Single-cell Phenotyping Research Articles

Single-Cell RNA Sequencing Suggests Novel Drivers of Chronic Lymphocytic Leukemia Patients with Ibrutinib Resistance

Objective:Ibrutinib is currently the most widely used BTK inhibitor that approved for the treatment of both initially diagnosed and relapsed and refractory chronic lymphocytic leukemia (CLL) patients. Although ibrutinib shows high response rates in clinical practice, it has certain limitations. There are still a certain number of patients who have to discontinue treatment due to drug-resistance or side effects. The ibrutinib resistance of CLL patients has caused widespread concerns, necessitating the development of novel treatment strategies.Methods:Here, we examined the heterogeneity of peripheral blood mononuclear cells (PBMCs) from patients with ibrutinib-sensitive (IBS) and -resistant (IBR) CLL by analyzing bulk and single-cell level gene expression profiles, clinical features, biological properties, and phenotypes. Seven distinct ibrutinib-resistant subpopulations were identified and two candidate genes LGALS1 (galectin 1, Gal-1) and LAG3 (lymphocyte-activating gene 3, CD223) were screened that contribute toward ibrutinib-resistance and poor survival in CLL patients. These results were validated in primary cells from CLL patients and also in ibrutinib-resistant CLL cell line (MEC1-IR) which was generated by culturing the parental cell line in vitro with progressively increasing concentrations of ibrutinib. Marker-gene expression was detected using qRT-PCR, western blotting, and ELISA, while functional analyses including CCK8, flow cytometry and trypan blue staining were conducted with or without OTX008, a selective Gal-1 inhibitor.Results:ScRNA-seq revealed that cells from IBR and IBS samples were distributed in different clusters and suggested that IBR cells display a unique transcriptional pattern (Fig A). IBR-B cells have higher stemness scores and are enriched in some energy metabolismPathways (Fig B). According to the proportion of B cells from IBR samples, we classified each B-cell cluster into three main subgroups, i.e., IBR, IBS, and shared cluster (Fig C). IBR-B cells displayed more interactions with monocytes, NK, T, and dendritic cells than IBS B cells, suggesting that IBR B cells may actively build connections with other immune cells to reshape the protective niche (Fig D). A close correlation between LGALS1 and LAG3 expression was observed and both of them were found to be highly expressed in IBR CLL patients (Fig E), their expression level gradually increased along the trajectory of B cells from IBS to IBR (Fig F). Diagnosis and prognosis stratification of CLL with receiver operating characteristic (ROC) curves revealed that patients with higher expression of both LGALS1 and LAG3 showed the poorest overall survival, indicating that LGALS1 and LAG3 are associated with ibrutinib-resistance and poor prognosis in CLL (Fig G). Concordantly, acquired resistance following chronic exposure to ibrutinib leads to upregulation of LGALS1 and LAG3 (Fig H). LGALS1 inhibitor OTX008 effectively inhibits the growth of ibrutinib-resistant CLL cells, particularly for IBR patients (Fig I).Conclusion:In conclusion, our findings demonstrate that ibrutinib-resistant CLL cells exhibit a unique transcriptional pattern. The combination of LGALS1 and LAG3 expression could serve as an indicator of the sensitivity of ibrutinib and prognosis of CLL patients. LGALS1 inhibitor OTX008 helps to overcome ibrutinib-resistance of CLL cells. Our findings may expand the current knowledge regarding ibrutinib-resistant CLL patients, identify improved biomarkers for patient selection, and offer a promising combinatorial therapeutic strategy for IBR CLL patients. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Peripheral Blood Single-Cell Genotyping and Phenotyping in Multiple Myeloma Reveals Shared Mutations across Multiple Hematopoietic Cell Lineages

Background:Multiple myeloma (MM) is a hematologic malignancy of terminally differentiated plasma cells. While most genomic studies of the disease have focused on characterizing isolated bone marrow plasma cells, few have addressed somatic mutations within the immune microenvironment. We previously demonstrated that somatic mutations are significantly more numerous in unsorted blood compared to bone marrow and that the number of mutations correlated with elevated markers of disease. We also reported that genes implicated in clonal hematopoiesis of indeterminate potential (CHIP) are commonly mutated in the blood from patients with MM.Aim:To integrate single-cell DNA mutation analysis and protein expression to map the clonal relationship between circulating plasma cells and non-plasma cells within the peripheral blood of patients with MM.Methods:Although bulk DNA sequencing can estimate clonal heterogeneity using analytic deconvolution techniques, it is unable to distinguish which mutations occur in the same clone(s) nor can it correlate genotype with immunophenotype from the same cell. To accurately describe the clonal architecture of the blood, we combined targeted single-cell DNA sequencing (scDNA-seq) coupled with protein expression to define mutations specific to cell phenotypes using the Tapestri Platform (Mission Bio). For this analysis, we developed a custom amplicon panel covering 22 frequently mutated genes in MM and/or CHIP to perform scDNA-seq and 4 antibodies targeting CD138, CD19, CD3, and CD33 for immunophenotyping or plasma cells, B cells, T cells, and myeloid cells respectively.Results:Peripheral blood mononuclear cells were isolated from 17 blood samples collected from 12 patients with MM. Three samples were collected at diagnosis before treatment, 8 were collected post-treatment during remission, and 6 were collected at relapse. Serial samples were obtained before and after autologous stem cell transplant from 4 patients. A total of 85,262 cells were sequenced uncovering 154 unique variants in 22 genes after quality filtering. There were 47 somatic variants, defined as those present in less than 40% of cells per sample. There were 52,136 total clones, defined as cells with identical genotypes, within this heterogenous population of cells. The most common non-synonymous somatic mutations were identified in genes SETD2, KMT2C, PPM1D. An immunophenotype was assigned to 82% of cells according to the protein with the most abundant number of reads. Dimensionality reduction of single-cell genotype using t-distributed stochastic neighbor embedding (t-SNE) effectively clustered cells according to sample and by patient in cases where there were multiple samples from the same individual. Patients with active myeloma and known circulating plasma cells detected by clinical flow cytometry were found to have the greatest proportion of CD138+ cells as well as the highest mutational burden. It was rare to detect the same clone in two separate samples collected from the same patient at different time points (median time be collection was 248 days) which may be due to under-sampling or clonal evolution. Surprisingly, all somatic variants detected in plasma cells, were also present in other cell types suggesting they were acquired from a common progenitor cell rather than after differentiation.Conclusions:scDNA-seq coupled with immunophenotyping of the peripheral blood of patients with MM reveals somatic variants are shared across multiple hematopoietic cell lineages including plasma cells indicating these mutational are acquired from a common progenitor. DisclosuresDurruthy-Durruthy: Mission Bio Inc.: Current Employment. Arribas-Layton: Mission Bio, Inc.: Current Employment. Wang: Mission Bio, Inc: Current Employment.

CD22 low/Bcl-2 high Expression Identifies Poor Response to Inotuzumab in Relapsed/ Refractory Acute Lymphoblastic Leukemia

Introduction: Despite outstanding cure rates for newly diagnosed patients with acute lymphoblastic leukemia (ALL), outcomes for pediatric patients with relapsed or refractory (R/R) disease remain unsatisfactory. Inotuzumab ozogamicin (InO), a CD22-directed antibody-drug conjugate, has shown remarkable activity; however, predictors of response to InO beyond CD22 expression and site density have not yet been reported.Methods: In order to identify better predictors of response to InO, we analyzed 68 samples from 28 patients with multiply R/R ALL enrolled in Children's Oncology Group trial AALL1621 (NCT02981628). Samples were collected before and after treatment with InO. We performed a B-ALL-centric protein profiling approach for which we designed a custom CyTOF panel, encompassing 35 rationally selected proteins (antigens) as potential predictors of InO treatment. Those proteins included surface markers (such as CD10/19/20/22 expressed in B cells and CD3/CD14, CD33 expressed in non B cells), intracellular signaling pathways (such as MAPK, PI3K, JAK/STATs), survival pathways (such as BCL-2 family members) and pathways reported to be involved in resistance to various treatments (such as p53/pCHK1 pathway, ABC drug efflux transporters, and NF-kB). This approach allowed measurement of protein levels of all those antigens. We then designed a high-dimensional tumor cell-community clustering algorithm providing dimensionality reduction to determine the extent of antigen expression across all patients at diagnosis and end of cycle 1 and cycle 2 of treatment.Results: high-dimensional clustering analysis depicted distinct tumor profiles between complete responder and partial responder patient groups (Figure 1). While this clustering measured many antigens, those that contributed the most to identification of the groups were Bcl-xl, Bcl-2, p21, CD22, Mcl1, pCHK1 and pGP whereas those contributing the least were BAD, BIM, p4EBP1 and p53. Our analyses identified the presence of CD22 high cells and CD22 low/Bcl-2 high cells as predictors of good and poor response, respectively. Furthermore, analysis of residual leukemia cells at the end of cycle 1 or 2 showed persistent high expression of Bcl-2 family members.Conclusions: We have shown for the first time that a novel strategy for multidimensional single cell phenotyping of lymphoblasts can reliably identify a predictive dual-marker signature with CD22 high expression predicting good response to InO versus CD22 low/Bcl-2 high expression predicting poor response. This approach also identifies dynamic changes of tumor composition following InO treatment. These data provide new insights into predictors of response to InO and suggest that Bcl-2 inhibition may have the potential for synergistic clinical efficacy, allowing for a potential patient-stratified approach for InO combinatorial treatments. Given that this experimental approach can be readily done in any laboratory equipped with flow or mass cytometry, we expect that our findings may be further replicated and validated in other studies using InO.AcknowledgementsThis work was supported by U10CA180886 and U10CA180899, the St. Baldrick's Foundation (MLL), a Pfizer ASPIRE award (MLL, EDF, AW, MO, SZ, AT), the German Cancer Aid (AW) and Uehara Memorial Foundation (KI). MLL is the Benioff Chair of Children's Health and the Deborah and Arthur Ablin Chair of Pediatric Molecular Oncology. [Display omitted] DisclosuresWood: Juno, Pfizer, Amgen, Seattle Genetics: Other: Laboratory Services Agreement; Pfizer, Amgen, Seattle Genetics: Honoraria. O'Brien: Jazz: Honoraria; Pfizer: Honoraria, Research Funding. Loh: MediSix therapeutics: Membership on an entity's Board of Directors or advisory committees.

Survival Genie: A Web Portal for Single-Cell Data, Gene-Ratio, and Cell Composition-Based Survival Analyses

The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. Many packages and tools have been developed to correlate single-gene features to clinical outcomes, but lack in performing such analysis based on multiple-genes, gene sets, and genes ratio. Furthermore, cluster marker genes associated with cell types, states and function from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates associations between the enrichment of known cell types and survival outcome across cancers.We have developed Survival Genie (https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/, a web tool to perform survival analysis on single-cell RNA-seq data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden (Fig. 1). For comprehensive survival evaluation, the Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs for both adult and pediatric cancers including different types of leukemia. Users can upload single-cell data or gene sets and select partitioning methods (i.e., mean, median, quartile, cutp) to determine the effect of their levels on patient survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile (Fig. 1). The Survival Genie source code is written in the R programming language and the interactive web application with the R Shiny framework.We demonstrate the application of the Survival Genie tool by exploring the prognostic utility of blast cell and immune cell markers generated from single cell RNA-seq analysis of paired pediatric AML bone marrow samples taken at the time of diagnosis and end of induction (Thomas, Perumalla et al. 2020) . We identified AML blast specific signature consisting of 7 genes (CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH) that depicted significant association with poor survival (HR=2.3 and Log Rank P-value=.007). Further analysis of AML relapse-associated single cell clusters showed increased levels of individual markers, including CRIP1, FLNA, and RFLNB/FAM101B and their significant association with poor survival in TARGET AML dataset. Additionally, expression of combined RFLNB/FAM101B and WDFY4 genes was associated with poor overall survival (HR=1.8 Log Rank P-value=0.01) and shorter event-free survival (HR=1.9, Log Rank P-value<0.0001). This clearly shows the usefulness of Survival Genie tool in exploring the prognostic association of genes as well as gene sets.Survival Genie is a one-stop web-portal for single-cell phenotype clusters, list of genes, and cell composition-based survival analyses across multiple cancer datasets including hematological malignancies. The analytical options and harmonized collection of multiple cancer types makes Survival Genie a comprehensive resource to correlate gene sets, pathways, cellular enrichment, and single cell clusters to clinical outcome to assist in developing next generation prognostic and therapeutic biomarkers. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Evaluating sources of technical variability in the mechano-node-pore sensing pipeline and their effect on the reproducibility of single-cell mechanical phenotyping.

Cellular mechanical properties can reveal physiologically relevant characteristics in many cell types, and several groups have developed microfluidics-based platforms to perform high-throughput single-cell mechanical testing. However, prior work has performed only limited characterization of these platforms’ technical variability and reproducibility. Here, we evaluate the repeatability performance of mechano-node-pore sensing, a single-cell mechanical phenotyping platform developed by our research group. We measured the degree to which device-to-device variability and semi-manual data processing affected this platform’s measurements of single-cell mechanical properties. We demonstrated high repeatability across the entire technology pipeline even for novice users. We then compared results from identical mechano-node-pore sensing experiments performed by researchers in two different laboratories with different analytical instruments, demonstrating that the mechanical testing results from these two locations are in agreement. Our findings quantify the expectation of technical variability in mechano-node-pore sensing even in minimally experienced hands. Most importantly, we find that the repeatability performance we measured is fully sufficient for interpreting biologically relevant single-cell mechanical measurements with high confidence.

Blebbistatin protects iPSC-CMs from hypercontraction and facilitates automated patch-clamp based electrophysiological study

Recently, there have been great advances in cardiovascular channelopathy modeling and drug safety pharmacology using human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). The automated patch-clamp (APC) technique overcomes the disadvantages of the manual patch-clamp (MPC) technique, which is labor intensive and gives low output. However, the application of the APC platform is still limited in iPSC-CM based research, due to the difficulty in maintaining the high quality of single iPSC-CMs during dissociation and recording. In this study, we improved the method for single iPSC-CM preparation by applying 2.5 µM blebbistatin (BB, an excitation–contraction coupling uncoupler) throughout APC procedures (dissociation, filtration, storage, and recording). Under non-BB buffered condition, iPSC-CMs in suspension showed a severe bleb-like morphology. However, BB-supplement led to significant improvements in morphology and INa recording, and we even obtained several CMs that showed spontaneous action potentials with typical morphology. Furthermore, APC faithfully recapitulated the single-cell electrophysiological phenotypes of iPSC-CMs derived from Brugada syndrome patients, as detected with MPC. Our study indicates that APC is capable of replacing MPC in the modeling of cardiac channelopathies using human iPSC-CMs by providing high-quality data with higher throughput.

Flow cytometry method for absolute counting and single-cell phenotyping of mycobacteria

Detection and accurate quantitation of viable Mycobacterium tuberculosis is fundamental to understanding mycobacterial pathogenicity, tuberculosis (TB) disease progression and outcomes; TB transmission; drug action, efficacy and drug resistance. Despite this importance, methods for determining numbers of viable bacilli are limited in accuracy and precision owing to inherent characteristics of mycobacterial cell biology—including the tendency to clump, and “differential” culturability—and technical challenges consequent on handling an infectious pathogen under biosafe conditions. We developed an absolute counting method for mycobacteria in liquid cultures using a bench-top flow cytometer, and the low-cost fluorescent dyes Calcein-AM (CA) and SYBR-gold (SG). During exponential growth CA + cell counts are highly correlated with CFU counts and can be used as a real-time alternative to simplify the accurate standardisation of inocula for experiments. In contrast to CFU counting, this method can detect and enumerate cell aggregates in samples, which we show are a potential source of variance and bias when using established methods. We show that CFUs comprise a sub-population of intact, metabolically active mycobacterial cells in liquid cultures, with CFU-proportion varying by growth conditions. A pharmacodynamic application of the flow cytometry method, exploring kinetics of fluorescent probe defined subpopulations compared to CFU is demonstrated. Flow cytometry derived Mycobacterium bovis bacillus Calmette-Guérin (BCG) time-kill curves differ for rifampicin and kanamycin versus isoniazid and ethambutol, as do the relative dynamics of discrete morphologically-distinct subpopulations of bacilli revealed by this high-throughput single-cell technique.

Massively parallel quantification of phenotypic heterogeneity in single-cell drug responses.

Single-cell analysis tools have made substantial advances in characterizing genomic heterogeneity; however, tools for measuring phenotypic heterogeneity have lagged due to the increased difficulty of handling live biology. Here, we report a single-cell phenotyping tool capable of measuring image-based clonal properties at scales approaching 100,000 clones per experiment. These advances are achieved by exploiting a previously unidentified flow regime in ladder microfluidic networks that, under appropriate conditions, yield a mathematically perfect cell trap. Machine learning and computer vision tools are used to control the imaging hardware and analyze the cellular phenotypic parameters within these images. Using this platform, we quantified the responses of tens of thousands of single cell–derived acute myeloid leukemia (AML) clones to targeted therapy, identifying rare resistance and morphological phenotypes at frequencies down to 0.05%. This approach can be extended to higher-level cellular architectures such as cell pairs and organoids and on-chip live-cell fluorescence assays.

Abstract 127: Aspirin Resistant Biomechanical Platelet Activation In Fibromuscular Dysplasia: Novel Mechanisms Of Platelet Activation &amp; Stroke

Background: Fibromuscular dysplasia (FMD) is a non-atherosclerotic, non-inflammatory disorder characterized by abnormal arterial morphology and turbulent blood flow. In regions of disturbed blood flow, circulating platelets may become activated. Cerebrovascular FMD is common and increases the risk of stroke in affected patients. Most FMD patients are treated with antiplatelet agents, however these medications target biochemical and not biomechanical pathways of platelet activation. Methods: Thrombotic outcomes were determined by multivariate regression analysis of 105,887 patients with FMD. Platelets were isolated from humans and activation was assessed by FACS and aggregometry following exposure to ex vivo steady laminar and disturbed flow (SF and DF, respectively) conditions using a cone and flow system. Single-cell phenotyping of control and FMD platelets with transcriptomics (RNAseq) and proteomics were performed. Cellular bioenergetics were evaluated by real-time metabolic analyses. Results: In patients with FMD, long-term aspirin therapy is paradoxically an independent risk factor for acute ischemic stroke (OR 1.64, 95% CI 1.29-1.94) but seems to protect against acute hemorrhagic stroke (OR 0.47, 95% CI 0.24-0.89). FMD platelet activation and aggregation were hyporeactive to biochemical agonists, but hyperreactive to ex vivo mechanical, disturbed blood flow conditions compared to age/gender-matched controls. FMD platelet activation in DF was attenuated by the mechanosensitive channel inhibitor, GsMTx4. Principle component analyses of RNAseq and proteomics identified markedly different platelet phenotypes with key differences in mitochondrial function/fission. Platelet imaging and metabolic analyses revealed abnormal mitochondrial architecture and respiration in FMD. Conclusions: FMD platelets display a divergent, dysregulated platelet phenotype with attenuated biochemical but augmented biomechanical activation. DF exposure of platelets in irregularly shaped arteries in FMD may alter the platelet phenotype and metabolic function. Therapeutics targeting biomechanical pathways of platelet activation may provide a superior mechanism for stroke prevention without unintended bleeding consequences.

Vibrio splendidus persister cells induced by host coelomic fluids show a similar phenotype to antibiotic-induced counterparts.

Persister cells are dormant variants of regular cells that are multidrug tolerant and have heterogeneous phenotypes; these cells are a potential threat to hosts because they can escape the immune system or antibiotic treatments and reconstitute infectious. Skin ulcer syndrome (SUS) frequently occurs in the sea cucumber (Apostichopus japonicus), and Vibrio splendidus is one of the main bacterial pathogens of SUS. This study found that the active cells of V. splendidus became persister cells more readily in the presence of A. japonicus coelomic fluids. We showed that the A. japonicus coelomic fluids plus antibiotics induce 100-fold more persister cells in V. splendidus compared with antibiotics alone via nine sets of experiments including assays for antibiotic resistance, metabolic activity, and single-cell phenotypes. Furthermore, the coelomic fluids-induced persister cells showed similar phenotypes as the antibiotic-induced persister cells. Further investigation showed that guanosine pentaphosphate/tetraphosphate (henceforth ppGpp) and SOS response pathway involved in the formation of persister cells as determined using real-time RT-PCR. In addition, single-cell observations showed that, similar to the antibiotic-induced V. splendidus persister cells, the coelomic fluids-induced persister cells have five resuscitation phenotypes: no growth, expansion, elongation, elongation and then division, and elongation followed by death/disappearance. In addition, dark foci formed in the majority of persister cells for both the antibiotic-induced and coelomic fluids-induced persister cells. Our results highlight that the pathogen V. splendidus might escape from the host immune system by entering the persister state during the process of infection due to exposure to coelomic fluids.

Systematic detection of m6A-modified transcripts at single-molecule and single-cell resolution

SummaryEpigenetic modifications control the stability and translation of mRNA molecules. Here, we present a microscopy-based platform for quantifying modified RNA molecules and for relating the modification patterns to single-cell phenotypes. We directly capture mRNAs from cell lysates on oligo-dT-coated coverslips, then visually detect and sequence individual m6A-immunolabled transcripts without amplification. Integration of a nanoscale device enabled us to isolate single cells on the platform, and thereby relate single-cell m6A modification states to gene expression signatures and cell surface markers. Application of the platform to MUTZ3 leukemia cells revealed a marked reduction in cellular m6A levels as CD34+ leukemic progenitors differentiate to CD14+ myeloid cells. We then coupled single-molecule m6A detection with fluorescence in situ hybridization (FISH) to relate mRNA and m6A levels of individual genes to single-cell phenotypes. This single-cell multi-modal assay suite can empower investigations of RNA modifications in rare populations and single cells.

Tissue Multiplex Analyte Detection in Anatomic Pathology - Pathways to Clinical Implementation.

Background: Multiplex tissue analysis has revolutionized our understanding of the tumor microenvironment (TME) with implications for biomarker development and diagnostic testing. Multiplex labeling is used for specific clinical situations, but there remain barriers to expanded use in anatomic pathology practice.Methods: We review immunohistochemistry (IHC) and related assays used to localize molecules in tissues, with reference to United States regulatory and practice landscapes. We review multiplex methods and strategies used in clinical diagnosis and in research, particularly in immuno-oncology. Within the framework of assay design and testing phases, we examine the suitability of multiplex immunofluorescence (mIF) for clinical diagnostic workflows, considering its advantages and challenges to implementation.Results: Multiplex labeling is poised to radically transform pathologic diagnosis because it can answer questions about tissue-level biology and single-cell phenotypes that cannot be addressed with traditional IHC biomarker panels. Widespread implementation will require improved detection chemistry, illustrated by InSituPlex technology (Ultivue, Inc., Cambridge, MA) that allows coregistration of hematoxylin and eosin (H&E) and mIF images, greater standardization and interoperability of workflow and data pipelines to facilitate consistent interpretation by pathologists, and integration of multichannel images into digital pathology whole slide imaging (WSI) systems, including interpretation aided by artificial intelligence (AI). Adoption will also be facilitated by evidence that justifies incorporation into clinical practice, an ability to navigate regulatory pathways, and adequate health care budgets and reimbursement. We expand the brightfield WSI system “pixel pathway” concept to multiplex workflows, suggesting that adoption might be accelerated by data standardization centered on cell phenotypes defined by coexpression of multiple molecules.Conclusion: Multiplex labeling has the potential to complement next generation sequencing in cancer diagnosis by allowing pathologists to visualize and understand every cell in a tissue biopsy slide. Until mIF reagents, digital pathology systems including fluorescence scanners, and data pipelines are standardized, we propose that diagnostic labs will play a crucial role in driving adoption of multiplex tissue diagnostics by using retrospective data from tissue collections as a foundation for laboratory-developed test (LDT) implementation and use in prospective trials as companion diagnostics (CDx).

Multimodal FACED imaging for large-scale single-cell morphological profiling

Free-space angular-chirp-enhanced delay (FACED) is an ultrafast laser-scanning technique that allows for high imaging speed at the scale orders of magnitude greater than the current technologies. However, this speed advantage has only been restricted to bright-field and fluorescence imaging—limiting the variety of image contents and hindering its applicability in image-based bioassay, which increasingly demands rich phenotypic readout at a large scale. Here, we present a new high-speed quantitative phase imaging (QPI) based on time-interleaved phase-gradient FACED image detection. We further integrate this system with a microfluidic flow cytometer platform that enables synchronized and co-registered single-cell QPI and fluorescence imaging at an imaging throughput of 77 000 cells/s with sub-cellular resolution. Combined with deep learning, this platform empowers comprehensive image-based profiling of single-cell biophysical phenotypes that can offer not only sufficient label-free power for cell-type classification but also cell-cycle phase tracking with high accuracy comparable to the gold-standard fluorescence method. This platform further enables correlative, compartment-specific single-cell analysis of the spatially resolved biophysical profiles at the throughput inaccessible with existing QPI methods. The high imaging throughput and content given by this multimodal FACED imaging system could open new opportunities in image-based single-cell analysis, especially systematic analysis that correlates the biophysical and biochemical information of cells, and provide new mechanistic insights into biophysical heterogeneities in many biological processes.

Extensive Immunosuppression in the Acute Myeloid Leukemia (AML) Bone Marrow and Discovery of NK Cells As Biomarker of Superior Survival

BackgroundThe immune system has been harnessed in the treatment of AML patients by eliciting the graft-versus-leukemia response after hematopoietic stem cell transplant (HSCT). Recently, several other immunotherapy modalities such as immune checkpoint inhibitors, leukemia antigen-targeted antibodies, and adoptive cell therapy have been studied with hope for less toxic and more effective alternatives to conventional chemotherapeutic regimes. Yet, little is known on the clinical significance of the pretreatment immune microenvironment. Here, we characterized the immunologic landscape of the AML bone marrow (BM) with a novel multiplex immunohistochemistry (mIHC) method to identify prognostic immune biomarkers.MethodsDiagnostic-phase BM biopsies of AML patients (n=69) treated in the Helsinki University Hospital during 2005-2017 and non-leukemic controls (n=14) were collected. Using hematopathologic expertise, tissue microarrays (TMA) were constructed from duplicate BM spots and analyzed using mIHC combining simultaneously up to six out of 25 examined lymphoid, myeloid, and immune checkpoint marker. We complemented mIHC with machine learning-based image analysis. Immune cell subsets were compared with Mann-Whitney U test, and p-values adjusted with the Benjamini-Hochberg procedure (q-values). By combining mIHC findings with extensive diagnostic-phase demographic, peripheral blood and BM aspirate laboratory test, and treatment data, we developed a risk stratification model predicting relapse-free survival (RFS) using bootstrapped L1-penalized elastic net Cox regression. We validated results with diagnostic-phase AML BM aspirates (n=84) analyzed with flow cytometry (FC) in the centralized university hospital clinical laboratory (2005-2016).ResultsUnsupervised hierarchical clustering of integrated immune profiles separated AML patients distinctly from control subjects. In AML patients, immune cell subsets and phenotypes associated with anti-cancer immunity were decreased (e.g. lower granzyme B and CD57 expression in CD3+CD4+ and CD3+CD8+ T cells), while features of immunosuppression were accentuated (e.g. higher proportion of FOXP3+ CD4+ T cells and lower expression of class I HLA-ABC in all BM cells).Higher levels of T cell exhaustion markers PD1+ in both CD4+ and CD8+ T cells (15.7% vs. 1.7% and 13.2% vs. 2.0%, q<0.001 for both), and CTLA4+ (2.0% vs. 0.9%, q=0.02) in CD4+ T cells were noted in AML BM.Lower level of CD68+/pSTAT1+cMAF- (0.033% vs. 5.9%, q<0.001) and higher CD68+/pSTAT1-cMAF+ (24.8% vs. 1.7%, q<0.001), e.g. M1 and M2-polarized macrophages, were observed in AML vs. control BM, thus shifting the M1/M2 ratio from 3.5 in control to 0.0013 in AML BM. In addition, higher amount of CD11b+CD33+HLADR-, e.g. myeloid-derived suppressor cells (MDSC), were observed in AML BM (1.0% vs. 0.038% of all cells, q<0.001).The most predictive features from the L1-penalized regression analysis were selected with multivariate Cox regression. High patient age and low amount of CD3-CD56+ (NK) cells were significantly associated with worse RFS both in univariate and multivariate setting after adjusting for induction therapy protocol (AUC 0.84 and R2 0.45, p<0.001 log-rank test). Interestingly, the model predicted also overall survival (OS) (AUC 0.86 and R2 0.38, p<0.001). The model was categorized into even-sized low, intermediate (hazard ratio (HR) 2.5, 95%CI [1.1-5.6]) and high-risk groups (HR 8.3, 95%CI [3.7-18.8]) to predict RFS (Fig 1).In the independent validation cohort, CD45+CD2+CD3- (NK) cell count was categorized into even-sized groups based on tertiles. Low and intermediate NK cell count (<0.75% and 0.75-2.0% of all cells, respectively) predicted worse RFS (HR 3.3 p=0.005 and HR 2.2 p=0.05) and OS (HR 2.6 p=0.03 and HR 2.3 p=0.05) after adjusting for induction therapy protocol and HSCT.ConclusionTissue cytometrics of TMA slides with mIHC and automated image analysis enable fast and objective single-cell phenotyping of large patient cohorts. The AML BM is characterized by myeloid and lymphoid lineage immunosuppression. Results of immune cell analyses with both mIHC and FC suggest low NK cell count as biomarker of poor RFS and OS. Other treatment response and survival endpoints remain to be analyzed and complemented with extensive flow cytometric, cytogenetic and molecular genetic data. [Display omitted] DisclosuresPorkka:Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Mustjoki:Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; BMS: Honoraria, Research Funding.

Integrin-mediated interactions with a laminin-presenting substrate modulate biosynthesis and phenotypic expression for cells of the human nucleus pulposus.

With aging and pathology, cells of the nucleus pulposus (NP) de-differentiate towards a fibroblast-like phenotype, a change that contributes to degeneration of the intervertebral disc (IVD). Laminin isoforms are a component of the NP extracellular matrix during development but largely disappear in the adult NP tissue. Exposing human adult NP cells to hydrogels made from PEGylated-laminin-111 (PEGLM) has been shown to regulate NP cell behaviors and promote cells to assume a biosynthetically active state with gene/protein expression and morphology consistent with those observed in juvenile NP cells. However, the mechanism regulating this effect has remained unknown. In the present study, the integrin subunits that promote adult degenerative NP cell interactions with laminin-111 are identified by performing integrin blocking studies along with assays of intracellular signaling and cell phenotype. The findings indicate that integrin α3 is a primary regulator of cell attachment to laminin and is associated with phosphorylation of signaling molecules downstream of integrin engagement (ERK 1/2 and GSK3β). Sustained effects of blocking integrin α3 were also demonstrated including decreased expression of phenotypic markers, reduced biosynthesis, and altered cytoskeletal organization. Furthermore, blocking both integrin α3 and additional integrin subunits elicited changes in cell clustering, but did not alter the phenotype of single cells. These findings reveal that integrin-mediated interactions through integrin α3 are critical in the process by which NP cells sense and alter phenotype in response to culture upon laminin and further suggest that targeting integrin α3 has potential for reversing or slowing degenerative changes to the NP cell.

The cellular architecture of the antimicrobial response network in human leprosy granulomas.

Granulomas are complex cellular structures composed predominantly of macrophages and lymphocytes that function to contain and kill invading pathogens. Here, we investigated the single-cell phenotypes associated with antimicrobial responses in human leprosy granulomas by applying single-cell and spatial sequencing to leprosy biopsy specimens. We focused on reversal reactions (RRs), a dynamic process whereby some patients with disseminated lepromatous leprosy (L-lep) transition toward self-limiting tuberculoid leprosy (T-lep), mounting effective antimicrobial responses. We identified a set of genes encoding proteins involved in antimicrobial responses that are differentially expressed in RR versus L-lep lesions and regulated by interferon-γ and interleukin-1β. By integrating the spatial coordinates of the key cell types and antimicrobial gene expression in RR and T-lep lesions, we constructed a map revealing the organized architecture of granulomas depicting compositional and functional layers by which macrophages, T cells, keratinocytes and fibroblasts can each contribute to the antimicrobial response.

Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations.

Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.

P002 Methodological development of single-cell phenotyping and spatial analysis of intestinal leukocyte, stromal and epithelial cell populations in inflammatory bowel disease formalin fixed paraffin embedded tissue by Hyperion imaging mass cytometry

Abstract Background Conventional cellular phenotyping of intestinal cell populations by multi-parameter fluorescence cytometry is reliant on collection of fresh tissue for immediate enzymatic or mechanical disaggregation, or cryopreservation of samples. These factors limit widescale use of tissue for research, increase cost, and time for sample collection or preparation. Due to tissue disaggregation suspension cytometry does not provide data regarding spatial localisation of cells in tissue. Formalin fixed paraffin embedded (FFPE) tissue is widely collected at endoscopy and surgery for clinical histopathological assessment, and can be stored and transported at room temperature. Methods We aimed to develop a method for analysing FFPE intestinal tissue using Imaging Mass Cytometry (IMC) in combination with an analysis pipeline for cellular phenotyping and spatial characterisation that preserved multi-parameter, high dimensional phenotyping capabilities normally only afforded by suspension methodologies. FFPE blocks were accessed following written informed consent in accordance with research and ethics committee approval. Carrier-free antibodies specific to cell subsets of interest were selected based on conventional suspension fluorescence cytometry and immunohistochemistry data. Results Antibodies were conjugated to metal isotopes. Antigen retrieval and antibody dilution was optimised on 4µm tissue sections using Tris-EDTA pH 9 initially by immunofluorescence then in multiple assays by Hyperion (Fluidigm) IMC (Figure 1A). An analysis pipeline was developed based on the “Bodenmiller approach” using a combination of R, Python and MATLAB packages: CellProfiler and ilastik to segment single cells, and ImaCyte to explore the resident phenotypes and cellular neighbourhoods in diseased and healthy tissues. A staining panel with 25 antibodies was optimised to identify stromal, epithelial and leukocyte populations. Training algorithms allowed computational segmentation of nuclear, cytoplasmic and non-cellular regions (Figure 1B), cell mask, segmentation and spatial analysis (Figure 1C), and t-SNE (Figure 1D). Representative three parameter images created in MCD viewer (Fluidigm) are shown in Figure 1E to demonstrate cell populations and spatial localisation. Conclusion Quantifiable, multiparameter cellular phenotyping with spatial visualisation can be undertaken with FFPE intestinal tissue using IMC. Due to the existence of archival healthcare samples, the ease of tissue acquisition, processing and storage of FFPE specimens this provides a valuable resource for investigation, including mechanisms of disease pathogenesis, molecular biomarker discovery, and longitudinal pharmacodynamic analysis in clinical trials.

Monitoring Neutrophil Elastase and Cathepsin G Activity in Human Sputum Samples

Proteases are regulators of countless physiological processes and the precise investigation of their activities remains an intriguing biomedical challenge. Among the ~600 proteases encoded by the human genome, neutrophil serine proteases (NSPs) are thoroughly investigated for their involvement in the onset and progression of inflammatory conditions including respiratory diseases. Uniquely, secreted NSPs not only diffuse within extracellular fluids but also localize to plasma membranes. During neutrophil extracellular trap (NETs) formation, NSPs become an integral part of the secreted chromatin. Such complex behavior renders the understanding of NSPs pathophysiology a challenging task. Here, detailed protocols are shown to visualize, quantify and discriminate free and membrane-bound neutrophil elastase (NE) and cathepsin G (CG) activities in sputum samples. NE and CG are NSPs whose activities have pleiotropic roles in the pathogenesis of cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD): they promote tissue remodeling, regulate downstream immune responses and correlate with lung disease severity. The protocols show how to separate fluid and cellular fraction, as well as the isolation of neutrophils from human sputum for enzymatic activity quantification via small-molecule Förster resonance energy transfer-based (FRET) reporters. To gather specific insights into the relative role of NE and CG activities, a FRET readout can be measured by different technologies: i) in vitro plate reader measurements allow for high-throughput and bulk detection of protease activity; ii) confocal microscopy spatiotemporally resolves membrane-bound activity at the cell surface; iii) small-molecule FRET flow cytometry enables for the rapid evaluation of anti-inflammatory treatments via single-cell protease activity quantification and phenotyping. The implementation of such methods opens the doors to explore NSPs pathobiology and their potential as biomarkers of disease severity for CF and COPD. Given their standardization potential, their robust readout and simplicity of transfer, the described techniques are immediately shareable for implementation across research and diagnostic laboratories.

Monitoring Neutrophil Elastase and Cathepsin G Activity in Human Sputum Samples.

Proteases are regulators of countless physiological processes and the precise investigation of their activities remains an intriguing biomedical challenge. Among the ~600 proteases encoded by the human genome, neutrophil serine proteases (NSPs) are thoroughly investigated for their involvement in the onset and progression of inflammatory conditions including respiratory diseases. Uniquely, secreted NSPs not only diffuse within extracellular fluids but also localize to plasma membranes. During neutrophil extracellular trap (NETs) formation, NSPs become an integral part of the secreted chromatin. Such complex behavior renders the understanding of NSPs pathophysiology a challenging task. Here, detailed protocols are shown to visualize, quantify and discriminate free and membrane-bound neutrophil elastase (NE) and cathepsin G (CG) activities in sputum samples. NE and CG are NSPs whose activities have pleiotropic roles in the pathogenesis of cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD): they promote tissue remodeling, regulate downstream immune responses and correlate with lung disease severity. The protocols show how to separate fluid and cellular fraction, as well as the isolation of neutrophils from human sputum for enzymatic activity quantification via small-molecule Förster resonance energy transfer-based (FRET) reporters. To gather specific insights into the relative role of NE and CG activities, a FRET readout can be measured by different technologies: i) in vitro plate reader measurements allow for high-throughput and bulk detection of protease activity; ii) confocal microscopy spatiotemporally resolves membrane-bound activity at the cell surface; iii) small-molecule FRET flow cytometry enables for the rapid evaluation of anti-inflammatory treatments via single-cell protease activity quantification and phenotyping. The implementation of such methods opens the doors to explore NSPs pathobiology and their potential as biomarkers of disease severity for CF and COPD. Given their standardization potential, their robust readout and simplicity of transfer, the described techniques are immediately shareable for implementation across research and diagnostic laboratories.