Fluorescence sensitivity monitor for flow cytometry

Abstract

Systems and methods for fluorescence sensitivity monitoring in a flow cytometer include measuring fluorescence of sheath fluid to determine sheath fluid noise; and setting the threshold detection value using the sheath fluid noise. Fluorescence of a plurality of samples having predetermined fluorescence intensities at different wavelengths is measured using a threshold detection value. A gate is made for each of a plurality of samples having predetermined fluorescence intensities at different wavelengths, and a mean fluorescence intensity (MFI) is identified for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths using the gate. One or more fluorescence channels of a flow cytometer are calibrated by calculating an equivalent soluble fluorescent molecule (MESF) using MFI and sheath fluid noise for each of a plurality of samples having predetermined fluorescence intensities at different wavelengths.

Description

[0001] Cross-reference to related applications

[0002] This application was filed as a PCT international application on January 31, 2025, and claims the benefit and priority of U.S. Provisional Application No. 63 / 548,653, filed on February 1, 2024, the disclosure of which is incorporated herein by reference in its entirety. Background Technology

[0003] Fluorescence sensitivity monitoring is used to ensure the accuracy and reliability of fluorescence detectors. The primary purpose of monitoring fluorescence sensitivity is to guarantee the precise measurement of the fluorescence signal emitted by cells or particles labeled with fluorescent dyes. This process involves regular quality control checks to maintain instrument performance and detect any deviations in sensitivity. By optimizing settings such as the photodetector voltage for each fluorescent dye, laboratories can improve sensitivity without signal saturation, thus contributing to consistent and reliable experimental results. Summary of the Invention

[0004] The examples presented herein relate to a method for monitoring fluorescence sensitivity in a flow cytometer. The method includes: measuring the fluorescence of the sheath fluid to determine sheath fluid noise; using the sheath fluid noise to set a threshold detection value; and using the threshold detection value to measure the fluorescence of multiple samples having predetermined fluorescence intensities at different wavelengths. The method also includes: gating each of the multiple samples having predetermined fluorescence intensities at different wavelengths; using the gating to identify the mean fluorescence intensity (MFI) for each of the multiple samples having predetermined fluorescence intensities at different wavelengths; and calibrating one or more fluorescence channels of the flow cytometer by calculating the equivalent amount of soluble fluorescent molecules (MESF) for each of the multiple samples having predetermined fluorescence intensities at different wavelengths using the MFI and the sheath fluid noise.

[0005] In other examples presented herein, the method further includes filtering the sheath fluid. In yet another example presented herein, the sheath fluid is a 5 nm sheath fluid.

[0006] In other examples presented herein, sheath fluid noise is the MFI of the sheath fluid. In other examples presented herein, multiple samples with predetermined fluorescence intensities at different wavelengths comprise multiple hard-dyed beads. In yet another example presented herein, the MESF is calculated using a calibration equation determined by: measuring the fluorescence of multiple color reader beads, each color reader bead being associated with a known amount of fluorophore; defining the MFI for each of the multiple color reader beads per fluorescence channel; and defining a calibration equation for each fluorescence channel using the relationship between the MFI and the known amount of fluorophore.

[0007] In other examples presented herein, identifying the MFI for each of a plurality of samples having a predetermined fluorescence intensity at different wavelengths includes: for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths, determining the peak intensity associated with the sample. In further examples presented herein, the method also includes determining the median and standard deviation for each peak.

[0008] Other examples presented herein relate to a method for determining a detection limit on a flow cytometer. This method includes: measuring fluorescence on the sheath fluid to determine sheath fluid noise; using the sheath fluid noise to set a threshold detection value; and using the threshold to measure the fluorescence of multiple fluorescent samples. In other examples presented herein, the method further includes filtering the sheath fluid. In yet another example presented herein, the sheath fluid is a 5 nm sheath fluid. In yet another example presented herein, the sheath fluid noise is the MFI of the sheath fluid.

[0009] Other examples presented herein relate to a method for calibrating one or more fluorescence channels of a flow cytometer. The method includes: measuring the fluorescence of a plurality of samples having predetermined fluorescence intensities at different wavelengths using a predetermined detection threshold; gating each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; identifying the average fluorescence intensity (MFI) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; and calibrating one or more fluorescence channels of the flow cytometer by calculating an equivalent amount of soluble fluorescent molecules (MESF) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths using the MFI and the predetermined detection threshold.

[0010] In other examples presented herein, the predetermined detection threshold is determined by measuring fluorescence on the sheath fluid to determine sheath fluid noise, and using the sheath fluid noise to set the predetermined detection threshold. In other examples presented herein, multiple samples with predetermined fluorescence intensities or conditions comprise multiple hard-stained microspheres. In yet another example presented herein, the multiple hard-stained microspheres comprise 8-peak microspheres.

[0011] In other examples presented herein, the MESF is calculated using a calibration equation determined by: measuring the fluorescence of a plurality of color reader microspheres, each color reader microsphere being associated with a known amount of fluorophore; defining the MFI for each of the plurality of color reader microspheres per fluorescence channel; and defining a calibration equation for each fluorescence channel using the relationship between the MFI and the known amount of fluorophore. In other examples presented herein, identifying the MFI for each of a plurality of samples having a predetermined fluorescence intensity or condition includes: determining the peak intensity associated with the sample for each of the plurality of samples having a predetermined fluorescence intensity or condition. In further examples presented herein, the method also includes determining the median and standard deviation for each peak.

[0012] Another example presented herein relates to a system for monitoring fluorescence sensitivity in a flow cytometer. The system includes: a laser configured to emit light toward a detection location to generate a fluorescence signal from particles guided through the detection location in a fluid flow; a fluorescence detector configured to detect the fluorescence signal from the particles guided through the detection location; and a controller communicating with the fluorescence detector, and including at least one processor and a non-transitory memory storing instructions. When executed by the controller, the instructions cause the controller to: measure the fluorescence of the sheath fluid using the fluorescence detector to determine sheath fluid noise; set a threshold detection value using the sheath fluid noise; measure the fluorescence of a plurality of samples having predetermined fluorescence intensities at different wavelengths using the fluorescence detector and the threshold detection value; gate each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; identify the average fluorescence intensity (MFI) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; and calibrate one or more fluorescence channels of the flow cytometer by calculating an equivalent amount of soluble fluorescent molecules (MESF) for each of the plurality of samples having predetermined fluorescence intensities or conditions, using the MFI and the sheath fluid noise.

[0013] Other examples presented herein relate to a non-transitory computer-readable medium comprising program instructions that, when executed by a processor, cause the processor to: measure the fluorescence of sheath fluid to determine sheath fluid noise; use the sheath fluid noise to set a threshold detection value; use the threshold detection value to measure the fluorescence of a plurality of samples having predetermined fluorescence intensities at different wavelengths; gate each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; use the gate to identify the mean fluorescence intensity (MFI) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; and calibrate one or more fluorescence channels of a flow cytometer by calculating an equal amount of soluble fluorescent molecules (MESF) using the MFI and sheath fluid noise for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths.

[0014] In other examples presented herein, the non-transitory computer-readable medium includes additional program instructions that, when executed by a processor, also cause the processor to filter the sheath fluid. In yet another example presented herein, the non-transitory computer-readable medium includes additional program instructions that, when executed by a processor, also cause the processor to calculate the MESF using a calibration equation determined by: measuring the fluorescence of a plurality of color reader microspheres, wherein each color reader microsphere is associated with a known amount of fluorophore; defining the MFI for each of the plurality of color reader microspheres per fluorescence channel; and defining a calibration equation for each fluorescence channel using the relationship between the MFI and the known amount of fluorophore. In yet another example presented herein, the non-transitory computer-readable medium includes additional program instructions that, when executed by a processor, also cause the processor to determine the median and standard deviation for each peak.

[0015] Various additional inventive aspects will be set forth in the following description. Inventive aspects may involve individual features and combinations of features. It should be understood that the foregoing general description and the following detailed description are merely exemplary and illustrative, and not intended to limit the broad inventive concept on which the embodiments disclosed herein are based. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate several aspects of this disclosure. A brief description of the drawings is as follows:

[0017] Figure 1 This is a schematic block diagram illustrating an example of a flow cytometer system.

[0018] Figure 2 This is an example of peaks resolved in the side scattering channel and fluorescence channel using 8-peak microspheres for fluorescence sensitivity monitoring.

[0019] Figure 3 A comparison of noise measurements of 8-peak microsphere buffer and sheath fluid on the purple side scattering channel was depicted.

[0020] Figure 4 A comparison of the resolution of the 8-peak microspheres when triggered on each of the side scattering and fluorescence channels is depicted.

[0021] Figure 5 This is a flowchart of an example method for monitoring fluorescence sensitivity in a flow cytometer.

[0022] Figure 6 This is a flowchart of an example method for determining the detection limit on a flow cytometer.

[0023] Figure 7This is a flowchart of an example method for calibrating one or more fluorescence channels of a flow cytometer.

[0024] Figure 8 This shows what can be used to implement Figure 1 An exemplary architecture of the computing device for various aspects of a flow cytometry system. Detailed Implementation

[0025] Fluorescence sensitivity monitoring in flow cytometry is a procedure used to define the lower limit of fluorescence detection. A significant limitation of routine fluorescence sensitivity monitoring is the lack of fluorophore-associated calibrators, which are reduced to the level of a few fluorescent molecules. Another important aspect is the procedure itself and how the calibrators are used in the flow cytometer. As part of routine quality control, current methods or systems used for fluorescence sensitivity monitoring do not provide quantitative methods for assessing the lower limit of fluorescence detection, making it more difficult for flow cytometer users to evaluate whether the instrument is ready for testing.

[0026] While fluorescence sensitivity monitoring has been incorporated into some routine flow cytometers, existing procedures have several drawbacks. First, these procedures are typically performed only in response to user requests and therefore do not cover routine instrument monitoring. Second, the minimum equivalent soluble fluorescent molecule (MESF) is defined based on 1 µm blank microspheres, which cannot be distinguished from detected background noise and cannot establish an accurate detection limit.

[0027] Reference will now be made in detail to exemplary aspects of this disclosure, which are illustrated in the accompanying drawings. Where possible, the same reference numerals will be used throughout the drawings to refer to the same or similar parts.

[0028] Figure 1 This is a schematic block diagram illustrating an example of a flow cytometry system 100. Typically, flow cytometry is a technique used to measure and analyze the physical and chemical properties of samples of particles or cells. Data from millions of cells can be collected within minutes and displayed to researchers or clinicians in various formats. Some example applications include: phenotypic analysis for identifying and counting specific cell types within a population; analyzing DNA or RNA content; determining the presence of antigens on or within cell surfaces; and assessing cell health status.

[0029] Flow cytometry can be used to analyze and sort cells based on their physical and chemical properties. It is commonly used in various fields, including immunology, oncology, hematology, and microbiology. Flow cytometers measure the properties of individual cells as they pass through a fluid system. Several features of flow cytometry, which will be discussed in further detail below, help distinguish different cell and particle types, including all forward scattering (FSC), side scattering (SSC), and fluorescence detectors, multiparameter analysis, and functional and quantitative assays.

[0030] A flow cytometry system 100 typically comprises three main component subsystems: a fluid system 110, an optical system 120, and a computing device 130. The fluid system 110 includes a nozzle 112 that receives a sample containing particles or cells suspended in a fluid. The nozzle 112 generates and ejects a fluid flow 114 of particles, which are arranged in a single queue. Each particle passes through one or more beams of light generated by a laser 102. The point where a particle intersects with the beam is referred to as the interrogation location 116.

[0031] Optical system 120 includes laser 102, optical element 122, and detector 124. At detection position 116, light from laser 102 strikes a particle and scatters. Optical element 122 guides the scattered light toward detector 124. Detector 124 may include: a forward scattering (FSC) detector for measuring scattering along the path of laser 102; a side scattering (SSC) detector for measuring scattering at a 90-degree angle relative to laser 102; and / or one or more (FL1, FL2, and FL3) fluorescence detectors for measuring the emission fluorescence intensity at different wavelengths of light.

[0032] Typically, FSC provides information about cell size, while SSC provides insights into cell granularity or internal complexity. By analyzing both FSC and SSC, different cell types can be distinguished based on cell size and internal structure. Generally, due to light diffraction around the particle, the intensity of FSC is proportional to the size or diameter of the particle. Therefore, FSC can be used to differentiate particles by size. On the other hand, SSC is generated based on the light refracted or reflected by the particle's internal structure, thus SSC can provide information about the particle's internal complexity or granularity.

[0033] Different fluorescent dyes can be used to label different cell types or cell markers. For example, antibodies conjugated to fluorescent dyes can specifically bind to cell surface markers, thereby enabling the identification of specific cell populations. By adding fluorescent labels to samples, different fluorescent signals / channels (e.g., green, orange, and red) can be analyzed for the functional characteristics of cells. For example, since T cells have CD3 binding sites, samples containing T cells can be "stained" using anti-CD3 antibodies conjugated to fluorescent molecules. When these cells pass through detection site 116, a laser excites the fluorescent tag or fluorescent dye, causing it to emit photons at a wavelength detectable by a fluorescence detector. Therefore, detector 124 can simultaneously measure multiple parameters and enable particle classification based on particle function according to the wavelength of the detected light.

[0034] The number of detectors 124, particularly the number of fluorescence detectors (FL1, etc.), can be determined based on specific parameters of a given experiment. For example, multicolor flow cytometry, used for the simultaneous analysis and sorting of multiple properties of individual cells, involves the use of multiple fluorescent markers. Each marker has a different emission spectrum and labels specific molecules or cellular components within the cell. By measuring the emitted light at different wavelengths, researchers can gather a wealth of information about cell properties, such as surface markers, intracellular protein and DNA content. This technique is particularly valuable for studying complex cell populations, including immune cells, and is commonly used in immunology, hematology, and cancer research to characterize and sort cells based on their unique molecular profiles.

[0035] Fluorescence sensitivity monitoring is used to ensure the accuracy and reliability of fluorescence detectors. Consistency between experiments is a key benefit of fluorescence sensitivity monitoring, as it makes results from different experimental procedures comparable. Early detection and problem-solving are another important aspect, as variations in sensitivity can indicate issues such as optical misalignment, component degradation, or electronic problems within the flow cytometer. Furthermore, fluorescence sensitivity monitoring is part of a validation process, allowing laboratories to verify that the instrument operates within established parameters and conforms to standards and regulations. This proactive quality control approach not only prevents data variability but also instills user confidence in the reliability of the flow cytometer and its results. Overall, fluorescence sensitivity monitoring is indispensable for maintaining the accuracy, consistency, and compliance of flow cytometry data, thus contributing to the robustness of scientific and clinical analysis.

[0036] Figure 1The flow cytometer system 100 includes elements shown and described for discussion purposes, and it should be understood that many variations of components and functions are possible. Optical elements 122 may include a series of filters, dichroic mirrors, and / or beam splitters to select different wavelengths of light and provide those wavelengths to an appropriate detector 124. For example, detector 124 may include a photodetector, such as a photomultiplier tube (PMT) or an avalanche photodiode (APD).

[0037] The computing device 130 receives and processes signals received from the detector 124, and in some examples, the computing device 130 may include waveform acquisition means and waveform analysis means. In some embodiments, the computing device 130 includes a computing device communicatively coupled to the flow cytometer 101 via a network. In other embodiments, the computing device 130 is integrated with the flow cytometer 101.

[0038] The computing device 130 performs data processing on the output of the detector 124 and converts the raw signal into meaningful information about the particles being analyzed. In this embodiment, the analog signal from the detector 124 is then digitized, converting it into a digital format suitable for computer processing. Specialized data analysis software is used to extract parameters, gate the cells to separate specific populations of interest, and generate histograms representing the distribution of data points. Researchers use this software to calculate statistical data for each gated population, thereby providing quantitative insights into the characteristics of different cell populations.

[0039] Data visualization tools aid in the creation of scatter plots and other graphical representations, facilitating the interpretation of complex datasets. Quality control checks are implemented throughout the workflow to ensure the reliability and accuracy of results. Researchers can validate their findings by comparing them to known standards or by implementing internal controls. Processed data, along with visualizations and statistics, can be exported for further analysis or included in scientific publications. Overall, the data processing of detector outputs in flow cytometry represents a comprehensive and systematic approach, enabling researchers to unravel the complexities of cellular properties at the single-cell level.

[0040] In an embodiment, computing device 130 is used to store, for example, instructions for automatic or manual fluorescence sensitivity monitoring of flow cytometer 101 in fluorescence sensitivity monitoring module 132, and / or to perform automatic or manual fluorescence sensitivity monitoring. Fluorescence sensitivity monitoring is conventionally performed by measuring a predetermined number of peaks of fluorescence intensity based on a trigger on a side-scatter detector. Typically, eight hard-stained microspheres are used to generate the predetermined number of peaks, conventionally and herein referred to as "8-peak microspheres," but those skilled in the art will understand that other numbers of peaks can be used for fluorescence sensitivity monitoring. Gating is performed on the microspheres and the noise population, and based on this data, the number of peaks distinguished from the noise in each fluorescence channel is limited.

[0041] Figure 2 This is an example of peaks resolved in the side scattering and fluorescence channels using 8-peak microspheres for fluorescence sensitivity monitoring. The top row depicts a series of side scattering detections 202, and the bottom row depicts a series of fluorescence detections 204. Figure 222 depicts violet side scattering, Figure 224 depicts yellow side scattering, Figure 226 depicts blue side scattering, and Figure 228 depicts red side scattering. Figure 242 depicts the violet fluorescence channel at approximately 447 nm, Figure 244 depicts the blue fluorescence channel at approximately 531 nm, Figure 246 depicts the yellow fluorescence channel at approximately 595 nm, and Figure 248 depicts the red fluorescence channel at approximately 670 nm. In the series of side scattering detections 202, the noise peak 230 is most prominent in Figure 222 depicting violet side scattering.

[0042] As disclosed in this paper, the high noise associated with the buffer solution routinely used with the 8-peak microspheres masks the true lower limit of instrument detection. Figure 3 A comparison of noise measurements on the 8-peak microsphere buffer and sheath fluid in the purple side-scattering channel is depicted. Figure 302 depicts the lower level of noise measurement 306 on the conventional microsphere buffer, which can be seen to cover a wide range of values ​​and has somewhat blurred resolution. In contrast, Figure 304 depicts the lower level of noise measurement 308 on the sheath fluid, which can be seen to be resolved as tight and limited peaks.

[0043] Because this pattern is consistently observable in repeated measurements, the median sheath fluid noise is significantly lower than the median buffer noise. As disclosed herein, this reduction in median noise contributes to increasing the Fisher distance between the noise and the first resolvable peak in each channel. The Fisher distance (FD) is defined based on the following equation:

[0044]

[0045] Where MFI1 and MFI2 are the median (or average fluorescence intensity) of the two populations for noise measurement, and δ1 and δ2 are the standard deviations of the two populations. FD is used to define the distance between the detection limit determined based on noise measurement and the first resolvable peak. As embodied in the systems and methods disclosed herein, using sheath fluid for noise determination, rather than the conventional practice of resolving noise from a buffer solution of microspheres, the Fischer distance value increases with a correlated increase in instrument sensitivity.

[0046] While switching to using sheath fluid as the basis for the lower detection threshold is advantageous and produces a more accurate threshold for lower levels of detection, additional advantages are achieved by defining a clear cutoff between the negative population (e.g., noise) and the positive population (e.g., the first resolvable peak from each channel). By defining this cutoff more clearly, the threshold can be set with greater precision, and values ​​above the threshold can be detected more accurately.

[0047] Using a fluorescence channel to measure noise, rather than the conventional practice of triggering based on side-scattering detection, provides more control when setting the threshold. Compared to the broad noise spread seen in side-scattering, fluorescence detection can be configured to make the noise from the sheath fluid appear as a precise peak or knife-edge shape, which can be used as a lower cutoff.

[0048] Figure 4 A comparison of the resolution of the eight-peak microspheres when triggered on each of the side-scattering and fluorescence channels is depicted. Figure 352 shows the peaks resolved when triggered on the side-scattering channel, and Figure 354 shows the peaks resolved when triggered on the fluorescence channel. As can be seen in this example, the peaks in Figure 354 exhibit clearer resolution at lower values ​​compared to the peaks in Figure 352, where noise from the sheath fluid and / or buffer solution is expected.

[0049] Figure 5 This is a flowchart of an example method 400 for monitoring fluorescence sensitivity in a flow cytometer. In an embodiment, method 400 is controlled by a controller or computing device associated with the flow cytometer (e.g., Figure 1 The method is executed by a computing device 130. In an embodiment, method 400 is executed by a separate device or a downstream data processing system that receives processed waveform data from the flow cytometer.

[0050] At operation 402, the fluorescence of the sheath fluid is measured to determine the sheath fluid noise. The method may also include filtering the sheath fluid. Filtering the sheath fluid can be performed integrated with flow cytometry and can represent routine processing of the sheath fluid within the system. Filtering the sheath flow can further reduce the generated noise by reducing noise-generating debris present in the fluid. In one embodiment, the sheath fluid is a 5 nm sheath fluid. In some embodiments, the 5 nm sheath fluid is a sheath fluid that has been filtered to remove impurities larger than 5 nm. In some cases, the MFI of the sheath fluid is used as the sheath fluid noise.

[0051] At operation 404, sheath fluid noise is used to set the threshold detection value. Setting a threshold for the detection limit is used to distinguish the true sample signal from background noise, especially for events with low fluorescence or abundance. By systematically evaluating background noise, using negative controls, calculating the signal-to-noise ratio, and validating with known samples, researchers can establish a reliable detection limit in flow cytometry. This helps ensure accurate interpretation of experimental results. The threshold detection value can be automatically set by the system in response to sheath fluid noise measurements, or it can be approved or set by user input.

[0052] At operation 406, a threshold detection value is used to measure the fluorescence of multiple samples having a predetermined fluorescence intensity at different wavelengths. In this embodiment, the multiple samples having a predetermined fluorescence intensity at different wavelengths include multiple hard-stained microspheres. The multiple hard-stained microspheres may be 8-peak microspheres.

[0053] At operation 408, each of the multiple samples having a predetermined fluorescence intensity at different wavelengths is gated. Gating the fluorescence signal is a process used to establish a baseline and monitor the sensitivity of the flow cytometer by using reference microspheres or particles with a predetermined fluorescence intensity, thereby ensuring the accuracy and reliability of the fluorescence sensitivity data. In some examples, negative controls or samples lacking a biomarker of interest are included to help identify background noise and to set a threshold for distinguishing true signals. Gating and information on the fluorescence intensity range covering the expected dynamic range are set on a scatter plot or histogram to separate the population of interest. The gate can be adjusted to exclude background noise while capturing the relevant fluorescence signal.

[0054] At operation 410, for each of a plurality of samples having a predetermined fluorescence intensity at different wavelengths, a gate is used to identify the mean fluorescence intensity (MFI). In an embodiment, the MFI is determined as the peak intensity associated with the sample. In some cases, determining the MFI includes determining the median and standard deviation of each peak.

[0055] In flow cytometry, MFI is a quantification of the average fluorescence intensity within a population of microspheres, cells, or particles labeled with a fluorescent marker. This technique enables the analysis of individual entities within a sample or group exhibiting multiple fluorescence signals. MFI can be calculated using data analysis software by determining the average fluorescence intensity of events within a defined gate.

[0056] MFI calculation involves summing the fluorescence intensity values ​​of all events within a gate and then dividing that sum by the number of events. This yields a representative value indicating the central tendency of fluorescence within the selected population. Higher MFI values ​​generally indicate increased expression of the target marker on the cell surface or within the cell. Recognizing that absolute values ​​can vary between experiments and instruments, MFI is a useful parameter for comparing different samples or conditions in a single experiment.

[0057] At operation 412, one or more fluorescence channels of the flow cytometer are calibrated by calculating the equivalent amount of soluble fluorescent molecules (MESF) for each of multiple samples with a predetermined fluorescence intensity at different wavelengths using MFI and sheath fluid noise.

[0058] Calculating the MESF presents a new challenge of lowering the detection limit, as many fluorophore-associated calibrators do not drop to the level of a few fluorescent molecules. To determine a sufficiently accurate equation for calculating the MESF, color reader microspheres are used to determine the number of fluorophores associated with the measured MFI value.

[0059] In the example, microspheres with a known number of capture sites (e.g., antibody capture sites) are used, and equations are determined based on a known fluorophore / protein ratio. Since each microsphere is associated with a known number of fluorophores, the measured MFI associated with the color reader microsphere can be used to generate a graph of the MESF versus MFI for each fluorescence channel, based on the number of capture sites and the number of fluorophores for each protein. Using this graph, the slope and intercept can be determined for each fluorescent dye, and these slope and intercept can be used to define the associated calibration equation. In this implementation, no plotting is performed, and the equations are defined based on the mathematical relationship with a known number of fluorophores determined using the MFI. Once defined, the equations for each fluorescent dye or each fluorescence channel are used to calculate the MESF for each measured MFI during fluorescence sensitivity monitoring (sheath fluid noise and reference microspheres).

[0060] In this implementation, each calibration curve is defined for the actual fluorescent dye, and MESF values ​​are assigned to each peak of, for example, the 8-peak microsphere and the sheath fluid noise, by extending the calibration curves. The MESF assignment value for the sheath fluid noise is used as a cutoff value above which the instrument is sufficiently sensitive to detect available sample values. These values ​​can be varied depending on the calibrator used. In this implementation, the calibration curves are predetermined and can be associated with the instrument, for example, through metadata or through non-transitory memory stored in the controller or computing device associated with the instrument.

[0061] While Example Method 400 presents a general approach to fluorescence sensitivity monitoring, in implementations, fluorescence sensitivity monitoring can be divided into sub-methods that can be performed independently to monitor or adjust instrument operation. For example, establishing the detection limit and calibrating the fluorescence channel can be performed separately.

[0062] Figure 6 This is a flowchart of an example method 500 for determining the detection limit on a flow cytometer. In an embodiment, method 500 is performed by a controller or computing device associated with the flow cytometer (e.g., Figure 1 The method is performed by a computing device 130. In an embodiment, method 500 is performed by a separate device or a downstream data processing system that receives processed waveform data from the flow cytometer.

[0063] At operation 502, fluorescence on the sheath fluid is measured to determine sheath fluid noise. The method may also include filtering the sheath fluid. Filtering the sheath fluid can be performed integrated with flow cytometry and can represent routine processing of the sheath fluid within the system. Filtering the sheath flow can further reduce the generated noise by reducing noise-generating debris present in the fluid. In this embodiment, the sheath fluid is a 5 nm sheath fluid. In some cases, the MFI of the sheath fluid is used as the sheath fluid noise.

[0064] At operation 504, sheath fluid noise is used to set the threshold detection value. Setting a threshold for the detection limit is used to distinguish the true sample signal from background noise, especially for events with low fluorescence or abundance. The threshold detection value can be automatically set by the system in response to sheath fluid noise measurement, or it can be approved or set by user input.

[0065] At operation 506, a threshold is used to measure the fluorescence of multiple fluorescent samples. In this embodiment, the multiple samples having a predetermined fluorescence intensity at different wavelengths comprise multiple hard-stained microspheres. These multiple hard-stained microspheres may be 8-peak microspheres.

[0066] Figure 7 This is a flowchart of an example method 600 for calibrating one or more fluorescence channels of a flow cytometer. In an embodiment, method 600 is performed by a controller or computing device associated with the flow cytometer (e.g., Figure 1 The method is performed by a computing device 130. In an embodiment, method 600 is performed by a separate device or a downstream data processing system that receives processed waveform data from the flow cytometer.

[0067] At operation 602, a predetermined detection threshold is used to measure the fluorescence of multiple samples having a predetermined fluorescence intensity at different wavelengths. In this implementation, methods such as... Figure 6 Method 500 is used to determine a predetermined detection threshold. In one embodiment, multiple samples having predetermined fluorescence intensities at different wavelengths comprise multiple hard-stained microspheres. These multiple hard-stained microspheres may be 8-peak microspheres.

[0068] At operation 604, each of the multiple samples having a predetermined fluorescence intensity at different wavelengths is gated. Gating the fluorescence signal is a process used to ensure the accuracy and reliability of fluorescence sensitivity data by establishing a baseline using reference microspheres or particles with a predetermined fluorescence intensity and monitoring the sensitivity of the flow cytometer. Gates are set on scatter plots or histograms, along with information on the fluorescence intensity range covering the expected dynamic range, to separate populations of interest.

[0069] At operation 606, for each of a plurality of samples having a predetermined fluorescence intensity at different wavelengths, the MFI is identified. In an embodiment, the MFI is determined as the peak intensity associated with the sample. In some cases, determining the MFI includes determining the median and standard deviation for each peak. The MFI is a quantified measure of the average fluorescence intensity within a population of microspheres, cells, or particles that have been labeled with a fluorescent marker. This technique enables the analysis of individual entities within a sample or group having multiple fluorescence signals. The MFI can be calculated using data analysis software by determining the average fluorescence intensity of events within a defined gate.

[0070] At operation 608, one or more fluorescence channels of the flow cytometer are calibrated by calculating MESF for each of a plurality of samples having a predetermined fluorescence intensity or condition using MFI and a predetermined detection threshold.

[0071] Figure 8 An exemplary architecture of a computing device, including computing device 300, is shown that can be used to implement various aspects of the present disclosure. Figure 8 The computing devices shown can be used to execute the operating systems, applications, and software modules (including software engines) described herein.

[0072] In some embodiments, computing device 130 includes at least one processing device 902, such as a central processing unit (CPU). Various processing devices are available from various manufacturers, such as Intel or Advanced Micro Devices. In this example, computing device 130 also includes system memory 906 and a system bus 904, which couples various system components, including system memory 906, to processing device 902. System bus 904 is one of any number of types of bus architectures, including a memory bus or memory controller; a peripheral bus; and a local bus using any of a variety of bus architectures.

[0073] Examples of computing devices suitable for computing device 130 include server computers, desktop computers, laptop computers, tablet computers, mobile computing devices (such as smartphones, iPod® or iPad® mobile digital devices or other mobile devices), or other devices configured to process digital instructions.

[0074] System memory 906 includes read-only memory 908 and random access memory (RAM) 910. Read-only memory 908 typically stores a basic input / output system 912, which includes basic routines for transferring information within computing device 130, for example, during startup. In some embodiments, waveform analysis device 150 ( Figure 1 It has a large memory capacity, for example, equal to or greater than one trillion bytes of RAM. The RAM can be used by the GPU 152 to load and subsequently analyze waveform data (e.g., raw waveform data, such as data stored in a raw waveform data file, which may include digitized waveform data).

[0075] In some embodiments, the computing device 130 further includes an auxiliary storage device 914, such as a hard disk drive, for storing digital data. The auxiliary storage device 914 is connected to the system bus 904 via an auxiliary storage interface 916. The auxiliary storage device 914 and its associated computer-readable medium provide the computing device 130 with non-volatile storage of computer-readable instructions (including application programs and program modules), data structures, and other data.

[0076] While the exemplary environment described herein employs a hard disk drive as a secondary storage device, other types of computer-readable storage media are used in other embodiments. Examples of these other types of computer-readable storage media include magnetic tape cartridges, flash memory cards, digital video discs, Bernoulli cartridges, optical disc read-only memory, digital universal disc read-only memory, random access memory, or read-only memory. Some embodiments include non-transitory media. Additionally, such computer-readable storage media may include local storage or cloud-based storage.

[0077] Numerous program modules, including an operating system 918, one or more application programs 920, other program modules 922 (such as the software engine described herein), and program data 924, can be stored in auxiliary storage device 914 or memory 906. Computing device 130 can use any suitable operating system, such as Microsoft Windows™, Google Chrome™, Apple OS, and any other operating system suitable for computing devices.

[0078] In some implementations, a user provides input to the computing device 130 via one or more input devices 926. Examples of input devices 926 include a keyboard 928, a mouse 930, a microphone 932, and a touch sensor 934 (e.g., a touchpad or touch-sensitive display). Other implementations include other input devices 926. Input devices 926 are often connected to the processing device 902 via input / output interfaces 936 coupled to a system bus 904. These input devices 926 can be connected via any number of input / output interfaces, such as parallel ports, serial ports, game ports, or universal serial buses. Wireless communication between the input devices and the interface 936 is also possible, and in some possible implementations include infrared, BLUETOOTH® wireless technology, 802.11a / b / g / n, cellular, or other radio frequency communication systems.

[0079] In this example embodiment, display device 938, such as a monitor, liquid crystal display device, projector, or touch-sensitive display device, is also connected to system bus 904 via an interface such as video adapter 940. In addition to display device 938, computing device 130 may include various other peripheral devices (not shown), such as speakers or printers.

[0080] When used in a local area network (LAN) or wide area network (WAN) environment (such as the Internet), computing device 130 is typically connected to a network via a network interface 942, such as an Ethernet interface. Other possible implementations use other communication devices. For example, some implementations of computing device 130 include a modem for cross-network communication.

[0081] Computing device 130 typically includes at least some form of computer-readable medium. Computer-readable medium includes any available medium that can be accessed by computing device 130. By way of example, computer-readable medium includes computer-readable storage media and computer-readable communication media.

[0082] Computer-readable storage media includes volatile and non-volatile, removable and non-removable media implemented in any device configured to store information such as computer-readable instructions, data structures, program modules or other data. Computer-readable storage media includes, but is not limited to, random access memory, read-only memory, electrically erasable programmable read-only memory, flash memory or other memory technologies, optical disc read-only memory, digital universal disk or other optical storage devices, magnetic tape cassettes, magnetic tape, disk storage devices or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by computing device 130. Computer-readable storage media does not include computer-readable communication media.

[0083] Computer-readable communication media typically embody computer-readable instructions, data structures, program modules, or other data in the form of modulated data signals (such as carrier waves) or other transmission mechanisms, and include any information delivery medium. The term "modulated data signal" refers to a signal whose characteristics are set or altered in a manner that encodes information within the signal. By way of example, computer-readable communication media include: wired media, such as wired networks or direct wired connections; and wireless media, such as acoustic media, radio frequency media, infrared media, and other wireless media. Any combination of the above is also included within the scope of computer-readable media.

[0084] Figure 8 The computing devices shown are also examples of programmable electronic devices, which may include one or more such computing devices, and when multiple computing devices are included, such computing devices may be coupled together using a suitable data communication network to jointly perform the various functions, methods or operations disclosed herein.

[0085] Illustrative examples of the systems and methods described herein are provided below. Implementations of the systems or methods described herein may include any one or more of the clauses described below, as well as any combination of the clauses.

[0086] Clause 1. A method for monitoring fluorescence sensitivity in a flow cytometer, the method comprising: measuring the fluorescence of a sheath fluid to determine sheath fluid noise; using the sheath fluid noise to set a threshold detection value; using the threshold detection value to measure the fluorescence of a plurality of samples having predetermined fluorescence intensities at different wavelengths; gatening for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; using the gate to identify the mean fluorescence intensity (MFI) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; and calibrating one or more fluorescence channels of the flow cytometer by calculating an equivalent amount of soluble fluorescent molecules (MESF) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths using the MFI and the sheath fluid noise.

[0087] Clause 2. The method described in Clause 1 further includes filtering sheath fluid.

[0088] Clause 3. The method according to Clause 2, wherein the sheath fluid is a 5 nm sheath fluid.

[0089] Clause 4. The method according to any one of Clauses 1 to 3, wherein the sheath fluid noise is the MFI of the sheath fluid.

[0090] Clause 5. The method according to any one of Clauses 1 to 4, wherein the plurality of samples having a predetermined fluorescence intensity at different wavelengths comprises a plurality of hard-stained microspheres.

[0091] Clause 6. The method according to any one of Clauses 1 to 5, wherein the MESF is calculated using a calibration equation determined by: measuring the fluorescence of a plurality of color reader microspheres, wherein each color reader microsphere is associated with a known amount of fluorophore; defining the MFI for each of the plurality of color reader microspheres per fluorescence channel; and defining a calibration equation for each fluorescence channel using the relationship between the MFI and the known amount of fluorophore.

[0092] Clause 7. The method according to any one of Clauses 1 to 6, wherein identifying the MFI for each of a plurality of samples having a predetermined fluorescence intensity at different wavelengths comprises: determining a peak intensity associated with the sample for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths.

[0093] Clause 8. The method described in Clause 7 further includes determining the median and standard deviation for each peak.

[0094] Clause 9. A method for determining a detection limit on a flow cytometer, the method comprising: measuring fluorescence on a sheath fluid to determine sheath fluid noise; using the sheath fluid noise to set a threshold detection value; and using the threshold to measure fluorescence of a plurality of fluorescent samples.

[0095] Clause 10. The method described in Clause 9 further includes filtering sheath fluid.

[0096] Clause 11. The method according to Clause 10, wherein the sheath fluid is a 5 nm sheath fluid.

[0097] Clause 12. The method according to any one of Clauses 9 to 11, wherein the sheath fluid noise is the MFI of the sheath fluid.

[0098] Clause 13. A method for calibrating one or more fluorescence channels of a flow cytometer, the method comprising: measuring the fluorescence of a plurality of samples having a predetermined fluorescence intensity at different wavelengths using a predetermined detection threshold; gating each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths; identifying the average fluorescence intensity (MFI) for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths; and calibrating one or more fluorescence channels of the flow cytometer by calculating an equivalent amount of soluble fluorescent molecules (MESF) for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths using the MFI and the predetermined detection threshold.

[0099] Clause 14. The method according to Clause 13, wherein the predetermined detection threshold is determined by measuring fluorescence on the sheath fluid to determine sheath fluid noise; and using the sheath fluid noise to set the predetermined detection threshold.

[0100] Clause 15. The method according to Clause 13 or 14, wherein the plurality of samples having a predetermined fluorescence intensity or condition comprises a plurality of hard-stained microspheres.

[0101] Clause 16. The method according to Clause 15, wherein the plurality of hard-stained microspheres comprises 8-peak microspheres.

[0102] Clause 17. The method according to any one of Clauses 13 to 16, wherein the MESF is calculated using a calibration equation determined by: measuring the fluorescence of a plurality of color reader microspheres, wherein each color reader microsphere is associated with a known amount of fluorophore; defining the MFI for each of the plurality of color reader microspheres per fluorescence channel; and defining a calibration equation for each fluorescence channel using the relationship between the MFI and the known amount of fluorophore.

[0103] Clause 18. The method according to any one of Clauses 13 to 17, wherein identifying the MFI for each of a plurality of samples having a predetermined fluorescence intensity or condition comprises: determining, for each of the plurality of samples having a predetermined fluorescence intensity or condition, a peak intensity associated with the sample.

[0104] Clause 19. The method described in Clause 18 further includes determining the median and standard deviation for each peak.

[0105] Clause 20. A system for monitoring fluorescence sensitivity in a flow cytometer, the system comprising: a laser configured to emit light toward a detection location to generate a fluorescence signal from particles guided through the detection location in a fluid flow; a fluorescence detector configured to detect the fluorescence signal from the particles guided through the detection location; a controller communicating with the fluorescence detector and including at least one processor and a non-transitory memory storing instructions which, when executed by the controller, cause the controller to: measure the fluorescence of a sheath fluid using the fluorescence detector to determine sheath fluid noise; set a threshold detection value using the sheath fluid noise; measure the fluorescence of a plurality of samples having predetermined fluorescence intensities at different wavelengths using the fluorescence detector and the threshold detection value; gate each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; identify the average fluorescence intensity (MFI) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; and calibrate one or more fluorescence channels of the flow cytometer by calculating an equivalent amount of soluble fluorescent molecules (MESF) using the MFI and the sheath fluid noise for each of the plurality of samples having predetermined fluorescence intensities or conditions.

[0106] Clause 21. A non-transitory computer-readable medium comprising program instructions that, when executed by a processor, cause the processor to: measure the fluorescence of a sheath fluid to determine sheath fluid noise; use the sheath fluid noise to set a threshold detection value; use the threshold detection value to measure the fluorescence of a plurality of samples having predetermined fluorescence intensities at different wavelengths; gate each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; use the gate to identify the mean fluorescence intensity (MFI) for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths; and calibrate one or more fluorescence channels of a flow cytometer by calculating an equivalent amount of soluble fluorescent molecules (MESF) using the MFI and the sheath fluid noise for each of the plurality of samples having predetermined fluorescence intensities at different wavelengths.

[0107] Clause 22. The non-transitory computer-readable medium according to Clause 21 further includes additional program instructions that, when executed by a processor, also cause the processor to filter sheath fluid.

[0108] Clause 23. The non-transitory computer-readable medium according to Clause 21 or 22 further includes additional program instructions that, when executed by a processor, also cause the processor to calculate the MESF using a calibration equation determined by: measuring the fluorescence of a plurality of color reader microspheres, wherein each color reader microsphere is associated with a known amount of fluorophore; defining the MFI for each of the plurality of color reader microspheres per fluorescence channel; and defining a calibration equation for each fluorescence channel using the relationship between the MFI and the known amount of fluorophore.

[0109] Clause 24. The non-transitory computer-readable medium according to any one of Clauses 21 to 23 further includes additional program instructions that, when executed by a processor, also cause the processor to determine the median and standard deviation for each peak.

[0110] Preferred aspects and implementations of this disclosure have been described, and modifications and equivalents of the disclosed concept will readily occur to those skilled in the art. However, such modifications and equivalents are intended to be included within the scope of the appended claims.

Claims

1. A method for monitoring fluorescence sensitivity in a flow cytometer, the method comprising: Measure the fluorescence of the sheath fluid to determine sheath fluid noise; The threshold detection value is set using the sheath fluid noise; The threshold detection value is used to measure the fluorescence of multiple samples with a predetermined fluorescence intensity at different wavelengths; Gating is performed on each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths; For each of the plurality of samples that have a predetermined fluorescence intensity at different wavelengths, a gate is used to identify the average fluorescence intensity (MFI). as well as The flow cytometer is calibrated by calculating an equal amount of soluble fluorescent molecules (MESF) using the MFI and the sheath fluid noise for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths.

2. The method according to claim 1 further includes filtering the sheath fluid.

3. The method according to claim 2, wherein, The sheath fluid is a 5 nm sheath fluid.

4. The method according to any one of claims 1 to 3, wherein, The sheath fluid noise is the MFI of the sheath fluid.

5. The method according to any one of claims 1 to 4, wherein, The plurality of samples, which have a predetermined fluorescence intensity at different wavelengths, comprise a plurality of hard-stained microspheres.

6. The method according to any one of claims 1 to 5, wherein, The MESF is calculated using calibration equations determined in the following manner: The fluorescence of multiple color reader microspheres was measured, wherein each color reader microsphere was associated with a known amount of fluorophore; For each fluorescence channel, a defined MFI is established for each of the multiple color reader microspheres; as well as The relationship between the MFI and the known amount of fluorophores is used to define a calibration equation for each fluorescence channel.

7. The method according to any one of claims 1 to 6, wherein, Identifying the MFI for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths includes: for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths, determining the peak intensity associated with the sample.

8. The method of claim 7, further comprising determining the median and standard deviation for each peak.

9. A system for monitoring fluorescence sensitivity in a flow cytometer, the system comprising: A laser is configured to emit light toward a detection location to generate a fluorescence signal from particles that are guided from the fluid flow through the detection location; A fluorescence detector configured to detect the fluorescence signal from a particle guided through the detection location; A controller, which communicates with the fluorescence detector, and includes at least one processor and a non-transitory memory storing instructions that, when executed by the controller, cause the controller to: The fluorescence of the sheath fluid is measured using the fluorescence detector to determine the sheath fluid noise; The threshold detection value is set using the sheath fluid noise; Using the fluorescence detector, the fluorescence of multiple samples with predetermined fluorescence intensities at different wavelengths is measured using the threshold detection value; Gating is performed on each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths; For each of the plurality of samples that have a predetermined fluorescence intensity at different wavelengths, the average fluorescence intensity (MFI) is identified. as well as The flow cytometer is calibrated by calculating an equal amount of soluble fluorescent molecules (MESF) for each of the plurality of samples having a predetermined fluorescence intensity or condition, using the MFI and the sheath fluid noise.

10. The system of claim 9 further includes a filter for filtering the sheath fluid.

11. The method according to claim 10, wherein, The sheath fluid is a 5 nm sheath fluid.

12. The method according to any one of claims 9 to 11, wherein, The sheath fluid noise is the MFI of the sheath fluid.

13. The method according to any one of claims 9 to 12, wherein, The plurality of samples, which have a predetermined fluorescence intensity at different wavelengths, comprise a plurality of hard-stained microspheres.

14. The method according to any one of claims 9 to 13, wherein, The instructions for calculating MESF use a calibration equation determined by executing additional instructions stored in the non-transitory memory via the controller, which in turn cause the controller to: The fluorescence of multiple color reader microspheres was measured, wherein each color reader microsphere was associated with a known amount of fluorophore; For each fluorescence channel, a defined MFI is established for each of the multiple color reader microspheres; as well as The relationship between the MFI and the known amount of fluorophores is used to define a calibration equation for each fluorescence channel.

15. The method according to any one of claims 9 to 14, wherein, The instructions for identifying the MFI for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths include additional instructions stored in the non-transitory memory, which cause the controller to determine for each of the plurality of samples having a predetermined fluorescence intensity at different wavelengths: Peak intensities associated with the sample; as well as For each peak, the median and standard deviation.

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