Device and method for assessment of secreted proteins from single cells in a culture

Abstract

Provided herein are methods for the high throughput screening of cells secreting a target protein comprising, consisting of, or consisting essentially of obtaining cells for screening, labelling at least one cell surface marker of the cells with a first label that binds to the cell surface marker and a second label specific for the target protein, wherein the second label binds the first label, allowing the cells to secrete the target protein, wherein the secreted target protein attaches to the second label, conjugating the secreted target protein bound to the second label with a magnetic nanoparticle-bound label, and sorting the labeled cells in a microfluidic device based on the target protein secretion levels on the cell surface of the cells, wherein the microfluidic device detects the magnetic nanoparticle-bound label.

Description

DEVICE AND METHOD FOR ASSESSMENT OF SECRETED PROTEINS FROMSINGLE CELLS IN A CULTURECROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application Serial No. 63 / 529,601, filed July 28, 2023, the contents of which are hereby incorporated by reference in its entiretySTATEMENT OF GOVERNMENT SUPPORT

[0002] This invention was made with government support under grant number CA204574 awarded by the National Institutes of Health. The government has certain rights in the invention.FIELD OF THE INVENTION

[0003] The present invention relates to a method and device for assessing secretion levels of target proteins from cells in a high throughput manner. In certain embodiments, the invention further allows for the isolation of the cells based on its secretion levels of the target protein for post-capture analysis.BACKGROUND

[0004] Inherently, cellular immunity has a high level of functional heterogeneity1. There are many subsets of immune cells, with each subset responding to specific stimuli, responses are initiated by individual cells within each subset and communicated to other subsets, leading to a complex population-level immune response2. These immune responses often involve intermediate extracellular signalling acting as autocrine modulators when cells respond to their own secretion or as paracrine modulators when neighbouring cells respond to secreted factors3. Characterizing such dynamic stimulus-response relationships by analyzing the genes and respective regulatory networks responsible for immune cell secretion would be valuable for better understanding and controlling immune responses and would significantly aid therapeutic discovery and the development of new disease treatments4, 5. In the immune system, the immune effector functions are broadly mediated by a panel of effector proteins (e.g., cytokines and chemokines) secreted from single cells. Performing single-cell analysisof cells within a population is essential to accurately couple autocrine and paracrine secretion cascades due to the network-level dependency of secretion that is implemented through paracrine-based cell-to-cell communication6.

[0005] A variety of approaches have been developed for analysis of cell secretion at the single-cell level. Intracellular staining combined with flow cytometry is a traditional means of analysing cell secretion after blocking its release with transport inhibitors7. However, this approach is not compatible with live cells and reports on intracellular accumulation rather than secretion of molecules or their functional states. Another strategy for secretion analysis relies on the confinement of single cells within uniform compartments to prevent crosstalk. Although ELISpot8and FLUOROSpot9assays are sensitive enough to detect single-cell secretion - these assays are not suitable for quantitative analysis of cytokines. Several micro- and nano-technology based approaches have been developed to measure low-abundance analytes with high sensitivities10, 11or to enable the analysis of hundreds of thousands of cells, such as microengraving12, immunospot array assay on a chip (ISAAC)13, single-cell barcode chip (SCBC)3, and hierarchical loading (HL) chip14. Despite the vast utility of these approaches and their impressive multiplexing capabilities14'16, they still lack the throughput required for the analysis of hundreds of millions of cells that is typically required for large- scale functional genetic screens (e.g., CRISPR screens).

[0006] Droplet microfluidics can be used to compartmentalize cells with capture beads or within capture gel matrices and sort droplets containing cells of interest using custom droplet sorters or fluorescence-activated cell sorters (FACS)17'21. Cells sorted by FACS suffer from physical stress associated with high voltage and pressure, which is compounded by chemical stress from the sheath solution used for cell suspension that can induce perturbations in cellular metabolism and functions22. In addition, the background fluorescence in the droplets resulting from unbound fluorescent reagents cannot be avoided in some methods. In general, solitary confinement of cells within wells or droplets does not permit the analysis of paracrine secretion due to the lack of cell-to-cell signaling. In addition, compartmentalized cells can be affected by the high local concentration of secreted factors leading to feedback signaling that might alter the level of secretion over time23. Optofluidic approaches, such as the optoelectropositioning (OEP) technology, can transport and compartmentalize single cells using optically induced di electrophoretic manipulation24, 25, but lack high levels of throughput.

[0007] Identification and quantification of secreted factors in the context of their localized signaling milieu can prevent the degradation of secreted proteins by proteases orsequestration in cell culture media prior to analysis26, 27. Several single-cell secretion assays relied on coating the cell surface with antibodies specific to the secreted factors using streptavidin as a linker after biotinylating the cell surface28or using antibodies modified with lipid molecules29to facilitate cell tethering. In addition, other assays utilized a cell-secretion specific antibody coupled with a cell-surface targeting antibody through heterobifunctional crosslinkers30or using functionalized beads31, 32. However, these assays are either low- throughput or dependent on FACS for cell sorting. It thus remains an unmet need to perform high-throughput profiling of cell secretion at the single-cell level.SUMMARY OF THE INVENTION

[0008] In one aspect, provided herein is a method for high throughput screening of cells secreting a target protein comprising, consisting of, or consisting essentially of obtaining cells for screening, labelling at least one cell surface marker of the cells with a first label that binds to the cell surface marker and a second label specific for the target protein, wherein the second label binds the first label, allowing the cells to secrete the target protein, wherein the secreted target protein attaches to the second label, conjugating the secreted target protein bound to the second label with a magnetic nanoparticle-bound label, and sorting the labeled cells in a microfluidic device based on the target protein secretion levels on the cell surface of the cells, wherein the microfluidic device detects the magnetic nanoparticle-bound label.

[0009] In some aspects, more than one cell surface marker is labeled. In some aspects, the first label comprises, consists of, or consists essentially of antibodies specific for the at least one cell surface marker. In yet another aspect, the antibodies are labeled with streptavidin, His, HA, Myc, or FGP. In yet another aspect, the cell surface marker comprises, consists of, or consists essentially of CD4, CD45, CD3, CD8, CD56, or CD25.

[0010] In yet another aspect, the sorting comprises, consists of, or consists essentially of passing the labeled cells on an affinity matrix comprising a plurality of capture zones with differing linear velocities to capture cells with varying levels of secreted target protein.

[0011] In yet another aspect, the cells are modified to produce a targeted protein for secretion. In some aspects, the cells are edited using a CRISPR gene editing system. In yet another aspect, the CRISPER gene editing system is a CRISP-CAS system. In yet another aspect, the CRISPR-CAS gene editing system is a genome-wide CRISPR-CAS9 knockout screen. In some aspects, the CRISPR-CAS gene editing comprises, consists of, or consistsessentially of a CRISPR activation screen, a CRISPR interference screen, and / or CRISPR loss-of-function screen.

[0012] In some aspects, the targeted protein comprises, consists of, or consists essentially of a cytokine. In some aspect, the isolated cells may be further expanded. In some aspects, the cells are isolated directly from a patient. In some aspects, the cells comprise, consist of, or consist essentially of any one of B cells, plasma cells, T cells, NK cells, macrophages, monocytes, neutrophils, mast cells, fibroblasts, keratinocytes, epithelial cells, adipocytes, and / or bone cells, or any combination thereof. In some aspects, the cells comprise, consist of, or consist essentially of T cells. In some aspects, the T cells are modified using CRISPR. In some aspects, the T cells are modified using a genome-wide CRISPR-Cas9 knockout screen to identify a cell having a desired secretion profile for the target protein

[0013] A further aspect relates to identifying regulators of secretion of a target protein using the above method. The method may optionally be combined with CRISPR-editing technology to modify a target DNA region to create a modified cell, which is then evaluated according to the method to determine whether or not secretion of the target protein(s) is increased or decreased, thus identifying modifiers of target protein secretion. Alternatively, the cells may be isolated directly from living tissue and sorted using the above method. In one aspect of the invention, the sorted cells are further isolated based on their secretion levels for further post-capture analysis, including sequencing analysis to identify key genetic modifiers of target protein secretion. In one aspect, novel cells are identified with an optimized secretion profile and expanded for culturing to produce target protein(s).BRIEF DESCRIPTION OF THE DRAWINGS

[0014] FIG. 1A illustrates a representative workflow consistent with the principles of the invention;

[0015] FIG. IB depicts an exemplary method of converting cells for use in the system and methods of the present invention;

[0016] FIG. 1C depicts an exemplary method of isolating and sorting cells consistent with the present invention;

[0017] FIG. ID depicts an exemplary rationale for separating cells based on simulated linear flow velocity profiles;

[0018] FIG. IE illustrates the magnitude of linear flow velocity along the blue lines shown in FIG. ID;

[0019] FIG.s 2A-2B illustrate secretion analysis of representative proteins, specifically different cytokines, secreted by CD4+ T cells using microfluidic-based cell secretion assay (Fig. 2A) and flow cytometry (Fig. 2B).

[0020] FIGs. 2C-2D illustrate secretion analysis of exemplary cytokines from various cell types microfluidic-based cell secretion assay (Fig. 2C) and flow cytometry (Fig. 2D).

[0021] FIG. 2E illustrates a representative analysis of cytokines secreted by different proportions of CD4+ T cells in a mixture with B cells using microfluidic-based cell secretation assay.

[0022] FIG. 2F represents a depiction of the sensitivity of the SECRE method of the present invention relative to the commercially available IFNy assay kit.

[0023] FIG. 2G represents the quantification of cellular fluorescence of cells captured in each zone as a function of number of magnetic nanoparticles.

[0024] FIG. 2H depicts a representative transmission electron microscopy (TEM) imaging of CD4+ T cells to visualize the magnetic nanoparticles attached to the cell surface subsequent to IFNy analysis using the microfluidic approach.

[0025] FIG. 3A illustrates a schematic of a representative CRISPR screen workflow.

[0026] FIG. 3B depicts exemplary genes targeted by sgRNAs detected in the SECRE-chip IFNyneg / IFNylowscreen, ranked by normalized Z score as calculated using DrugZ algorithm.

[0027] FIG. 3C provides an exemplary comparison between SECRE-chip and FACS screen results. Normalized Z scores are displayed, coloured by density with contours indicated. The dashed lines indicate the top and bottom 90thpercentile of the data. Overlapping hits at <30% FDR are shown.

[0028] FIG. 3D illustrates the exemplary overlap of hits obtained from SECRE-chip and FACS IFNy screens at <30% FDR.

[0029] FIG. 4A illustrates an exemplary flow cytometric analysis of top hits: LRRK2, SLK, STK10, and STK24 proteins before and after knocking down the corresponding genes with siRNAs in CD4+ T cells.

[0030] FIG. 4B depicts a representative analysis of IFNy secretion using the SECRE method after knocking down LRRK2, SLK, STK10, and STK24 in CD4+ T cells using non-targeting (NT) siRNA as a control. Data were analyzed by two-way ANOVA with Dunnett’s multiple comparisons test.

[0031] FIG. 4C depicts a representative analysis of IFNy secretion by a high-sensitivity ELISA after knocking down the previous genes in CD4+ T cells with specific siRNAs, using NT siRNA as a control.

[0032] FIG. 4D depicts a representative analysis of IFNy secretion using the SECRE method after knocking ov LRRK2, SLK, STK10, and STK24 with the first set of guide sequences in CD4+ T cells using CRISPR. Data were analyzed by two-way ANOVA with Dunnett’s multiple comparisons test.

[0033] FIG. 4E depicts a representative analysis of IFNY secretion by a high-sensitivity ELISA after knocking out the previous genes in CD4+ T cells. Data were analyzed by oneway ANOVA with Turkey’s multiple comparisons test.

[0034] FIG. 4F depicts an exemplary heatmap of selected secreted cytokine / chemokine measurements performed using the cytokine Luminex assay subsequent to knocking out the previous genes in CD4+ T cells.

[0035] FIG. 4G depicts a representative analysis of kinase inhibitors using ADP-Glo assay. Curve fits were performed where the enzyme activity at the highest inhibitor concentration was less than 65% and the ICso values were determined using GraphPad Prism software.

[0036] FIG. 4H illustrates an exemplary analysis of IFNy secretion by SECRE method after incubation of CD4+ T cells with XMU-MP1 (STE20 like kinase 1 / 2 inhibitor), SB-633825 (STK10 inhibitor), momelotinib (ACVR1 inhibitor), erlotinib (SLK and STK10 inhibitor), and bosutinib (STK24 inhibitor), using the cells incubated with the solvent (DMSO) as a control. Data were analyzed by two-way ANOVA with Dunnett’s multiple comparisons test.

[0037] FIG. 41 depicts a representative analysis of IFNy secretion by a high-sensitivity ELISA after incubation of CD4+ T cells with the previous inhibitors using the cells incubated with DMSO as a control. Data were analyzed by one-way ANOVA with Turkey’s multiple comparisons test. A total of IxlO6cells were analysed per sample. Data are mean ± s.d. of biological replicates («=3).

[0038] FIG. 5A depicts the chemical structure of XMU-MP1.

[0039] FIG. 5B provides a schematic illustration of representative in vivo workflow. Mice (w=8) were fed formulated drinking water containing 2% DSS for 7 days and 0.5% DSS in day 8 and received a daily i.p. injection of 1 mg kg1XMU-MP1 for 8 days. A control group of mice («=7) were fed DSS in drinking water and received a daily i.p. injection of the vehicle (3% DMSO in PBS). Another control group of mice («=5) received tap water only.

[0040] FIG. 5C describes the effect of XMU-MP1 on mouse body weight during colitis induction. Weight changes were calculated as a percentage of weight prior to DSS treatment (Day 0). Data were analysed by two-way ANOVA with Turkey’s multiple comparisons test.

[0041] FIG. 5D depicts the representative changes in colon length during XMU-MP1 treatment of DSS-induced colitis mice. Data are mean ± s.d. of biological replicates (w=5-8).

[0042] FIG. 5E and 5F illustrate the representative analysis of mouse IFNy (Fig. 5E) and myeloperoxidase (MPO) activity (Fig. 5F) in the homogenized colons of XMU-MP1 treated mice prior to colitis induction. Data are mean ± s.d. of technical replicates («=3). Data were analysed by one-way ANOVA with Turkey’s multiple comparisons test.

[0043] FIG. 5G provides representative images of Olfm4+ ISCs in the colons of mice (w=10 independent sections per group) after being fed with tap water only, DSS and daily 3% DMSO, and DSS and daily 1 mg kg1XMU-MP1 in 3% DMSO.

[0044] FIG. 5H depicts the percentage of 01fm4++cells per section. Data were analysed by unpaired two-tailed student’s / -test.

[0045] FIG. 6. The SECRE-chip used for secreted protein analysis. A photograph of the device (left), showing the difference in channel thickness using a food dye. The thickness of zone 1 and 2 is 150 pm and 300 pm, respectively. SEM image of fabricated device showing the height of microfabricated X-structure in each zone (right). The fabricated chips were sputter- coated with 50 nm Au and imaged by SEM using 2 kV accelerating voltage and high- vacuum mode.

[0046] FIG. 7. Phenotyping of CD4+ T cells used in the trials. Primary CD4+ T cells or leukemic B cells (1,000,000) were cultured in RPMI 1640 medium supplied with 10% FBS and activated with a cell activation mixture (CD3, CD28, and CD2) for 3 days. The cells were immunostained with either PE-labeled CD 19, APC-labeled CD4, APC-labeled CD45, or PerCP- Cy5.5-labeled CD69 and APC-Cy7-labeled CD25 antibody for 30 min at room temperature. Samples were analyzed with Attune NxT flow cytometer. Compared to B cells (control), primary CD4+ T cells maintained the CD4+ / CD19- / CD45+ phenotype during longterm culture (~3 weeks) (upper panel). Also, the cells maintained the CD25+ / CD69+ phenotype, subsequent to activation with CD3 / CD28 / CD2 cocktail (lower panel). The table shows the percentage of positive populations. CD4 is T helper cell marker. CD45 is a leukocyte common antigen. CD25 & CD69 are activated T cell markers. CD 19 is leukemic B cell marker.

[0047] FIG. 8. Analysis of IFNy after treatment of CD4+ T cells with CD4 and / or CD45 antibodies using a high-sensitivity ELISA test. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by CD4+ T after incubation with CD4 and / or CD45 antibodies. A control experiment was carried out using untreated CD4+ T cells. (C) Percentage of IFNy secretion by treated and untreated CD4+ T cells. lxlC)6 cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANOVA with Turkey’s multiple comparisons test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, *** / ? < 0.001, and ****p < 0.0001).

[0048] FIG. 9. Raw data for analysis of IFNy, IL10, and TNFa produced by CD4+ T cells using the microfluidic-based cell secretion assay. The cells were incubated with streptavidin- labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to the secreted protein. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin- labeled antibody specific to the secreted protein. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE- chip at a flow rate of 2 mL h_l. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. 2x10^ cells were used in these trials. Data are mean ± s.d. of biological replicates («=3).

[0049] FIG. 10. Raw data for analysis of IFNy produced by CD4+ T, Jurkat and B cells using the microfluidic-based cell secretion assay. The cells were incubated with streptavidin- labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_1. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. 2x10^ cells were used in these trials. Data are mean ± s.d. of biological replicates (w=3).

[0050] FIG. 11. Flow cytometric analysis of sorted CD4+ T cells in the SECRE chip using forward flow and reverse flow. CD4+ T cells were incubated with streptavidin- labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using acell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to ZFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_l. The cells were sorted using forward flow (Z1 0 Z2) and reverse flow (Z2 0 Zl). The cells were subsequently incubated with APC-labeled mouse specific antibody. Sorted cells were collected from zone 1, zone 2, and effluent. 1x10^ cells were used in these trials. A control experiment was carried out using unsorted cells. Samples were injected into CytoFlex flow cytometer (Beckman- Coulter) and the measurements were plotted as histograms.Absorbance values were normalized to unstained control. A total of 10,000 cells were analyzed per sample.

[0051] FIG. 12. Raw data for analysis of ZFNy secreted by different proportions of CD4+ T cells in a mixture with B cells using the microfluidic-based cell secretion assay. Different proportions of CD4+ T cells (100%, 75%. 50%, 25%, and 0%) were mixed with B cells and incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to ZFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin- labeled antibody specific to ZFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_l. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. 1x10^ cells were used in these trials. Data are mean ± s.d. of biological replicates («=3).

[0052] FIG. 13. Flowcytometric analysis of ZFNy secreted by different proportions of CD4+ T cells in a mixture with B cells. A. Zntracellular cytokine staining (ZCS) for ZFNy in CD4+ T cells subsequent to cell fixation and permeabilization. B. Flow cytometry histograms for ZFNy analysis using the cell secretion assay. CD4+ T cells (100%, 75%. 50%, 25%, and 0%) in a mixture with B cells were incubated with streptavidin-labeled CD4 antibody and streptavidin- labeled CD45 antibody. The cells were subsequently incubated with a biotin- labeled antibody specific to ZFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to ZFNy. The cells were then incubated with a FZTC-labeled antibody specific to biotin. A control experiment was carried out using an isotype control. 1x10^ cells were used in these trials. Samples were injected into Attune NxT flow cytometer and the measurements were plottedas histograms. Absorbance values were normalized to unstained control. A total of 100,000 cells were analyzed per sample.

[0053] FIG. 14. Performance of SECRE technique benchmarked against an IFNy assay kit. (A) Flow cytometry histograms and (B) median fluorescence intensity (MFI) for IFNy analysis using SECRE technique and a commercially available assay kit. In SECRE, CD4+ T cells were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin- labeled antibody specific to IFNy. The cells were then incubated with a FITC-labeled antibody specific to biotin. Analysis of IFNy using the assay kit was carried out according to the manufacturer’s protocol. A control experiment was carried out using CD4+T cells previously fixed with 4% PF A. 1x10^ cells were used in these trials. Samples were injected into Attune NxT flow cytometer and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. A total of 100,000 cells were analyzed per sample. Data are mean ± s.d. of biological replicates («=3). Data were analyzed by unpaired two-tailed Student’s t- test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001).

[0054] FIG. 15. Quantification of cellular fluorescence of cells captured in each zone as a function of number of magnetic nanoparticles. CD4+ T cells were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin- labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_l.ThecellsweresubsequentlyincubatedwithAF488- labeledmousespecificantibody. 1x10^ cells were used in these trials. Cells were imaged immediately using a confocal-like microscope and the images wereprocessedwithZensoftware.Imageswereacquiredbyoverlayingthebright field, blue, and green, fluorescent images. Imaging was optimized (brightness: 2500, contrast: 500) for AF488 and kept constant. Corrected total cell fluorescence (CTCF) was measured using Imaged and the background fluorescence was subtracted. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by unpaired two-tailed Student’s / -test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, ***p < 0.001, and****p < o.OOOl). FIG. 16. Resolution of the SECRE-chip determined by flow cytometry. CD4+ T cells were incubated with streptavidin-labeled CD4 antibody and streptavidin- labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2mLh_l.The cells were subsequently incubated with AF488-labeled mouse specific antibody. Sorted cells were collected from zone 1, zone 2, and effluent. A control experiment was carried out in which unsorted cells were incubated with an isotype control. 1x10^ cells were used in these trials. Samples were injected into Attune NxT flow cytometer and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. A total of 20,000 cells were analyzed per sample.

[0055] FIG. 17. Determination of the sorting capacity of SECRE-chip. Analysis of IFNy produced by different counts of CD4+ T cells. The cells were incubated with streptavidin- labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_1. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter.

[0056] FIG. 18. Sorting of CRISPR-edited CD4+ T cells obtained from the 5^ passage using the microfluidic device and FACS. CRISPR-edited CD4+ T cells from passage 5 (30x10^) were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. The cells were aliquoted into 60 tubes (1x10^ each) and incubated with the cell activation mixture. The cells were incubated with biotin-labeled antibody specific to IFNy. After washing, the aliquots were combined into 5 aliquots. (A) Each aliquot (3x10^ cells) was incubated with biotin specific antibody conjugated with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_l. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. Data are mean ± s.d.of technical replicates («=5). (B) The cells (15x10^) were incubated with the blocking buffer 2% BSA in PBS on ice. The cells were incubated with FITC-labeled biotin specific antibody then sorted with FACS. The forward scatter area vs. side scatter area was used to separate the cell events from debris. The following gating strategy was adopted. The forward scatter area vs. forward scatter width was used to separate single cells from aggregates. The forward scatter area vs. B530 / 30 area was used to separate CD4+ T cell subpopulations with different levels of secreted IFNy.

[0057] FIG. 19. Sorting of CRISPR-edited CD4+ T cells obtained from the 8^ passage using the microfluidic device and FACS. CRISPR-edited CD4+ T cells from passage 8 (30x10^) were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. The cells were aliquoted into 60 tubes (1x10^ each) and incubated with the cell activation mixture. The cells were incubated with biotin-labeled antibody specific to IFNy. After washing, the aliquots were combined into 5 aliquots. (A) Each aliquot (3x10^ cells) was incubated with biotin specific antibody conjugated with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_l. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. Data are mean ± s.d. of technical replicates (n=5). (B) The cells (15x10^) were incubated with the blocking buffer 2% BSA in PBS on ice. The cells were incubated with FITC-labeled biotin specific antibody then sorted with FACS. The following gating strategy was adopted. The forward scatter area vs. side scatter area was used to separate the cell events from debris. The forward scatter area vs. forward scatter width was used to separate single cells from aggregates. The forward scatter area vs. B530 / 30 area was used to separate CD4+ T cell subpopulations with different levels of secreted IFNy.

[0058] FIG. 20. Analysis of sgRNA / gene enrichment with several bioinformatics tools. (A) Correlation between DrugZ and MAGeCK. The NormZ score calculated for DrugZ and the log fold change calculated for MAFeCK are highly correlated. (B) Number of significant genes determines using 5 different bioinformatic tools, including DrugZ, MAFeCK, edgeR, STARS, and RIGER.

[0059] FIG. 21. Raw data for microfluidic analysis of IFNy secreted by CD4+ T cells after knockdown of identified genes. CD4+ T cells were incubated with siRNAs specific to LRRK2, SLK, STK24, using non-targeting siRNA as a control. The cells were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells weresubsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin- labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_1. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. 1x10^ cells were used in these trials. Data are mean ± s.d. of biological replicates («=3).

[0060] FIG. 22. ELISA analysis of IFNy after knocking down top hits with siRNAs. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by live and fixed CD4+ T cells as well as CD4+ T cells previously incubated with siRNAs specific to LRRK2, SLK, STK10, and STK24 and non-targeting siRNAs. In addition, uncaptured IFNy was measured after performing the microfluidic-based cell secretion assay to assess the assay performance. 1x10^ cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANOVA with Turkey’s multiple comparisons test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001).

[0061] FIG. 23. ELISA analysis of IFNy after knocking down hits identified with FACS using siRNAs. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by CD4+ T cells previously incubated with siRNAs specific to CDKL4, PI4KB, MAP2K4, IPMK, DCLK3, and CSK. A control experiment was carried out using non-targeting siRNAs. (C) Percentage of IFNy secretion by treated and untreated CD4+ T cells. 1x10^ cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANOVA with Turkey’s multiple comparisons test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001).

[0062] FIG. 24. Intracellular cytokine staining for IFNy after knocking out top hits using the first set of guide sequences. CD4+ T cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator. One hour after restimulation, Golgi Plug protein transport inhibitor was added at. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PFA and permeabilized with 4% PFA and permeabilized with 0.2% Triton X-100. The cells were immunostained with APC-labeled CD4 antibody and FITC-labeled IFNy antibody.

[0063] FIG. 25. Raw data for microfluidic analysis of IFNy secreted by CD4+ T cells after knocking out the identified genes with the first set of guide sequences. CD4+ T cells were transduced with specific sgRNAs targeting the top hits retrieved from the screen, including LRRK2, SLK, STK10, and STK24. A negative control was carried out using one sgRNA for human cells. The cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein for editing. Electroporated cells were selected by incubation with puromycin for 72 hours. CRSIPR-edited cells were incubated with streptavidin- labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin- labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_l. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. 1x10^ cells were used in these trials. Data are mean ± s.d. of biological replicates («=3).

[0064] FIG. 26 ELISA analysis of IFNy after knocking out top hits using the first set of guide sequences. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by CD4+ T cells after knocking out top hit, including LRRK2, SLK, STK10, and STK24. A control experiment was carried out using unedited cells. lxl()6 cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANOVA with Turkey’s multiple comparisons test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, *** / ? < 0.001, and ****p < 0.0001).

[0065] FIG. 27. Intracellular cytokine staining for IFNy after knocking out top hits using the second set of guide sequences. CD4+ T cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator. One hour after restimulation, Golgi Plug protein transport inhibitor was added at. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PFA and permeabilized with 4% PFA and permeabilized with 0.2% Triton X-100. The cells were immunostained with APC-labeled CD4 antibody and FITC-labeled IFNy antibody.

[0066] FIG. 28. ELISA analysis of IFNy after knocking out top hits using the second set of guide sequences. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by CD4+ T cells after knocking out top hit, includingLRRK2, SLK, STK10, and STK24. A control experiment was carried out using unedited cells. (C) Percentage of IFNy secretion by treated and untreated CD4+ T cells. 1x10^ cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANO VA with Turkey’s multiple comparisons test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001).

[0067] FIG. 29. Heatmap of selected secreted cytokine / chemokine measurements performed using the cytokine Luminex assay. This was carried out subsequent to knocking out the previous genes using the second set of guide sequences in CD4+ T cells.

[0068] FIG. 30. Raw data for microfluidic analysis of IFNy secreted by CD4+ T cells after treatment with inhibitors. CD4+ T cells were incubated with XMU-MP1 (STE20 like kinase 1 / 2 inhibitor), SB-633825 (STK10 inhibitor) and kinase inhibitors, including momelotinib, erlotinib, and bosutinib using the cells incubated with the solvent (DMSO) as a control. For IFNy analysis, the cells were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin- labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h_l. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. 1x10^ cells were used in these trials. Data are mean ± s.d. of biological replicates ( =3).

[0069] FIG. 31. Analysis of IFNy after treatment with inhibitors using a high- sensitivity ELISA test. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by CD4+ T cells previously incubated with XMU- MP1 (STE20 like kinase 1 / 2 inhibitor), SB-633825 (STK10 inhibitor) and kinase inhibitors, including momelotinib, erlotinib, and bosutinib, using the cells incubated with the solvent (DMSO) as a control. 1x10^ cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANOVA with Turkey’s multiple comparisons test. Statistical significance was defined as follows: ns (p > 0.05), *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001).

[0070] FIG. 32. Changes in body weight of DSS-induced colitis mice. Mice (w=8) were fed formulated drinking water containing 2% DSS for 7 days and 0.5% DSS in day 8 and received a daily i.p. injection of 1 mg kg_l XMU-MP1 in PBS containing 3% DMSO for 8days. A control group of mice («=7) were fed 2.5% DSS in drinking water for 7 days and 0.5% DSS in day 8 and received a daily i.p. injection of the vehicle (3% DMSO in PBS) for 8 days. Another control group of mice («=5) received tap water only for 8 days. The body weight was measured daily. Data are mean ± s.d. of biological replicates (n=5- 8).

[0071] FIG. 33. Changes in colon length of DSS-induced colitis mice. Mice (w=8) were fed formulated drinking water containing 2% DSS for 7 days and 0.5% DSS in day 8 and received a daily i.p. injection of 1 mg kg_l XMU-MP1 in PBS containing 3% DMSO for 8 days. A control group of mice («=7) were fed 2.5% DSS in drinking water for 7 days and 0.5% DSS in day 8 and received a daily i.p. injection of the vehicle (3% DMSO in PBS) for 8 days. Another control group of mice («=5) received tap water only for 8 days. At day 9, the mice were euthanized, and the colons were resected between the ileocecal junction and proximal rectum. The colons were placed on non-adsorbent surface and their lengths were measured with a ruler.

[0072] FIG. 34. Analysis of mouse ZFNy in the homogenized colons of DSS- induced colitis mice. Using mouse ZFNy ELISA kit, a standard curve was generated using different concentrations of recombinant mouse ZFNy. Data are mean ± s.d. of technical replicates (w=3).

[0073] FIG. 35. Analysis of mouse myeloperoxidase activity in the homogenized colons of DSS-induced colitis mice. Using a myeloperoxidase assay kit, a standard curve was generated using different concentrations of standard TNB. Data are mean ± s.d. of technical replicates 3)-

[0074] FIG. 36. Over-representation analysis of overlapped pathways. Overlapped pathways were determined for the current ZFNy CRZSPR-KO screen in CD4+ T cells and previous ZFNy CRZSPRi screen in CD8+ T cells as well as ZL2 CRZSPRi screen in CD4+ T cells.

[0075] FIG. 37. Raw data for analysis of ZFNy secreted by different proportions of CD4+ T cells in a mixture with B cells using the microfluidic-based cell secretion assay. Different proportions of CD4+ T cells (100%, 75%. 50%, 25%, and 0%) were mixed with B cells and incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to ZFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to ZFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h-1. Sorted cells were collected from zone 1, zone 2,and effluent and were counted using a cell counter. IxlO6cells were used in these trials. Data are mean ± s.d. of biological replicates («=3).

[0076] FIG. 38. Intracellular cytokine staining for IFNy after knocking out top hits using the first set of guide sequences. CD4+ T cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator. One hour after restimulation, Golgi Plug protein transport inhibitor was added at. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PFA and permeabilized with 4% PFA and permeabilized with 0.2% Triton X-100. The cells were immunostained with APC-labeled CD4 antibody and FITC-labeled IFNy antibody.

[0077] FIG. 39. Raw data for microfluidic analysis of IFNy secreted by CD4+ T cells after knocking out the identified genes with the first set of guide sequences. CD4+ T cells were transduced with specific sgRNAs targeting the top hits retrieved from the screen, including LRRK2, SLK, STK10, and STK24. A negative control was carried out using one sgRNA for human cells. The cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein for editing. Electroporated cells were selected by incubation with puromycin for 72 hours. CRSIPR-edited cells were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin-labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin- labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h1. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. IxlO6cells were used in these trials. Data are mean ± s.d. of biological replicates («=3).

[0078] FIG. 40. ELISA analysis of IFNy after knocking out top hits using the first set of guide sequences. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by CD4+ T cells after knocking out top hit, including LRRK2, SLK, STK10, and STK24. A control experiment was carried out using unedited cells. IxlO6cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANOVA with Turkey’s multiple comparisons test.

[0079] FIG. 41. Intracellular cytokine staining for IFNy after knocking out top hits using the second set of guide sequences. CD4+ T cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator. One hour after restimulation, Golgi Plug protein transportinhibitor was added at. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PFA and permeabilized with 4% PFA and permeabilized with 0.2% Triton X-100. The cells were immunostained with APC-labeled CD4 antibody and FITC-labeled IFNy antibody.

[0080] FIG. 42. ELISA analysis of IFNy after knocking out top hits using the second set of guide sequences. (A) Standard curve generated using different concentrations of recombinant IFNy. (B) Analysis of IFNy produced by CD4+ T cells after knocking out top hits, including LRRK2, SLK, STK10, and STK24. A control experiment was carried out using unedited cells. (C) Percentage of IFNy secretion by treated and untreated CD4+ T cells. IxlO6cells were used in these trials. Data are mean ± s.d. of technical replicates («=3). Data were analyzed by ordinary one-way ANOVA with Turkey’s multiple comparisons test.

[0081] FIG. 43. Flow cytometric analysis of IFNy secreted by different proportions of CD4+ T cells in a mixture with B cells. A. Intracellular cytokine staining (ICS) for IFNy in CD4+ T cells subsequent to cell fixation and permeabilization. B. Flow cytometry histograms for IFNy analysis using the cell secretion assay. CD4+ T cells (100%, 75%. 50%, 25%, and 0%) in a mixture with B cells were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin- labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to IFNy. The cells were then incubated with a FITC-labeled antibody specific to biotin. IxlO6cells were used in these trials. Unstained controls are shown in the lower panel. Samples were injected into Attune NxT flow cytometer and the measurements were plotted as histograms.Absorbance values were normalized to unstained control. A total of 100,000 cells were analysed per sample.

[0082] FIG. 44. Analysis of sgRNA / gene enrichment with several bioinformatics tools. (A) Correlation between DrugZ and MAGeCK. The NormZ score calculated for DrugZ and the log fold change calculated for MAFeCK are highly correlated. (B) Number of significant genes determines using 5 different bioinformatic tools, including DrugZ, MAFeCK, edgeR, STARS, and RIGER.DETAILED DESCRIPTION

[0083] The present invention relates to a method of screening cells, which secrete a target protein. In one embodiment, Secretion-Enabled Cell Ranking and Enrichment (SECRE)technique is a high-throughput, microfluidics-based immunomagnetic cell sorting strategy. This technique employs microfluidics to sort the cells based on the level of protein. SECRE may, in one embodiment, be combined with CRISPR-editing technology to identify modifiers of cell secretion. Alternatively, the cells may be isolated directly from living tissue and sorted using the present invention. In one aspect of the invention, the sorted cells are further isolated based on their secretion levels for further post-capture analysis. For example, the cells may be sequenced to identify key genetic modifiers of cell secretion.

[0084] In another aspect of the invention, the invention enables converting the cell producing a specific protein into a sensing platform for the protein being secreted. Briefly, targeted secreted proteins are captured and displayed on the production cells where they are recognized and labelled with magnetic nanoparticles. These cells are then profiled in a microfluidic cell sorting device that separates cells based on their magnetic content as a readout of the amount of target protein being displayed on the cell surface. This system is able to analyze a variety of proteins (e.g. cytokines, antibodies, etc..), secreted by large number of cells (~1 X 10A8 per setup), enabling effective screening of regulators for secretion and secretion-related bioprocesses.

[0085] In accordance with an embodiment of the present invention, live cells are obtained for screening. Any suitable cell may be used that are being screened for a desired target protein being secreted by the cell. For example, primary cells or cells taken directly from living tissue of a patient may be used. Non-limiting examples include lymphocytes, such as B cells and T cells, and other immune cells (including NK cells, plasma cells, dendritic cells, macrophages, monocytes, neutrophils and mast cells). Other cell types may also be used including fibroblasts, keratinocytes, epithelial cells, endothelial cells, neural cells, adipocytes, and bone cells.

[0086] In another aspect of the invention, modified cells are used. Cells may be gene-edited using known methods. For example, CRISPR-editing technology has been established to assist in the identification of underlying mechanisms for combating medical conditions and diseases. According to the present invention, CRISPR technology may be used to identify modifiers of cell secretion. Any suitable CRISPR technology may be used for these purposes, including but not limited to, CRISPR-CAS systems, such as CRISPR-Cas9, CRISPR-Casl2, or CRISPR-Casl3. Other base editing systems, such as prime editing, may also be utilized. In one embodiment, a CRISPR knockout screen, a CRISPR activation screen, a CRISPR interference screen, and / or CRISPR loss-of-function screen is employed. In another embodiment, the screening system is a genome-wide CRISPR knockout screen,such as a genome-wide CRISPR-Cas9 knockout screen, is used. In another embodiment, the CRISPR-Cas9 technology is a kinome-wide CRISPR-Cas9 loss-of-function screen, is used.

[0087] Suitably, the target protein may be any protein secreted by the cell or modified to be secreted by the cell. In one embodiment, the examples of the present invention describes targeting kinases in CRISPR-Cas9 screens due to their established druggability and clinical safety profile33. However, any suitable target protein that is secreted by a cell may be analyzed, including cytokines, antibodies, enzymes, exosomes, and hormones.

[0088] Cell surface biomarkers on the cells to be screened are labeled using at least one label that binds to the cell surface biomarker. Any cell surface biomarker may be used for the particular cell being screened. For example, for T cells, suitable cell surface marker may include CD3, CD4, CD8, or CD25. For CD4+ T cells, suitable cell surface markers may include CD45 or CD4, for example. For CD8+ T cells, suitable cell surface markers may include CD3, CD8 or CD45. For NK cells, suitable cell surface markers may include CD56.

[0089] One or more cell surface biomarkers on the cell may be labeled. In one embodiment, the cells may be coated with streptavidin via incubation with streptavidin-labeled anchoring antibodies specific for a specific cell surface marker. Solely by way of example, in one embodiment, FIG. IB depicts that two cell surface proteins, CD4 and CD45, on CD4+ T cells are labeled with the streptavidin-labeled anchoring antibodies specific for these two cell surface proteins. This cell surface biomarker label is then tagged with a second label specific for the targeted protein. For example, in FIG. IB, the cell surface biomarker is tagged with a biotin-labeled cytokine-specific antibody via biotin-streptavidin coupling. Any suitable labeling system may be used provided that the labels are stable and does not interfere with the function of the labeled molecules. For example, streptavidin-biotin and avidin-biotin systems may be employed. Any natural / engineered epitopes may be utilized. For example, His- tag / anti-his tag antibody, Myc-tag / anti-myc antibody, and HA tag / anti-HA antibody may be used.

[0090] After labelling, the cells secrete the targeted protein. The cells may be optionally induced to produce and secrete the targeted protein using known methods. The secreted target protein attaches to the second label specific for the targeted protein. By way of example, as shown in FIG. IB, the released cytokine is directly captured by the specific primary antibody attached to the cell surface, then a biotin-labeled antibody specific to the cytokine is added to form a sandwich.

[0091] These cells are then incubated with a biotin-specific antibody conjugated with magnetic nanoparticles. (FIG. 1B(5)-1B(6)). The magnetic nanoparticles allow the amount ofthe secreted target protein to be converted into a magnetic content using the microfluidic device. An example of a suitable magnetic nanoparticle is iron oxide nanoparticles.

[0092] Sorting of the cells takes place on a microfluidic device (e.g., SECRE-chip), which is fabricated by scaled three-dimensional (3D) printing. The aliquots of the cells are collected and transferred to the microfluidic device positioned on top of an array of magnets.Sequential capture zones may be established to determine various levels of secreted targeted proteins using different heights (e.g., 150 pm and 300 pm) to facilitate capturing cells with different magnetic content and consequently varying levels of secreted cytokines. The difference in heights is helpful to quantitatively capture the cells base on their levels of secretions. The quantitative capture is more comprehensive than binary capture. Typical heights may range from about 50 um to about 800 um. This allows cells with high, medium, low or no target protein secretion levels to be detected. By way of example and as depicted in FIG. 1C, the sorted cells may be retrieved from zone 1, zone 2 and effluent, and enumerated using a cell counter.

[0093] The microfluidic device is capable of high-throughput cell sorting, which was developed based on previous work related to sorting rare tumor cells based on the expression of cell-surface proteins34, intracellular proteins35, and intracellular mRNAs36. The chip is designed for configurable, quantitative, and volumetric cell separation. The SECRE-chip is positioned on an array of magnets and features two capture zones with differing linear velocities to capture cells with varying levels of the secreted cellular product (Fig. lb and Fig. 6). Each capture zone contains microfabricated structures to create localized regions of low flow velocity and improved capture dynamics (Fig. 1c). The first zone exhibits high linear velocity and thus retains cells with high magnetic loading, whereas the second zone exhibits reduced linear velocity, thus trapping cells with lower magnetic loading (Fig. Id). These capture zones may be customized based on the flow velocity and capture dynamics of the cells and target protein. Different capture zones are defined by their heights. In one embodiment, a series of devices with 50 to 800 um thickness can be used. They can be assembled flexibly to tailor the platform for specific cells or proteins for best performance.

[0094] An exemplary simulation of cell capture within the device at the operational flow rate are included in the Example 7. The captured cells are then recovered by removing the external magnet followed by disconnecting the capture zones and aspiring the cells from each zone separately. It is worth noting that the SECRE-chips are cost-effective (~$10), mass- producible (> 40 devices per operator per day), and highly customizable.

[0095] CRISPR knockout screens have been pursued using primary mouse immune cells from Cas9-expressing transgenic mice58'60, including a screen for regulators of innate cytokine response in dendritic cells57. Recently, genome-wide CRIPSR activation and interference screens were used to decode the regulators of IL2 production in CD4+ T cells as well as IFNy production in CD8+ T cells61. Al 5-25% overlapped pathways between the current screen and the previous screens through over-representation analysis has been noted according to the present invention (FIG. 36). This is expected considering that the kinome only covers 5% of the genome as well as the difference in cell type (i.e., CD4+ not CD8+ T cells) and nature of assay (i.e., SECRE not ICS). The cell secretion assay described here enabled the first microfluidics based functional CRISPR screen, permitting the analysis of immune cell secretion as well as its genetic regulators. The combined capabilities developed for the current method are not present together in existing microfluidic approaches for interrogating cell secretion at the single-cell level.

[0096] The method of the present invention addresses crucial requirements for performing large-scale functional genetic screens in several ways. First, the method enables a rapid (~7 h) and high throughput (-25X107cells per device) analysis of cell secretion and sorting the producing cells on the basis of their secretion patterns, which makes it amenable to large- scale functional genetic screens. Second, maintaining live cells post analysis permits ex-vivo expansion of analysed cells and / or further downstream analysis. Third, no cell proliferation is required, thus opening the way to directly screen primary cells (e.g., B cells or plasma cells), which can be particularly useful for the cloning of antibodies from disease survivors producing therapeutically relevant antibodies of unknown identity. Fourth, both autocrine and paracrine cell secretion can be interrogated by permitting the analysis of single cells within a population of cells. Fifth, secreted analytes are captured directly on the cell surface and analysed in a single modality, thus reduces their sequestration in the medium or digestion by proteases. Sixth, the method links the functional signature of the cell with its phenotype, allowing the selective isolation of subsets of cells based on the expression of specific cellsurface markers as well as the secretion of specific factors. Seventh, the assay design permits improved dynamics by increasing the number of antibodies specific to the secreted analyte on the cell surface via biotin-streptavidin coupling. Lastly, the assay is modular, permitting cell sorting by microfluidics or FACS via changing the reporter antibody. The performance of SECRE is compared with other conventional approaches, such as FACS, and MACS in Table 1, Below.

[0097] While the examples of the SECRE technique focuses on CD4+ T cells, it is expected that this approach is straightforward to adapt to delineating the functional states of other cell types. Preferably, a large number of cells are used with the SECRE-chip. Further, the flow cytometry-based format of the assay provides the resolution needed to distinguish between different secretory products, whereas the microfluidics-based format provides the throughput needed to for CRISPR screening. Finally, this method can be easily interfaced with other methods for specific endpoint measurements and single-cell gene expression that further expands possible assays from the integrated platform.

[0098] This invention is further illustrated by the following additional examples that should not be construed as limiting. The contents of all references, patents and published patent applications cited throughout this application, as well as the Figures, are incorporated herein by reference in their entirety.EXAMPLESExample 1 - Identification of the druggable modulators of cell secretion via a high- throughput single-cell secretion assay.

[0099] The overall workflow of the approach to identifying modulators of cell secretion is shown in Fig. la. Cells are isolated on the basis of cell secretion, which is performed using the SECRE approach (Fig. lb) that captures secreted factors on the surface of the cell. The captured proteins are then labeled with magnetic nanoparticles and sorted with high resolution depending on the level of secretion. An affinity matrix specific for the secreted product of interest is first created on the surface of the analysed cell. This step involves the binding of streptavidin-labeled anchoring antibodies to two cell-surface markers (e.g., CD4 and CD45 in CD4+ T cells) to fully and indirectly coat the surface of target cell with streptavidin. Subsequently, a biotin-labeled primary antibody specific to the secreted product (e.g., biotin-labeled IFNy antibody for IFNy analysis) is bound to the streptavidin molecules coating the cell surface. This step improves the capacity of the assay to collect secreted molecules due to the ability of each streptavidin molecule to bind to four biotin-labeled antibodies. The cells are aliquoted into the wells of a microtitre plate and are mitogenically activated to secrete the product of interest for a defined period and the cellular product is subsequently captured on the cell surface by its specific antibody. The captured cellular product is then labeled with a specific biotin-labeled secondary antibody (e.g., biotin-labeled IFNy for IFNy analysis) to form a sandwich. Finally, a biotin-specific detection antibody conjugated with magnetic nanoparticles is added to facilitate sorting of secreting cells within a microfluidic device. In parallel, the cells can be immunostained with a fluorescently labeled biotin-specific antibody to enable flow cytometric sorting of the cells based on a secreted product as an alternative approach for sorting and to assess the performance of the microfluidics-based cell sorting method.

[0100] FIG. 1 A - Overall workflow. The workflow starts with CRISPR-editing the target cells followed by sorting the cells according to the level of secreted target protein using the SECRE technique. Cells with no / low secretion are collected and genome-sequenced to identify regulators of cell secretion, followed by in-vivo validation of the druggable regulators of secretion. FIG. IB - Isolation of cells with perturbed secretion profiles using the SECRE-chip. The cells (e.g., CD4+ T lymphocytes) secreting the target cellular product (e.g., cytokine) are first coated with streptavidin via incubation with streptavidin-labeled anchoring antibodies specific to two cell-surface proteins (e.g., CD4 and CD45). The cell surface is thentagged with an antibody specific to the secreted cytokine (e.g., biotin-labeled cytokine specific antibody) via biotin-streptavidin coupling. Aliquots of the tagged cells are added to the wells of a microtiter plate and activated to stimulate the release of cytokines. The released cytokine is directly captured by the specific primary antibody attached to the cell surface, then a biotin-labeled antibody specific to the cytokine is added to form a sandwich. The cells are then incubated with a biotin-specific antibody conjugated with magnetic nanoparticles to convert the amount of secreted cytokine into a magnetic content. The aliquots are then collected from the wells of the microtiter plate, combined, and loaded into a microfluidic device positioned on top of an array of magnets. FIG. 1C - Cell isolation. The cells are sorted according to the level of secreted cytokine using a microfluidic device featuring two sequential capture zones with different heights (150 pm and 300 pm) to facilitate capturing cells with different magnetic content and consequently varying levels of secreted cytokines. The sorted cells are retrieved from zone 1, zone 2 and effluent, and enumerated using a cell counter. FIG. ID - Separation rationale. Simulated linear flow velocity profile at a flow rate of 2 ml h_1. Formation of capture pockets was observed in the valley of X-shaped microstructures. FIG. IE - Magnitude of linear flow velocity along the blue lines shown in FIG. ID. The average linear flow velocity in capture zone 2 is approximately 50% of capture zone 1.

[0101] The cells tagged with magnetic nanoparticles are sorted within a microfluidic device (SECRE-chip) fabricated by scaled three-dimensional (3D) printing. The chip is designed for configurable, quantitative, and volumetric cell separation. The SECRE-chip is positioned on an array of magnets and features two capture zones with differing linear velocities to capture cells with varying levels of the secreted cellular product (Fig. IB and Fig. 6). Each capture zone contains microfabricated structures to create localized regions of low flow velocity and improved capture dynamics (Fig. 1C). The first zone exhibits high linear velocity and thus retains cells with high magnetic loading, whereas the second zone exhibits reduced linear velocity, thus trapping cells with lower magnetic loading (Fig. ID). The captured cells are then recovered by removing the external magnet followed by disconnecting the capture zones and aspiring the cells from each zone separately. It is worth noting that the SECRE-chips are cost-effective (~$ 10), mass-producible (> 40 devices per operator per day), and highly customizable.

[0102] As a proof-of-concept model, primary CD4+ T cells were selected, which produce interferon gamma (IFNy) because elevated production of IFNy has been widely implicated inseveral autoimmune diseases, such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), hemophagocytic lymphohistiocytosis (HLH)37. In addition, numerous studies have found that IFNy plays an essential role in the development and severity of celiac disease, inflammatory bowel disease (IBD)38, and immune-mediated graft failure39. In a first set of experiments, the ability of the SECRE-chip to sort CD4+ T cells was assessed according to the secretion levels of three different cytokines, including IFNy, IL 10, and tumor necrosis factor alpha (TNFa) after stimulating the cells by a combination of phorbol 12- myristate 13-acetate (PMA) and ionomycin. TCR-independent activation was selected to probe a broad range of responses40. Prior to experiments, CD4+ T cells used in these trials were phenotyped (Fig. 7). The effects of CD4 and / or CD45 specific antibodies on IFNY secretion by CD4+ T cells was tested and no significant effects were noted (Fig. 8). It was found that CD4+ T cells sorted based on IFNy secretion, were captured mainly in the first zone, whereas cells sorted according to IL 10 secretion were slightly shifted towards the second zone. The distribution of the cells sorted based on TNFa secretion was further shifted towards the second zone (Fig. 2a and Fig. 9). The results indicated that the secretion of IFNy > IL10 > TNFa by CD4+ T cells. Flow cytometry was used to measure the secretion of the three cytokines by CD4+ T cells and both methods generated comparable results (Fig. 2b), indicating that the microfluidic approach can analyse and sort cells based on cytokine secretion. Sorting out three different cell types, including CD4+ T cells, Jurkat, and leukemic B cells based on IFNy secretion was then set out. The results showed that IFNy secretion by CD4+ T cells > Jurkat > leukemic B cells (Fig. 2c and Fig. 10). Comparable results were obtained using flow cytometry (Fig. 2d), which further validated the sorting ability of the microfluidic approach. The CD4+ T cells in the SECRE-chip based on IFNy using forward flow (from Z1 to Z2) and reverse flow (from Z2 to Zl) were sorted and the sorted cell populations were analysed with flow cytometry (Fig. 11). Similar profiles were observed for the sorted cell population in Zl for forward flow and Z2 for reverse flow and hence crosscontamination or enhanced binding in locally concentrated regions in the device would not remarkably affect the sorting results.Example 2 - Validation of SECRE Method

[0103] FIG. 2A-2B describes the cytokine secretion analysis. Analysis of three different cytokines (IFNy, IL10, and TNFa) secreted by CD4+ T cells, using the microfluidic-based cell secretion assay (Fig. 2A) and flow cytometry (Fig. 2B). FIG. 2C-2D describes the analysis of IFNy secreted by three different cell types (CD4+ T cells, Jurkat, and leukemic Bcells) using the microfluidic-based cell secretion assay (Fig. 2C) and flow cytometry (Fig. 2D). FIG. 2E describes the analysis of IFNy secreted by different proportions of CD4+ T cells (100%, 75%, 50%, 25%, 0%) in a mixture with B cells using the microfluidic-based cell secretion assay. A total of IxlO6cells were analysed per sample. The error bars represent the s.d. of biological replicates («=3). Data were analyzed by two-way ANOVA with Turkey’s multiple comparisons test. FIG. 2F describes the sensitivity of the SECRE method benchmarked against a commercially available IFNy assay kit. Median fluorescence intensity (MFI) for flow cytometric analysis of IFNy using the microfluidic approach and assay kit. A total of IxlO5cells were analysed per sample. Data are mean ± s.d. of biological replicates («=3). Data were analyzed by unpaired two-tailed Student’s / -test. FIG. 2G describes the quantification of cellular fluorescence of cells captured in each zone as a function of number of magnetic nanoparticles. FIG. 2H depicts the transmission electron microscopy (TEM) imaging of CD4+ T cells to visualize the magnetic nanoparticles attached to the cell surface subsequent to IFNy analysis using the microfluidic approach.

[0104] The ability of the microfluidic device to sort different populations of CD4+ T cells according to the levels of secreted IFNy using different proportions of CD4+ T cells ranging between 100% and 0% in a mixture with B cells was assessed. Increasing the proportion of non-secretors (i.e., B cells) gradually shifted the cell distribution to the second zone and effluent, with most of the 100% B cells detected in the effluent (Fig. 2e and Fig. 12). The frequency of IFNy-positive cells in CD4+ T cells using intracellular cytokine staining was also determined (Fig. 13). It was found that the percentage of sorted cells either with the SECRE chip or flow cytometry correlates with the percentage of IFNy-positive cells determined by ICS (Fig. 2e and Fig. 13). The results indicate the amenability of the device to sorting CRISPR-edited cells, which typically comprise non-secretors as well as different cell subpopulations with varying levels of IFNy secretion. Having established the technical feasibility of SECRE, it was sought to benchmark the method’s performance using a commercially available IFNy assay kit. Using fluorescence readout for both assays, flow cytometry data showed that the sensitivity of SECRE is around 5 times the sensitivity of the assay kit (Fig. 2f and Fig. 14). The ability of the device to sort CD4+ T cells based on their magnetic loading (i.e., captured IFNy) was also tested. In these trials, the magnetic nanoparticle-labeled biotin-specific antibody with a fluorescently labeled species-specific antibody was targeted. Varying fluorescence intensities among the cells captured in each zone using fluorescence microscopy was observed (Fig. 2g and Fig. 15) and flow cytometry (Fig.16). In addition, transmission electron microscopy (TEM) images revealed a uniform layer of magnetic nanoparticles on the surface of CD4+ T cells, which was absent in IFNy'veB cells (Fig. 2h). The sorting capacity of the SECRE-chip was then determined, and it was found that an optimal separation can be achieved using 25 x 106cells per run (Fig. 17).Example 3 - SECRE combined with a CRISPR screen identifies regulators of IFNy secretion.

[0105] Evidence from a growing number of rodent models of IBD supports a central role for dysregulated CD4+ T cells responses41. IBD pathogenesis is associated with loss of epithelial barrier functions leading to excessive bacterial translocation. The characteristic chronically relapsing intestinal inflammation of IBD is thought to arise from an exaggerated immune response to the commensal microbiota. Cytokines, such as IFNy are considered major drivers of this excessive immune response, leading to massive leukocyte infiltration and mucosal damage42. More interestingly, blockade of IFNy by a specific antibody was accompanied by reduced vascular permeability and disease severity in IBD mouse models43. To identify novel therapeutic targets of IBD, Applicant combined SECRE with a kinome-wide CRISPR-Cas9 loss-of-function screen to identify IFNy-regulators in CD4+ T cells. As an initial test, singleguide RNA (sgRNA) library targeting 763 human kinase coding genes was screened for potential genes involved in the regulation of IFNy secretion (Fig. 3a). Transduced CD4+ T cells were sorted using the SECRE-chip, as well as FACS to assess the performance of the SECRE-chip in two independent experiments (Figs. 18, 19). Applicant sequenced the sgRNA barcodes of cells collected from the effluent of the SECRE-chip, as well as from IFNylowcell population sorted by FACS. Applicant also sequenced the sgRNA barcodes of unsorted initial pool of cells as a control. Top sgRNA hits were identified with DrugZ algorithm using NormZ scores > 2 and false discovery rate (FDR) < 0.3 (Fig. 3b). Gene-level statistical analysis of IFNy CRISPR screen performed using SECRE-chip and FACS revealed 21 and 12 hits, respectively, including 4 shared hits (Figs. 3c, d). As expected, Applicant identified known IFNy-regulator kinases (e.g., LRRK2 MYLK35thus confirming that our screening approach was effective.

[0106] FIG. 3 A provides a schematic of CRISPR screen workflow. FIG. 3B depicts genes targeted by sgRNAs detected in the SECRE-chip IFNyneg / IFNylowscreen, ranked by normalized Z score as calculated using DrugZ algorithm. FIG. 3C compares SECRE-chip and FACS screen results. Normalized Z scores are displayed, coloured by density with contours indicated. The dashed lines indicate the top and bottom 90thpercentile of the data.Overlapping hits at <30% FDR are shown. FIG. 3D depicts the overlap of hits obtained from SECRE-chip and FACS IFNy screens at <30% FDR.Example 4 - Validation of identified hits.

[0107] The sgRNA / gene enrichment results using different algorithms was assessed and a high correlation between DrugZ and MAGeCK results was found (Fig. 20), however DrugZ was more sensitive46. Strikingly, most of the screen hits were not described previously and are potential novel regulators of IFNy secretion. It was hypothesized that the novel hits detected only by the microfluidic approach reflect the higher resolution of the microfluidic device compared to FACS47. Validation experiments were conducted using four individual siRNAs specific for LRRK2 (leucine rich repeat kinase 2), as well as three novel hits, including SLK (STE20 like kinase), STK10 (serine / threonine kinase 10), and STK24 (serine / threonine kinase 24). Flow cytometry was used to confirm the knockdown efficiency of each siRNA pool (Fig. 4a). Knockdown of the previous genes was accompanied by a significant dampening of IFNy secretion, which was analysed using the SECRE technique (Fig. 4b and Fig. 21) and confirmed with ELISA (Fig. 4c and Fig. 22). ELISA was also used to assess the performance of SECRE technique. It was found that the assay captured 91.6±2.4% of secreted IFNy in the culture medium, which is indicative of the high efficiency of the assay (Fig. 22). Furthermore, validation experiments were conducted for the hits identified with FACS using four individual siRNAs specific for CDKL4 (cyclin dependent kinase like 4), PI4KB (phosphatidylinositol 4-kinase beta), MAP2K4 (mitogen-activated protein kinase 4), IPMK (inositol polyphosphate multikinase), DCLK3 (doublecortin like kinase 3), and CSK (C-terminal Src kinase). Knockdown of the previous genes was accompanied by a significant reduction in IFNy secretion, which was analysed using ELISA (Fig. 23).

[0108] FIG. 4A describes the flow cytometric analysis of top hits: LRRK2, SLK, STK10, and STK24 proteins before and after knocking down the corresponding genes with siRNAs in CD4+ T cells. FIG. 4B describes the analysis of IFNy secretion using the SECRE method after knocking down LRRK2, SLK, STK10, and STK24 in CD4+ T cells using non-targeting (NT) siRNA as a control. Data were analyzed by two-way ANOVA with Dunnett’s multiple comparisons test. FIG. 4C describes the analysis of IFNy secretion by a high-sensitivity ELISA after knocking down the previous genes in CD4+ T cells with specific siRNAs, using NT siRNA as a control. FIG. 4D describes the analysis of IFNy secretion using the SECRE method after knocking out LRRK2, SLK, STK10, and STK24 with the first set of guidesequences in CD4+ T cells using CRISPR. Data were analyzed by two-way ANOVA with Dunnett’s multiple comparisons test. FIG. 4E describes the analysis of IFNy secretion by a high-sensitivity ELISA after knocking out the previous genes in CD4+ T cells. Data were analyzed by one-way ANOVA with Turkey’s multiple comparisons test. FIG. 4F depicts a heatmap of selected secreted cytokine / chemokine measurements performed using the cytokine Luminex assay subsequent to knocking out the previous genes in CD4+ T cells. FIG. 4G describes an analysis of kinase inhibitors using ADP-Glo assay. Curve fits were performed where the enzyme activity at the highest inhibitor concentration was less than 65% and the IC50 values were determined using GraphPad Prism software. FIG. 4H depicts the analysis of IFNY secretion by SECRE method after incubation of CD4+ T cells with XMU- MP1 (STE20 like kinase 1 / 2 inhibitor), SB-633825 (STK10 inhibitor), momelotinib (ACVR1 inhibitor), erlotinib (SLK and STK10 inhibitor), and bosutinib (STK24 inhibitor), using the cells incubated with the solvent (DMSO) as a control. Data were analyzed by two-way ANOVA with Dunnett’s multiple comparisons test, (i) Analysis of IFNy secretion by a high- sensitivity ELISA after incubation of CD4+ T cells with the previous inhibitors using the cells incubated with DMSO as a control. Data were analyzed by one-way ANOVA with Turkey’s multiple comparisons test. A total of IxlO6cells were analysed per sample. Data are mean ± s.d. of biological replicates («=3).

[0109] Another validation was carried out using CRISPR knockouts of the top hits using two different sgRNAs from a different library that was not used in the initial screen. It was found that knocking out LRRK2, SLK, STK10, and STK24 in CD4+ T cells was accompanied by a significant dampening of IFNy secretion, which was analysed using intracellular cytokine staining (Fig. 24 and 27), the SECRE technique (Fig. 4d and Fig. 25) and confirmed with ELISA (Figs. 4e, 26, and 28). It was also assessed how individual CRISPRi perturbations affect cytokine production by measuring a panel of 71 cytokines and chemokines, 53 of which were detected (Fig. 4f and Fig. 29). Abroad dampening in cytokine and chemokine production was observed.

[0110] To further validate the hits and identify druggable kinase targets, Applicant carried out a drug screen for one shared hit, namely ACVR1 (activin A receptor type 1), as well as for three of the novel hits, including SLK, STK10, STK24. In this screen, Applicant used several kinase inhibitors, including XMU-MP1 (STE20 like kinase 1 / 2 inhibitor)48, SB-633825 (STK10 inhibitor)49, and three FDA approved kinase inhibitors, including momelotinib (ACVR1 inhibitor)50, bosutinib (STK24 inhibitor)51, and erlotinib, which has been suggestedto have an off-target inhibitory effect on both SLK and STK1052. Applicant first compared the inhibitory effects of these drugs on their target kinases using ADP-Glo assay and determined the IC50 values (Fig. 4g). The drug screen nominated XMU-MP1, SB-633825, and bosutinib as potent inhibitors of IFNy secretion, which was analysed using the SECRE technique (Fig. 4h and Fig. 30) and confirmed with ELISA (Fig. 4i and Fig. 31). As expected, the inhibitors had no effect on cell viability at the tested concentration.

[0111] Example 5 - Validation of IFNy inhibition in DSS-induced colitis mouse model

[0112] To showcase the therapeutic potential of these inhibitors, the effect of XMU-MP1 (Fig. 5a) on the colon of mice treated for 8 days with oral dextran sodium sulfate (DSS), an agent that induces colon tissue ulceration that resembles ulcerative colitis in humans (Fig. 5b), was examined. DSS-induced colitis is widely regarded as a useful murine model of IBD because the histological changes as well as expression profile of cytokines in DSS-induced colitis are similar to those observed in human IBD, particularly ulcerative colitis53. DSS exerts direct toxicity to colonic epithelial cells, increasing the permeability of the intestinal mucosa and allowing leakage of luminal bacterial products to submucosal tissues54. Also, DSS treatment triggers the recruitment and activation of leukocytes and in turn inflammation of the colon.

[0113] FIG. 5 A depicts the chemical structure of XMU-MP1. FIG. 5B provides a schematic illustration of in vivo workflow. Mice (w=8) were fed formulated drinking water containing 2% DSS for 7 days and 0.5% DSS in day 8 and received a daily i.p. injection of 1 mg kg1XMU-MP1 for 8 days. A control group of mice («=7) were fed DSS in drinking water and received a daily i.p. injection of the vehicle (3% DMSO in PBS). Another control group of mice («=5) received tap water only. The effect of XMU-MP1 on mouse body weight during colitis induction was described in FIG. 5C. Weight changes were calculated as a percentage of weight prior to DSS treatment (Day 0). Data were analysed by two-way ANOVA with Turkey’s multiple comparisons test. FIG. 5D depicts the changes in colon length during XMU-MP1 treatment of DSS-induced colitis mice. Data are mean ± s.d. of biological replicates (n=5- 8). Analysis of mouse IFNy (FIG. 5E) and myeloperoxidase (MPO) activity (FIG. 5F) in the homogenized colons of XMU-MP1 treated mice prior to colitis induction is depicted. Data are mean ± s.d. of technical replicates («=3). Data were analysed by one-way ANOVA with Turkey’s multiple comparisons test. FIG. 5G provides representative images of Olfm4+ ISCs in the colons of mice (w=10 independent sections per group) after being fed with tap water only, DSS and daily 3% DMSO, and DSS and daily 1 mg kg1XMU-MP1 in3% DMSO. FIG. 5H describes the percentage of 01fm4++cells per section. Data were analysed by unpaired two-tailed student’s / -test.

[0114] Stimulation of local IFNy secretion and subsequent fFNy-dependent induction of chemokines (e.g., IP-10, MIG, MCP-1, etc.) represent the aetiological link between DSS- mediated epithelial damage and inflammation55. In addition, IFNy production might impair the barrier function of intestinal epithelial cells56. Furthermore, it was recently demonstrated that IFNy produced by T helper cells induces JAK1- and STAT1 -dependent toxicity, triggering apoptosis of intestinal stem cells (ISCs) resident in the crypt bottom of the epithelium and marked by the gene 0LFM4, thus inhibiting intestinal regeneration upon damage39, 57.

[0115] In these trials, DSS-treated mice exhibited a significant loss of body weight starting at day 8 (Fig. 5c and Fig. 32). On the contrary, XMU-MP1 -treated mice showed resistance to DSS-induced colitis, evident by significantly less weight loss and suppression of colitis symptoms, which were assessed by measuring the colon length as an indication of colonic inflammation (Fig. 5d and Fig. 33). It was also found that the colons of tap water fed mice produced low level of IFNY (Fig- 5e and Fig. 34) and exhibited low myeloperoxidase (MPO) activity (Fig. 5f and Fig. 35), while IFNY production as well as MPO activity were drastically induced after daily administration of DSS. However, XMU-MP1 -treated mice exhibited reduced production of IFNY and MPO activity in the gut, compared to untreated DSS-fed mice. Immunohistochemical analysis revealed the disruption of the mucosal epithelium and loss of Olfm4+ISCs in DSS-fed mice, whereas the colons of XMU-MP1 -treated mice remained virtually normal in appearance and did not show significant loss of ISCs (Fig. 5g and h). These results suggest that inhibition of IFNy production in the gut may represent an ideal means to control IBD, providing a promising strategy for therapeutic molecular targeting of IBD.Example 6Methods

[0116] Device fabrication. The SECRE-chip was fabricated by a stereolithographic 3D printer (pMicrofluidics Edition, Creative CADworks) using ‘CCW master mold for PDMS’ resin with a layer thickness of 25 pm (Resinworks 3D). PDMS (Sylgard 184) was cast on printed molds, followed by incubation for 2 hours at 70°C. The cured replicas were punched and plasma-bonded to thickness no. 1 glass coverslips (Cat.# 260462, Ted Pella). Afterward, silicon tubing was attached to the inlet and outlet of the device. Before use, the device was conditioned with 1% Pluronic F68 (Cat.# P5556, Sigma-Aldrich) in phosphate-bufferedsaline (PBS, Wisent Bioproducts), overnight to reduce non-specific adsorption. Each device was positioned on top of an array of N52 Nd FeB magnets (1.5 mm by 8 mm, K&J Magnetics), with alternating polarity.

[0117] Cell culture. Leukemic B cell line (CCRF-SB) and Jurkat (Clone: E6-1) were purchased from ATCC and cultured in RPML1640 medium (ATCC 30-2001), supplied with 10% fetal bovine serum (FBS, Wisent Bioproducts) and 1% penicillin-streptomycin (PS, Wisent Bioproducts). Human peripheral blood CD4+T cells (Cat.# 70026, Stem Cell technologies) were cultured in ImmunoCult-XF T cell expansion medium (Cat.# 10981, Stem Cell technologies), supplied with 50 ng mL1CHO-expressed Human recombinant IL2 (Cat.# 78036, Stem Cell Technologies). Primary T cells were activated using Immnocult Human T cell activator (Cat.# 10970, Stem Cell technologies), for 3 days every 10 - 14 days. Prior to use, the cells were filtered using a 40pm BD falcon cell strainer (Becton, Dickinson and Company). Expression of CD4, CD45, CD25, and CD69 was regularly checked by flow cytometry to ensure maintaining proper phenotypes during expansion.

[0118] Phenotyping of CD4+ T cells. The cells were incubated with the blocking buffer (2% bovine serum albumin (BSA) in PBS) for 30 min on ice. The cells were incubated with either 20 pL of PE-labeled CD19 antibody (Cat.# 555413, BD Biosciences, RRID:AB_395813), 20 pL of APC-labeled CD4 antibody (Cat.# 555349, BD Biosciences, RRID:AB_398593), 20 pL of APC-labeled CD45 antibody (Cat.# 555485, BD Biosciences, RRID:AB_398600), or 5 pL of PerCP-Cy5.5-labeled CD69 antibody (Cat.# 560738, BD Biosciences, RRID:AB_1727510) and 5 pL of APC-Cy7-labeled CD25 antibody (Cat.# 557753, BD Biosciences, RRID:AB_396859), for 30 min at room temperature. A control experiment was carried out using B cells. Prior to analysis, the cells were washed three times with the blocking buffer. Finally, the samples were injected into Attune NxT flow cytometer (Thermo Fisher Scientific) and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. A total of 20,000 cells were analysed per sample.

[0119] Preparation of streptavidin-conjugated antibodies. Three antibodies, including antibodies specific to CD4 (Cat.# 317404, Biolegend, RRID:AB_571961) and CD45 (Cat.# 393402, Biolegend, RRID:AB_2749886), were modified with streptavidin using a streptavidin conjugation kit (Cat.# ab 102921, Abeam), according to the manufacturer’s protocol. Briefly, 100 pL of the antibody solution (1 mg mL1) were gently shaken with 10 pL of the activator. The activated antibodies were then incubated with 33 pg streptavidin for 3 hours at room temperature. Afterward, 10 pL of the quencher were added to stop thereaction. Finally, sodium azide was added to a final concentration of 0.02% (w / v) and the solution (400 pg mL1) was stored at 4°C until use.

[0120] Analysis of secreted cytokines using the microfluidic approach. CD4+ T cells (IxlO6) were incubated with a mixture of 5 pL of 400 pg mL1streptavidin-labeled CD4 antibody and 5 pL of 400 pg mL1streptavidin-labeled CD45 antibody and the suspension was gently shaken for 45 min at room temperature. After washing, the cells were incubated with either 5 pL of 500 pg mL1biotin-labeled IFNy antibody (Cat.# 554550, BD Biosciences, RRID:AB_395472) for IFNY analysis, or biotin-labeled IL10 antibody (Cat.# 501502, Biolegend, RRID:AB_315178) for IL 10 analysis, or biotin-labeled TNFa antibody (Cat.# 502904, Biolegend, RRID:AB_315256) for TNFa analysis, and the suspension was gently shaken for 30 min at room temperature. After washing, the cells were incubated with 2 pL of cell activation cocktail (without Brefeldin A) (Cat.# 423302, Biolegend), for 4 hours at 37°C. After washing, the cells were incubated with either 5 pL of 500 pg mL1biotin-labeled IFNy antibody for IFNy analysis, or biotin-labeled IL10 antibody for IL10 analysis, or biotin- labeled TNFa antibody for TNFa analysis, and the suspension was gently shaken for 45 min at room temperature. After washing, the cells were incubated with 5 pL of biotin specific antibody conjugated with magnetic nanoparticles (Cat.# 130-105-637, Miltenyi Biotec, RRID:AB_2811216), and the suspension was gently shaken for 45 min at room temperature. The cells were then loaded into the SECRE-chip at a flow rate of 2 mL h using a syringe pump (Chemyx). The sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter.

[0121] Analysis of secreted cytokines using flow cytometry. CD4+ T cells (IxlO6) were incubated with a mixture of 5 pL of 400 pg mL1streptavidin-labeled CD4 antibody and 5 pL of 400 pg mL1streptavidin-labeled CD45 antibody and the suspension was gently shaken for 45 min at room temperature. After washing, the cells were incubated with either 5 pL of 500 pg mL1biotin-labeled IFNy antibody for IFNy analysis, or biotin-labeled IL 10 antibody for IL10 analysis, or biotin-labeled TNFa antibody for TNFa analysis, and the suspension was gently shaken for 30 min at room temperature. After washing, the cells were incubated with 2 pL of cell activation cocktail for 4 hours at 37°C. After washing, the cells were incubated with either 5 pL of 500 pg mL1biotin-labeled IFNy antibody for IFNy analysis, or biotin- labeled IL10 antibody for IL10 analysis, or biotin-labeled TNFa antibody for TNFa analysis, and the suspension was gently shaken for 45 min at room temperature. After washing, the cells were incubated with 2 pL of FITC-labeled biotin specific antibody (Cat.# 130-113-290,Miltenyi Biotec, RRID:AB_2733612) or APC-labeled biotin specific antibody (Cat.# 130- 113-288, Miltenyi Biotec, RRID:AB_2726071), and the suspension was gently shaken in the dark for 45 min at room temperature. A control experiment was carried out using biotin- labeled mouse IgGl kappa isotype control (Cat.# 130-113-198, Miltenyi Biotec, RRID:AB_2733563), instead of biotin-labeled IFNy antibody. Prior to analysis, the cells were washed 3 times with 2% BSAin PBS. Finally, the samples were injected into Cytoflex (Beckman Coulter) flow cytometer, and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. Atotal of 10,000 cells were analysed per sample.

[0122] Cell staining and imaging. CD4+ T cells (IxlO6) were sorted using the SECRE-chip based on the expression of IFNY,aspreviously described. Captured cells were immunostained using 1 pL of 2 mg mL1AF488-labeled goat anti-mouse IgG (Cat.# abl50113, Abeam, RRID:AB_2576208) in 500 pL PBS containing l% BSA and 0.1% Tween-20 (Sigma-Aldrich). Immunostaining was carried out for 45 min in the dark. After washing with 0.1% Tween-20 in PBS, the cells were stained with 2 drops of 4’,6-diamidino- 2-phenylindole (DAPI Prolong Gold nuclear stain, Invitrogen) in 500 pL PBS for 10 min. After staining, the cells were washed with 0.1% Tween-20 in PBS. Devices were imaged immediately using a confocal-like microscope (Zeiss Axio Observer) and the images were processed with Zen software (Blue edition, Zeiss). The exposure time was set individually for each chip and kept constant during imaging. Images were acquired by overlaying the bright field, blue, and green fluorescent images.

[0123] MACS IFNy secretion assay. Analysis of IFNY produced by activated CD4+ T cells and fixed CD4+ T cells (control) was carried our using MACS IFNY secretion assay kit (Cat.# 130-090-433, Miltenyi Biotec), according to the manufacturer’s protocol. CD4+ T cells (IxlO6in culture medium) were incubated with 2 pL of cell activation cocktail in a culture plate for 6 hours at 37°C in the CO2 incubator. The cells were collected from the plate, washed and resuspended in 80 pL of cold buffer (0.5% BSA and 2 mM EDTA in PBS). Then, 20 pL of Cytokine Catch Reagent were added and the cells were incubated for 5 min on ice. Afterward, 10 mL of warm culture medium were added, and the cells were gently shaken for 45 min at 37°C. The cells were washed and resuspended in 80 pL of cold buffer, then 20 pL of Cytokine Detection antibody (FITC-labeled) were added and the cells were incubated for 10 min on ice. A control experiment was carried out using CD4+ T cells (IxlO6) previously fixed using 4% PF A, then treated under the same experimental conditions. Prior to analysis,the cells were washed 3 times with 2% BSA in PBS. Finally, the samples were injected into Attune NxT flow cytometer (Thermo Fisher Scientific) and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. Atotal of 100,000 cells were analysed per sample.

[0124] Intracellular cytokine staining (ICS). CD4+ T cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator (Cat.# 10990, Stem Cell Technologies) using 6.25 pL mL1of culture medium at 2 * 106cells mL1. One hour after restimulation, Golgi Plug protein transport inhibitor (Cat.# 555029, BD Biosciences) was added at 1 / 1000 dilution. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PFA and permeabilized with 0.2% Triton X-100. The cells were incubated with 5 pL of 500 pg mL1biotin-labeled ZFNy antibody (Cat.# 554550, BD Biosciences, RRID:AB_395472) for 45 min at room temperature. After washing, the cells were incubated with 2 pL of FITC- labeled biotin specific antibody (Cat.# 130-113-290, Miltenyi Biotec, RRID:AB_2733612), and the suspension was gently shaken in the dark for 45 min at room temperature. Prior to analysis, the cells were washed 3 times with 2% BSA in PBS. Finally, the samples were injected into Cytoflex flow cytometer (Beckman Coulter), and the measurements were plotted as histograms. Absorbance values were normalized to unstained control.

[0125] Scanning electron microscopy (SEM). Fabricated chips were sputter-coated with 50 nm gold (Denton Desk II, Leica) and imaged under FEI XL30 SEM (Thermo Fisher Scientific), using 2 kV accelerating voltage and high-vacuum mode.

[0126] Transmission electron microscopy (TEM). CD4+ T cells (IxlO7) were sorted using the SECRE-chip based on the expression of IFNy, as previously described, and the cells were released from capture zone 1 in the SECRE-chip. A control experiment was carried out in which B cells (IxlO7) were sorted based on the expression of IFNY and the cells were collected from the effluent. Collected samples were fixed with 2% glutaraldehyde in 0.1 M sodium cacodylate buffer (pH 7.3), for 2 hours at room temperature. After washing three times with the same buffer, the cells were post-stained with 1% osmium tetroxide in 0.1 M sodium cacodylate buffer (pH 7.3), for 1 hour at room temp. After washing, the cells were dehydrated with 70% ethanol (10 min), 90% ethanol (10 min), 70% ethanol (2 changes in 30 min), 90% ethanol (2 changes in 45 min), 100% ethanol (3 changes in 30 min), and propylene oxide (2 changes in 20 min). The cells were gently shaken with a mixture of Quetol-Spurr resin (Cat.# EM0300, Sigma-Aldrich) and propylene oxide (Sigma-Aldrich) (1 : 1), for 1 hour at room temperature. Samples were then gently shaken with Quetol-Spurr resin for 1 hourthen overnight at room temperature. Samples were sliced to 70- 80 nm sections with an ultracut microtome (Ultracut RMC MT6000, Leica Microsystems), then loaded onto carbon- coated copper grids (Ted Pella) and left to dry at room temperature. Cells were examined with TEM (FEI Tecnai39520, Thermo Fisher Scientific), using 100 kV accelerating voltage.

[0127] Pooled CRISPR screen. CRISPR screens in primary CD4+ T cells were performed using Brunello Human kinome CRISPR Knockout library (Cat.# 75312, Addgene). Briefly, 500xl06cells were infected with the lentiviral library at multiplicity of infection (MOI) of ~0.3 for 24 hours, followed by electroporation to deliver Cas9 (Cat.# A36498, Thermo Fisher Scientific) or Cas9-GFP protein (Cat.# CAS9GFPPRO, Sigma-Aldrich) for editing. The electroporation was carried out with Neon Transfection System (Cat.# MPK5000, Thermo Fisher Scientific) using a 100 pL kit under the following conditions: pulse voltage: 2000 V; pulse width: 20; pulse number: 2; cell density: 2xl07cells ml-1; Cas9 concentration: 100 pg ml-1. These conditions typically allow a transfection efficiency of -20% based on flow cytometric analysis of GFP expression. Electroporated cells were selected by incubation with puromycin for 48 hours and used for FACS or microfluidic sorting. A control experiment was carried out using 2xl06unsorted cells (more than 500-fold coverage of the library).

[0128] The sorted cells were collected from the effluent and each capture zone within the microfluidic device as well as the cell populations sorted by FACS were collected for genomic DNA extraction using QIAamp DNA Micro Kit (Cat.# 56304, Qiagen) or Mini Kit (Cat.# 51304, Qiagen). The genomic DNA was amplified and sequenced using the protocol recommended by the library supplier. Sequenced data were FastQCed and mapped to read counts using the workflow described before46. Fold changes and normalized Z scores were calculated using drugZ (v.1.1.0.2). Genes were indexed by the order of normalized Z scores. Hits were selected using the following criteria: Norm Z scores > 2 and FDR < 0.3.

[0129] Sorting of CRISPR-edited CD4+ T cells. CRISPR-edited CD4+ T cells from passage #5 (30xl06) and passage #8 (30xl06) were incubated with a mixture of 5 pL of 400 pg mL1streptavidin-labeled CD4 antibody and 5 pL of 400 pg mL1streptavidin-labeled CD45 antibody (per 1x106cells) and the suspension was gently shaken for 45 min at room temperature. After washing, the cells were incubated with 5 pL of 500 pg mL1biotin-labeled IFNy antibody (per IxlO6cells) and the suspension was gently shaken for 30 min at room temperature. The cells were aliquoted into 60 tubes (IxlO6each) and incubated with 2 pL of cell activation cocktail, for 4 hours at 37°C. After washing, the cells were incubated with 5 pL of 500 pg mL1biotin-labeled IFNY antibody and the suspension was gently shaken for 45min at room temperature. After washing, the aliquots from each passage were combined into 5 aliquots. Each aliquot (3xl06cells) was incubated with 15 pL of biotin specific antibody conjugated with magnetic nanoparticles and the suspension was gently shaken for 45 min at room temperature. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h1. Sorted cells were collected from zone 1, zone 2, and effluent and counted using a cell counter. Cells collected from the effluent were centrifuged and used for DNA extraction.

[0130] Fluorescent-activated cell sorting (FACS). The cells either from passage #5 or 8 (15xl06each) were incubated with the blocking buffer (2% BSA in PBS) on ice. The cells were incubated with 30 pL FITC-labeled biotin specific antibody for 45 min at room temperature. Prior to sorting, the cells were filtered with 70 pm cell strainer and suspended in a sorting buffer containing 2% FBS and 1 mM ED TA in PBS. FACS sorting was performed using BD FACSAria IIIu (BD Biosciences), equipped with 4 lasers (405 / 488 / 561 / 633 nm) and 85 pm nozzle. The bottom 5% fraction gated on the FITC channel was collected in flow tubes. Collected cells were centrifuged and used for DNA extraction.

[0131] siRNA knockdown in CD4+ T cells. Applicant used Accel smart pool siRNAs to knock down the top hits identified in CD4+ T cells, according to the manufacturer’s protocol. Briefly, CD4+ T cells (100,000 cells) were cultured at 37°C and 5% CO2 in 48-well plate overnight. Stock solutions of 100 iM LRRK2 specific Accel smart pool siRNA (E-006323- 00-0005, PerkinElmer), SLK specific Accel smart pool siRNA (E-003850-00-0005, PerkinElmer), STK10 specific Accel smart pool siRNA (E-004168-00-0005, PerkinElmer), STK24 specific Accel smart pool siRNA (E-004872-00-0005, PerkinElmer), IPMK specific Accel smart pool siRNA (E-006740-00-0005, PerkinElmer), CSK specific Accel smart pool siRNA (E-003110-01-0005, PerkinElmer), CDKL4 specific Accel smart pool siRNA (E- 022660-00-0005, PerkinElmer), DCLK3 specific Accel smart pool siRNA (E-005337-00- 0005, PerkinElmer), PI4KB specific Accel smart pool siRNA (E-006777-00-0005, PerkinElmer), an . MAP2K4 specific Accel smart pool siRNA (E-003574-00-0005, PerkinElmer) in lx siRNA buffer (B-002000-UB-100, PerkinElmer) were prepared and gently shaken for 90 min at 37°C. Then, 15 pl of siRNA were mixed with 1.5 ml of the cell suspension in Accel delivery medium (B-005000-500, PerkinElmer) to a final concentration of 1 pM and the cells were incubated for 120 h at 37°C and 5% CO2. A control experiment was carried out in which the cells were incubated with non-targeting (NT) siRNA (D-001910- 10-20, PerkinElmer) in the Accel Delivery medium under the same conditions. Finally, the cells were collected and the LRRK2, SLK, STK10 and STK24 protein levels weredetermined with flow cytometry. Also, the IFNy levels were measured using ELISA and the proposed assay.

[0132] Validation of the IFNy hits using CRISPR Knockout. CD4+ T cells were transduced using two different sgRNAs targeting the top hits in the screen. The sgRNAs sequences were retrieved from TKV03 (Cat.# 125517, Addgene), which is different from the library used for the CRISPR screen. The first set of guide sequences include: LRRK2 (AGGCTGAACAATGTCCAGGA) (Cat.#34208, Addgene), SLK (ATTATAGGAGAACTGGGCGA) (Cat.#56779, Addgene), STK10 (TAGACAGGCGCAGGATGCGG) (Cat.#59027, Addgene), and STK24 (GCCACTCTACCTCATCCTGG) (Cat.#59055, Addgene).

[0133] The second set of guide sequences include: LRRK2 (AATGTGGAAGTCCTCATGAG) (Cat.#34210, Addgene), ), SLK (CATTAGCACAGCCATCCAGA) (Cat.#56780, Addgene), STK10 (GGAGCTGGAGGACTACATCG) (Cat.#59028, Addgene), and STK24 (GCCTTTGAACACCTCTCCAA) (Cat.#59056, Addgene). Briefly, 2xl07cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein (Cat.# CAS9GFPPRO, Sigma-Aldrich) for editing. The electroporation was carried out with Neon Transfection System (Cat.# MPK5000, Thermo Fisher Scientific) using a 100 pL kit under the following conditions: pulse voltage: 2100 V; pulse width: 20; pulse number: 1; cell density: 2xl07cells mL Cas9 concentration: 100 pg mL1. Electroporated cells were selected by incubation with 2 pg mL1puromycin for 72 hours and used for ICS, microfluidic analysis, ELISA, and cytokine Luminex assay.

[0134] Cytokine Luminex assay. One day 9 after activation, CD4+ T cells at a concentration of 2xl06cells / mL were restimulated with ImmunoCult Human CD3 / CD28 / CD2 (Cat.# 10970, Stem Cell Technologies) at 6.25 pL mL1. Twenty -four hours after restimulation, the supernatant was collected and frozen at -20°C. After a serial pilot titration, cytokine / chemokine analysis was performed at 1 / 200 dilution using the Luminex xMAP technology on the Luminex 200 system (Eve Technologies). A total of 71 cytokines / chemokines were analyzed, whereas undetectable cytokines / chemokines were removed.

[0135] Validation of the IFNy hits using kinase inhibitors. Applicant used XMU-MP1 (Cat.# S8334, Shelleckchem) to inhibit the expression of SLK, SB-633825 (Cat.# HY- 108333, MedChemExpress) to inhibit the expression of STK10, and Applicant also testednonspecific kinase inhibitors, including momelotinib (CYT387, Cat.# S2219, Shelleckchem), erlotinib (CYT387, Cat.# S7786, Shelleckchem), and bosutinib (SKI-606, Cat.# S1014, Shelleckchem). Briefly, CD4+ T cells (100,000 cells) were cultured at 37°C and 5% CO2 in 48-well plate overnight. A stock solution of 10 mM of each inhibitor in DMSO was prepared. The inhibitors were added to 4 ml of the cell suspension to a final concentration of 50 pM. A control experiment was carried out in which the cells were incubated with the same DMSO volume. The cells were incubated for 72 hours at 37°C and 5% CO2. Finally, the cells were collected and the ZFNy levels were measured using ELISA and the proposed assay.

[0136] ADP-Glo assay. This is a three-step luminescent ADP assay in which the kinase reaction with a lipid substrate is carried out in the presence of ATP. The reaction is then quenched, and the remaining ATP is depleted using the ADP-Glo reagent. Finally, kinase detection reagent is added to convert ADP to ATP, which is measured using a luciferase / luciferin reaction. Briefly, the target kinase was gently mixed with the substrate solution and the tested inhibitor (IxlO'5, 3.33xl0'6, l. llxlO'6, 3.7xl0'7, 1.23xl0'7, 4.12xl0'8, 1.37xl0'8, 4.57xl0'9, 1.52xl0'9, 5.08xl0'10, 0 M) in 100% DMSO was added to the reaction mixture and incubated for 20 min at room temperature. Next, 10 pM ATP was added to the reaction mixture and incubated for 60 min at 30°C. The reaction was then quenched by incubation with the ADP-Glo reagent for 40 min. The detection mixture was added and incubated for 30 min then the luminescence was measured. Curve fits were performed where the enzyme activity at the highest inhibitor concentration was less than 65% and the IC50 values were determined using GraphPad Prism software. A control compound, staurosporine, was tested in 10-dose IC50 mode with 4-fold serial dilution starting at 20 pM during the analysis of XMU-MP1 and erlotinib (SLK), and bosutinib (STK24). A control compound, RO-31-8220, was tested in 10-dose IC50 mode with 3-fold serial dilution starting at 20 pM during the analysis of SB-633825 and erlotinib (STK10). A control compound, LDN193189, was tested in 10-dose IC50 mode with 3 -fold serial dilution starting at 10 pM during the analysis of momelotinib (ACVR1).

[0137] IFNy analysis using ELISA. Analysis of IFNy produced by live and fixed CD4+ T cells as well as CD4+ T cells previously incubated with either siRNAs, kinase inhibitors, or CRISPR-edited was carried out using IFNy high-sensitivity Human ELISA kit (Cat.# ab236895, Abeam), according to the manufacturer’s protocol. In addition, the assay was used to determine the level of unbound IFNY after performing the proposed microfluidic assay. A sample of IFNY was obtained after incubating IxlO6of CD4+ T cells with 2 pL of cellactivation cocktail for 4 hours at 37°C, followed by centrifugation and collecting the supernatant. Also, a sample of unbound fFNy was collected from the supernatant after performing the IFNy secretion assay on IxlO6of CD4+ T cells. For ELIS A measurements, 50 pL of blank control, standard recombinant IFNy concentrations in sample diluent NS, and aliquots of the previously described samples in the sample diluent NS were added to the wells of the microtiter plate. In addition, 50 pL of the antibody cocktail (capture antibody and detector antibody) in the antibody diluent 4BI were added to the wells and the plate was shaken for 1 hour at room temperature. After washing with buffer PT, 100 pL of TMB solution were added to each well, and the plate was shaken in the dark for 10 min at room temperature. Finally, 100 pL of the stop solution were added to each well and the optical density was recorded at 450 nm using a spectrophotometer.

[0138] Analysis of knocked-down proteins using flow cytometry. CD4+ T cells (IxlO6) were incubated with the blocking buffer (2% BSA in PBS) for 30 min on ice. The cells were fixed with 4% paraformaldehyde (PF A, Sigma-Aldrich) and permeabilized with 0.2% Triton X-100. The cells were incubated with 10 pL of 100 pg mL1biotin-labeled LRRK2 antibody (Cat.# NB110-58771B, Novus Biologicals, RRID:AB_1849213) or biotin-labeled SLK antibody (Cat.# NBP2-98859B, Novus Biologicals) or biotin-labeled STK10 antibody (Cat.# NBP2-99860B, Novus Biologicals) or biotin-labeled STK24 antibody (Cat.# LS-C317555- 50, LSBio) for 45 min at room temperature. A control experiment was carried out in which the cells were incubated with 10 pL of 100 pg mL1biotin-labeled rabbit isotype control (Cat.# ab200208, Abeam) for 45 min at room temperature. The cells were incubated with 2 pL of 500 pg mL1FITC-labeled streptavidin (Cat.# 405202, Biolegend) for 30 min at room temperature. Prior to analysis, the cells were washed 3 times with 2% BSA in PBS. Finally, the samples were injected into Attune NxT flow cytometer and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. A total of 20,000 cells were analysed per sample.

[0139] Dextran sodium sulfate-induced colitis mouse model. All animal experiments were carried out in accordance with the protocol approved by the University of Toronto Animal Care Committee and were in strict accordance with good animal practice as defined by the University of Toronto Animal Facility. Male C57BL / 6 mice (8-10 weeks) were purchased from Envigo and maintained under pathogen-free conditions at the University of Toronto Animal Facility. The mice were split into three groups. The first group of mice (n = 8) was fed formulated drinking water containing 2% dextran sodium sulfate (DSS) for 7 days and0.5% DSS in day 8 and received a daily intraperitoneal (i.p.) injection of 1 mg kg1XMU- MP1 in PBS containing 3% DMSO for 8 days. A control group of mice (n = 7) were fed 2.5% DSS in drinking water for 7 days and 0.5% DSS in day 8 and received a daily i.p. injection of the vehicle (3% DMSO in PBS) for 8 days. Another control group of mice (n = 5) received tap water only for 8 days. The mice were monitored for daily body weights, and the weights were recorded as percentage of initial body weight. At day 9, the mice were euthanized, and the colons were resected between the ileocecal junction and proximal rectum and their content was removed. The colons were placed on non-adsorbent surface and their lengths were measured with a ruler. The colons were rinsed with chilled PBS and placed in PBS supplemented with complete mini, EDTA-free protease inhibitor cocktail (Cat.# 11836170001, Roche Diagnostics) using 1 tablet per 10 ml PBS. The colons were homogenized, and the homogenate was centrifuged at 11,000g for 15 min at 4°C, to remove any insoluble material. The supernatant was collected and stored at -80°C before use for analysis of IFNy and myeloperoxidase activity. For immunohistochemical analysis, the colons were removed from the 3 groups, fixed in 10% formalin, paraffin-embedded, and sliced into 5 pm thick sections. The sliced colons were placed on slides and the intestinal stem cells (ISCs) were immunostained with Olfm4 antibody (Cat.# 39141 S, Cell Signaling Technology, RRID:AB_2650511) and SignalStain DAB substrate kit (Cat.# 8059S, New England Biolabs). The slides were scanned using Aperio digital pathology slide scanner (Leica Biosystems) and quantified using Halo image analysis software v3.3 (Indica Labs) using a built-in cytonuclear counter (cut-off: 0.2 for dim and 0.5 for bright).

[0140] Analysis of mouse IFNy using ELISA. Analysis of IFNy produced in the gut of DSS and control mice was carried out using mouse IFNy ELISA kit (Cat.# ab 100689, Abeam), according to the manufacturer’s protocol. Briefly, 100 pL of blank control, standard recombinant IFNy concentrations, and aliquots of samples in sample diluent A were added to the wells of the microtiter plate and the plate was shaken for 2.5 hours at room temperature. After washing, 100 pL of biotinylated ZFNy detection antibody in assay diluent B were added and the plate was shaken for 1 hour at room temperature. After washing, 100 pL of horseradish peroxidase (HRP)- streptavidin solution in assay diluent B were added and the plate was shaken for 45 min at room temperature. After washing, 100 pL of TMB solution were added to each well, and the plate was shaken in the dark for 30 min at room temperature. Finally, 50 pL of the stop solution were added to each well and the optical density was recorded at 450 nm using a spectrophotometer.

[0141] Analysis of myeloperoxidase activity in mice. Analysis of myeloperoxidase (MPO) activity in the gut of DSS and control mice was carried out using myeloperoxidase activity assay kit (Cat.# abl05136, Abeam), according to the manufacturer’s protocol. Briefly, different concentrations of TNB standard (0.5 pL DTNB probe, 0.5 pL TCEP, 49 pL assay buffer) were added to each well and the volume was completed to 150 pL using MPO assay buffer. Samples, positive control, and sample background were added to the wells and the volume was completed to 150 pL using MPO assay buffer. 50 pL of the reaction mix (40 pL MPO assay buffer, 10 pL MPO substrate) were added to the wells containing samples and positive controls. 50 pL of the background control mix (40 pL MPO assay buffer, 10 pL distilled water) were added to the background sample wells. The plate was incubated for 2 hours at room temperature. Then, 2 pL of the stop mix were added to all wells and the plate was incubated for 10 min at room temperature. Subsequently, 50 pL of the TNB standard were added to each sample, positive control, and background sample well and the plate was incubated for 10 min at room temperature. Finally, the optical density was recorded at 412 nm using a spectrophotometer. The MPO activity was calculated according to the formula: MPO activity = (B / T x V) x sample dilution factor, where: B = TNB amount calculated from absorbance of sample background - absorbance of sample (in nmol), T = incubation time (in min), and V = pre-adjusted sample volume added into the reaction well (in mL). One unit of MPO activity is the amount of MPO which hydrolyzes the substrate and generates taurine chloramine to consume 1.0 pmol of TNB per minute at room temperature.

[0142] Numerical simulations. Flow velocity profiles were numerically simulated using COMSOL Multiphysics (version 5.3, COMSOL Inc.), employing a 3D creeping flow module. The simulation parameters were as follow: wall condition: no slip; boundary condition: pressure of 0 Pa; suppression of backflow: yes; mesh size: physics-controlled, normal. The simulated flow velocity field was processed using a script in MATLAB R2017b (Math Works), to extract the normalized linear velocity per zone.

[0143] Statistical analyses. All statistical analyses were performed using the GraphPad Prism software. The specifics of the statistical tests and number of replicates are stated in the FIG. legends. The threshold for significance in all tests was p < 0.05.EXAMPLE 7

[0144] Simulations: Cell capture in the SECRE-chip

[0145] Cell capture occurs when the magnetic force acting on the cells counterbalances the drag force exhibited by the flow. Maxwell’s equation can be used to determine the magnetic flux density.

[0146] Where, F is the pull-force (N) and equals to 0.19 lbs for 1 magnet. B is the magnetic flux (T)A is the area at the surface (m^) pO is the permeability of free space, (4K X 10_)

[0147] The magnetic force acting on the cell containing magnetic nanoparticles can be calculated using the following formula:

[0148] Where Nb is the number of beads per cell, Vm is the bead volume, A / bead [unitless] represents the difference between the magnetic susceptibility of the bead and the medium, pO [H / m] is the permeability of free spaceH / m), and B [T] is the applied magnetic field. Here Applicant used magnetic beads with diameter of 100 nm.

[0149] Stokes’ law can be used to determine the transverse drag force acting on a cell, neglecting wall effects at low Reynolds numbers, according to formula (II):

[0150] Where r [m] is the cell radius (10 pm), q [Pa*s] is the dynamic viscosity of the medium (0.001 Pa*s), and v [m / s] is the velocity of the cell.

[0151] The perimeter of the capture regions is defined around the X structures by the most significant decrease in the magnitude of the flow velocity. The flow velocity at the edge these areas are used to calculate a maximum threshold for the drag force required to capture a cell. The simulated flow rate was set at 2 mL h“l .EXAMPLE 8

[0152] Analysis of IFNy secreted by different proportions of CD4+ T cells (100%, 75%, 50%, 25%, 0%) in a mixture with B cells using the microfluidic-based cell secretion assay.

[0153] A mixture of CD4+ T cells (IxlO6) and B cells (IxlO6) was prepared according to the previous ratios and was incubated with a mixture of 5 pL of 400 pg mL1streptavidin-labeled CD4 antibody and 5 pL of 400 pg mL1streptavidin-labeled CD45 antibody. The suspension was gently shaken for 45 min at room temperature. After washing, the cells were incubated with 5 pL of 500 pg mL1biotin-labeled IFNy antibody (Cat.# 554550, BD Biosciences, RRID:AB_395472) and the suspension was gently shaken for 30 min at room temperature. After washing, the cells were incubated with 2 pL of cell activation cocktail (without Brefeldin A) (Cat.# 423302, Biolegend), for 4 hours at 37°C. After washing, the cells were incubated with 5 pL of 500 pg mL1biotin-labeled IFNy antibody, and the suspension was gently shaken for 45 min at room temperature. After washing, the cells were incubated with 5 pL of biotin specific antibody conjugated with magnetic nanoparticles (Cat.# 130-105-637, Miltenyi Biotec, RRID:AB_2811216), and the suspension was gently shaken for 45 min at room temperature. The cells were then loaded into the SECRE-chip at a flow rate of 2 mL h using a syringe pump (Chemyx). The sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. (FIG. 37).

[0154] CD4+ T cells were transduced with the first set of sgRNAs targeting the top hits in the screen. The sgRNAs sequences were retrieved from TKV03 (Cat.# 125517, Addgene), which is different from the library used for the CRISPR screen. The first set of guide sequences include: LRRK2 (AGGCTGAACAATGTCCAGGA) (Cat.#34208, Addgene), SLK (ATTATAGGAGAACTGGGCGA) (Cat.#56779, Addgene), STK10 (TAGACAGGCGCAGGATGCGG) (Cat.#59027, Addgene), and STK24 (GCCACTCTACCTCATCCTGG) (Cat.#59055, Addgene).

[0155] Briefly, 2xl07cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein (Cat.# CAS9GFPPRO, Sigma-Aldrich) for editing. The electroporation was carried out with Neon Transfection System (Cat.# MPK5000, Thermo Fisher Scientific) using a 100 pL kit under the following conditions: pulse voltage: 2100 V; pulse width: 20; pulse number: 1; cell density: 2xl07cells mL Cas9 concentration: 100 pg mL1. Electroporated cells were selected by incubation with 2 pg mL1puromycin for 72 hours. CD4+ T cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator (Cat.# 10990, Stem Cell Technologies) using 6.25 pL mL1of culture medium at 2 * 106cells mL1. One hour after restimulation, Golgi Plug protein transport inhibitor (Cat.# 555029, BD Biosciences) was added at 1 / 1000 dilution. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PFA and permeabilizedwith 0.2% Triton X-100. The cells were incubated with 5 pL of 500 pg mL1biotin-labeled IFNy antibody. (Cat.# 554550, BD Biosciences, RRID:AB_395472) for 45 min at room temperature. After washing, the cells were incubated with 2 pL of FITC-labeled biotin specific antibody (Cat.# 130-113-290, Miltenyi Biotec, RRID:AB_2733612), and the suspension was gently shaken in the dark for 45 min at room temperature. Prior to analysis, the cells were washed 3 times with 2% BSA in PBS. Finally, the samples were injected into Cytoflex flow cytometer (Beckman Coulter), and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. (FIG. 38).

[0156] CD4+ T cells were transduced with the first set of guide sequences. Briefly, 2xl07cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein (Cat.# CAS9GFPPRO, Sigma-Aldrich) for editing. The electroporation was carried out with Neon Transfection System (Cat.# MPK5000, Thermo Fisher Scientific) using a 100 pL kit under the following conditions: pulse voltage: 2100 V; pulse width: 20; pulse number: 1; cell density: 2xl07cells mL Cas9 concentration: 100 pg mL1. Electroporated cells were selected by incubation with 2 pg mL1puromycin for 72 hours.

[0157] CRSIPR-edited cells were incubated with streptavidin-labeled CD4 antibody and streptavidin-labeled CD45 antibody. The cells were subsequently incubated with a biotin- labeled antibody specific to IFNy. Cytokine secretion was stimulated using a cell activation cocktail and the cells were incubated with a biotin-labeled antibody specific to IFNy. The cells were then incubated with a biotin specific antibody modified with magnetic nanoparticles. The cells were loaded into the SECRE-chip at a flow rate of 2 mL h1. Sorted cells were collected from zone 1, zone 2, and effluent and were counted using a cell counter. IxlO6cells were used in these trials. (FIG. 39).

[0158] CD4+ T cells were transduced with the first set of guide sequences. Briefly, 2xl07cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein (Cat.# CAS9GFPPRO, Sigma-Aldrich) for editing. The electroporation was carried out with Neon Transfection System (Cat.# MPK5000, Thermo Fisher Scientific) using a 100 pL kit under the following conditions: pulse voltage: 2100 V; pulse width: 20; pulse number: 1; cell density: 2xl07cells mL Cas9 concentration: 100 pg mL1. Electroporated cells were selected by incubation with 2 pg mL1puromycin for 72 hours. ELISA analysis of IFNy was carried out after knocking out top hits using the first set of guide sequences using IFNy high-sensitivity Human ELISA kit (Cat.# ab236895, Abeam),according to the manufacturer’s protocol. A sample of IFNy was obtained after incubating IxlO6of CD4+ T cells with 2 pL of cell activation cocktail for 4 hours at 37°C, followed by centrifugation and collecting the supernatant. For ELISA measurements, 50 pL of blank control, standard recombinant IFNy concentrations in sample diluent NS in the sample diluent NS were added to the wells of the microtiter plate. In addition, 50 pL of the antibody cocktail (capture antibody and detector antibody) in the antibody diluent 4BI were added to the wells and the plate was shaken for 1 hour at room temperature. After washing with buffer PT, 100 pL of TMB solution were added to each well, and the plate was shaken in the dark for 10 min at room temperature. Finally, 100 pL of the stop solution were added to each well and the optical density was recorded at 450 nm using a spectrophotometer. (FIG. 40).

[0159] d CD4+ T cells were transduced with the second set of sgRNAs targeting the top hits in the screen. The sgRNAs sequences were retrieved from TKV03 (Cat.# 125517, Addgene), which is different from the library used for the CRISPR screen. The second set of guide sequences include: LRRK2 (AATGTGGAAGTCCTCATGAG) (Cat.#34210, Addgene), ), SLK (CATTAGCACAGCCATCCAGA) (Cat.#56780, Addgene), STK10 (GGAGCTGGAGGACTACATCG) (Cat.#59028, Addgene), and STK24 (GCCTTTGAACACCTCTCCAA) (Cat.#59056, Addgene).

[0160] Briefly, 2xl07cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein (Cat.# CAS9GFPPRO, Sigma-Aldrich) for editing. The electroporation was carried out with Neon Transfection System (Cat.# MPK5000, Thermo Fisher Scientific) using a 100 pL kit under the following conditions: pulse voltage: 2100 V; pulse width: 20; pulse number: 1; cell density: 2xl07cells mL Cas9 concentration: 100 pg mL1. Electroporated cells were selected by incubation with 2 pg mL1puromycin for 72 hours. CD4+ T cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator (Cat.# 10990, Stem Cell Technologies) using 6.25 pL mL1of culture medium at 2 * 106cells mL1. One hour after restimulation, Golgi Plug protein transport inhibitor (Cat.# 555029, BD Biosciences) was added at 1 / 1000 dilution. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PFA and permeabilized with 0.2% Triton X-100. The cells were incubated with 5 pL of 500 pg mL1biotin-labeled IFNy antibody. (Cat.# 554550, BD Biosciences, RRID:AB_395472) for 45 min at room temperature. After washing, the cells were incubated with 2 pL of FITC-labeled biotin specific antibody (Cat.# 130-113-290, Miltenyi Biotec, RRID:AB_2733612), and the suspension was gently shaken in the dark for 45 min at room temperature. Prior to analysis,the cells were washed 3 times with 2% BSA in PBS. Finally, the samples were injected into Cytoflex flow cytometer (Beckman Coulter), and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. (FIG. 41).

[0161] CD4+ T cells were transduced with the second set of guide sequences. Briefly, 2xl07cells were infected with the lentiviral library for 24 hours, followed by electroporation to deliver Cas9-GFP protein (Cat.# CAS9GFPPRO, Sigma-Aldrich) for editing. The electroporation was carried out with Neon Transfection System (Cat.# MPK5000, Thermo Fisher Scientific) using a 100 pL kit under the following conditions: pulse voltage: 2100 V; pulse width: 20; pulse number: 1; cell density: 2xl07cells mL Cas9 concentration: 100 pg mL1. Electroporated cells were selected by incubation with 2 pg mL1puromycin for 72 hours. ELISA analysis of IFNy was carried out after knocking out top hits using the second set of guide sequences using IFNy high-sensitivity Human ELISA kit (Cat.# ab236895, Abeam), according to the manufacturer’s protocol. A sample of IFNy was obtained after incubating IxlO6of CD4+ T cells with 2 pL of cell activation cocktail for 4 hours at 37°C, followed by centrifugation and collecting the supernatant. For ELISA measurements, 50 pL of blank control, standard recombinant IFNy concentrations in sample diluent NS in the sample diluent NS were added to the wells of the microtiter plate. In addition, 50 pL of the antibody cocktail (capture antibody and detector antibody) in the antibody diluent 4BI were added to the wells and the plate was shaken for 1 hour at room temperature. After washing with buffer PT, 100 pL of TMB solution were added to each well, and the plate was shaken in the dark for 10 min at room temperature. Finally, 100 pL of the stop solution were added to each well and the optical density was recorded at 450 nm using a spectrophotometer. (FIG. 42).

[0162] Analysis of IFNy secreted by different proportions of CD4+ T cells (100%, 75%, 50%, 25%, 0%) in a mixture with B cells was carried out using intracellular cytokine staining (ACS).

[0163] A mixture of CD4+ T cells (IxlO6) and B cells (IxlO6) was prepared according to the previous ratios. The cells were stimulated with ImmunoCult Human CD3 / CD28 / CD2 Cell Activator (Cat.# 10990, Stem Cell Technologies) using 6.25 pL mL1of culture medium at 2 x 106cells mL1. One hour after restimulation, Golgi Plug protein transport inhibitor (Cat.# 555029, BD Biosciences) was added at 1 / 1000 dilution. Nine hours after the addition of the inhibitor, CD4+ T cells were fixed with 4% PF A and permeabilized with 0.2% Triton X-100. The cells were incubated with 5 pL of 500 pg mL1biotin-labeled IFNy antibody. (Cat.#554550, BD Biosciences, RRID:AB_395472) for 45 min at room temperature. After washing, the cells were incubated with 2 pL of FITC-labeled biotin specific antibody (Cat.# 130-113- 290, Miltenyi Biotec, RRID:AB_2733612), and the suspension was gently shaken in the dark for 45 min at room temperature. Prior to analysis, the cells were washed 3 times with 2% BSA in PBS. Finally, the samples were injected into Cytoflex flow cytometer (Beckman Coulter), and the measurements were plotted as histograms. Absorbance values were normalized to unstained control. (FIG. 43).

[0164] Analysis of sgRNA / gene enrichment was carried out using several bioinformatics tools. The correlation between DrugZ and MAGeCK was determined. The NormZ score calculated for DrugZ and the log fold change calculated for MAFeCK were highly correlated. The number of significant genes determined using 5 different bioinformatic tools, including DrugZ, MAFeCK, edgeR, STARS, and RIGER, was calculated. (FIG. 44).LIST OF CITED REFERENCES1. Satija, R. & Shalek, A.K. Heterogeneity in immune responses: from populations to single cells. Trends Immunol 35, 219-229 (2014).2. Shalek, A.K. et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 510, 363-369 (2014).3. Ma, C. et al. A clinical microchip for evaluation of single immune cells reveals high functional heterogeneity in phenotypically similar T cells. Nat Med 17, 738-743 (2011).4. Behar, M., Barken, D., Werner, S.L. & Hoffmann, A. The dynamics of signaling as a pharmacological target. Cell 155, 448-461 (2013).5. Li, Y. et al. Microfluidics Cell Loading-Dock System: Ordered Cellular Array for Dynamic Lymphocyte-Communication Study. Adv Biosyst 1, el700085 (2017).6. Xue, Q. et al. Analysis of single-cell cytokine secretion reveals a role for paracrine signaling in coordinating macrophage responses to TLR4 stimulation. Set Signal 8, ra59 (2015).7. Lovelace, P. & Maecker, H.T. Multiparameter intracellular cytokine staining. Methods Mol Biol 699, 165-178 (2011).8. Czerkinsky, C.C., Nilsson, L.A., Nygren, H., Ouchterlony, O. & Tarkowski, A. A solid-phase enzyme-linked immunospot (ELISPOT) assay for enumeration of specific antibody-secreting cells. J Immunol Methods 65, 109-121 (1983).9. Ahlborg, N. & Axelsson, B. Dual- and triple-color fluorospot. Methods Mol Biol 792, 77-85 (2012).10. Norman, M. et al. Ultrasensitive high-resolution profiling of early seroconversion in patients with CO VID-19. Nat Biomed Eng 4, 1180-1187 (2020).11. Rissin, D.M. et al. Single-molecule enzyme-linked immunosorbent assay detects serum proteins at subfemtomolar concentrations. Nat Biotechnol 28, 595-599 (2010).12. Love, J.C., Ronan, J.L., Grotenbreg, G.M., van der Veen, A.G. & Ploegh, H.L. A microengraving method for rapid selection of single cells producing antigen-specific antibodies. Nat Biotechnol 24, 703-707 (2006).13. Jin, A. et al. A rapid and efficient single-cell manipulation method for screening antigen-specific antibody-secreting cells from human peripheral blood. Nat Med 15, 1088- 1092 (2009).14. Zhou, Y. et al. Evaluation of Single-Cell Cytokine Secretion and Cell-Cell Interactions with aHierarchical Loading Microwell Chip. Cell Rep 31, 107574 (2020).15. Lu, Y. et al. Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands. Proc Natl Acad Sci USA 112, E607-615 (2015).16. Chen, Z. et al. Multiplexed, Sequential Secretion Analysis of the Same Single Cells Reveals Distinct Effector Response Dynamics Dependent on the Initial Basal State. Adv Sci (Weinh) 6, 1801361 (2019).17. Turcanu, V. & Williams, N.A. Cell identification and isolation on the basis of cytokine secretion: a novel tool for investigating immune responses. Nat Med 7, 373-376 (2001).18. Eyer, K. et al. Single-cell deep phenotyping of IgG-secreting cells for high-resolution immune monitoring. Nat Biotechnol 35, 977-982 (2017).19. Mazutis, L. et al. Single-cell analysis and sorting using droplet-based microfluidics. Nat Protoc 8, 870-891 (2013).20. Lee, S., de Rutte, J., Dimatteo, R., Koo, D. & Di Carlo, D. Scalable Fabrication and Use of 3D Structured Microparticles Spatially Functionalized with Biomolecules. ACS Nano (2021).21. Segaliny, A.I. et al. Functional TCR T cell screening using single-cell droplet microfluidics. Lab Chip 18, 3733-3749 (2018).22. Binek, A. et al. Flow Cytometry Has a Significant Impact on the Cellular Metabolome. JProteome Res 18, 169-181 (2019).23. Torres, A.J., Hill, A.S. & Love, J.C. Nanowell-based immunoassays for measuring single-cell secretion: characterization of transport and surface binding. Anal Chem 86, 11562- 11569 (2014).24. Chiou, P.Y., Ohta, A.T. & Wu, M.C. Massively parallel manipulation of single cells and microparticles using optical images. Nature 436, 370-372 (2005).25. Le, K. et al. A novel mammalian cell line development platform utilizing nanofluidics and optoelectro positioning technology. Biotechnol Prog 34, 1438-1446 (2018).26. Fu, Z. et al. Highly Selective Cleavage of Cytokines and Chemokines by the Human Mast Cell Chymase and Neutrophil Cathepsin G. J Immunol 198, 1474-1483 (2017).27. Zhao, W. et al. Cell-surface sensors for real-time probing of cellular environments. Nat Nanotechnol 6, 524-531 (2011).28. Manz, R., Assenmacher, M., Pfltiger, E., Miltenyi, S. & Radbruch, A. Analysis and sorting of live cells according to secreted molecules, relocated to a cell-surface affinity matrix. Proc Natl Acad Sci USA 92, 1921-1925 (1995).29. Kida, A. et al. Cell surface-fluorescence immunosorbent assay for real-time detection of hybridomas with efficient antibody secretion at the single-cell level. Anal Chem 85, 1753- 1759 (2013).30. Brosterhus, H. et al. Enrichment and detection of live antigen-specific CD4(+) and CD8(+) T cells based on cytokine secretion. Eur J Immunol 29, 4053-4059 (1999).31. Armbrecht, L. et al. Quantification of Protein Secretion from Circulating Tumor Cells in Microfluidic Chambers. Adv Sci (Weinh) 7 , 1903237 (2020).32. van Neel, T.L., Berry, S.B., Berthier, E. & Theberge, A.B. Localized Cell-Surface Sampling of a Secreted Factor Using Cell-Targeting Beads. Anal Chem 92, 13634-13640 (2020).33. Ferguson, F.M. & Gray, N.S. Kinase inhibitors: the road ahead. Nat Rev Drug Discov 17, 353-377 (2018).34. Poudineh, M. et al. Tracking the dynamics of circulating tumour cell phenotypes using nanoparticle-mediated magnetic ranking. Nat Nanotechnol 12, 274-281 (2017).35. Labib, M. et al. Tracking the expression of therapeutic protein targets in rare cells by antibody-mediated nanoparticle labelling and magnetic sorting. Nat Biomed Eng 5, 41-52 (2021).36. Labib, M. et al. Single-cell mRNA cytometry via sequence-specific nanoparticle clustering and trapping. Nat Chem 10, 489-495 (2018).37. Barrat, F.J., Crow, M.K. & Ivashkiv, L.B. Interferon target-gene expression and epigenomic signatures in health and disease. Nat Immunol 20, 1574-1583 (2019).38. Langer, V. et al. IFN-y drives inflammatory bowel disease pathogenesis through VE- cadherin-directed vascular barrier disruption. J Clin Invest 129, 4691-4707 (2019).39. Takashima, S. et al. T cell-derived interferon-y programs stem cell death in immune- mediated intestinal damage. Sci Immunol 4 (2019).40. Han, Q. et al. Polyfunctional responses by human T cells result from sequential release of cytokines. Proc Natl Acad Sci USA 109, 1607-1612 (2012).41. Imam, T., Park, S., Kaplan, M.H. & Olson, M.R. Effector T Helper Cell Subsets in Inflammatory Bowel Diseases. Front Immunol 9, 1212 (2018).42. Neurath, M.F. Cytokines in inflammatory bowel disease. Nat Rev Immunol 14, 329- 342 (2014).43. Haep, L. et al. Interferon Gamma Counteracts the Angiogenic Switch and Induces Vascular Permeability in Dextran Sulfate Sodium Colitis in Mice. Inflamm Bowel Dis 21, 2360-2371 (2015).44. Gardet, A. et al. LRRK2 is involved in the IFN-gamma response and host response to pathogens. J Immunol 185, 5577-5585 (2010).45. Wang, F. et al. Interferon-gamma and tumor necrosis factor-alpha synergize to induce intestinal epithelial barrier dysfunction by up-regulating myosin light chain kinase expression. Am J Pathol 166, 409-419 (2005).46. Colic, M. et al. Identifying chemogenetic interactions from CRISPR screens with drugZ. Genome Med 11, 52 (2019).47. Mair, B. et al. High-throughput genome-wide phenotypic screening via immunomagnetic cell sorting. Nat Biomed Eng 3, 796-805 (2019).48. Fan, F. et al. Pharmacological targeting of kinases MST1 and MST2 augments tissue repair and regeneration. Sci TranslMed 8, 352ral08 (2016).49. Elkins, J.M. et al. Comprehensive characterization of the Published Kinase Inhibitor Set. Nat Biotechnol 34, 95-103 (2016).50. Asshoff, M. et al. Momelotinib inhibits ACVR1 / ALK2, decreases hepcidin production, and ameliorates anemia of chronic disease in rodents. Blood 129, 1823-1830 (2017).51. Rix, U. et al. A comprehensive target selectivity survey of the BCR-ABL kinase inhibitor INNO-406 by kinase profiling and chemical proteomics in chronic myeloid leukemia cells. Leukemia 24, 44-50 (2010).52. Yamamoto, N., Honma, M. & Suzuki, H. Off-target serine / threonine kinase 10 inhibition by erlotinib enhances lymphocytic activity leading to severe skin disorders. Mol Pharmacol 80, 466-475 (2011).53. Egger, B. et al. Characterisation of acute murine dextran sodium sulphate colitis: cytokine profile and dose dependency. Digestion 62, 240-248 (2000).54. Mashimo, H., Wu, D.C., Podolsky, D.K. & Fishman, M.C. Impaired defense of intestinal mucosa in mice lacking intestinal trefoil factor. Science 274, 262-265 (1996).55. Ito, R. et al. Interferon-gamma is causatively involved in experimental inflammatory bowel disease in mice. Clin Exp Immunol 146, 330-338 (2006).56. Chiba, H., Kojima, T., Osanai, M. & Sawada, N. The significance of interferon- gamma-triggered internalization of tight-j unction proteins in inflammatory bowel disease. Sci STKE 2006, pel (2006).57. Biton, M. et al. T Helper Cell Cytokines Modulate Intestinal Stem Cell Renewal and Differentiation. Cell 175, 1307-1320.el322 (2018).58. Parnas, O. et al. A Genome-wide CRISPR Screen in Primary Immune Cells to Dissect Regulatory Networks. Cell 162, 675-686 (2015).59. Dong, M.B. et al. Systematic Immunotherapy Target Discovery Using Genome-Scale In Vivo CRISPR Screens in CD8 T Cells. Cell 178, 1189-1204.el 123 (2019).60. Henriksson, J. et al. Genome-wide CRISPR Screens in T Helper Cells Reveal Pervasive Crosstalk between Activation and Differentiation. Cell 176, 882-896. e818 (2019).61. Schmidt, R. et al. CRISPR activation and interference screens decode stimulation responses in primary human T cells. Science 375, eabj4008 (2022).* * *

[0165] Although the foregoing refers to particular preferred embodiments, it will be understood that the present invention is not so limited. It will occur to those of ordinary skill in the art that various modifications may be made to the disclosed embodiments and that such modifications are intended to be within the scope of the present invention.

[0166] All of the publications, patent applications and patents cited in this specification are incorporated herein by reference in their entirety.

Claims

WHAT IS CLAIMED IS:

1. A method for the high throughput screening of cells secreting a target protein comprising obtaining cells for screening, labelling at least one cell surface marker of the cells with a first label that binds to the cell surface marker and a second label specific for the target protein, wherein the second label binds the first label, allowing the cells to secrete the target protein, wherein the secreted target protein attaches to the second label, conjugating the secreted target protein bound to the second label with a magnetic nanoparticle-bound label, and sorting the labeled cells in a microfluidic device based on the target protein secretion levels on the cell surface of the cells, wherein the microfluidic device detects the magnetic nanoparticle-bound label.

2. The method of claim 1, wherein more than one cell surface markers is labeled.

3. The method of claim 1, wherein the first label is selected from the group consisting of antibodies specific for the at least one cell surface marker.

4. The method of claim 3, wherein the antibodies are labeled with streptavidin, His, HA, Myc, or GFP.

5. The method of claim 1, wherein the cell surface marker is selected from the group consisting of CD4, CD45, CD3, CD8, CD56, and CD25.

6. The method of claim 1, wherein the sorting comprises passing the labeled cells on an affinity matrix comprising a plurality of capture zones with differing linear velocities to capture cells with varying levels of secreted target protein.

7. The method of claim 6, further comprising isolating the cells from the plurality of capture zones.

8. The method of claim 1, wherein the cells are modified to produce a targeted protein for secretion.

9. The method of claim 8, wherein the cells are edited using a CRISPR gene editing system.

10. The method of claim 9, wherein the CRISPR gene editing system is a CRISPR-CAS system.

11. The method of claim 9, wherein the CRISPR-CAS gene editing is a genome-wide CRISPR-Cas9 knockout screen.

12. The method of claim 10, wherein the CRISPR-CAS gene editing comprises a CRISPR activation screen, a CRISPR interference screen, and / or CRISPR loss-of-function screen.

13. The method of claim 1, wherein targeted protein is a cytokine, antibody, enzyme, or hormone.

14. The method of claim 13, wherein the targeted protein is a cytokine.

15. The method of claim 7, wherein the isolated cells may be further expanded.

16. The method of claim 1, wherein the cells are isolated directly from a patient.

17. The method of claim 16, wherein the cells are selected from the group consisting of B cells, plasma cells, T cells, NK cells, macrophages, monocytes, neutrophils, mast cells, fibroblasts, keratinocytes, epithelial cells, adipocytes, and bone cells.

18. The method of claim 1, wherein the cells are T cells.

19. The method of claim 18, wherein the T cells are modified using CRISPR.

20. The method of claim 19, wherein the T cells are modified using a genome-wideCRISPR-Cas9 knockout screen to identify a cell having a desired secretion profile for the target protein.

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