Method for analysis of asynchronous activity patterns in two- and three-dimensional cell cultures

Abstract

The disclosure provides methods for analysis of asynchronous activity in a cell culture sample, such as neuronal or retinal organoids. The method includes selecting one or more regions of interest in cell culture sample images; and extracting time-dependent patterns for the standard deviation of fluorescence intensity in the regions of interest for characterization of asymmetric activity.

Description

METHOD FOR ANALYSIS OF ASYNCHRONOUS ACTIVITY PATTERNSIN TWO- AND THREE-DIMENSIONAL CELL CULTURESCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority to U.S. Provisional Application No. 63 / 677,661 filed July 31, 2024, the disclosure of which is herein incorporated by reference in its entirety.BACKGROUND

[0002] Random or asynchronous activity exhibited by different cells and cell clusters is a commonly observed phenotype with neuronal 2D cultures and iPSC- derived 3D neuronal organoids. There have been challenges in analyzing patterns of asynchronous functional activity in neuronal organoids, retinal organoids, and immature cardiac organoids, and the like. In some cases, organoid average fluorescence intensity over time tends to cancel itself out or does not provide sufficient information necessary for analysis. It has been problematic to analyze asynchronous patterns and provide quantitative measurements reflecting changes in cell activity, disease models, compounds effects, and differences between various genetic phenotypes.SUMMARY

[0003] Methods for analysis of asynchronous activity patterns in two- or three- dimensional neuronal and retinal cell cultures are provided.

[0004] The disclosure provides methods for analysis of asynchronous activity in a cell culture sample including selecting one or more regions of interest in the 2D or 3D cell culture sample, and extracting time-dependent patterns to obtain the standard deviation of fluorescent intensity over time. The method allows visualization of spikes in activity and helps characterize the functional activity and characterize the patterns of a multiplicity of spikes, including number of spikes, frequency, amplitude, main peak amplitude, linear decay slope, main peak interval, early afterdepolarization-like event (EAD-like) intervals, rise slope, EAD-like event amplitude, decay slope, calcium-transient duration (CTD), calcium transient duration from peak position (CTDP90), start of an event, main peak, early afterdepolarization-like event (EAD-like), and the like. Different samples can be compared using this method, which can comprise disease models, gene modification, compound effects, toxicity effects, and the like.

[0005] A method for analysis of asymmetric activity patterns in a cell culture sample is provided, the method comprising staining a cell culture sample in a well plate with a fluorescent dye; acquiring a plurality of time-lapsed images of the stained cell culture sample using a digital imaging device comprising confocal imaging microscopy; selecting one or more regions of interest in the stained cell culture sample images; extracting time-dependent patterns for the standard deviation of fluorescence intensity in the regions of interest; and analyzing the time-dependent patterns for the standard deviation of fluorescence intensity in the regions of interest to characterize the asymmetric activity patterns in the cell culture sample. In some cases, the staining comprises permeating the cell culture sample with the fluorescent dye. In some cases, the cell culture sample is a multicellular cell culture sample.

[0006] A method for analysis of asymmetric activity patterns in a cell culture sample is provided, the method comprising permeating a cell culture sample in a well plate with a fluorescent dye; acquiring a plurality of time-lapsed images of the permeated cell culture sample using a digital imaging device comprising confocal imaging microscopy; selecting one or more regions of interest in the permeated cell culture sample images; extracting time-dependent patterns for the standard deviation of fluorescence intensity in the regions of interest; and analyzing the time-dependent patterns for the standard deviation of fluorescence intensity in the regions of interest to characterize the asymmetric activity patterns in the cell culture sample.

[0007] The well plate may be any appropriate well plate. In some cases, the well plate comprises a multiplicity of wells. In some cases, the well plate may have from 2- 1536, 4-384, 6-96, 6-24, 2, 4, 6, 12, 24, 96, 384, or 1536 wells. In some cases, the well has a transparent base, and optionally the digital imaging device has an objective disposed below the base.

[0008] In some cases, the cell culture sample is a 2D cell culture sample or a 3D cell culture sample. In some cases, the 3D cell culture sample is selected from thegroup consisting of a neuronal organoid, cerebral organoid, midbrain organoid, pituitary organoid, forebrain organoid, cortical organoid, thalamic organoid, hypothalamic organoid, hippocampal organoids, cerebellum organoid, choroid plexus organoid, medial ganglionic eminence (MGE) organoid, hindbrain organoid, brain assembloid, neuronal spheroid, neuronal progenitor cell (NPC), two-dimensional neuronal cell, retinal organoid, and cardiac organoid, optionally wherein the cardiac organoid is an immature cardiac organoid.

[0009] In some cases, the fluorescent dye is a calcium-sensitive fluorescence indicator. In some cases, the calcium-sensitive fluorescence indicator can comprise a dye selected from fura-2, fura-4F, fura-6F, fura-FF, indo-1, fluo-3, fluo-4, fluo-5F, fluo-4 FF, Mag-fluo-4, rhodium-based calcium indicators, rhod-2, rhod-3, BAPTA, Calcium Green™, X-rhod-1, X-rhod-5F, fura-red, and the like. In some cases, the dye may be in the form of an acetoxymethyl (AM) ester.

[0010] The method can further include recording kinetic fluorescence intensities from the time-lapsed images to determine calcium flux patterns in the cell culture sample regions of interest. In some cases, the calcium flux patterns are further characterized by one or more parameters selected from the group consisting of number of peaks, peak amplitude, peak intensity, number of fluxes, peak frequency, peak width, peak width at half height, distance between peaks, peak rise, decay times, main peak amplitude, linear decay slope, main peak interval, early afterdepolarization-like event (EAD-like) intervals, rise slope, EAD-like event amplitude, decay slope, calcium- transient duration (CTD), calcium transient duration from peak position (CTDP90), start of an event, main peak, and early afterdepolarization-like event (EAD-like).

[0011] The method can further include exposing the cell culture sample to a stimulus. In some cases, the stimulus is a light stimulus, electrical stimulus, or chemical stimulus. In some cases, the stimulus is an excitatory stimulus or a modulatory stimulus. In some cases, the stimulus is an excitatory stimulus. In some cases, the excitatory stimulus comprises optogenetic stimulation. In some cases, the chemical stimulus is a chemical modulator or stimulator. In some cases, the chemical stimulus can be used to regulate or increase the cell culture activity. In some cases, the method includes comparing the asymmetric activity patterns in the cell culture sample before and after the exposing to the stimulus. In some cases, the method includescomparing the asymmetric activity patterns in the cell culture sample before and after the exposing to an excitatory stimulus.

[0012] The method can further include exposing the cell culture sample to a candidate compound for a first period of time. In some cases, the effect on the cell culture sample is determined by comparing the calcium flux patterns in the cell culture sample exposed to the candidate compound to calcium flux patterns in a comparable control cell culture sample stained with the calcium-sensitive fluorescence indicator without exposing to the candidate compound.

[0013] The method can further include generating the cell culture sample from pluripotent stem cells while treating the cells with the candidate compound, and comparing development or functionality of the cell culture sample with development of a comparable cell culture sample that was not treated with the candidate compound.

[0014] In some cases, the confocal imaging microscopy is spinning disk confocal microscopy.

[0015] In some cases, the acquiring images comprises using the digital imaging device to acquire a first plurality of vertically spaced-apart images of the cell culture sample in the well plate, each image having a different height along a Z axis, such that a first volumetric image stack is generated with respect to the well. In some cases, each image of the plurality of images comprises a combined plurality of smaller images all captured at the same height along the Z-axis. In some cases, the plurality of smaller images is combined based on respective known positions of the digital imaging device with respect to a horizontal plane. In some cases, respective Z-coordinates of sequential images in the volumetric image stack differ by at least about 20 micrometers. In some cases, the respective Z-coordinates of sequential images in the volumetric image stack differ by less than about 50 micrometers. In some cases, the respective Z- coordinates of sequential images in the volumetric image stack differ by between 25 micrometers and 45 micrometers.

[0016] The one or more regions of interest can comprise a plurality of nonoverlapping partial regions of the cell culture sample images, and optionally the plurality of non-overlapping regions comprise at least one, at least 2, at least 3, at least4, at least 4, 2-20, 3-15, or 4-10 regions of interest. In some cases, the one or more regions of interest is selected manually, or by an automated method, optionally wherein the automated method comprises a machine learning method, optionally wherein the machine learning method comprises a model selected from the group consisting of a supervised learning model, unsupervised learning model, semi-supervised learning model, and reinforcement learning model.

[0017] In some cases, the analyzing of the time-dependent patterns comprises plotting peak fluorescence intensity standard deviation in the selected regions of interest against time. In some cases, the method comprises setting a peak threshold for analysis.

[0018] In some cases, the method comprises calculating the difference in peak fluorescence intensity standard deviation in the selected regions of interest of the same cell culture sample before and after the exposing to the excitatory stimulus.

[0019] The methods provided herein allow for analysis of asymmetric activity patterns in two- or three-dimensional neuronal or retinal cell cultures or other multicellular cell cultures.BRIEF DESCRIPTION OF THE DRAWINGS

[0020] FIG. 1 shows representative calcium-flux signal traces (standard deviation of fluorescence intensity, normalized) for optogenetics (blue light excitation) vs. time (sec) in four regions of a retinal organoid. BR1-BR4 represents the baseline readouts after analysis of regions 1 through 4 of the organoids over 50 seconds. ER1-ER4 represents the excited readouts after analysis of the regions 1 through 4 over 250 seconds.

[0021] FIG. 2 shows a bar graph of average peak counts across each of the selected regions shown in FIG. 1 obtained through the inventive method of analysis for baseline and excited states in the organoid. The asymmetric activity in the organoid in baseline and excited states is characterized by the average number of peaks in each of the selected regions.

[0022] FIG. 3 shows representative images of a healthy retinal organoid without excitation (upper left), a disease retinal organoid without excitation (upper right), a healthy retinal organoid after excitation (lower left), and a disease retinal organoid after excitation (lower right).

[0023] FIG. 4A shows how analysis of first retinal organoid maximum fluorescence intensity (upper panel), minimum intensity (middle panel), and average intensity (lower panel) across all the time points of activity cancel themselves out or do not provide sufficient information necessary for the analysis.

[0024] FIG. 4B shows how analysis of second retinal organoid maximum fluorescence intensity (upper panel), minimum intensity (middle panel), and average intensity (lower panel) across all the time points of activity cancel themselves out or do not provide sufficient information necessary for the analysis.

[0025] FIG. 4C shows how analysis of a third retinal organoid maximum fluorescence intensity (upper panel), minimum intensity (middle panel), and average intensity (lower panel) across all of the time points of activity cancel themselves out or do not provide sufficient information necessary for the analysis.

[0026] FIG. 5A shows an image of an excited healthy retinal organoid (upper panel). Calcium activity is extracted from the image, with a plot of average intensity from the organoid (lower panel) providing information of the activity.

[0027] FIG. 5B shows an image of an excited disease retinal organoid (upper panel). Calcium activity is extracted from the image, with a plot of average intensity from the organoid (lower panel) providing information of the activity.

[0028] FIG. 6A shows an image of baseline retinal organoid. Ten different regions are circled in the image and the intensity standard deviation is plotted over time for each region over 50 seconds (lower panel). Even in the baseline state, regional differences can be distinguished in the graph, where some areas exhibit greater or lesser intensity standard deviation and appear to correlate with appearance of each region in the image. In this case, the regions were manually selected. Alternatively, region selection can be performed with software automation with journal setup.

[0029] FIG. 6B shows an image of the same retinal organoid as shown in FIG. 6A having different selected regions circled in the image. After excitation, a graph of the intensity standard deviation for each region is plotted over 250 seconds (lower panel). Regional differences can be easily distinguished in the graph, for example, as number of peaks, peak amplitude, peak intensity, number of fluxes, peak frequency, peak width, peak width at half height, distance between peaks, peak rise, and decay times, etc. The plot of intensity standard deviation appears to correlate with appearance of each region in the image. In this case, the regions were manually selected. Alternatively, region selection can be performed with software automation with journal setup.

[0030] FIG. 7A shows an image of a retinal organoid having a Region 1 encircled (left upper and lower panels) and a plot of intensity standard deviation at baseline over 50 seconds (upper right graph) and a plot of intensity standard deviation after excitation over 250 seconds (lower right graph).

[0031] FIG. 7B shows an image of a retinal organoid having a Region 2 encircled (left upper and lower panels) and a plot of intensity standard deviation at baseline over 50 seconds (upper right graph) and a plot of intensity standard deviation after excitation over 250 seconds (lower right graph).

[0032] FIG. 7C shows an image of a retinal organoid having a Region 3 encircled (left upper and lower panels) and a plot of intensity standard deviation at baseline over 50 seconds (upper right graph) and a plot of intensity standard deviation after excitation over 250 seconds (lower right graph).

[0033] FIG. 7D shows an image of a retinal organoid having a Region 4 encircled (left upper and lower panels) and a plot of intensity standard deviation at baseline over 50 seconds (upper right graph) and a plot of intensity standard deviation after excitation over 250 seconds (lower right graph).

[0034] FIG. 8A upper panel shows an overlay of plots of normalized intensity standard deviation in Region 1 overtime (50 seconds) for baseline (BRI) and excited (ER1) states. FIG. 8A lower panel shows an overlay of plots of normalized intensity standard deviation in Region 2 over time (50 seconds) for baseline (BR2) and excited (ER2) states.

[0035] FIG. 8B upper panel shows an overlay of plots of normalized intensity standard deviation in Region 3 over time (50 seconds) for baseline (BR3) and excited (ER3) states. FIG. 8B lower panel shows an overlay of plots of normalized intensity standard deviation in Region 4 over time (50 seconds) for baseline (BR4) and excited (ER4) states.

[0036] FIG. 8C upper panel shows an overlay of plots of normalized intensity standard deviation in Region 5 over time (50 seconds) for baseline (BR5) and excited (ER5) states.

[0037] FIG. 9 shows an overlay of plots of normalized intensity standard deviation vs. time for baseline in all regions (BRI -5) to excited states in all regions (ER1-5), over 50 seconds.

[0038] FIG. 10 shows a representative plot of a dorsal brain organoid exhibiting synchronous activity as Relative Fluorescence Units (RFU) vs. time (400 seconds) as detected on a Fluorescence Imaging Plate Reader (FLIPR®) instrument.

[0039] FIG. 11 shows a representative plot of a midbrain organoid baseline exhibiting asynchronous activity as RFU vs. time (400 seconds) which was not detected on the FLIPR® instrument.

[0040] FIG. 12 shows regional analysis of a midbrain organoid (region encircled in image at left panel) exhibiting asynchronous activity which was detected and plotted as intensity standard deviation vs. time (right panel) using ImageXpress® Micro Confocal High Content Imaging System (Molecular Devices) regional analysis of the organoid.DETAILED DESCRIPTION OF THE INVENTION

[0041] Definitions

[0042] The singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0043] The term "and / or" refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0044] The term "about," when referring to a measurable value such as an amount of a compound, dose, time, temperature, and the like, is meant to encompass variations of + / -10%, 5%, 1%, 0.5%, or even 0.1% of the specified amount.

[0045] The terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Unless otherwise defined, all terms, including technical and scientific terms used in the description, have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. In the event of conflicting terminology, the present specification is controlling.

[0046] The term “target cells” refers to cells for automated cell culture applications of the present disclosure, such as organoids, tumoroids, spheroids, stem cells, or a production cell line. In some embodiments, the target cells are spheroids, tumoroids, organoids and / or other multi-cellular bodies. In some embodiments, the target cells may be stem cells. In some embodiments, the target cells may be a production cell line. The target cells may be derived from a target tissue. The target tissue may be a mammalian primary tissue, or an organoid, or tumoroid. The mammalian tissue may be derived from a patient biopsy sample. In some cases, the target cells may be derived from an iPSC via an embryoid body (EB). The organoids may be cultivated within a hydrogel dome in the primary well of the well unit. For example, the organoids may be grown from stem cells or from organoid fragments in the primary (culture) well within a hydrogel dome (such as Matrigel). The target tissue may be derived from target organs such as, e.g., lung, intestine such as small intestine, colon, stomach, pancreas, liver, kidney, skin, bone marrow, blood-brain barrier, brain, heart, and the like.

[0047] Organoid, spheroid, tumoroid, and three-dimensional (3D) cell culture models are useful in many applications such as disease modeling and regenerative medicine. 3D cellular models like organoids and spheroids may be useful to better understand complex biology in a physiologically relevant context because cells often retain natural shape and proper spatial orientation, such as in aggregates or spheroids, whereas 2D models of cells grown in a sheet or monolayer may not be as successfill. Gene and protein expression of 3D cell culture may more closely mimic gene andprotein expression. For example, 3D cell cultures may be useful for drug target identification, lead compound identification, compound optimization, preclinical attesting, solid tumor modeling, genetic disease modeling, drug discovery, precision medicine, organs-on-chips, and bioprinting.

[0048] The term “spheroids” refers to three dimensional (3D) multicellular in vitro tissue cultures aggregates composed of one or more cell types that grow and proliferate, and may exhibit enhance physiological responses, but do not undergo differentiation or self-organization. Common cell sources for spheroids are primary tissues or immortalized cell lines. Spheroids may bridge the gap between monolayers and complex organs.

[0049] The term “organoids” refers to three dimensional (3D) multicellular in vitro tissue culture aggregates composed of one or more cell types, in which cells spontaneously self-organize into properly differentiated functional cell types and progenitors that resemble their in vivo counterparts in at least one aspect. Organoids mimic their corresponding in vivo organs. Organoids can be derived from pluripotent stem cells (PSCs), induced pluripotent stem cells (iPSCs), neonatal tissue stem cells, embryonic stem cells (ESCs), adult stem cells, or primary tissue. Organoid cultures can be crafted to resemble much of the complexity of an organ, therefore are useful for study of disease etiology and treatment. Organoid technology has recently emerged as an essential tool for both fundamental and biomedical research. The organoid cultures may be selected from different types of target organs such as, e.g., brain, retinal, cardiac, lung, intestine such as small intestine, colon, stomach, pancreas, liver, kidney, skin, bone marrow, blood-brain barrier, and the like.

[0050] The term “tumoroid” refers to three dimensional (3D) multicellular in vitro tissue culture aggregates composed of one or more cell types typically derived from primary tumors harvested from oncological patients and can mimic human tumor microenvironment. Tumoroids may be useful for studies on novel cancer drugs or for use in precision medicine in the field of oncology. Cancer cell lines may be, for example, bladder, breast, colon, hematopoietic and lymphoid, liver, lung, ovary, prostate, skin, and the like.

[0051] The term “stem cells” refers to undifferentiated cells that have the potential to develop into many different cell types that carry out different functions. Pluripotent stem cells, such as those found in embryos, can give rise to any type of cell such as those in brain, bone, heart, and skin. Some human adult cells can be reprogrammed into embryonic stem cell-like state called induced pluripotent stem cells (iPSCs). Multipotent stem cells, for example, found in adults or in babies' umbilical cords, may develop into the cells that make up the organ system that they originated from. When grown under certain cell culture conditions, pluripotent stem cells can remain undifferentiated. To generate differentiated cells, the chemical composition of the culture medium may be changed, the surface of the culture dish may be altered, or the cells may be modified by forcing expression of certain genes.

[0052] Different media components may be required for each type of source cells used, and the type of differentiation to be achieved. Growth factors such as EGF (epidermal growth factor), Noggin (NOG), R-spondin (RSPO1), HGF (hepatocyte growth factor), BMP (bone morphogenic protein), FGF (fibroblast growth factor), and the like may be essential components of organoid media. The tissue culture media may comprise growth factors. The growth factors may be generated by the feeder cells. The growth factors may be recombinant growth factors. The recombinant growth factor proteins for organoid culture may include, for example, recombinant human EGF protein, recombinant HGF proteins such as, for example, human HGF protein, cynomolgus HGF protein, human FGF10, human Noggin / NOG protein, human RSPO1 protein, human BMP-2 protein, and the like. Additional recombinant growth factors for organoid culture may include, for example, EGF, FGF2, FGF7, FGF9, FGF10, HGF, NOG, RSPO1, RSPO3, Activin A, BMP2, and BMP4, and the like. The tissue culture media, or recombinant growth factor proteins for organoid culture, may be commercially available from, for example, Sino Biological, Inc., or Thermo Fisher Scientific.

[0053] 3D cellular models like organoids and spheroids may be cultivated in a tissue culture media comprising a hydrogel, such as in a hydrogel dome within the media.

[0054] The term “hydrogel” or “hydrogels” refers to an extracellular matrix useful for culturing organoids. The hydrogel may include murine EHS sarcoma matrix, forexample, available commercially as Matrigel (Coming), Cultex (Trevigen), Geltrex (Gibco), collagen type I, fibrin, hyaluronic acid (HA), gelatin methacrylate (GelMA), decellularized matrices, or biopolymers such as alginate, silk, nanocellulose; engineered materials such as polyethylene glycol (PEG), self-assembling peptides such as RADA16 / PuraMatrixbQ13, poly(lactic / (co)glycolic) acid, polycaprolactone, polyacrylamide, oligo(ethylene glycol)-substituted polyisocyanopeptides, ELP (elastinlike protein), or combinations of these polymers.

[0055] The term “well plane” refers to a focal plane or Z-plane defined as a specific Z-position or Z-height above the bottom of a well in a well plate.

[0056] The term “calcium flux” refers to the dynamic movement of calcium ions (Ca ^) into and out of calls. Calcium flux is essential for various cell functionalities including synaptic information transfer, modulation of excitability, synaptic plasticity, excitation-transcription coupling, signal transduction, muscle contraction, myofilament contraction, mitochondrial motility, neurotransmitter release, intracellular communication, regulation of ionic currents, and enzyme activity. Calcium facilitates cell attachment to substrates, attachment to one another, and mediates cellular events that affect cell movement, shape, and three-dimensional structure.

[0057] The term “development” in reference to a cell culture refers to characterization by one or more of cell attachment to one another, cell attachment to substrate, cell culture shape, cell culture three dimensional structure, cell movement, and number of cells over time during onset, duration, or onset and duration of a phase of cell growth selected from the group consisting of latent phase before growth begins (lag phase), exponential growth phase (log phase), stationary phase in which increase in cell numbers slows, and death phase in which cells begin to die.

[0058] The term “functionality” in reference to a cell culture depends on the type of cell culture, e.g., type of organoid. For example, in cardiac organoids functionality can be determined by one or more of calcium flux, calcium upstroke rate, calcium decay rate, cardiac contraction motion, contraction velocity, relaxation velocity, retinoic acid signaling, transverse tubule structure, protein expression, atrial chamber formation, and the like. For example, brain organoid functionality can be determined by one or more ofneuronal firing frequency, alpha-synuclein aggregation, neural induction, brain region specific patterning, expression of radial glial markers, and the like.

[0059] All patents, patent applications, and publications referred to herein are incorporated by reference in their entirety.

[0060] The embodiments described in one aspect of the present disclosure are not limited to the aspect described. The embodiments may also be applied to a different aspect of the disclosure as long as the embodiments do not prevent these aspects of the disclosure from operating for its intended purpose.

[0061] Random or asynchronous activity with different cell and clusters is a commonly observed phenotype with neuronal 2D cultures, also iPSC-derived 3D organoids (e.g., Lancaster, 2014, Generation of cerebral organoids from human pluripotent stem cells. Nat Protocol. Oct 9(10), 2329-40; Pasca, 2018, The rise of three- dimensional human brain cultures. Nature 553, 437-445). Random or asynchronous activity is also observed in retinal organoids. It has been problematic to analyze asynchronous patterns and provide quantitative measurements reflecting changes in cell activity, disease models, compounds effects, and differences between various genetic phenotypes.

[0062] High-throughput kinetic cellular screening systems are available that allow for real-time screening of iPSC-derived cardiomyocytes or neurons, G-protein-coupled receptors (GPCRs), and ion channels. For example, FLIPR® Penta High-Throughput Cellular Screening System (Molecular Devices) comprises a high-speed camera option and Peak Pro 2® software module that allows for measurement and analysis of synchronous calcium oscillations of human iPSC-derived cardiomyocytes and neurons. Images can be taken at up to 100 times per second and patterns quickly analyzed using more than about 30 measurement options.

[0063] Asynchronous activity in a 2D or 3D multicellular cell culture can be difficult to characterize on high-throughput kinetic cellular screening systems.

[0064] Representative images of a healthy retinal organoid without excitation (upper left), a disease retinal organoid without excitation (upper right), a healthy retinal organoid after excitation (lower left), and a disease retinal organoid after excitation(lower right) are shown at instants in time within time points of activity in FIG. 3. Differences between the healthy / disease retinal organoid with no excitation compared to the healthy / disease organoid after excitation can be visualized over time (though not apparent from FIG.3) using this method of analysis. Distinct differences in the patterns of calcium oscillations in the select region of interest, i.e., here the peripheral photoreceptor region, can be observed as a substantial increase in standard deviation of fluorescence intensity before and after stimulus (blue-light exposure) as a baseline vs excited state readouts of wild-type and the disease models.

[0065] However, it can be difficult to characterize asynchronous activity in, for example, neuronal organoids, using the same manner as synchronous activity using calcium-sensitive fluorescence indicators.

[0066] The problem is illustrated herein in FIGs. 4A-5B as discussed below.

[0067] Analysis of asynchronous activity in a first retinal organoid using a calciumsensitive fluorescence indicator is shown in FIG. 4A. Maximum fluorescence intensity (upper panel), minimum intensity (middle panel), and average intensity (lower panel) across all of the time points of activity cancel themselves out or do not provide sufficient information necessary for the analysis.

[0068] Analysis of asynchronous activity in a second retinal organoid using a calcium-sensitive fluorescence indicator is shown in FIG. 4B. Maximum fluorescence intensity (upper panel), minimum intensity (middle panel), and average intensity (lower panel) across all of the time points of activity cancel themselves out or do not provide sufficient information necessary for the analysis.

[0069] Analysis of asynchronous activity in a third retinal organoid using a calcium-sensitive fluorescence indicator is shown in FIG. 4C. Maximum fluorescence intensity (upper panel), minimum intensity (middle panel), and average intensity (lower panel) across all of the time points of activity cancel themselves out or do not provide sufficient information necessary for the analysis.

[0070] An image of an excited healthy retinal organoid using a calcium-sensitive fluorescence indicator is shown in FIG. 5A (upper panel); calcium activity is extracted from the image, with a plot of average intensity from the organoid (lower panel)providing information on the activity. The information does not however include sufficient peak information to assess the activity.

[0071] An image of an excited disease retinal organoid (upper panel) using a calcium-sensitive fluorescence indicator is shown in FIG. 5B; calcium activity is extracted from the image, with a plot of average intensity from the organoid (lower panel) providing information on the activity. The information does not however include sufficient peak information to assess the activity.

[0072] A method has been developed to characterize asynchronous activity in a 2D or 3D multicellular cell culture.

[0073] It has been found that selecting a plurality of regions in a cell culture sample image, and plotting fluorescence intensity standard deviation in the cell culture within one or more of the selected regions allows for analysis of asymmetric activity patterns in the cell culture sample.

[0074] An image of a retinal organoid is shown in FIG. 6A. Ten different manually selected regions were circled in the image and the baseline intensity standard deviation is plotted over time for each region over time (50 seconds, lower panel). Even in the baseline state, regional differences can be distinguished in the graph, where some areas exhibit greater or lesser intensity standard deviation and appear to correlate with appearance of each region in the image. In this case, the regions were manually selected. Alternatively, region selection can be performed with software automation with journal setup.

[0075] An image of the retinal organoid is shown in FIG. 6B having 10 different manually selected regions circled in the image. After excitation, a graph of the intensity standard deviation for each region was plotted over time (250 seconds, lower panel). Regional differences can be easily distinguished in the graph after excitation, for example, as number of peaks, peak amplitude, peak intensity, number of fluxes, peak frequency, peak width, peak width at half height, distance between peaks, peak rise, and decay times, etc. The plot of intensity standard deviation appears to correlate with appearance of each region in the image. In this case, the regions were manuallyselected. Alternatively, region selection can be performed with software automation with journal setup.

[0076] An image of a retinal organoid having a Region 1 encircled (left upper and lower panels) is shown in FIG. 7A. A plot of intensity standard deviation at baseline over time (50 seconds, upper right graph) is shown compared to a plot of intensity standard deviation after excitation over time (250 seconds, lower right graph).

[0077] An image of a retinal organoid having a Region 2 encircled (left upper and lower panels) is shown in FIG. 7B. A plot of baseline intensity standard deviation over time (50 seconds, upper right graph) is shown compared to a plot of intensity standard deviation after excitation over time (250 seconds, lower right graph).

[0078] An image of a retinal organoid having a Region 3 encircled (left upper and lower panels) is shown in FIG. 7C. A plot of intensity standard deviation at baseline over time (50 seconds, upper right graph) is shown compared to a plot of intensity standard deviation after excitation over time (250 seconds, lower right graph).

[0079] An image of a retinal organoid having a Region 4 encircled (left upper and lower panels) is shown in FIG. 7D. A plot of intensity standard deviation at baseline over time (50 seconds, upper right graph) and a plot of intensity standard deviation after excitation over time (250 seconds, lower right graph). Differences in excited vs. baseline plots in terms of number of peaks is apparent in Region 4.

[0080] An overlay of plots of normalized intensity standard deviation in Region 1 over time (50 seconds) for baseline (BRI) and excited (ER1) states is shown in FIG. 8A, upper panel. The normalized intensity standard deviation of the excited organoid increases after about 10 seconds compared to the baseline organoid in Region 1.

[0081] An overlay of plots of normalized intensity standard deviation in Region 2 over time (50 seconds) for baseline (BR2) and excited (ER2) states is shown in FIG. 8A lower panel. The normalized intensity standard deviation of the excited organoid increases after about 35 seconds compared to that of the baseline organoid in Region 2.

[0082] An overlay of plots of normalized intensity standard deviation in Region 3 over time (50 seconds) for baseline (BR3) and excited (ER3) states is shown in FIG. 8Bupper panel. The normalized intensity standard deviation of the excited organoid is increased compared to that of the baseline organoid in Region 3 from 0-50 seconds.

[0083] An overlay of plots of normalized intensity standard deviation in Region 4 over time (50 seconds) for baseline (BR4) and excited (ER4) states is shown in FIG. 8B lower panel. The normalized intensity standard deviation of the excited organoid is increased compared to that of the baseline organoid in Region 4 from 0-50 seconds.

[0084] An overlay of plots of normalized intensity standard deviation in Region 5 over time (50 seconds) for baseline (BR5) and excited (ER5) states is shown in FIG. 8C upper panel. The normalized intensity standard deviation of the excited organoid is increased compared to the baseline organoid in Region 5 after about 28 seconds.

[0085] An overlay of plots for normalized intensity standard deviation vs. time for baseline in all regions (BRI -5) to excited states in all regions (ER1-5), over 50 seconds, is shown in FIG. 9. Each of the selected regions 1 to 5 exhibits characterizable differences in normalized intensity standard deviation of the excited organoid compared to the baseline organoid.

[0086] Cell culture samples

[0087] The cell culture samples can be any appropriate multicellular culture sample. In some cases, the cell culture sample is a two-dimensional (2D) cell culture sample or a three-dimensional (3D) cell culture sample. In some cases, the 3D cell culture sample is selected from the group consisting of a neuronal organoid, brain organoid such as a cerebral organoid, midbrain organoid, pituitary organoid, forebrain organoid, cortical organoid, thalamic organoid, hypothalamic organoid, hippocampal organoids, cerebellum organoid, choroid plexus organoid, medial ganglionic eminence (MGE) organoid, hindbrain organoid, brain assembloid, neuronal spheroid, neuronal progenitor cell (NPC), two-dimensional neuronal cell, retinal organoid, and cardiac organoid. The cardiac organoid can be an immature cardiac organoid. The cell culture sample may be a healthy cell culture sample or a disease cell culture sample.

[0088] Several neural models have been developed using induced pluripotent stem cells (iPSC) derived cells including 2D neuronal and 3D neuronal models and 3D organoids. 2D neuronal models can be used for high-throughput screening assays. 3Dneuronal organoids can be generated by an iPSC-differentiation process and include different neuronal and cell types and some structural organization and can be better at recapitulating in vivo morphology.

[0089] Neuronal organoids acquire greater cellular diversity and some brain-like organization compared to 2D models, however, their complexity, batch-to-batch variation, limited co-culture differentiation, and lengthy maturation times can limit use in HTS- assays. Cortical neural spheroids, which have been produced from neural stem cells (NSCs) that mature into differentiated excitatory and inhibitory neurons in the spheres can be more adaptable for HTS than organoids. Hay, M et al., 2014, Clinical development success rates for investigational drugs. Nat. Biotechnol. 32, 40-51.

[0090] Brain organoids can be obtained commercially or can be produced by protocols known in the art. Cerebral organoids, for example, can be produced by the method of Lancaster et al., 2014 Generation of cerebral organoids from human pluripotent stem cells. Nat Protocol. Oct 9(10), 2329-40 (2014). In this method the organoids are grown in a culture medium that promotes self-organization and patterning. Embryoid bodies are further differentiated in an extracellular matrix (Matrigel) to improve polarization of the neuroepithelia as well as support the growth of the large epithelia buds. These buds extend from the EBs and contain cavities similar to brain ventricles. Day 0 starts with EB formation. Germ layer differentiation is carried out on days 2-5. Neural induction starts at day 5. The EBs are transferred on day 7 to Matrigel droplets. Neuroepithelial bud expansion occurs on days 8-10. Maturation of brain tissue growth and expansion starts on day 11. An exemplary protocol for production of cerebral organoids can be found in Lim and Sirenko Application Note Automated monitoring of development and activity analysis of iPSC- derived 3D Cerebral Organoids, 2022, Molecular Devices. The brain organoid can be a normal brain organoid or a disease model brain organoid.

[0091] Cell Culture

[0092] Briefly, human iPSC cells are adapted to feeder free conditions (SC102A-1, System Biosciences) thawed and cultured in Complete mTeSR™ Plus culture medium (STEMCELL Technologies) in Matrigel-coated plates (cat.# 354277, Coming). Media is changed every day except once per week when a double volume of media is added toskip changing media on one day. Cells are passaged every 4-5 days using the enzyme- free reagent ReLeSR™ (STEMCELL Technologies) at a 1 :6-l :10 split ratio.

[0093] Cerebral Organoid Differentiation

[0094] Reagents used to generate cerebral organoids are from the STEMdiff ™ Cerebral Organoid Kit *STEMCELL Technologies #08570). The kit has been optimized for cerebral organoid formation based on Lancaster et al. 2014. Briefly, iPSC cells are seeded at 9000 cells / well in the embryoid body (EB) seeding media in a 96- well ultra-low attachment plate (Coming). The media is replaced with EB formation media. On day 5, EBs are imaged to ensure they are ready for neural induction. EBs are transferred to a 24-well plate containing the induction medium. On day 7, EBs are transferred into Matrigel (Coming) droplets. About 6-8 droplets are placed in each well of a 6-well plate containing Maturation medium. The plate containing organoids is allowed to mature at 37 deg C incubator on an orbital shaker. Fresh media was replaced every 3-4 days.

[0095] Calcium flux assay

[0096] Calcium flux can be assessed using the FLIPR® Calcium 6 Assay Kit (Molecular Devices) according to the manufacturer protocol. Starting from day 17, one cerebral organoid is loaded with dye for 2 hrs and then imaged on the ImageXpress® Micro Confocal High Content Imaging System (Molecular Devices).

[0097] Immunofluorescence

[0098] Whole organoids are fixed with 4% PFA overnight at 4 deg C, followed by a quick wash with PBS. Permeabilization was done with 0.5% triton-X in PBS. Organoids are incubated with, e.g., the following antibodies and stained for 48 hrs: Hoechst (33 |1M, frivitrogen #33342), Alexa Fluor™ 555 mouse anti-beta-tubulin (1:100 Becton Dickinson cat # 562139), Alexa Fluor™ Plus 750 Phalloidin (ThermoFisher Scientific cat # A30105).

[0099] Image acquisition and analysis

[0100] All images can be acquired on the Image Xpress Micro Confocal system (Molecular Devices) using MetaXpress® High Content Image Acquisition andAnalysis software. IN Carta™ Image Analysis Software is used for all analysis. The IN Carta™ SINAP module is used to carry out segmentation of images. Each model is trained and verified before being put to use in the analysis protocol. For calcium imaging, images are acquired with camera binning set to 2. To increase acquisition speed, the 50 pm confocal slit module was used.

[0101] Neuronal spheroids can be obtained commercially or generated by any appropriate method known in the art. Strong et al, 2023, describes functional brain region neural spheroids for modeling neurological disease and therapeutics screening. Communications Biology (2023) 6:1211 doi.org / 10.1038 / s42003-023-05582-8. Strong describes the development of high throughput screening (HTS)-compatible neural spheroid system, also referred to as brain region-specific spheroids which are assembled by cell aggregation of pluripotent stem cells (iPSC)-derived neurons and astrocytes in a scaffold-free environment. Neuronal spheroids can mimic the physiology of distinct brain regions, including the prefrontal cortex (PFC), and ventral tegmental area (VTA) by mixing different neuronal types to mimic the composition of different brain regions in vivo. Matured and differentiated iPSC-derived neural cells can be combined in different ratios reflecting the cell-type compositions of specific regions in the human brain, e.g., PFC-like prefrontal cortex-like, VTA-ventral tegmental -like, X-like other brain regions of choice. i-PSC-derived mature neuronal subtypes and astrocytes may include glutamatergic neurons, dopaminergic neurons, GABAergic neurons, and astrocytes which can be marker- validated, cryopreserved stocks and may include healthy or include associated mutations. After thawing and mixing selected neuronal subtypes / astrocytes at desired ratios in a culture plate (e.g., a multi-well plate, such as a 384-well, round bottom plates), culturing over time (e.g., 3 weeks), mature neuronal spheroids of desired composition ratios are obtained.

[0102] Retinal organoids (ROs) can be obtained commercially or generated by any appropriate technique known in the art. Human PSCs have been successfully differentiated into 3D retinal organoids that have multi-layer laminar structure with a ratio of rod and cone photoreceptors in the outer layer similar to that of the human para- or perifovea. Retinal organoids can be used for modeling human degenerative diseases that target photoreceptors and for screening and testing of drugs. Saha et al., Cone photoreceptors in human stem cell derived retinal organoids demonstrate intrinsic lightresponses that mimic those of primate fovea. Cell Stem Cell. 2022 March 03; 29(2): 460-471. Directed differentiation of iPSCs into three-dimensional (3D) retinal organoids has enabled modeling of retinopathies in patient-specific background. Kruczek et al., Gene therapy of dominant CRX-Leber Congenital Amaurosis using patient stem cell-derived retinal organoids. Stem Cell Reports Vol. 16, 252-263, Feb.9, 2021. A model of human cancer retinoblastoma based on patient-derived iPSCs exhibited molecular, cellular, and genomic features indistinguishable from human retinoblastomas. Norrie et al., 2021 Retinoblastoma from human stem cell-derived retinal organoids. Nature Communications, (2021) 12:4535 doi.org / 10.1038 / s41467- 021-24781-7.

[0103] Dyes

[0104] Voltage-gated calcium channels play pivotal roles in gene transcription, neuronal excitability, and neurotransmitter release. Williams et al., Calcium channels in retinal function and disease., Annu Rev Vis Sci 2022 Sept 15; 8; 53-77.Neurotransmission requires interaction between Ca2+, various neurotransmitters including glutamate, gamma-amino butyric acid (GABA), glycine, dopamine, and acetylcholine (Ach) and their respective receptors. Boff et al., The interplay between neurotransmitters and calcium dynamics in retinal synapses during development, health, and disease. 2024, Int. J. Mol. Sci. 2024, 25, 2226. Activity of individual neurons induces calcium influx through voltage-dependent calcium channels, which can be monitored by using calcium indicator dyes.

[0105] The dye may be any appropriate fluorescent dye that is capable of detecting changes in a cell membrane potential. The dye may be any appropriate fluorescent dye that is capable of detecting changes in intracellular free Ca2+concentrations. In some cases, the dye is a calcium-sensitive fluorescence indicator.

[0106] The calcium-sensitive fluorescence indicator can be any appropriate calcium-sensitive fluorescence indicator known in the art. Several calcium-sensitive fluorescence indicators are commercially available. For example, see Molecular Probes™ Handbook, a guide to fluorescent probes and labeling techniques, 11thEd. (2010), Ch. 19, Indicators for Ca2+, Mg2+, Zn2+and other metal ions, ThermoFisher Scientific. For example, the calcium-sensitive fluorescence indicator can comprise adye selected from fura-2, fura-4F, fura-6F, fura-FF, indo-1, fluo-3, fluo-4, fluo-5F, fluo-4 FF, Mag-fluo-4, rhod-2, rhod-3, BAPTA, Calcium Green ™, X-rhod-1, X-rhod- 5F, fura-red, and the like. The BAPTA moiety can be, for example, such as Oregon Green™ 488 Bapta-1, Oregon Green™ 488 Bapta-2, Oregon Green™ 488 Bapta-5N, or Oregon Green™ 488 Bapta-6F. The dye may be in the form of an acetoxymethyl (AM) ester, salt form, or dextran conjugate which can influence the cell-loading method and affects the indicators intracellular distribution and retention. The cellpermeant AM ester can be passively loaded into cells where they are cleaved into cell- impermeant products by intracellular esterases. The salt and dextran forms are typically loaded by microinjection, electroporation, microprojectile bombardment, or by using a pinocytic cell-loading reagent.

[0107] In some cases, the calcium-sensitive fluorescence indicator can be present in a kit. Kit components can be mixed with a buffer and incubated for about 2 hours to load the cells. During incubation, the calcium indicator passes through the cell membrane, and esterases in the cytoplasm cleave the acetoxymethyl (AM) portion of the molecule. After incubation with the dye, the cells can be assayed. When the target is activated, direct measurement of the intracellular fluorescence is enabled due to increased calcium concentration. In some cases, a masking dye is employed. The masking dye does not enter the cell but reduces the background originating from extracellular fluorescence of the calcium indicator, media, and other components. In some cases, a masking dye is not employed. Responses can be measured as described herein. In some cases, responses can be measured as fluorescence intensity standard deviation. In some cases, to enable comparison, data can be normalized as % response over baseline.

[0108] Region selection

[0109] In a multi-cellular cell culture, one or more regions of interest, or a plurality of regions of interest are selected for analysis. In some cases, the region of interest is smaller than the entire organoid or other multi-cellular cell culture but larger than a single cell. In some cases, the region of interest is selected based on one or more activity landmarks, such as fluorescence activity. In some cases, the one or more landmarks depend on the organoid model and study of interest. In some cases, the region of interest is selected based on or one or more structural landmarks, such asperipheral landmarks, for example, photoreceptors in retinal organoids, or in brain organoids ventricular zone (VZ) structures that contain apical radial glia, subventricular zone (SVZ) areas that contain intermediate progenitors and outer radial glia, and emerging cortical plates (CP) that contains neurons.

[0110] Cell Culture Excitation

[0111] The cell culture may be excited by any technique known in the art. In some cases, the neuronal or retinal organoid can be excited by any appropriate excitatory stimulus. Neuronal excitability can be influenced by the activity of various membrane proteins, such as inhibitory and excitatory receptors and voltage-gated ion channels.

[0112] In some cases, the neuronal or retinal organoid can be excited by a light stimulus, electrical stimulus, or chemical stimulus.

[0113] In some cases, the cell culture may be stimulated by light via optogenetics. For example, retinal organoids comprising photoreceptors, or hairlike structures on the periphery of the organoid, may be employed. Neuronal cell cultures can be engineered to express exogenous photosensitive proteins to make them responsive to light by alteration of membrane potential or signaling pathway. Several bacterial photosensitive proteins including any appropriate light-sensitive opsins, such as a channelrhodopsin, a halorhodopsin, or a CoChR blue-light-sensitive opsin may be employed. Forli et al, Optogenetic strategies for high-efficiency all-optical interrogation using blue-light sensitive opsins, eLife 2021; 10:63359. In general, expression of light-sensitive opsins induces alteration of membrane ion permeability in response to illumination. In some cases, blue light can increase neuronal activity- regulated gene expression in the absence of optogenetic proteins. Tyssowski et al, Blue light increases neuronal activity-regulated gene expression in absence of optogenetic proteins, 2019 doi.org / 10.1523 / eNeuro.0085-19.2019. In some cases, the cell culture may be treated with a chemical stimulus. In some cases, the chemical stimulus may be a chemical modulator or stimulator. In some cases, the chemical stimulus can be used to regulate or increase the organoid activity. In the case of brain organoids, for example, a chemical stimulus such as gamma-aminobutyric acid (GABA) or 4- aminopyridine (4-AP) can be used to decrease or increase the neural activity, respectively. In some cases, the cell culture may be treated with an electrical stimulus.EXAMPLESExample 1. Retinal Organoid Asynchronous Activity Characterization

[0114] Random asynchronous activity with different cells and clusters is a commonly observed phenotype with neuronal 2D cultures, iPSC-derived 3D organoids, retinal organoids, and the like. It has been difficult to analyze those patterns and provide numeric measurements reflecting changes in cell activity, compounds effects, and various genetic phenotypes.

[0115] To overcome this obstacle, a method has been developed to allow analysis and quantitation of asynchronous activities in multiple cell culture types (neural 2D cultures, neural 3D organoids, retinal organoids, cardiac organoids, etc.).

[0116] Retinal organoid samples were maintained according to the supplier protocol. On the day of assay, retinal organoids were loaded with 2X cone, of FLIPR® Calcium 6 dye indicator (Molecular Devices) and incubated for 2h. A high-content confocal system (ImageXpress® Micro Confocal High Content Imaging System, Molecular Devices) was used to measure the patterns and frequencies of spontaneous calcium waveforms from the organoids. Baseline recordings with FITC filter were acquired for the 50s before the blue light excitation (optogenetics) and then were exposed to 30secs each of 2 maximum exposure time blue light pulses (DAPI filter) on the system from which 250secs acquisitions on FITC filter were made. Peak analysis of these time-series reads was accomplished with MetaXpress® software (Molecular Devices), allowing the characterization of peaks, as well as complex asynchronous calcium oscillation patterns.Analysis steps using MetaXpress® SW:

[0117] The acquired plate data was reviewed, and the following steps were performed:1. Time Point vs Well planes were selected and loaded into a stack.2. Regions for measuring activity in certain areas were selected on the organoid stack.3. Next region measurements were considered for all planes on the selected FITC filter to include all active regions from the dropdown list.4. The multiple (~5-8) regions of interest were selected on organoids images selected as such to allow to cover organoid or part of organoid (regions could be saved as region files for future references).5. Fluorescent intensity read-outs were visualized over the time for particular regions.6. Since following “average intensity” measurements was not apparently productive for analysis of erratic spikes, the ST Deviation of fluorescence was selected as a read-out. By plotting intensity standard deviation against the time in MetaXpress® software, instead of average fluorescence intensity, the phenotypic responses of intracellular Calcium fluctuations were observed that correlated well with visual perception. Further analysis of traces was performed by using Excel, that can be incorporated into the MetaXpress® software for imaging or FLIPR® software, for example, ScreenWorks® and / or Peak Pro™ 2 software.7. These traces were further processed for better understanding and normalization. The select Labels can be exported to Excel for each organoid and region type into a .csv file for further analysis.8. The exported numeric data (standard deviation (STDEV) of fluorescence intensity vs Time) was further processed in Excel and normalized using averages of each region. An arbitrary threshold of 0.9 was chosen to analyze the peak data in FIG. 1, and to obtain the peak information in Table 1. The difference in peak information regions of the same organoid before and after excitation calculated by the new method was graphically represented in FIG. 2.

[0118] Results

[0119] There was a significant increase in peak count and amplitude after excitation in comparison to before excitation is support of the new method of analysis for the asynchronous region of interest-based study. FIG. 1 shows representative calcium-flux signal traces (standard deviation of fluorescence intensity, normalized) for optogenetics (blue light excitation). BR1-BR4 represents the baseline readouts after analysis of regions 1 through 4 of the organoids and ER1-ER4 represents the excited readouts after analysis of regions 1 through 4. Table 1 shows averages of peak counts of both baseline and excited states of same regions on an organoid.

[0120] Table 1. The averages of peak counts across selected regions of both baseline and excited states of same regions on an organoid

[0121] FIG. 2 shows a bar graph of average peak counts across each of the selected regions shown in FIG. 1 obtained through the inventive method of analysis for baseline and excited states in the organoid. The asymmetric activity in the organoid in baseline and excited states is characterized by the average number of peaks in each of the selected regions.

[0122] The ability to perform fast-kinetic fluorescence imaging ofCa2+ oscillations in 2D and 3D neuronal cultures with the ImageXpress® Micro system and analysis with MetaXpress® Peak Analysis tool with this method can enable compound screening and studies of neural function, cardiac function, and other organoid types, plus optogenetics studies.

[0123] Example 2. Brain Organoid Asynchronous Activity Characterization

[0124] A representative plot of a dorsal brain organoid exhibiting synchronous activity as Relative Fluorescence Units (RFU) vs. time (400 seconds) as detected on a Fluorescence Imaging Plate Reader (FLIPR®) instrument is shown in FIG. 10. In contrast, FIG. 11 shows representative plot of a midbrain organoid baseline exhibiting asynchronous activity as RFU vs. time (400 seconds) which was not detected on the FLIPR® instrument. The method developed for use in retinal organoids was applied to brain organoids.

[0125] Brain organoids were maintained according to protocol. On the day of assay, brain organoids were loaded with 2X cone, of FLIPR® Calcium 6 dye indicator (Molecular Devices) and incubated for 2h. A high-content confocal system (ImageXpress® Micro) was used to measure the patterns and frequencies of spontaneous calcium waveforms from the organoids. Peak analysis of these time-series reads was accomplished with MetaXpress® software (Molecular Devices), allowing the characterization of peaks, as well as complex asynchronous calcium oscillation patterns.

[0126] A representative image of a midbrain organoid (region encircled in image at left panel) exhibiting asynchronous activity is shown in FIG. 12, which was detected and plotted as intensity standard deviation vs. time (right panel) using ImageXpress® Micro Confocal High Content Imaging System (Molecular Devices) regional analysis of the organoid.Clauses

[0127] Clause 1. A method for analysis of asymmetric activity patterns in a cell culture sample, the method comprising staining a cell culture sample in a well plate with a fluorescent dye; acquiring a plurality of time-lapsed images of the stained cell culture sample using a digital imaging device comprising confocal imaging microscopy; selecting one or more regions of interest in the stained cell culture sample images; extracting time-dependent patterns for the standard deviation of fluorescence intensity in the one or more regions of interest; andanalyzing the time-dependent patterns for the standard deviation of fluorescence intensity in the regions of interest to characterize the asymmetric activity patterns in the cell culture sample.

[0128] Clause 2. The method of clause 1, wherein the cell culture sample is a 2D cell culture sample or a 3D cell culture sample.

[0129] Clause 3. The method of clause 1 or 2, wherein the cell culture sample is a 3D cell culture sample selected from the group consisting of a neuronal organoid, cerebral organoid, midbrain organoid, pituitary organoid, forebrain organoid, cortical organoid, thalamic organoid, hypothalamic organoid, hippocampal organoids, cerebellum organoid, choroid plexus organoid, medial ganglionic eminence (MGE) organoid, hindbrain organoid, brain assembloid, neuronal spheroid, neuronal progenitor cell (NPC), two-dimensional neuronal cell, retinal organoid, and cardiac organoid.

[0130] Clause 4. The method of clause 3, wherein the cardiac organoid is an immature cardiac organoid.

[0131] Clause 5. The method of any one of clauses 1-4, wherein the fluorescent dye is a calcium-sensitive fluorescence indicator.

[0132] Clause 6. The method of any one of clauses 1-5, further comprising recording kinetic fluorescence intensities from one or more of the time-lapsed images to determine calcium flux patterns in the cell culture sample regions of interest.

[0133] Clause 7. The method of clause 6, wherein the calcium flux patterns are further characterized by one or more parameters selected from the group consisting of number of peaks, peak amplitude, peak intensity, number of fluxes, peak frequency, peak width, peak width at half height, distance between peaks, peak rise, and decay times.

[0134] Clause 8. The method of any one of clauses 1-7, further comprising exposing the cell culture sample to an excitatory stimulus; and comparing the asymmetric activity patterns in the cell culture sample before and after the exposing to the excitatory stimulus.

[0135] Clause 9. The method of claim 8, wherein the excitatory stimulus comprises optogenetic stimulation.

[0136] Clause 10. The method of any one of clauses 1-9, further comprising exposing the cell culture sample to a candidate compound for a first period of time.

[0137] Clause 11. The method of clause 10, wherein an effect on the cell culture sample is determined by comparing the calcium flux patterns in the cell culture sample exposed to the candidate compound to calcium flux patterns in a comparable control cell culture sample stained with the calcium-sensitive fluorescence indicator without exposing to the candidate compound.

[0138] Clause 12. The method of clause 11 , further comprising generating the cell culture sample from pluripotent stem cells while treating the cells with the candidate compound; and comparing development or functionality of the cell culture sample with development of a comparable cell culture sample that was not treated with the candidate compound.

[0139] Clause 13. The method of clause 12, wherein the development of the cell culture is characterized by one or more of cell attachment to one another, cell attachment to substrate, cell culture shape, cell culture three dimensional structure, cell movement, and number of cells over time during onset, duration, or onset and duration of a phase of cell growth selected from the group consisting of latent phase, exponential growth phase, stationary phase, and death phase.

[0140] Clause 14. The method of any one of clauses 1-13, wherein the confocal imaging microscopy is spinning disk confocal microscopy.

[0141] Clause 15. The method of any one of clauses 1-14, wherein the acquiring images comprises using the digital imaging device to acquire a first plurality of vertically spaced-apart images of the cell culture sample in the well plate, each image captured at a different height along a Z axis, such that a first volumetric image stack is generated with respect to the well.

[0142] Clause 16. The method of clause 15, wherein each image of the plurality of images comprises a combined plurality of smaller images all captured at the same height along the Z-axis.

[0143] Clause 17. The method of clause 16, wherein the plurality of smaller images is combined based on respective known positions of the digital imaging device with respect to a horizontal plane.

[0144] Clause 18. The method of any one of clauses 15-17, wherein respective Z- coordinates of sequential images in the first volumetric image stack differ by at least about 20 micrometers.

[0145] Clause 19. The method of any one of clauses 15-18, wherein the respective Z-coordinates of sequential images in the first volumetric image stack differ by less than about 50 micrometers.

[0146] Clause 20. The method of any one of clauses 15-19, wherein the respective Z-coordinates of sequential images in the volumetric image stack differ by between 25 micrometers and 45 micrometers.

[0147] Clause 21. The method of any one of clauses 1-20, wherein the well has a transparent base, and wherein the digital imaging device has an objective disposed below the base.

[0148] Clause 22. The method of any one of clauses 1-21, wherein the one or more regions of interest comprise a plurality of non-overlapping partial regions of the cell culture sample images.

[0149] Clause 23. The method of clause 22, wherein the plurality of nonoverlapping regions comprises at least one, at least 2, at least 3, at least 4, at least 4, 2- 20, 3-15, or 4-10 regions of interest.

[0150] Clause 24. The method of any one of clauses 1-23, wherein the one or more regions of interest is selected manually, or by an automated method.

[0151] Clause 25. The method of any one of clauses 1-24, wherein the one or more regions of interest is selected by an automated method comprising a machine learning method.

[0152] Clause 26. The method of any one of clauses 1-25, wherein the one or more regions of interest is selected by an automated method comprising a machine learning method comprising a model selected from the group consisting of a supervised learning model, unsupervised learning model, semi-supervised learning model, and reinforcement learning model.

[0153] Clause 27. The method of any one of clauses 1-26, wherein the analyzing of the time-dependent patterns comprises plotting peak fluorescence intensity standard deviation in the selected regions of interest against time.

[0154] Clause 28. The method of clause 27, further comprising setting a peak threshold for analysis.

[0155] Clause 29. The method of clause 27 or 28, further comprising calculating the difference in peak fluorescence intensity standard deviation in the selected regions of interest of the same cell culture sample before and after the exposing to the excitatory stimulus.

[0156] The above specification, examples and data provide a complete description of the manufacture and use of the composition of the invention. Since many embodiments of the invention can be made without departing from the spirit and scope of the invention, the invention resides in the claims hereinafter appended.

Claims

WHAT IS CLAIMED IS:

1. A method for analysis of asymmetric activity patterns in a cell culture sample, the method comprising staining a cell culture sample in a well plate with a fluorescent dye; acquiring a plurality of time-lapsed images of the stained cell culture sample using a digital imaging device comprising confocal imaging microscopy; selecting one or more regions of interest in the stained cell culture sample images; extracting time-dependent patterns for a standard deviation of fluorescence intensity in the regions of interest; and analyzing the time-dependent patterns for the standard deviation of fluorescence intensity in the regions of interest to characterize the asymmetric activity patterns in the cell culture sample.

2. The method of claim 1, wherein the cell culture sample is a 2D cell culture sample or a 3D cell culture sample.

3. The method of claim 2, wherein the 3D cell culture sample is selected from the group consisting of a neuronal organoid, cerebral organoid, midbrain organoid, pituitary organoid, forebrain organoid, cortical organoid, thalamic organoid, hypothalamic organoid, hippocampal organoids, cerebellum organoid, choroid plexus organoid, medial ganglionic eminence (MGE) organoid, hindbrain organoid, brain assembloid, neuronal spheroid, neuronal progenitor cell (NPC), two-dimensional neuronal cell, retinal organoid, and cardiac organoid, optionally wherein the cardiac organoid is an immature cardiac organoid.

4. The method of any one of claims 1-3, wherein the fluorescent dye is a calciumsensitive fluorescence indicator.

5. The method of any one of claims 1-4, further comprisingrecording kinetic fluorescence intensities from the time-lapsed images to determine calcium flux patterns in the cell culture sample regions of interest.

6. The method of claim 5, wherein the calcium flux patterns are further characterized by one or more parameters selected from the group consisting of number of peaks, peak amplitude, peak intensity, number of fluxes, peak frequency, peak width, peak width at half height, distance between peaks, peak rise, and decay times.

7. The method of any one of claims 1-6, further comprising exposing the cell culture sample to an excitatory stimulus, optionally wherein the excitatory stimulus comprises optogenetic stimulation; and comparing the asymmetric activity patterns in the cell culture sample before and after the exposing to the excitatory stimulus.

8. The method of any one of claims 1-7, further comprising exposing the cell culture sample to a candidate compound for a first period of time.

9. The method of claim 8, wherein an effect on the cell culture sample is determined by comparing calcium flux patterns in the cell culture sample exposed to the candidate compound to calcium flux patterns in a comparable control cell culture sample stained with the calcium-sensitive fluorescence indicator without exposing to the candidate compound.

10. The method of claim 9, further comprising generating the cell culture sample from pluripotent stem cells while treating the cells with the candidate compound; and comparing development or functionality of the cell culture sample with development of a comparable cell culture sample that was not treated with the candidate compound.

11. The method of any one of claims 1-10, wherein the confocal imaging microscopy is spinning disk confocal microscopy.

12. The method of any one of claims 1-11, wherein the acquiring images comprises using the digital imaging device to acquire a first plurality of vertically spaced-apart images of the cell culture sample in the well plate, each image captured at a different height along a Z axis, such that a first volumetric image stack is generated with respect to the well.

13. The method of claim 12, wherein each image of the plurality of images comprises a combined plurality of smaller images all captured at the same height along the Z-axis.

14. The method of claim 13, wherein the plurality of smaller images is combined based on respective known positions of the digital imaging device with respect to a horizontal plane.

15. The method of any one of claims 12-14, wherein respective Z-coordinates of sequential images in the volumetric image stack differ by at least about 20 micrometers.

16. The method of any one of claims 12-15, wherein the respective Z-coordinates of sequential images in the volumetric image stack differ by less than about 50 micrometers.

17. The method of any one of claims 12-16, wherein the respective Z-coordinates of sequential images in the volumetric image stack differ by between 25 micrometers and 45 micrometers.

18. The method of any one of claims 1-17, wherein the well has a transparent base, and wherein the digital imaging device has an objective disposed below the base.

19. The method of any one of claims 1-18, wherein the one or more regions of interest comprise a plurality of non-overlapping partial regions of the cell culturesample images, optionally wherein the plurality of non-overlapping regions comprises at least one, at least 2, at least 3, at least 4, at least 4, 2-20, 3-15, or 4-10 regions of interest,20. The method of any one of claims 1-19, wherein the one or more regions of interest is selected manually, or by an automated method, optionally wherein the automated method comprises a machine learning method, optionally wherein the machine learning method comprises a model selected from the group consisting of a supervised learning model, unsupervised learning model, semi-supervised learning model, and reinforcement learning model.

21. The method of any one of claims 1 -20, wherein the analyzing of the timedependent patterns comprises plotting peak fluorescence intensity standard deviation in the selected regions of interest against time.

22. The method of claim 21, further comprising setting a peak threshold for analysis.

23. The method of claim 22, further comprising calculating the difference in peak fluorescence intensity standard deviation in the selected regions of interest of the same cell culture sample before and after the exposing to the excitatory stimulus.

Images