP and htSMT are adapted to distinguish between recovery after exposure to a compound caused by an increase in dwell time (k* off decrease in chromatin binding rate (k* on It is not possible to distinguish between recovery caused by boundThis results in an increase in the number of dwell times. By modifying the SMT acquisition conditions to reduce the illumination intensity and collect longer frame exposures, only immobile proteins form spots. Under these imaging conditions, the distribution of track lengths provides a measure of relative dwell times.

[0118] Exemplary OLS htSMT combined workflows include the following individual strategies and combinations of the following strategies that combine two or more strategic requirements: For example, but not by way of limitation, the disclosed workflow includes both illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by a subset of fluorescent target proteins in live cells, the subset of fluorescent target proteins being present in about 30 to about 80 live cells illuminated within the field of view in the sample plane, and illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by a subset of fluorescent target proteins in live cells, the subset of fluorescent target proteins comprising a range of about 1,000 to about 1,000,000 proteins. Similarly, illuminating the sample plane to illuminate about 30 to about 80 live cells per FOV and / or generating fluorescence from about 1,000 to about 1,000,000 proteins can be combined with any of the other strategic requirements disclosed herein, such as determining that the average change in the movement of a fluorescent target protein in the presence of a compound is about 1% to about 5% or about 1% to about 10% compared to the absence of the compound (e.g., when the addition of the compound is replaced with a control, including but not limited to DMSO), detecting fluorescence from multiple fluorescent target proteins within the field of view of the sample plane at a rate of about 10,000 to about 18,000 per day per system, and achieving a Z-factor greater than 0.5 based on a single field of view.

[0119] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in live cells is a K offand determining whether a compound reduces the activity of a cell in a population of living cells, the workflow comprising: (a) contacting a sample comprising a population of living cells with a compound, the living cells comprising a fluorescent target protein; and (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells, the subset of fluorescent target proteins being present in about 30 to about 80 living cells illuminated in the field of view in the sample plane depending on the particular cell type used; e.g., for U2OS cells, the range is about 30 to about 40 per FOV. , whereas in the case of HCT116 cells, the range is about 50 to about 80 considering differences in area. The tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method being adapted to selectively detect localized fluorescence. The workflow further includes (c) determining a change in the movement of the fluorescent target protein in the presence of a compound, where an increase in the signal detected from the fluorescent target protein in the presence of the compound compared to the signal of the fluorescent target protein in the absence of the compound (e.g., when the addition of the composition is replaced with a control such as, but not limited to, DMSO) indicates that the compound has a K off This indicates that it induces a decrease in

[0120] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in live cells is a K offand determining whether a compound reduces a protein of interest, the workflow comprising: (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to induce fluorescence by at least a subset of the target fluorescent proteins in the live cells; the subset of fluorescent target proteins comprising a range of about 1,000 to about 1,000,000 proteins; and the number of proteins in the subset is determined based on the expression level of the protein of interest and the robust S. and a dye concentration deemed appropriate for labeling a subset of proteins for MTs, both of which can be calculated and / or configured by a person skilled in the art based on the disclosure of the present application; the tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method being adapted to selectively detect localized fluorescence; the workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound, wherein an increase in the signal detected from the fluorescent target proteins in the presence of the compound compared to the signal from the fluorescent target proteins in the absence of the compound indicates that the compound has a K off This indicates that it induces a decrease in

[0121] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in live cells is a K offthe workflow may include determining whether the compound reduces the K of the fluorescent target protein, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking including (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method adapted to selectively detect localized fluorescence; and the workflow may further include (c) determining a change in the movement of the fluorescent target protein in the presence of the compound, the average change in the movement of the fluorescent target protein in the presence of the compound being about 1% to about 5% or about 1% to about 10% compared to the absence of the compound; and an increase in the signal detected from the fluorescent target protein in the presence of the compound compared to the signal of the fluorescent target protein in the absence of the compound, indicating that the compound reduces the K of the fluorescent target protein. off This indicates that it induces a decrease in

[0122] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in live cells is a K offthe workflow may include determining whether a compound reduces K of the fluorescent target protein, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells comprising a fluorescent target protein, the workflow further including (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking including (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells, and (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method adapted to selectively detect localized fluorescence, the tracking further including (iii) achieving a Z-factor of greater than 0.5 based on a single field of view, the workflow further including (c) determining a change in the movement of the fluorescent target protein in the presence of the compound, wherein an increase in a signal detected from the fluorescent target protein in the presence of the compound compared to a signal from the fluorescent target protein in the absence of the compound indicates that the compound reduces K of the fluorescent target protein. off This indicates that it induces a decrease in

[0123] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow measures the capacity of a compound to induce a change in binding of a fluorescent target protein in live cells by determining whether the compound has a K offThe workflow can include determining whether the compound reduces the activity of the compound by determining whether the compound reduces the activity of the compound, the workflow comprising: (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the live cells, the subset of fluorescent target proteins being present in about 30 to about 80 live cells illuminated in the field of view in the sample plane, depending on the particular cell type used. For example, in the case of U2OS cells, the range is about 30 to about 40 per FOV, while in the case of HCT116 cells, the range is about 50 to about 80, taking into account the difference in area. The tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method being adapted to selectively detect localized fluorescence. The workflow further includes (c) determining a change in the movement of the fluorescent target protein in the presence of a compound, where an increase in the signal detected from the fluorescent target protein in the presence of the compound compared to the signal of the fluorescent target protein in the absence of the compound indicates that the compound has a K off This indicates that increasing the dose induces a decrease in drug metabolism due to increased residence time.

[0124] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow measures the capacity of a compound to induce a change in binding of a fluorescent target protein in live cells by determining whether the compound has a K offand determining whether the compound reduces the activity of the target fluorescent protein in a plurality of cells in the sample, the workflow comprising: (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to induce fluorescence by at least a subset of the target fluorescent proteins in the live cells, the subset of fluorescent target proteins comprising a range of about 1,000 to about 1,000,000 proteins, the number of proteins in the subset being determined based on the expression level of the protein of interest and the locus of the target fluorescent protein. and a dye concentration deemed appropriate for labeling a subset of proteins for robust SMT, both of which can be calculated and / or configured by a person skilled in the art based on the disclosure of the present application; the tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method being adapted to selectively detect localized fluorescence; the workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound, wherein an increase in the signal detected from the fluorescent target proteins in the presence of the compound compared to the signal from the fluorescent target proteins in the absence of the compound indicates that the compound has a K off These studies have shown that increasing the dose induces a decrease in the drug's metabolism, and in certain cases, increases in the drug's residence time, leading to a decrease in drug metabolism.

[0125] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow measures the capacity of a compound to induce a change in binding of a fluorescent target protein in live cells by determining whether the compound has a K offthe workflow may include (a) contacting a sample containing a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking including (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method adapted to selectively detect localized fluorescence; and (c) determining a change in the movement of the fluorescent target proteins in the presence of the compound, wherein an average change in the movement of the fluorescent target proteins in the presence of the compound is about 1% to about 5% or about 1% to about 10% compared to the absence of the compound; and wherein an increase in a signal detected from the fluorescent target proteins in the presence of the compound compared to the signal of the fluorescent target proteins in the absence of the compound indicates that the compound has a K of the fluorescent target proteins. off This indicates that increasing the dose induces a decrease in drug metabolism due to increased residence time.

[0126] In certain embodiments of the OLS htSMT binding workflow described herein, the workflow measures the capacity of a compound to induce a change in binding of a fluorescent target protein in live cells by determining whether the compound has a K offthe workflow may include (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of individual fluorescent target proteins in a plurality of cells in the sample, the tracking including (i) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, the method adapted to selectively detect localized fluorescence; the tracking further including (iii) achieving a Z-factor of greater than 0.5 based on a single field of view; and the workflow may further include (c) determining a change in the movement of the fluorescent target protein in the presence of the compound, wherein an increase in a signal detected from the fluorescent target protein in the presence of the compound compared to a signal from the fluorescent target protein in the absence of the compound indicates that the compound is a signal that corresponds to a K of the fluorescent target protein. off These results demonstrate that the drug induces a decrease in the amount of steroid hormone and, in some cases, an increase in dosage due to increased residence time leading to decreased drug metabolism.

[0127] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in a cell is a K of the fluorescently labeled target. offThe method can include using a microscope system configured to determine whether a fluorescent target protein reduces a signal, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; and (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, wherein a subset of the fluorescent target proteins in the sample is positioned within a field of view in the plane of the sample, the subset of fluorescent target proteins being present in about 30 to about 80 live cells illuminated within the field of view in the plane of the sample, depending on the particular cell type used; e.g., for U2OS cells, the range is about 30 to about 40 per FOV, while for HCT116 cells, the range is Taking into account differences in area, the number is about 50 to about 80. The system further includes (d) a detector device that monitors a light-based response from the fluorescent target protein in the presence of a compound, the detector device being configured to (i) block light received from a light source other than the sample surface where the fluorescent target protein is located, thereby tracking the position of the fluorescent target protein, and (ii) track the movement of each fluorescent target protein, the tracking being adapted to selectively detect localized fluorescence relative to dynamic fluorescence. The system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, the processor being capable of determining a change in the movement of the fluorescent target protein in the presence of the compound compared to the absence of the compound.

[0128] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in a cell is a K of the fluorescently labeled target. offThe method can include using a microscope system configured to determine whether a protein of interest is reduced, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including fluorescent target proteins; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample; a subset of the fluorescent target proteins in the sample being positioned within a field of view in the plane of the sample; the subset of fluorescent target proteins including proteins in a range of about 1,000 to about 1,000,000; the number of proteins in the subset being dependent on the expression level of the protein of interest and a dye concentration deemed appropriate for labeling the subset proteins for robust SMT, both of which are dependent on the expression level of the protein of interest and a dye concentration deemed appropriate for labeling the subset proteins for robust SMT. The system can be calculated and / or constructed by one skilled in the art based on the disclosure of the present application, and further includes (d) a detector device that monitors a light-based response from the fluorescent target protein in the presence of the compound, wherein the detector device is configured to (i) block light received from a light source other than the sample plane where the fluorescent target protein is located, thereby tracking the position of the fluorescent target protein, and (ii) track the movement of individual fluorescent target proteins, wherein the tracking is adapted to selectively detect localized fluorescence versus dynamic fluorescence, and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the fluorescent target protein in the presence of the compound compared to the absence of the compound.

[0129] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in a cell is a K of the fluorescently labeled target. offThe present invention can include use of a microscope system configured to determine whether a compound reduces a certain level of ... (i) blocking light received from a light source other than the sample plane where the compound is being detected, thereby tracking the positions of the fluorescent target proteins; and (ii) tracking the movement of individual fluorescent target proteins, wherein the tracking is adapted to selectively detect localized fluorescence relative to dynamic fluorescence, and an average change in the movement of the fluorescent target proteins in the presence of the compound compared to the absence of the compound is about 1% to about 5% or about 1% to about 10%, and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining the change in the movement of the fluorescent target proteins in the presence of the compound compared to the absence of the compound.

[0130] In certain embodiments of the OLS htSMT screening workflow described herein, the workflow determines whether a compound that induces a change in binding of a fluorescent target protein in a cell is a K of the fluorescently labeled target. offThe present invention can include use of a microscope system configured to determine whether a compound reduces a light-based response from the fluorescent target proteins, the system including: (a) a stage supporting a sample, the sample including a population of cells, the cells including fluorescent target proteins; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens focusing the light beam onto the sample in a plane of the sample, wherein a subset of the fluorescent target proteins in the sample is positioned within a field of view of the plane of the sample; and the system further including: (d) a detector device monitoring the light-based response from the fluorescent target proteins in the presence of a compound, the detector device detecting (i) the fluorescent target proteins; and (ii) blocking light received from a light source other than the sample plane where the protein is located, thereby tracking the position of the fluorescent target proteins; and (ii) tracking the movement of individual fluorescent target proteins, wherein the tracking is adapted to selectively detect localized fluorescence versus dynamic fluorescence; the detector device is further configured to (iii) achieve a Z-factor of greater than 0.5 based on a single field of view; and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the fluorescent target proteins in the presence of the compound compared to the absence of the compound.

[0131] 4.3OLS Kinetic SMT Because SMT can identify the rate of biological interaction between a compound and a target, it can be used to distinguish between direct and indirect effects on target activity, among other parameters. Given the live-cell setting of SMT, a data collection mode (kinetic SMT or kSMT) can be configured that allows protein movement after compound addition to be measured at set intervals to determine the rate of biological interaction between the compound and the target.

[0132] Exemplary OLS kinetic SMT workflows include the following individual strategies and combinations of the following strategies that combine two or more strategic requirements: For example, but not by way of limitation, the disclosed workflow includes both illuminating a field of view in a sample plane disposed within a sample with a light beam to induce fluorescence by a subset of fluorescent target proteins in live cells, the subset of fluorescent target proteins being present in about 30 to about 80 live cells illuminated within the field of view in the sample plane, and illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by a subset of fluorescent target proteins in live cells, the subset of fluorescent target proteins comprising a range of about 1,000 to about 1,000,000 proteins. Similarly, illuminating the sample plane to illuminate about 30 to about 80 live cells per FOV and / or generating fluorescence from about 1,000 to about 1,000,000 proteins can be combined with any of the other strategic requirements disclosed herein, such as determining that the average change in the movement of a fluorescent target protein in the presence of a compound is about 1% to about 5% or about 1% to about 10% compared to the absence of the compound (e.g., when the addition of the compound is replaced with a control, including but not limited to DMSO), detecting fluorescence from multiple fluorescent target proteins within the field of view of the sample plane at a rate of about 10,000 to about 18,000 per day per system, and achieving a Z-factor greater than 0.5 based on a single field of view.

[0133] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include identifying an incidence of biological interactions between a compound and a target in live cells, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells including a fluorescent target protein, the workflow further including (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample at multiple time points, the tracking including (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to cause fluorescence by a subset of the target fluorescent proteins in the live cells, the fluorescent target proteins The subset of cells is present in approximately 30 to approximately 80 illuminated live cells within the field of view of the sample plane, depending on the specific cell type used. For example, for U2OS cells, the range is approximately 30 to approximately 40 cells per FOV, while for HCT116 cells, the range is approximately 50 to approximately 80 cells, taking into account differences in area. The tracking further includes (ii) detecting fluorescence from multiple fluorescent target proteins within the field of view of the sample plane via a detector device. The workflow further includes (c) determining changes in the movement of the fluorescent target proteins in the presence of a compound, where the rate at which changes in the movement of the fluorescent target proteins occur in the presence of the compound indicates the rate of occurrence of biological interactions between the compound and the target.

[0134] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include identifying a rate of occurrence of a biological interaction between a compound and a target in live cells, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells including a fluorescent target protein, the workflow further including (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample at multiple time points, the tracking including (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to induce fluorescence by a subset of target fluorescent proteins in the live cells, the subset of fluorescent target proteins ranging from about 1000 to about 1 The subset includes proteins in the range of 100,000,000, where the number of proteins in the subset depends on the expression level of the protein of interest and the dye concentration deemed appropriate for labeling the subset proteins for robust SMT, both of which can be calculated and / or configured by a person skilled in the art based on the disclosure of the present application, and the tracking further includes (ii) detecting fluorescence from multiple fluorescent target proteins within a field of view of the sample plane via a detector device, and the workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound, where the rate at which the change in the movement of the fluorescent target proteins occurs in the presence of the compound indicates the occurrence rate of biological interaction between the compound and the target.

[0135] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include identifying a rate of occurrence of a biological interaction between a compound and a target in live cells, the workflow including: (a) contacting a sample including a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample at multiple time points, the tracking including: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to cause fluorescence by a subset of the target fluorescent proteins in the live cells; and (ii) detecting fluorescence from the plurality of fluorescent target proteins in the field of view in the sample plane via a detector device; and (c) determining a change in the movement of the fluorescent target proteins in the presence of the compound, wherein the average change in the movement of the fluorescent target proteins in the presence of the compound is about 1% to about 5%, or about 1% to about 10%, compared to the movement in the absence of the compound; and the rate at which the change in the movement of the fluorescent target proteins in the presence of the compound indicates a rate of occurrence of a biological interaction between the compound and the target.

[0136] In certain embodiments of the OLS kinetic htSMT combined workflow described herein, the workflow can include identifying the incidence of compound-target biological interactions among direct and indirect biological interactions between a compound and a fluorescent target protein in live cells, the workflow including (a) contacting a sample including a population of live cells with a compound, the live cells including the fluorescent target protein, the workflow further including (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample at multiple time points, the tracking including (i) tracking the movement of a subset of the target fluorescent proteins in the live cells. (ii) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence; and (iii) detecting fluorescence from a plurality of fluorescent target proteins within the field of view of the sample plane via a detector device. (iii) tracking the fluorescence from the plurality of fluorescent target proteins within the field of view of the sample plane at a rate of about 10,000 to about 18,000 per day per system. The workflow further includes (c) determining a change in the movement of the fluorescent target proteins in the presence of a compound, wherein the rate at which the change in the movement of the fluorescent target proteins occurs in the presence of the compound indicates the occurrence rate of a biological interaction between the compound and the target.

[0137] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include identifying a rate of occurrence of a biological interaction between a compound and a target in live cells, the workflow including: (a) contacting a sample including a population of live cells with a compound, the live cells comprising a fluorescent target protein; and (b) tracking the movement of a plurality of individual fluorescent target proteins in a plurality of live cells in the sample at multiple time points, the tracking including: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to cause fluorescence by a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from the plurality of fluorescent target proteins in the field of view in the sample plane, wherein detection based on a single field of view is associated with a Z-factor of greater than 0.5; and (c) determining a change in the movement of the fluorescent target protein in the presence of the compound, wherein a rate at which the change in the movement of the fluorescent target protein occurs in the presence of the compound indicates a rate of occurrence of the biological interaction between the compound and the target.

[0138] In certain embodiments of the OLS kinetic htSMT combined workflow described herein, the workflow can include determining a dose of a compound that induces a change in the movement of a fluorescent target protein in a live cell, the workflow including (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells, (ii) the live cells including a fluorescent target protein, and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations, the workflow further including (b) tracking the movement of individual target fluorescent proteins in a plurality of live cells of the sample at a plurality of time points, the tracking including (i) illuminating with a light beam a field of view in a sample plane located within the sample to induce fluorescence by at least a subset of the fluorescent target proteins in the live cells, The protein subset is present in approximately 30 to approximately 80 live cells illuminated within a field of view of the sample plane, depending on the specific cell type used. For example, for U2OS cells, the range is approximately 30 to approximately 40 per FOV, while for HCT116 cells, the range is approximately 50 to approximately 80 per FOV, taking into account differences in area. The tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins within the sample plane via a detector device. The workflow further includes (c) determining the rate at which a change in the movement of the fluorescent target protein occurs in the presence of the compound; and (d) repeating steps (b) to (c) for each of a plurality of samples over a range of compound concentrations, wherein the rate at which a change in the movement of the fluorescent target protein occurs in the presence of the compound indicates the rate of occurrence of a biological interaction between the compound and the target.

[0139] In certain embodiments of the OLS kinetic htSMT combined workflow described herein, the workflow can include determining a dose of a compound that induces a change in the movement of a fluorescent target protein in a live cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells; (ii) the live cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; the workflow further including: (b) tracking the movement of individual target fluorescent proteins in a plurality of live cells of the sample at multiple time points; the tracking including: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample to induce fluorescence by at least a subset of the fluorescent target proteins in the live cells; The subset may include proteins ranging from 0 to approximately 1,000,000, where the number of proteins in the subset depends on the expression level of the protein of interest and the dye concentration deemed appropriate for labeling the subset proteins for robust SMT, both of which can be calculated and / or configured by one of ordinary skill in the art based on the disclosure of the present application. The tracking further includes (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device, where the workflow further includes (c) determining a rate at which a change in the motion of the fluorescent target protein occurs in the presence of the compound; and (d) repeating steps (b)-(c) for each of a plurality of samples over a range of compound concentrations, where the rate at which a change in the motion of the fluorescent target protein occurs in the presence of the compound indicates a rate of occurrence of a biological interaction between the compound and the target.

[0140] In certain embodiments of the OLS kinetic htSMT combined workflow described herein, the workflow can include determining a dose response of a compound that induces a change in the movement of a fluorescent target protein in a live cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells; (ii) the live cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; the workflow further including: (b) tracking the movement of individual target fluorescent proteins in a plurality of live cells of the samples at multiple time points; and (ii) detecting fluorescence from one or more of the fluorescent target proteins in the sample plane via a detector device; the workflow further includes (c) determining a rate at which a change in the motion of the fluorescent target protein occurs in the presence of the compound, wherein the average change in the motion of the fluorescent target protein in the presence of the compound is about 1% to about 5% or about 1% to about 10% compared to the absence of the compound; and (d) repeating steps (b)-(c) for each of a plurality of samples over a range of compound concentrations, wherein the rate at which the change in the motion of the fluorescent target protein occurs in the presence of the compound indicates a rate of occurrence of a biological interaction between the compound and the target.

[0141] In certain embodiments of the OLS kinetic htSMT combined workflow described herein, the workflow can include determining a dose response of a compound that induces a change in the movement of a fluorescent target protein in a live cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells; (ii) the live cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; the workflow further including: (b) tracking the movement of individual target fluorescent proteins in a plurality of live cells of the samples at multiple time points; (ii) illuminating with a light beam a field of view in the plane of a sample disposed within the system; and (ii) detecting via a detector device fluorescence from one or more of the fluorescent target proteins in the plane of the sample; (iii) said tracking includes detecting fluorescence from a plurality of fluorescent target proteins in the field of view of the plane of the sample at a rate of about 10,000 to about 18,000 per day per system; the workflow further includes (c) determining a rate at which a change in the motion of the fluorescent target protein occurs in the presence of a compound; and (d) repeating steps (b)-(c) for each of a plurality of samples over a range of compound concentrations, wherein the rate at which a change in the motion of the fluorescent target protein occurs in the presence of the compound indicates a rate of occurrence of a biological interaction between the compound and the target.

[0142] In certain embodiments of the OLS kinetic htSMT combined workflow described herein, the workflow can include determining a dose of a compound that induces a change in the movement of a fluorescent target protein in a live cell, the workflow including: (a) contacting a plurality of samples with a compound, (i) each sample including a population of live cells; (ii) the live cells including a fluorescent target protein; and (iii) the plurality of samples being contacted with different concentrations of the compound over a range of compound concentrations; and the workflow further including: (b) tracking the movement of individual target fluorescent proteins in a plurality of live cells of the samples at a plurality of time points, wherein the tracking includes: (i) determining a change in the movement of at least one fluorescent target protein in the live cells. (ii) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to cause fluorescence from at least a subset of the fluorescent target proteins; and (ii) detecting via a detector device fluorescence from one or more of the fluorescent target proteins within the field of view in the sample plane, wherein detection based on a single field of view is associated with a Z-factor of greater than 0.5; and (c) determining a rate at which a change in the motion of the fluorescent target proteins occurs in the presence of the compound; and (d) repeating steps (b)-(c) for each of a plurality of samples across a range of compound concentrations, wherein the rate at which a change in the motion of the fluorescent target proteins occurs in the presence of the compound indicates a rate of occurrence of a biological interaction between the compound and the target.

[0143] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include the use of a microscopy system configured to determine the incidence of biological interactions between a compound and a target in live cells, the system including: (a) a stage supporting a sample, the sample including a population of live cells, the live cells including fluorescent target proteins; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens focusing the light beam onto the sample in a plane of the sample, wherein a subset of the fluorescent target proteins in the sample is positioned within a field of view in the sample plane, the subset of fluorescent target proteins being present in about 30 to about 80 live cells illuminated within the field of view in the sample plane, depending on the particular cell type used, e.g., For U2OS cells, the range is about 30 to about 40 cells per FOV, while for HCT116 cells, the range is about 50 to about 80 cells, taking into account the difference in area. The system further includes (d) a detector device that monitors a light-based response from the fluorescent target protein in the presence of a compound, the detector device being configured to (i) block light received from a light source other than the sample plane where the fluorescent target protein is located, thereby tracking the position of the fluorescent target protein at multiple time points, and (ii) track the movement of individual fluorescent target proteins. The system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, the processor being capable of determining a change in the movement of the fluorescent target protein in the presence of the compound compared to the absence of the compound.

[0144] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include use of a microscopy system configured to determine the incidence of biological interactions between a compound and a target in live cells, the system including: (a) a stage supporting a sample, the sample including a population of cells, the cells including fluorescent target proteins; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens that focuses the light beam onto the sample in a plane of the sample; a subset of the fluorescent target proteins in the sample is positioned within a field of view in the plane of the sample; the subset of fluorescent target proteins includes proteins in a range of about 1,000 to about 1,000,000; the number of proteins in the subset is determined based on the expression level of the protein of interest and the robust S and a dye concentration deemed appropriate for labeling the subset proteins for MT, both of which can be calculated and / or configured by one of ordinary skill in the art based on the disclosure of the present application; the system further includes (d) a detector device that monitors a light-based response from the fluorescent target proteins in the presence of the compound, the detector device being configured to (i) block light received from a light source other than the sample plane where the fluorescent target proteins are located, thereby tracking the positions of the fluorescent target proteins at multiple time points, and (ii) track the movement of individual fluorescent target proteins; the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, the processor being capable of determining a change in the movement of the fluorescent target proteins in the presence of the compound compared to the absence of the compound.

[0145] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include the use of a microscope system configured to determine the incidence of biological interactions between a compound and a target in live cells, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, wherein a subset of the fluorescent target proteins in the sample are positioned within a field of view of the sample plane; and the system further including: (d) a microscope system configured to determine the incidence of biological interactions between a compound and a target in live cells, the system including: (a) a stage for supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; the detector device is configured to monitor a light-based response from the fluorescent target protein, the detector device being configured to (i) block light received from a light source other than the sample plane on which the fluorescent target protein is disposed, thereby tracking the position of the fluorescent target protein at multiple time points, and (ii) track the movement of individual fluorescent target proteins, wherein an average change in the movement of the fluorescent target protein in the presence of the compound compared to the absence of the compound is about 1% to about 5% or about 1% to about 10%, and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining the change in the movement of the fluorescent target protein in the presence of the compound compared to the absence of the compound.

[0146] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include the use of a microscope system configured to determine the incidence of biological interactions between a compound and a target in living cells, the system including: (a) a stage supporting a sample, the sample including a population of cells, the cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens focusing the light beam onto the sample in a plane of the sample, the plurality of fluorescent target proteins in the sample being disposed in the plane of the sample; and (d) an objective lens focusing the light beam onto the sample in a plane of the sample, the plurality of fluorescent target proteins in the sample being disposed in the plane of the sample; The system further includes a detector device configured to (i) block light received from a light source other than the sample plane where the fluorescent target proteins are located, thereby tracking the positions of the fluorescent target proteins at multiple time points, and (ii) track the movement of individual fluorescent target proteins, wherein the tracking includes detecting fluorescence from the plurality of fluorescent target proteins within a field of view of the sample plane at a rate of about 10,000 to about 18,000 per day per system, and the system further includes (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the fluorescent target proteins in the presence of a compound compared to the absence of the compound.

[0147] In certain embodiments of the OLS kinetic htSMT binding workflow described herein, the workflow can include the use of a microscope system configured to determine the incidence of biological interactions between a compound and a target in live cells, the system including: (a) a stage for supporting a sample, the sample including a population of live cells, the live cells including a fluorescent target protein; the system further including: (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of fluorescent target proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a plane of the sample, wherein a subset of the fluorescent target proteins in the sample are positioned within a field of view of the sample plane; and the system further including: (d) a microscope system configured to determine the incidence of biological interactions between a compound and a target in live cells, the system including: (a) a stage for supporting a sample, the sample including a population of live cells, the live cells including a fluorescent target protein; The system further includes a detector device that monitors a light-based response from the fluorescent target protein in the presence of the compound, the detector device being configured to (i) block light received from a light source other than the sample plane where the fluorescent target protein is located, thereby tracking the position of the fluorescent target protein at multiple time points, (ii) track the movement of individual fluorescent target proteins, and (iii) achieve a Z-factor of greater than 0.5 based on a single field of view, the system further including (e) a memory and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the fluorescent target protein in the presence of the compound compared to the absence of the compound.

[0148] 5. Exemplary Embodiments A. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in living cells is capable of detecting the K offand (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of view in the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm). The method is adapted to selectively detect localized fluorescence. The method further comprises: (c) determining a change in the movement of the target fluorescent protein in the presence of the compound; and an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound reduces the K of the target fluorescent protein. off This indicates that it induces a decrease in

[0149] B. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in living cells is capable of detecting the K offThe present invention provides a method for determining whether a compound reduces the activity of a living cell, the method comprising: (a) contacting a sample containing a population of living cells with a compound, the living cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam so as to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells, the subset of target fluorescent proteins generating and tracking up to about 1,000,000 molecular trajectories within a single detection field. further comprising (ii) detecting, via the detector device, fluorescence from one or more of the target fluorescent proteins within a detection field at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence, the method further comprising (c) determining a change in the movement of the target fluorescent protein in the presence of a compound, wherein an increase in the signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K off This indicates that it induces a decrease in

[0150] C. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in living cells is capable of detecting the K off(b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of view in the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm). The method is adapted to selectively detect localized fluorescence compared to dynamic fluorescence. The method further comprises: (c) determining a change in the movement of the target fluorescent protein in the presence of the compound; and an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound reduces the K of the target fluorescent protein. off This indicates that it induces a decrease in

[0151] D. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in living cells is capable of detecting the K offThe present invention provides a method for determining whether a compound reduces the activity of a living cell, the method comprising: (a) contacting a sample comprising a population of living cells with a compound, the living cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam so as to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; and (ii) detecting fluorescence from one or more of the target fluorescent proteins in the detection field of the sample plane via a detector device. and (c) detecting a change in the movement of the target fluorescent protein in the presence of a compound, wherein an increase in the signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K of the target fluorescent protein. off This indicates that it induces a decrease in

[0152] E1. The detected change in motion corresponds to the binding state (f bound The method of any one of A to E, wherein the increase in immobility locus indicates an increase in occupancy or duration of the immobility locus.

[0153] E2. The method of any of A-E, wherein the detected change in motion is a change in (a) the median of the jump length distribution, (b) the third quartile of the jump length distribution, (c) the median radius of gyration, (d) the mean posterior diffusion coefficient, (e) the geometric mean posterior diffusion coefficient, (f) the mean squared displacement, (g) the median bond angle, (h) the maximum likelihood estimator of the diffusion coefficient, and / or (i) the inferred state occupancy.

[0154] E3. The method according to any one of A to E, wherein the target fluorescent proteins interact within a larger molecular assembly.

[0155] E4. The method of E3, wherein the target fluorescent protein is a ligand.

[0156] E5. The method of E3, wherein the target fluorescent protein is a receptor.

[0157] E6. The method according to any one of A to E, wherein the biological interaction is a direct interaction.

[0158] E7. The method of E6, wherein the direct interaction comprises binding of the compound to the target fluorescent protein.

[0159] E8. The method according to any one of A to E, wherein the biological interaction is an indirect interaction.

[0160] E9. The method of E8, wherein the indirect interaction comprises the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

[0161] F. The present disclosure defines the dose of a compound that induces a change in the binding of a target fluorescent protein in live cells as the K offand (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound, wherein an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K of the target fluorescent protein. off This indicates that it induces a decrease in

[0162] G. The present disclosure defines the dose of a compound that induces a change in binding of a target fluorescent protein in live cells as the K offThe present invention provides a method for determining whether a compound reduces the activity of a living cell, the method comprising: (a) contacting a sample comprising a population of living cells with a compound, the living cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam so as to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; the subset of target fluorescent proteins generating up to about 1,000,000 molecular trajectories within a single detection field; and and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins within a detection field at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence. The method further includes (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound, wherein an increase in the signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K off This indicates that it induces a decrease in

[0163] H. The present disclosure provides a method for determining the dose of a compound that induces a change in binding of a target fluorescent protein in live cells by determining whether the compound binds to the target fluorescent protein at a K offand (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound, wherein an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K of the target fluorescent protein. off This indicates that it induces a decrease in

[0164] I. The present disclosure defines the dose of a compound that induces a change in the binding of a target fluorescent protein in living cells as the K offa method for determining whether a compound reduces the activity of one or more of the target fluorescent proteins in a sample by determining whether the compound reduces the activity of one or more of the target fluorescent proteins in the sample, the method comprising: (a) contacting a sample comprising a population of live cells with a compound, the live cells comprising a target fluorescent protein; and (b) tracking the movement of individual target fluorescent proteins in a plurality of cells in the sample, the tracking comprising: (i) illuminating with a light beam a field of view in a sample plane disposed within the sample so as to cause fluorescence by at least a subset of the target fluorescent proteins in the live cells; and (ii) detecting, via a detector device, fluorescence from one or more of the target fluorescent proteins in the detection field of the sample plane. and (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of a compound, wherein an increase in a signal detected from the target fluorescent protein in the presence of the compound compared to a signal from the target fluorescent protein in the absence of the compound indicates that the compound has a K of the target fluorescent protein. off This indicates that it induces a decrease in

[0165] I1. The detected change in motion is due to the binding (f bound ) A method according to any one of F to I, wherein the increase in immobile loci indicates an increase in the target fluorescent protein.

[0166] I2. The method of any of F-I, wherein the detected change in motion is a change in (a) the median of the jump length distribution, (b) the third quartile of the jump length distribution, (c) the median radius of gyration, (d) the mean posterior diffusion coefficient, (e) the geometric mean posterior diffusion coefficient, (f) the mean squared displacement, (g) the median bond angle, (h) the maximum likelihood estimator of the diffusion coefficient, and / or (i) the inferred state occupancy.

[0167] I3. The method according to any one of F to I, wherein the target fluorescent protein interacts within a larger molecular assembly.

[0168] I4. The method according to I3, wherein the target fluorescent protein is a ligand.

[0169] I5. The method according to I3, wherein the target fluorescent protein is a receptor.

[0170] I6. The method according to any one of F to I, wherein the biological interaction is a direct interaction.

[0171] I7. The method of I6, wherein the direct interaction comprises binding of the compound to the target fluorescent protein.

[0172] I8. The method according to any one of F to I, wherein the biological interaction is an indirect interaction.

[0173] I9. The method of I8, wherein the indirect interaction involves the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

[0174] J. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in living cells is capable of determining the K of the target fluorescent protein. off and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound. The microscope system further includes: (a) a stage for supporting a sample, the sample comprising a population of cells, the cells comprising a target fluorescent protein; (b) a light source for emitting a light beam capable of inducing a light-based response from a plurality of target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a sample plane, wherein a subset of the target fluorescent proteins in the sample are positioned within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm); and the microscope system further includes: (d) a detector device for monitoring the light-based response from the target fluorescent proteins in the presence of a compound; (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound.

[0175] K. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in a living cell is capable of determining the K of the target fluorescent protein. off and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound. The microscope system further includes: (a) a stage for supporting a sample, the sample comprising a population of cells, the cells comprising a target fluorescent protein; (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in a sample plane; a subset of the target fluorescent proteins in the sample are positioned within a detection field of view in the sample plane; the subset of target fluorescent proteins generates up to about 1,000,000 molecular trajectories within a single detection field; the detection field has a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm); and the microscope system further includes: (d) a detector device for monitoring the light-based response from the target fluorescent proteins in the presence of a compound; (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound.

[0176] L. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in living cells is capable of detecting the K offand (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound compared to the absence of the compound.

[0177] M. The present disclosure provides a method for determining whether a compound that induces a change in the binding of a target fluorescent protein in living cells is capable of determining the K of the target fluorescent protein. off and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound. The microscope system further includes: (a) a stage for supporting a sample, the sample comprising a population of cells, the cells comprising a target fluorescent protein; (b) a light source emitting a light beam capable of inducing a light-based response from a plurality of target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam on the sample in a sample plane, wherein a subset of the target fluorescent proteins in the sample are positioned within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and 95% or more of the detection field achieves sufficient laser illumination to track protein movement. The microscope system further includes: (d) a detector device for monitoring the light-based response from the target fluorescent proteins in the presence of a compound; (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining a change in the movement of the target fluorescent proteins in the presence of the compound.

[0178] M1. The detected change in movement is the binding (f bound 31. The system according to claim 27, wherein the increase in immobile loci indicates an increase in the target fluorescent protein.

[0179] M2. The system of any of claims 27-30, wherein the detected change in motion is a change in (a) the median of the jump length distribution, (b) the third quartile of the jump length distribution, (c) the median radius of gyration, (d) the mean posterior diffusion coefficient, (e) the geometric mean posterior diffusion coefficient, (f) the mean squared displacement, (g) the median bond angle, (h) the maximum likelihood estimator of the diffusion coefficient, and / or (i) the inferred state occupancy.

[0180] M3. A system according to any one of J to M, wherein the target fluorescent proteins interact within a larger molecular assembly.

[0181] M4. The system according to M3, wherein the target fluorescent protein is a ligand.

[0182] M5. The system according to M3, wherein the target fluorescent protein is a receptor.

[0183] M6. A system described in any one of J to M, wherein the biological interaction is a direct interaction.

[0184] M7. The system of M6, wherein the direct interaction comprises binding of the compound to the target fluorescent protein.

[0185] M8. A system described in any one of J to M, wherein the biological interaction is an indirect interaction.

[0186] M9. The system of M8, wherein the indirect interaction comprises the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

[0187] 6. Working Example The presently disclosed subject matter will be better understood by reference to the following examples, which are provided by way of illustration of the presently disclosed subject matter, and not by way of limitation.

[0188] Example 1: Optical Line Scan System preface Single-molecule localization microscopy (SMLM) techniques, such as single-molecule tracking (SMT), enable in situ measurements in live and fixed cells, from which data-rich metrics can be extracted. SMT has been successfully applied to address a variety of biological questions and model systems, aiming to reveal protein function in healthy or pathological states, its impact on downstream pathways, and the spatiotemporal regulation of molecular mechanisms governing cellular function. While powerful, SMLM often suffers from issues such as low throughput, uneven illumination, and technical biases imposed by the microscope and user. Technical limitations in scaling SMLM techniques require tradeoffs between spatial resolution, temporal resolution, and throughput, limiting the use of these techniques to a small number of research groups.

[0189] This example describes the development of the OLS system disclosed herein to overcome limitations of other SMLM techniques. Briefly, a thin optical light sheet is shaped, focused into the back focal plane of a microscope objective, and scanned using a galvanometric mirror. This optical configuration results in a scannable oblique light sheet that can cover the entire FOV of a water-immersion high-NA objective (Figure 11A and Figures 12A-12F). Further details regarding this exemplary OLS system are provided below.

[0190] B. Exemplary OLS System SMT image acquisition of the OLS dataset was performed on a custom-built microscope based on a Nikon Ti2, motorized stage, stage-top environmental chamber (OKO Laboratory), a quad-band filter cube (Chroma), and a custom laser launch at 405 nm, 561 nm, and 642 nm wavelengths, delivering >10 mW, >150 mW, and >150 mW of power output, respectively, to the back focal plane of the objective. The custom laser launch consisted of three externally triggerable free-space laser sources (Cobolt 06-MLD; Huebner Photonics; 2RU-VFL-P-2000-560-M; MBP Communications Inc.; VFL-P-2000-642-M; MBP Communications Inc.).

[0191] An oblique line scanning (OLS, Figures 12A and 12D) unit is attached to the back port of the microscope and provides optical excitation and scanning. The OLS unit receives collimated Gaussian-shaped optical excitation via a polarization-maintaining single-mode fiber coupled to a laser beam coupler. The laser excitation is sent through a combination of a Powell lens, a custom-designed cylindrical lens, and an achromatic lens to shape the beam into a laser line. The beam is directed to a set of two adjustable right-angle prisms, followed by an aspheric achromatic lens, which positions the beam and focuses the scan axis onto a galvanometric scan mirror. The galvanometric scan mirror is adjusted to position the beam 3.8 mm offset relative to the central optical axis of the objective's back focal plane, achieving an illumination light sheet at a 60-degree tilt angle within the sample (Figure 12E).

[0192] Fluorescence emission was collected by a backlit sCMOS camera (ORCA-FusionBT, Humana) through a high-speed filter wheel (Satter Instruments). The sCMOS camera was operated in progressive mode with an exposure time of 407 μs and an internal line spacing of 4.87 μs to achieve a virtual rolling slit of approximately 200% of the optical excitation and fluorescence linewidth (Figure 12F). Images were acquired with a 60× 1.27 NA water immersion objective (Nikon). The environmental chamber was set to 37°C, 95% humidity, and 5% CO2.

[0193] System hardware control is achieved with a custom-designed, user-configurable electronic circuit board for software interface, synchronization, and device control. Data acquisition control is achieved with a custom-designed, user-configurable acquisition script in MicroManager and a custom-designed autofocus routine for raster scanning of the 384-well plate (Figure 12B). For downstream registration of trajectories to the nucleus and cytoplasm, one frame each in the Hoechst and Potomac Red channels was collected at the same frame rate.

[0194] Consideration In this example, we present OLS, a robust single-objective light-sheet-based illumination and detection modality that achieves nanoscale spatial resolution and submillisecond temporal resolution across a 250 × 190 μm field of view to overcome the limitations of other SMLM techniques. OLS was developed to expand the effective imaging area while homogenizing the SNR across the entire camera chip, generating high-quality SMLM and SMT raw image files without compromising the achieved spatiotemporal resolution. The relatively simple optical configuration used in OLS makes this approach easily implementable on an inverted microscope equipped with either a water- or oil-immersion high-numerical-aperture (NA) objective and an sCMOS camera with light-sheet mode capability.

[0195] Example 2: OLS High-Throughput Single Molecule Tracking (htSMT) preface This example describes an exemplary industrial-scale OLS htSMT technique using the exemplary OLS system of Example 1, and a comparison of such an OLS system with a highly inclined laminated optical sheet (HILO) system. This example further describes systems incorporating such OLS htSMT technology, hardware and software associated with such OLS htSMT technology, and methods for using such OLS htSMT technology. For example, the OLS htSMT technology described herein is capable of measuring protein movement in millions of cells per day. The OLS htSMT technology described herein demonstrates specific, robust, and reproducible results. The OLS htSMT technology described herein can be used for a variety of applications, including, but not limited to, traditional drug discovery activities such as screening compound libraries and elucidating SAR. Importantly, the OLS htSMT technology described herein can be used to characterize the contributions of both known and novel pathways to interaction networks, such as protein signaling interaction networks.

[0196] result Development and verification of htSMT system We developed a robotic system capable of handling reagents, collecting high-quality, high-speed SMT image series, and processing the time-sequenced raw images to generate molecular trajectories and extract biologically interesting features within defined cellular compartments (Figure 1). To investigate the performance of our htSMT system, we performed various measurements demonstrating the suitability of the disclosed image acquisition system and workflow for robust htSMT analysis. For example, Figure 3A shows a laser titration experiment demonstrating the relationship between laser power (mW) at the sample and signal-to-noise ratio (SNR) (left panel) and the average SNR at the well level across four image acquisition systems measuring six different 384-well plates per system (right panel). Figure 3C shows a dose-response experiment performed on Halo-tagged proteins using established and well-characterized compounds to assess plate-to-plate and day-to-day reproducibility (top panel), along with the respective EC50 values ​​(bottom panel). Figure 3D shows that the system described herein is configured to capture comparable protein diffusion coefficients per FOV per well; each point represents an individual FOV position averaged per plot for each concentration (top panel); both EC50 and Z-factor are presented (bottom panel). Figure 3E demonstrates the consistency of the data across multiple wells and experiments; each point represents one FOV from 14 independently generated dose-response curves.

[0197] In addition to establishing the suitability of the OLS workflow described herein for robust htSMT analysis, we conducted experiments comparing the OLS-based workflow described herein with a HILO-based approach. For example, comparing the Z-factors associated with the OLS-based data shown in Figures 3D and 3E to data collected using a HILO-based approach clearly demonstrates the improved performance of the OLS-based approach. These differences between the OLS-based and HILO-based approaches are particularly evident in Figure 3B, which shows the difference in spatial SNR heterogeneity between the OLS system of the present disclosure and the HILO-based approach. The top panel compares the spatial standard deviation observed with OLS to the HILO-based approach. The bottom panel shows the difference in FOV between the HILO-based and OLS-based approaches (left image) and a comparison of spatial heterogeneity across the FOV for the HILO-based approach (center image) and the OLS-based approach (right image).

[0198] To demonstrate the improved performance of the OLS-based approach compared to the HILO-based approach, we performed additional experiments. For these comparisons, we used a U2OS cell line (Halo-KEAP1) in which a HaloTag genome edit was introduced into the amino terminus of the KEAP1 gene. The rhodamine dye Janelia Fluorophor 549 (JF 549Initial imaging of sparsely labeled Halo-KEAP1 with HILO provided clear single-molecule resolution, to which spot detection, localization, and tracking analyses could be applied (Figure 11B). The performance of the OLS system was benchmarked against the HILO implementation. Both HILO and OLS collected 1.5 s of SMT data, and the resulting trajectories were plotted (Figure 11D). The average number of trajectories collected across the FOV increased from 25,765 ± 4,838 with HILO to 167,479 ± 46,324 with OLS, consistent with the calculated 6-fold increase in imaging field of view (Figure 11E). SMT data were collected across 1,224 FOVs across a 384-well plate, and the average signal-to-noise ratio (SNR) of all spots localized within each pixel of the FOV was calculated and a spatial SNR map was rendered (Figure 11F). The standard deviation and average SNR per FOV were then summarized across 308 wells for OLS and HILO, respectively. This demonstrated consistency in SNR and improved performance when comparing the two illumination modalities (Figure 11G).

[0199] For HILO, the sample was illuminated for 2 ms by pulsing the excitation laser over a subset of the camera's exposure time. For OLS, given the light sheet scanning rate, it was calculated that each fluorophore would be exposed to light for only 400 μs. Given this shorter fluorophore integration time, we expected a more consistent point spread function (PSF) across different diffusion rates. We verified this hypothesis by analyzing the average spot width of KEAP1 with and without KI-696 (Figure 13A). HILO illumination increased the average 2σ radius of single-molecule PSFs by 4.4%, while OLS illumination reduced it to 1.4% (Figures 13B and 13D). While a 400 μs strobe time would have provided a direct comparison of motion blur performance in OLS, we found that within this integration time, HILO did not enable single-molecule detection because the majority of PSFs did not exceed the noise threshold (Figure 13C).

[0200] One of the key advantages offered by OLS is that during scanning of the tilted light sheet, out-of-focus illumination emitters lie outside the strip of pixels recorded by the camera. To characterize this superior illumination-based optical sectioning method, samples consisting of increasing concentrations of His-HaloTag in solution were prepared to adjust the protein labeling density and downstream effects on SNR and PSF detection. This experiment significantly captures the expected improvement in sectioning capabilities provided by OLS. A more rapid decrease in the number of detected localizations was observed with HILO, which correlated with a decrease in SNR (Figures 13E and 13F). These results emphasize that under OLS illumination, single PSFs were better detected, regardless of local PSF overlaps that may result from increased dye or protein concentration. Combined with reduced motion blur, OLS offers the ability to track single particles at high density with high resolution.

[0201] To further evaluate the reproducibility of the illumination quality of the disclosed OLS optical system, comparative SMT measurements were performed on four different OLS-equipped microscopes using a previously described automated system (McSwiggen et al., bioRxiv:2023.2001.2005.522916(2023)). Six to seven 384-well plates per microscope were tested, and Halo-KEAP1 was treated with 20 concentrations of KI-696. KI-696 is a small molecule known to inhibit the interaction of KEAP1 with its binding partner, NRF2, thereby increasing the proportion of fast-diffusing Halo-KEAP1. Twelve wells per concentration were randomly replicated across the plate, with six fields of view per well. The mean dose-response profiles per microscope were highly consistent, with a median increase of 47–51% in diffusion and resulting EC 50The median SNR ranged from 7.37 to 8.58 nM across four independent microscopes (Figures 11C and 14A). Comparing the mean FOV-level SNR per microscope, the median SNR ranged from 28.08 to 28.89 across all four microscopes (Figure 14B). No variation across subsequent FOVs captured within a single well was observed, suggesting minimal disruption across the well when imaging a particular FOV (Figure 14C). This means that within this series of measurements, there appears to be no effect of location within the well. Furthermore, the effect of larger OLS FOV size on SMT sampling was directly characterized by comparing cropped regions of the same FOV with larger OLS FOVs. A significant increase in variance was observed as the number of captured cells reduced to an area spanning 83 × 83 μm (Figure 14D).

[0202] method cell line U2OS cells (ATCC Cat. No. HTB-96) are grown in DMEM (Cat. No. 1056601, Gibco DMEM, High Glucose, GlutaMAX Supplement, Thermofisher) supplemented with 10% fetal bovine serum (Cat. No. 16000044, Thermofisher) and 1% penicillin-strep (Cat. No. 15140122, Thermofisher), maintained in a humidified 37°C incubator with 5% CO2, and can be subcultured approximately every 2–3 days.

[0203] HaloTag-expressing cell lines For specific target-HaloTag fusions, mammalian expression vectors containing the appropriate fusion gene under the control of the weak L30 promoter and containing a neomycin resistance marker can be transfected into U2OS cells at 70% confluence using FuGENE6 (Cat. No. E2691, Promega). Transfected cells can be selected with 500 μg / mL G418 (Cat. No. 10131027, ThermoFisher) and then clonally isolated. Clones expressing the desired fusion gene can be identified by first selecting with 100 nM JF. 549 -HTL (Cat. No. GA1110, Promega) and 50 nM Hoechst 33342 staining, JF 549 This can be determined by identifying clones with the expected distribution of signals. Many clones can then be tested using SMT conditions for response to a control compound, and the most homogeneous clones can then be expanded for further testing.

[0204] To generate specific KEAP1-HaloTag cell lines (e.g., the cell lines used in Figures 14A-14D), ribonucleoprotein (RNP) complexes containing sgRNAs (Integrated DNA Technologies - IDT) targeting either the N- or C-terminal region and the Cas9 protein (PNA bio, catalog number CP01) were transfected with linear dsDNA donors (IDT) using the Lonza nucleofection method. Each donor consisted of 200-300 bp homology arms specific for each target, a codon-optimized HaloTag sequence, and a TEV linker (ENLYFQG) between the target and the HaloTag. After transfection, cells were transfected with HaloTag ligand JF. 646(internal) and imaged using the ImageXpress system (Molecular Devices) to confirm HaloTag integration. Cells were then subjected to single-cell sorting into 384-well plates. Clonal cells were expanded, imaged using the ImageXpress system, and genotyped by Sanger sequencing to confirm uniform HaloTag integration.

[0205] Western blot Cells can be grown under the same conditions as previously described. 1.5 x 10 cells per well in DMEM medium in a 6-well plate. 6 Cells can be seeded and cultured overnight, followed by compound treatment (DMSO or 100 nM fulvestrant) for 24 hours the following day. Cells can then be lysed in 200 μL of 1X Cell Lysis Buffer (Cat. No. 9803, Cell Signaling). Protein lysate concentrations can then be determined using a BCA Protein Assay Kit (Cat. No. 23225, Pierce™ BCA Protein Assay Kit) according to the manufacturer's instructions. Capillary Western immunoassays can then be performed using Jess Protein Simple according to the manufacturer's instructions (Protein Simple, USA). Anti-target antibody levels can be normalized to the loading control β-tubulin (1:100, NC0244815LI-COR92642213, ThermoFisher). Peaks can be analyzed using Compass software (Proteinimple, USA).

[0206] OLS single molecule tracking sample preparation Cells can then be seeded into tissue-culture-treated 384-well glass-bottom plates at 4,500–6,000 cells per well. The seeded cells can then be incubated overnight at 37°C and 5% CO2 to allow for attachment. For all SMT experiments, cells were incubated with 5–100 pM JF. 549Cells can be incubated with -HTL (catalog no. GA1110, Promega) and 50 nM Hoechst 33342 in complete medium for 1 hour. Cells are then washed three times with DPBS and twice with imaging medium. The imaging medium is fluoroBrite DMEM medium (catalog no. A1896701, ThermoFisher) supplemented with GlutaMAX (catalog no. 35050079, ThermoFisher) and the same serum and antibiotics as the growth medium. If appropriate, compounds can be serially diluted in Echo-certified 384-well low-dead-volume source microplates (0018544, Beckman Coulter) to generate dose-titrated source material. Compounds can be administered at a final dilution of 1:1000 in cell culture medium. Each compound dose can be replicated at least three times per plate, with up to three plate replicates prepared consecutively. 20 DMSO control wells and two no-dye control wells can be randomized across each plate. Compounds are allowed to incubate at 37° C. for 1 hour before image acquisition.

[0207] Image acquisition Unless otherwise noted, all image acquisition using SMT was performed using a custom-built microscope, motorized stage, stage-top environmental chamber, quad-band filter cube (Chroma), and a custom-built laser engine with wavelengths of 405 nm and 561 nm at the back focal plane of the objective. Fluorescence emission was passed through a high-speed filter wheel (Finger Lakes Instruments) and collected by a backlit CMOS camera (Hammamatsu Orca Fusion, running in light sheet mode). Images were acquired with a 60x 1.27NA water-immersion objective (Nikon). The environmental chamber was set to 37°C, 95% humidity, and 5% CO2. In a specific embodiment, the exposure time for each pixel was 400 microseconds, and recording the entire region of interest (ROI) took a total of 9 milliseconds. The galvanometer scanner position was then reset within 1 millisecond, e.g., with the laser turned off, and the next image was recorded. In such an embodiment, 100 frames per second can be recorded. Additionally or alternatively, a second setup using a smaller ROI can be employed to record 200 frames per second with the same 400 microsecond / pixel exposure and 4 millisecond image recording time, allowing for faster galvo resets.

[0208] Image analysis Image acquisition yields one JF per field of view 549 A video and one Hoechst were generated. JF 549 The video is from individual JF 549It can be used to track molecular movement, and Hoechst videos can be used for nuclear segmentation. Tracking can be achieved in three sequential steps using a combination of existing methods: detection, subpixel localization, and linking. Briefly, spots can be detected using a generalized log-likelihood ratio detector. After detection, starting from an initial guess obtained by a radial symmetry method, the estimated location of each emitter can be refined to subpixel resolution using Levenberg-Marquardt fitting with a unified 2D Gaussian spot model. Detected spots can be linked into trajectories using a custom modification of the hill-climbing algorithm. The same detection, subpixel localization, and linking setup can be used for all videos.

[0209] For nuclei segmentation, all frames of the Hoechst movie can be averaged to generate an average projection. This average projection can then be segmented with a neural network trained on human-labeled nuclei. Each spot can then be assigned to at most one nucleus using its subpixel coordinates.

[0210] To recover movement information from the trajectory, state sequences can be used, e.g., with the "RBME" likelihood function and a range of 0.01 to 100.0 μm. 2 s -1A Bayesian inference approach can be used using a grid of 100 diffusion coefficients and 31 localization error magnitudes ranging from 0.02 to 0.08 μm. After inference, the localization error can be minimized to obtain a one-dimensional distribution across the diffusion coefficients for each field of view. For single-cell analysis, for example, SMT and nuclear segmentation can be performed on a mixture of U2OS cells carrying H2B-HaloTag, HaloTag-CaaX, or free HaloTag. The marginal likelihood of each set of 100 diffusion coefficients for the set of trajectories within each segmented nucleus can then be evaluated. These marginal likelihood functions can be clustered using k-means, and the marginal likelihood functions for each cell can be ordered by its cluster index to create a heatmap. The fractional boundary values ​​(f bound ) to estimate 0.1 μm 2 s -1 The posterior distribution of the state sequence can be integrated below the free diffusion coefficient (D free ) to estimate 0.1 μm 2 s -1 It is possible to calculate the mean of the posterior distribution over

[0211] Single molecule tracking method Single-molecule tracking (SMT) data were processed with a custom pipeline operating on image sequences generated by the microscope. Briefly, individual emitters were detected by applying a generalized log-likelihood ratio test to each 11 x 11 subwindow in the image, as described above (see below for the signal-to-noise ratio definition and quantification section). Emitters were detected by identifying pixels with a log-likelihood ratio greater than 14. Detected emitters were localized to subpixel accuracy in a two-step procedure. First, the subpixel location was estimated by calculating the point of maximum radial symmetry. Next, this estimate was used to apply an iterative Levenberg-Marquardt fitting routine to a 2D integrated Gaussian within an 11 x 11 pixel subwindow centered on the detection.

[0212] A modification of Sbalzerini's hill-climbing algorithm, which uses Gibbs sampling to estimate data association uncertainty, can be used to temporally link local emitters to generate trajectories. For all SMT links, links longer than 1.25 μm were prohibited for cSMT, and links longer than two gap frames were also prohibited to limit association error. Emitters were assigned to segmentation categories (nucleus, cytoplasm) by comparing their subpixel locations to the semantic mask generated by the segmentation routine.

[0213] Data analysis The tracking results from the automated processing pipeline can be analyzed using KNIME or Spotfire (TIBCO). bound or D free Measurements of f can be associated with experiment metadata and aggregated by condition. bound The change in f of each well bound f of DMSO in the same plate bound The EC value can be calculated as the difference from the median of the EC. Wells that contained no cells in the field of view or where the field of view was out of focus can be excluded from further analysis. Compounds can be assessed for assay interference using the median fluorescence intensity of the tracking channel and can be excluded if it is more than three standard deviations higher than the median intensity of the DMSO wells. Similarly, plates that fail to clearly separate the active and negative controls or that deviate significantly from the performance of the rest of the screen can be excluded from further analysis. Finally, compounds with a variance more than three standard deviations above the mean compound variance can be excluded from downstream analysis. The Z' coefficient between the active control and DMSO on a plate can be calculated. EC 50 Values ​​can be calculated in Prism (GraphPad) by first log-transforming the molecule concentrations and then fitting them to a four-parameter logistic curve.

[0214] Clustering of active molecules Chemical structure-based clustering can be performed on the molecules identified as active. Molecular frameworks can be calculated as known in the art and as implemented in pipeline pilots. Molecular frameworks can be clustered using functional class fingerprints (FCFP_4) (e.g., a similarity threshold cutoff of 0.3 Tanimoto distance).

[0215] Kinetic Experiments Cells can be seeded into 384-well plates the day before and stained and washed as described above. One well with multiple FOVs per well can be taken as a baseline reading. Compounds can then be added manually or robotically to each well to a final concentration of 100 nM during imaging. Data can then be collected for that well. Pauses can be included between each FOV to ensure the entire imaging plan covers the assay window. bound The change in can be determined for each well relative to t=0.

[0216] For assays lasting 4 hours, the plate can be imaged twice using multiple FOVs at different FOV positions per well to prevent photobleaching from affecting the data.

[0217] Dwell time imaging Sample preparation and execution of dwell time imaging experiments can be performed in a similar manner to the single molecule tracking assay described above, with a few exceptions. Samples should be 1-10 pMJF. 549 Staining can be performed with 50 nM Fluorescence Intensity Imaging (Promega) and 50 nM Fluorescence Intensity Imaging (Promega) with 50 nM Fluorescence Spectroscopy (50 nM Fluorescence Intensity Imaging) for 1 hour. Multiple frames can be collected per field of view by setting the camera integration time to the desired time (milliseconds) and reducing the laser light source to the desired mW at the objective lens. The laser can be turned on continuously during image acquisition. Compound incubation can range from 1 to 4 hours.

[0218] Residence time analysis Image processing, including spot detection, localization, and tracking reconnection, may be performed using the same methods described above. Because dwell-time imaging selectively tracks slow-diffusing molecules, individual localizations can be limited to the maximum displacement distance of individual jump reconnections. The set of trajectories for each field of view is binned into a 1-CDF distribution as described above and fitted with a biexponential decay model.

number

[0219] Fluorescence recovery after photobleaching Images can be acquired with a custom-built OLS microscope using a Spectra Light Engine RS-232 as described herein, for example, in Example 1. Stimulation can be performed directly using a mini-scanner combined with a Coherent OBIS 561 nm 100 mW laser. All imaging can be performed using a 60x 1.27 NA water immersion objective (Nikon). All experiments can be performed at 37°C. For FRAP experiments, cells are seeded the day before in 384-well plates and irradiated with 50 nM HTL-JF. 549 The cells can be labeled with ATP and washed as described above. Compounds can be added to a final concentration of 100 nM before imaging. Pre-bleaching images can then be obtained by averaging 10 consecutive images. Next, 8-10 regions can be bleached (two background, six-eight cells), and two regions within the cells can be left unbleached. The bleached regions are then bleached at 10% power without scanning. For the next 30 seconds, images can be acquired every 200 ms, then every 1 second for 2 minutes. The background-subtracted average intensity can be measured over time in the region of interest and normalized to the average fluorescence in the baseline image, which can then be normalized to the unbleached region to account for readout-induced photobleaching of the fluorophore. For three biological experiments, data from multiple cells per experiment can be pooled.

[0220] HILO microscopy SMT image acquisition of the HILO dataset was performed on a custom-built microscope based on a Nikon Ti2, motorized stage, stage-top environmental chamber (OKO Laboratory), a quad-band filter cube (Chroma), and custom laser launch at 405 nm and 561 nm wavelengths, delivering >10 mW and >150 mW of power, respectively, to the back focal plane of the objective. Fluorescence emission was passed through a high-speed filter wheel (Finger Lakes Instruments) and collected with a backlit sCMOS camera (ORCA-FusionBT, Humana). Images were acquired with a 60x 1.27 NA water-immersion objective (Nikon). The environmental chamber was set to 37 °C, 95% humidity, and 5% CO2. For each field of view, 150 SMT frames were collected at a frame rate of 100 Hz using a 2 ms strobe laser pulse.

[0221] Trajectory measurement When reporting the number of trajectories, singlets (trajectories containing one detection) were excluded because they contribute little information to the dynamic estimates.

[0222] The average diffusion coefficient was calculated using the mean square displacement method (D est =MSD 2D / 4Δt). This estimate is σ loc 2 It is expected to overestimate the diffusion coefficient by / Δt, where σ loc 2 is the variance of the 1D localization error and Δt is the frame interval.

[0223] To resolve the trajectories of multiple dynamic states, the coefficients of a Brownian motion mixture model on a grid of diffusion coefficient values ​​and localized error values ​​were inferred using state ordering, a variational Bayesian routine based on Dirichlet process mixtures. The components of the mixture ranged from 0.01 to 100 μm. 2The variances were chosen as the direct product of 100 diffusion coefficients in logarithmic intervals of 1 / s and 31 localization error values ​​ranging from 0.02 to 0.08 μm (1D standard deviation). Occupancy is reported as the average posterior probability of each diffusion coefficient marginalized over all values ​​of localization error. To ensure reliable inference, we restricted the inference to 10,000 trajectories randomly sampled from each well.

[0224] Bias estimation for a single population sample was performed using analytical calculations that capture the probability of false links due to a finite search radius and truncation of the jump length distribution.

[0225] Empirical Estimation of Link Accuracy To estimate the accuracy of the linking algorithm, we used a bootstrap procedure. We overlapped detections from the first and second halves of the video and ran the tracking algorithm on the resulting set of detections, blinded to the origin of each detection. From this, we calculated the proportion of links generated, combining individual detections from different halves of the video. This proportion does not account for erroneous links between detections in the same half of the video, nor does it account for the effects of photobleaching, so this proportion forms a lower bound on the link error rate (ERLB).

[0226] Defining and Quantifying Signal-to-Noise Ratio The signal-to-noise ratio (SNR) is defined based on the likelihood ratio in the following hypothesis test: in the absence of a target, the local image is modeled as the sum of a constant offset and independent Gaussian noise, and in the presence of a target, the local image is modeled as the sum of a centrally located Gaussian peak (of known width but unknown amplitude), independent Gaussian noise, and a constant offset. SNR is expressed as:

number

number

number

[0227] D. Discussion Collectively, these results highlight the robustness and reproducibility of SMT measurements performed using OLS illumination within a large FOV. These results further demonstrate the superior performance of OLS compared to HILO when characterizing the motion of fast-moving proteins at high labeling densities. These data demonstrate how OLS, as a novel illumination scheme, enhances several properties of SMLM- and SMT-based techniques. Compared to the established technique HILO, OLS offers a large FOV, finer sectioning capabilities, and superior SNR, uniform illumination, and high spatiotemporal resolution. By reporting results from OLS illumination modules implemented on four different microscopes, we demonstrate the robustness of OLS and the consistent reproducibility of the resulting results. This robustness enables SMT measurements to be performed independently of any microscope to test large compound libraries for drug screening. Furthermore, the improved ability to filter out out-of-focus light improves single-molecule detection and localization, making OLS suitable for performing SMT on a variety of cellular systems and protein targets where background fluorescence was previously a limitation. Consistent with this idea, spheroid cultures from immortalized cancer cells using OLS achieved high SNR SMT results in more complex cell systems.

[0228] Example 3: OLS enables rapid SMT data acquisition and enables tracking of fast-migrating proteins This example demonstrates the impact of higher frame rate acquisition on improving the assay window and key imaging metrics of the OLS system of Example 1.

[0229] A. Results Considering the range and specificity of protein motion in live cells, we hypothesize that an optimal set of acquisition parameters exists for a particular protein of interest. Frame rate correlates with other experimental factors, such as localization and tracking errors, and determines the information recoverable from SMT (Figures 16A and 16B). To understand these effects, we performed optical dynamics simulations using complex mixtures of Brownian motion (Figure 16C) and then performed tracking on these simulated videos. We observed that increasing the frame rate improved both the average track length and tracking fidelity, with the sampled FOV size being the only obvious compromise (Figure 16D). We then estimated the underlying dynamical model for each simulation using state sequence analysis, a variational Bayesian method for recovering mixture models from observed trajectories. Increasing the frame rate improved the recovery of fast states but ultimately degraded the recovery of slow states (Figure 16E). We also observed that the lower and upper bounds on the mean squared displacement (MSD) estimate of the diffusion coefficient, determined by the localization error on the one hand and the search radius used for tracking on the other, roughly approximate this dynamic range (Figure 16E, green dotted line). These results suggest that an adjustable frame rate is a highly desirable property of SMT imaging systems.

[0230] For the experimental Halo-KEAP1 system described in Example 2, OLS-enabled SMT was performed at frame rates ranging from 100 to 1250 Hz (Figure 15A). Similar to the simulation results, both the average trajectory length and estimated link accuracy improved with increasing frame rate (Figures 17A and 17C). Furthermore, the OLS illuminator achieved this without a decrease in the average SNR (Figure 17B) or bleaching rate per frame (Figure 19). When performing state sequence analysis, faster motion was recovered with increasing frame rate, with estimates of approximately 9 μm for DMSO-treated Halo-KEAP1 at 400 Hz. 2 / s, and for KI-696-treated Halo-KEAP1, the estimated value was approximately 14 μm 2 The frame rate stabilized at 1 / s (Figure 18, Figure 15B). Interestingly, we noted that 400 Hz may represent a point of diminishing returns, potentially being an appropriate sampling frequency for capturing the fast-diffusing subset of KEAP1 under both DMSO and KI-696 treatments (Figure 15B). Furthermore, we simulated the measured diffusion coefficients of Halo-KEAP1+ / -KI-696 treatments at various frame rates, and the simulations closely matched the measurements (Figure 15C). Together, these results demonstrate that OLS line scanning can be used to increase frame rates, enabling accurate measurements of fast protein diffusion in cellular environments. While 400 Hz appears to be an appropriate sampling rate for KEAP1, other important biochemical processes in live cells are expected to be adequately captured only at significantly higher frame rates.

[0231] method SMT dynamic range estimation To estimate the effect of frame rate on the SMT dynamic range (as shown in Figures 15C and 16), we calculated the diffusion coefficient (

number

number

number

number

number

number

[0232] Optical-mechanical simulation To evaluate the tracking methodology and the effect of frame rate on the dynamic range of the SMT, optical-mechanical simulations were performed. These simulations applied a scalar diffraction approximation to a paraxial imaging system with NA = 1.2. Briefly, a discrete mixture of Brownian motion without state transitions was simulated in a 45 × 45 × 8 μm (XYZ) cube at frame rates of 12.5, 25, 50, 100, 200, 400, 800, or 1600 Hz. Particles were initialized at a density of 0.31 or 0.62 particles per cubic micron (depending on the simulation) and underwent photobleaching with a probability of 0.03 per frame. Particle positions coincident with 500 μs pulses (modeling strobe illumination in HILO or a rolling shutter in OLS) were accumulated on a simulated 2D camera via convolution with the system's 3D point difference function. This yielded a probability distribution of photon arrivals across all simulated camera pixels. Next, photons arriving from this distribution as a Poisson process were sampled to an average of 90 or 125 photons per particle (depending on the simulation). Finally, a Gaussian read noise of 3 photons RMS was added, multiplied by a gain factor of 4.3 counts per photon, and the video was discretized to 16 bits. This video was then subjected to tracking and state sequence inference with settings identical to those used for Halo-KEAP1 tracking.

[0233] Consideration OLS allows for frame rates of at least 1250 Hz without compromising SNR and tracking fidelity. A frame rate of 400 Hz is required to fully characterize the increased diffusion of drug-induced release from NRF2, as shown with Halo-KEAP1. It is anticipated that there are many biological processes involving rapid protein motion that were previously unmeasurable with other SMT illumination methods. OLS offers the opportunity to address novel protein and cellular mechanisms that may occur on the submillisecond scale.

[0234] Example 4: OLS captures cell-to-cell heterogeneity in single protein dynamics This example demonstrates that the OLS system of Example 1 can be used to analyze cell-to-cell heterogeneity in a sample.

[0235] result When assessing the consistency of SMT measurements, cell-to-cell heterogeneity was found to be the highest source of variability, exceeding FOV, well, plate, or microscopic variations. Cell-to-cell bias was at least one order of magnitude greater than FOV-to-FOV or well-to-well bias (Figures 25A-25B). This strongly suggests that biological heterogeneity dominates over technical variability in OLS-based SMT measurements (Figure 20A). Examples of cellular heterogeneity include cell cycle, cellular stress state, and genetic mutations. Single-cell measurements, such as large-FOV SMT, may enable more nuanced measurements to better understand such heterogeneity. This example illustrates such single-cell analysis by measuring the effect of the cell cycle on the dynamics of the proliferating cell nuclear antigen (PCNA) protein. PCNA is involved in DNA replication and relocalizes to replication foci during S phase, thus exhibiting distinct and specific protein dynamics throughout the cell cycle.

[0236] Halo-PCNA was introduced into U2OS isolates expressing the tagged protein at sub-endogenous levels (Figures 22A and 22B), and growth rates were found to be unaffected by Halo-PCNA expression (Figure 22C). The proper localization of Halo-PCNA was confirmed by colocalization analysis with an RFP-labeled anti-PCNA nanobody (Figure 22D).

[0237] To achieve near-saturating labeling, 50 nM JFX 650Time-lapse microscopy was performed on Halo-PCNA-labeled cells at 12 frames per hour for 12 hours (Figure 21A). Next, we used both the manually assigned cell stages and the time-based progression to train a machine learning model, achieving both G1, early S, mid S, late S, G2, and mitosis classifications, as well as regression predictions across the cell cycle continuum (Figure 21B). The predicted cell cycle classifications performed better than the manual annotations (Figure 21C). When the regression predictions were plotted over time, a clear progression of individual cells through the cell cycle was observed (Figure 21D). To further validate the cell cycle stage assignment model, we inhibited cell cycle progression at S phase with thymidine or the G2-M transition with the CDK-1 inhibitor RO-3306. Both treatments are expected to enrich the proportion of cells assigned to the respective cell phases (Figures 20B and 20C). Cells were then treated with 10 pM JF. 549 and 50nM of JFX 650 These cells were labeled with 0.043 and 9.88 mm m , which, combined with SMT measurements, allowed simultaneous cell cycle assignment based on near-saturating labeling. 2 / s, which likely represent PCNA bound to DNA replication sites and free PCNA, respectively (Figure 20D). Individual analysis of cells at each cell phase revealed that the slow-moving population of PCNA was found exclusively in cells predicted to be in S phase, while the fast-moving population was significantly reduced (Figure 20E). Next, we measured the average diffusion coefficient of PCNA for 4,081 individual cells to characterize the heterogeneity across the cell population, which is primarily explained by the cell cycle (Figure 20F). Together, these data demonstrate how the wide FOVSMT enabled by OLS can capture and elucidate cellular heterogeneity in protein dynamics.

[0238] B. Method Cell line engineering of CRISPR knock-in Halo-tagged proteins All U2OS cells were cultured in Dulbecco's modified Eagle's medium (DMEM) (gibco) supplemented with 10% fetal bovine serum (Corning), 100 units / mL penicillin, and 100 μg / mL streptomycin (Gibco) at 37°C and 5% CO .

[0239] To generate HaloTag-PCNA cell lines, ribonucleoprotein (RNP) complexes containing sgRNA (Integrated DNA Technologies, IDT) targeting either the N- or C-terminal region and the Cas9 protein (PNA bio, catalog number CP01) were transfected into linear dsDNA donors (IDT) using the Lonza nucleofection method. Each donor consisted of 200–300 bp homology arms specific for each target, a codon-optimized HaloTag sequence, and a TEV linker (ENLYFQG) between the target and the HaloTag.

[0240] After transfection, cells were treated with Halo ligand JF 646 (internal) and imaged using the ImageXpress system (Molecular Devices) to confirm HaloTag integration. Cells were then subjected to single-cell sorting into 384-well plates. Clonal cells were expanded, imaged using the ImageXpress system, and genotyped by Sanger sequencing to confirm uniform HaloTag integration.

[0241] B cell proliferation Cell proliferation in 6-well plates. Cells were seeded at 150,000 cells / well in 6-well plates (FisherScientific, 07-200-83) and allowed to settle uniformly for 20 minutes at room temperature. Plates were imaged in an Incucyte (Sartorius) system, acquiring nine images per well every 4 hours. A phase-masking algorithm was applied to determine cell confluence using Incucyte software v.S32019A.

[0242] c. Western blot analysis Protein was extracted from 1 to 2 million cells by diluting 1x Cell Lysis Buffer (CST, #9803) with UltraPure sterile water (Intermountain Life Sciences, 20804225) containing 1x Halt protease and phosphatase inhibitor cocktail (ThermoFisherScientific, 78440). Samples were collected using a cell scraper (FisherScientific, 08-100-241), placed on ice for 15 minutes, and then centrifuged at 15,000 RPM for 10 minutes. The supernatant was transferred to a new tube. Protein concentration was measured using the Pierce BCA Protein Assay Kit (ThermoFisherScientific, A55864) according to the manufacturer's protocol. Samples were run on the automated Western blot system Jess (ProteinSimple, 004-650) according to the manufacturer's protocol. The 12–230 kDa separation module was used for the detection of PCNA (CST, D3H8P, rabbit, 1:100 dilution, #13110), b-actin (CST, D6A8, rabbit, 1:50 dilution, #8457S), and Halo (Promega, mouse, 1:10 dilution, #G9211). Samples were diluted to 0.3 mg / mL with 0.1x lysis buffer and 5x master mix, heat denatured at 95°C for 5 min, and all primary antibodies were diluted in antibody diluent 2. All reagents were loaded into a microplate, and the 13-capillary cartridge was loaded into a Jess Western blot instrument. Run parameters were set using COMPASS software v6.0.0 (ProteinSimple). Bands corresponding to each protein were visualized using COMPASS software, and bands were normalized to the loading control, b-actin.

[0243] d. Machine Learning Architecture The cell cycle as described above can be visualized by images (e.g., JF 549The label can be automatically determined using the image of PCNA labeled with . A machine learning model, such as a neural network based on the U-Net architecture, can be trained to assign a label to each pixel (Figures 21A-21D). The decoder in this architecture can include a set of three independent decoders D = {D1, D2, D3}. The encoder E consumes the image. θ While is shared across D, each decoder can be configured with a different set of parameters and trained to perform three different tasks: 1) nucleus segmentation, 2) cell cycle classification, and 3) cell cycle regression. The network can be trained end-to-end using three different loss averages targeting these three tasks.

[0244] Each loss can be based on the class-balanced cross-entropy defined as:

number

[0245] The first loss may optimize the nuclei segmentation task, where the input x representing a 2D image of fluorescently labeled PCNA may be defined as: L segmentation =CB softmax (D1(E θ (x)), y1) Here, D1(E θ (x)) generates pixel-level predictions of three classes: nucleus, nuclear rim, and background.

[0246] The second loss can optimize the cell cycle classification task and can be defined as: L classification =CB softmax(D2(E θ (x)), y2) Here, D2(E θ (x)) generates pixel-level predictions for seven classes: background, mitosis, G1, early S, meta S, late S, and G2.

[0247] To represent cell cycle categories (M, G1, early S, mid S, late S, G2) continuously, a target encoding method can be used to linearly order the categories from 0 to 1, assigning 0 to cells classified as M and 0.8 to cells classified as G2. To minimize the complexity of aggregating the three losses, the regression task can be trained similarly using cross-entropy. The regression decoder D3 can generate two outputs, and the training data can be represented using a two-value vector (λ, 1-λ), where λ represents the cell cycle value between 0 and 1. A third loss can be used to optimize the cell cycle regression task and can be defined as follows: L regression =CB softmax (D3(E θ (x)), y3)

[0248] Finally, the total loss of the network is the average of these three losses.

number

[0249] Once the model is trained, nuclear segmentation can be performed and either a categorical or continuous representation of the cell cycle can be assigned to each nucleus based on the average pixel value that defines each nucleus.

[0250] e. Assessing the largest sources of variation from experiments: Jump resampling experiments To assess the contribution of well-to-well, FOV-to-FOV, and cell-to-cell biases to the estimated average 2D jump length, JF 549Full-plate (308-well) HILO and OLS data were acquired at 100 Hz using DMSO-treated KEAP1-HaloTag labeled with . After excluding the outer ring of wells in the 384-well plate, this resulted in a dataset containing 308 wells, 12 FOVs per well, and an average of approximately 44 cells per FOV (for OLS) or approximately 15 cells per FOV (for HILO). A simple model of jump length was considered: Let Y be the observed 2D jump length, and Y was modeled as the sum of: Y=Bwell+BFOV+Bcell+X B well , B FOV , and B cell is a random variable that models bias at the well, FOV, or cell level, and X models the inherent stochasticity of the jump length conditional on a particular well, FOV, and cell. well , B FOV , B cell , and X are assumed to be independent. In this simplification, Var(Y)=Var(B well )+Var(B FOV )+Var(B cell ) + Var(X). A more physically realistic model takes into account potential dependencies between these random variables.

[0251] Var(B well ), Var(B FOV ), Var(B cell ), and to estimate Var(X), we calculated the variance of the sample means for four different jump resampling schemes. Sample N jumps across the plate. The resulting sample average is calculated based on all sources of variation (B well , B FOV , B cell , and X). A well is sampled, then N jumps from that well are sampled. The resulting sample average is B FOV , B cell, and X, and the variance of these sample means increases as N increases. well ) is expected to approach Sample a well, then sample an FOV from that well, then sample N jumps from that FOV. The resulting sample average is B cell , and X, and the variance of these sample means increases as N increases. well )+Var(B FOV ) is expected to approach Sample a well, sample an FOV from that well, sample a cell from that FOV, sample N jumps from that cell. The resulting sample mean is the average of just X. The variance of these sample means decreases as N gets larger, Var(B well )+Var(B FOV )+Var(B cell ) is expected to approach

[0252] We performed 1000 samples for each resampling method, and the bias B was calculated based on the difference between the variances of the sample means generated by each resampling method. well , B FOV , and B cell As expected, only Var(X) depended on the sample size N, while the other sources of variation were stable with sample size after about 100 jumps (Figures 25A-25B).

[0253] Consideration This analysis suggests that the greatest source of variability in SMT measurements stems from cellular heterogeneity in protein movement. The large FOV enabled by OLS allows for simultaneous capture of more than 50 U2OS cells in culture, enabling capture of cell-to-cell heterogeneity. This was demonstrated for PCNA, where it was possible to simultaneously assign cell cycle phases while monitoring protein dynamics. These results clearly show that PCNA protein dynamics slows during S phase, which correlates with the protein's enrichment at DNA replication sites. A sharp increase in dynamics was observed during G1, G2, and M phases, corresponding to the uniform distribution of PCNA throughout the nucleus. These findings are consistent with previous characterizations of PCNA dynamics, but the approach presented here offers important improvements. Cell cycle phases were computationally predicted through a machine learning model using PCNA localization rather than manual assignment. Furthermore, the OLS platform now allows for rapid, automated capture and analysis of thousands of cells per condition, rather than the tens of cells typically analyzed using manual SMT approaches. When characterizing protein movement in heterogeneous cell populations and potentially rare cell subtypes, automated cell sorting and scaled SMT data collection and analysis will be critical to enable work comparable to flow cytometry and other single-cell analysis techniques.

[0254] Example 5: OLS is suitable for various SMLM techniques and acquisition schemes This example provides an extension of the applications using the OLS system of Example 1 to take advantage of OLS's advantages of uniform illumination, robustness, high spatiotemporal resolution, and imaging speed.

[0255] result The uniform illumination, high spatiotemporal resolution, imaging speed, and overall robustness of the OLS system may have broad benefits across multiple biological microscopy techniques. To demonstrate the ability to image SMTs across two spectrally distinct fluorophores, we used JF 549 and J.F.646 Halo-Keap1 time series labeled with both KI-696 and KI-696 were captured consecutively, resulting in clear single-molecule resolution across both wavelengths (Figure 23A). KI-696 was dose-titrated and the response was monitored using JF. 549 and J.F. 646 We measured both labeled Halo-Keap1 and the sCMOS signal, demonstrating the ability to measure changes in protein motion across two wavelengths (Figure 23B). Despite the reduced SNR due to the reduced sCMOS quantum efficiency in the far-red spectrum (Figure 24A), the SMT data were consistent with the red-shifted JF 646 The brighter JF 549 EC that matches the dye very well 50 The measured EC 50 are JF 549 4.96nM, JF 646 The yield of OLS-based SMT was 6.45 nM at 100 kJ / s. The robust measurement of protein dynamics with low SNR is potentially explained by the negligible decrease in the error rate lower bound (ERLB) (Figure 24B). Taken together, OLS-based SMT has great potential for multicolor imaging, facilitating the imaging of low quantum yield fluorophores and broadening the palette of fluorophores available for measuring protein motion across biological applications.

[0256] Due to the short integration time provided by OLS line scanning, we investigated whether dyes typically used for STORM imaging in fixed cells could produce images with high x,y resolution across a large FOV. Cells labeled with an anti-tubulin primary antibody and an AlexaFluor 647 (AF647)- or CF568-conjugated secondary antibody were imaged using STORM over a 60x full field of view with a total imaging time of approximately 60 seconds (Figures 23C-23F). Despite the short integration time of 400 μs used by OLS, we observed that spontaneous photoswitching ensured that a sufficient number of photons were collected, allowing for a lateral localization precision of approximately 15 nm using either AF647 or CF568 (Figures 23G and 23H). These results demonstrate the feasibility of conducting high-throughput phenotypic screening using STORM or other super-resolution microscopy techniques with OLS illumination.

[0257] Next, we utilize the line scan component of OLS to 549 Correlated SMT / FRAP experiments were performed on Halo-KEAP1 cells treated with KI-696 labeled with NF-kappa B. Before acquiring the full FOV with regular SMT acquisition, a 240x40µm region was bleached by focusing the scan area on a narrow subset of the FOV for 100-200 sweeps. This resulted in each frame consisting of a bleached region (FRAP region) and an unbleached region (Figure 23I). Instead of capturing intensity recovery over time after photobleaching, we measured normalized spot density after recovery (Figures 23K and 23L). 549 Average T at dye concentration 400pM 1 / 2 (DMSO) was 3.52 (SD=0.38), T 1 / 2The KI-696 (KI-696) was measured at 2.27 (SD = 0.43), which appears to be optimal for separating the two conditions (Figure 23J). This result is consistent with the reported SMT measurements, indicating that KI-696 significantly increases the local protein dynamics of Halo-KEAP1. To further confirm the consistency of the FRAP measurements, SMT was applied to both bleached and unbleached regions of the FOV. In both cases, an increase in Halo-KEAP1 dynamics was measured over a range of 1 µM KI-696 dye concentrations (Figures 23M and 24C). These results highlight and confirm that the advantageous properties provided by OLS, combined with the proposed tracking algorithm, enable highly sensitive spot detection and SMT.

[0258] method 384-well plate coating and cell seeding for SMT Cells were seeded at 40...

Claims

1. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ A method for determining whether a compound reduces (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence, the method further comprising: (c) determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

2. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ A method for determining whether a compound reduces (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells, wherein the subset of the target fluorescent proteins generates up to about 1,000,000 molecular trajectories within a single detection field, and said tracking further comprises: (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within the detection field of view at the sample plane, wherein the detection field has a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and the method is adapted to selectively detect localized fluorescence, and the method further comprises: (c) determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

3. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ A method for determining whether a compound reduces (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence compared to dynamic fluorescence, the method further comprising: (c) determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

4. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ A method for determining whether a compound reduces (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within a detection field of view at the sample plane, wherein the detection field has a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and 95% or more of the detection field achieves sufficient laser illumination to track protein motion, the method being adapted to selectively detect localized fluorescence, and the method further comprising: (c) determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

5. The detected change in motion indicates the binding state (f ｂｏｕｎｄ 5. The method of claim 1, wherein the increase in immobility loci indicates an increase in the occupancy or duration of immobility loci.

6. The detected change in movement may be (a) Median of the jump length distribution, (b) the third quartile of the jump length distribution; (c) median radius of gyration; (d) Mean posterior diffusion coefficient, (e) Geometric mean posterior diffusion coefficient, (f) mean square displacement, (g) median bond angle; (h) maximum likelihood estimator of the diffusion coefficient; and / or (i) State occupation by inference; The method according to any one of claims 1 to 4, wherein the change is

7. The method of any one of claims 1 to 4, wherein the target fluorescent proteins interact within a larger molecular assembly.

8. The method of claim 7 , wherein the target fluorescent protein is a ligand.

9. The method of claim 7 , wherein the target fluorescent protein is a receptor.

10. The method according to any one of claims 1 to 4, wherein the biological interaction is a direct interaction.

11. The method of claim 10 , wherein the direct interaction comprises binding of the compound to the target fluorescent protein.

12. The method according to any one of claims 1 to 4, wherein the biological interaction is an indirect interaction.

13. The method of claim 12 , wherein the indirect interaction involves the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

14. The dose of a compound that induces a change in the binding of a target fluorescent protein in living cells is determined by determining whether the compound induces a change in the K ｏｆｆ a method for determining whether a (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence, the method further comprising: (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

15. The dose of a compound that induces a change in the binding of a target fluorescent protein in living cells is determined by determining whether the compound induces a change in the K ｏｆｆ by determining whether the (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells, wherein the subset of the target fluorescent proteins generates up to about 1,000,000 molecular trajectories within a single detection field, and said tracking further comprises: (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within the detection field of view at the sample plane, wherein the detection field has a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and the method is adapted to selectively detect localized fluorescence, and the method further comprises: (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

16. The dose of a compound that induces a change in the binding of a target fluorescent protein in living cells is determined by determining whether the compound induces a change in the K ｏｆｆ a method for determining whether a (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), the method being adapted to selectively detect localized fluorescence, the method further comprising: (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

17. The dose of a compound that induces a change in the binding of a target fluorescent protein in living cells is determined by determining whether the compound induces a change in the K ｏｆｆ a method for determining whether a (a) contacting a sample comprising a population of live cells with the compound, wherein the live cells comprise the target fluorescent protein, the method further comprising: (b) tracking the movement of individual target fluorescent proteins in a plurality of the cells in the sample, wherein the tracking includes: (i) illuminating a field of view in a sample plane disposed within the sample with a light beam to induce fluorescence by at least a subset of the target fluorescent proteins in the living cells; (ii) detecting, via a detector device, the fluorescence from one or more of the target fluorescent proteins within a detection field of view at the sample plane, wherein the detection field has a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and 95% or more of the detection field achieves sufficient laser illumination to track protein motion, the method being adapted to selectively detect localized fluorescence, and the method further comprising: (c) determining a dose by determining a change in the movement of the target fluorescent protein in the presence of the compound; An increase in the signal detected from the target fluorescent protein in the presence of the compound compared to the signal from the target fluorescent protein in the absence of the compound indicates that the compound has activated the K ｏｆｆ This indicates that the The method.

18. The change in motion that is detected is called binding (f ｂｏｕｎｄ 18. The method according to any one of claims 14 to 17, wherein the increase in immobile loci indicates an increase in the target fluorescent protein.

19. The detected change in movement may be (a) Median of the jump length distribution, (b) the third quartile of the jump length distribution; (c) median radius of gyration; (d) Mean posterior diffusion coefficient, (e) Geometric mean posterior diffusion coefficient, (f) mean square displacement, (g) median bond angle; (h) maximum likelihood estimator of the diffusion coefficient; and / or (i) State occupation by inference; The method according to any one of claims 14 to 17, wherein the change is

20. The method of any one of claims 14 to 17, wherein the target fluorescent proteins interact within a larger molecular assembly.

21. 21. The method of claim 20, wherein the target fluorescent protein is a ligand.

22. 22. The method of claim 21, wherein the target fluorescent protein is a receptor.

23. The method according to any one of claims 14 to 17, wherein the biological interaction is a direct interaction.

24. 24. The method of claim 23, wherein the direct interaction comprises binding of the compound to the target fluorescent protein.

25. The method according to any one of claims 14 to 17, wherein the biological interaction is an indirect interaction.

26. 26. The method of claim 25, wherein the indirect interaction comprises the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

27. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ 1. A microscope system configured to determine whether to reduce (a) a stage for supporting a sample, the sample comprising a population of cells, the cells comprising the target fluorescent protein, the microscope system further comprising: (b) a light source that emits a light beam capable of inducing a light-based response from a plurality of the target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in the sample plane, wherein the subset of target fluorescent proteins in the sample is positioned within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and the microscope system further comprises: (d) a detector device that monitors the light-based response from the target fluorescent protein in the presence of the compound; and (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining the change in the movement of the target fluorescent protein in the presence of the compound. The microscope system.

28. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ 1. A microscope system configured to determine whether to reduce (a) a stage for supporting a sample, the sample comprising a population of cells, the cells comprising the target fluorescent protein, the microscope system further comprising: (b) a light source that emits a light beam capable of inducing a light-based response from a plurality of the target fluorescent proteins in the sample; and (c) an objective lens that focuses the light beam onto the sample in the sample plane, wherein the subset of target fluorescent proteins in the sample is positioned within a detection field of view at the sample plane, the subset of target fluorescent proteins generating up to about 1,000,000 molecular trajectories within a single detection field, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and the microscope system further comprises: (d) a detector device that monitors the light-based response from the target fluorescent protein in the presence of the compound; and (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining the change in the movement of the target fluorescent protein in the presence of the compound. The microscope system.

29. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ 1. A microscope system configured to determine whether to reduce (a) a stage for supporting a sample, the sample comprising a population of cells, the cells comprising the target fluorescent protein, the microscope system further comprising: (b) a light source that emits a light beam capable of inducing a light-based response from a plurality of the target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in the sample plane, wherein the subset of target fluorescent proteins in the sample is positioned within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and the microscope system further comprises: (d) a detector device that monitors the light-based response from the target fluorescent protein in the presence of the compound; and (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining the change in the movement of the target fluorescent protein in the presence of the compound compared to the absence of the compound. The microscope system.

30. A compound that induces a change in the binding of a target fluorescent protein in a living cell is a compound that induces a change in the K ｏｆｆ 1. A microscope system configured to determine whether to reduce (a) a stage for supporting a sample, the sample comprising a population of cells, the cells comprising the target fluorescent protein, the microscope system further comprising: (b) a light source that emits a light beam capable of inducing a light-based response from a plurality of the target fluorescent proteins in the sample; and (c) an objective lens for focusing the light beam onto the sample in the sample plane, wherein the subset of target fluorescent proteins in the sample is positioned within a detection field of view at the sample plane, the detection field having a size of a first dimension (about 150 μm to about 250 μm) by a second dimension (about 100 μm to about 210 μm), and 95% or more of the detection field achieves sufficient laser illumination to track protein motion, and the microscope system further comprises: (d) a detector device that monitors the light-based response from the target fluorescent protein in the presence of the compound; and (e) a memory; and (f) a processor in communication with the memory and the detector device, wherein the processor is capable of determining the change in the movement of the target fluorescent protein in the presence of the compound. The microscope system.

31. The change in motion that is detected is called binding (f ｂｏｕｎｄ 31. The system according to any one of claims 27 to 30, wherein the increase in immobile loci indicates an increase in the target fluorescent protein.

32. The detected change in movement may be (a) Median of the jump length distribution, (b) the third quartile of the jump length distribution; (c) median radius of gyration; (d) Mean posterior diffusion coefficient, (e) Geometric mean posterior diffusion coefficient, (f) mean square displacement, (g) median bond angle; (h) maximum likelihood estimator of the diffusion coefficient; and / or (i) State occupation by inference; The system according to any one of claims 27 to 30, wherein the change is

33. The system of any one of claims 27 to 30, wherein the target fluorescent proteins interact within a larger molecular assembly.

34. 34. The system of claim 33, wherein the target fluorescent protein is a ligand.

35. 34. The system of claim 33, wherein the target fluorescent protein is a receptor.

36. The system according to any one of claims 27 to 30, wherein the biological interaction is a direct interaction.

37. 37. The system of claim 36, wherein the direct interaction comprises binding of the compound to the target fluorescent protein.

38. The system according to any one of claims 27 to 30, wherein the biological interaction is an indirect interaction.

39. The system of claim 38, wherein the indirect interaction comprises the compound exerting an agonistic or antagonistic effect on a larger molecular assembly that includes the target fluorescent protein.

Images