Single-cell Phenotyping Research Articles

Development of a 2-dimensional atlas of the human kidney with imaging mass cytometry.

An incomplete understanding of the biology of the human kidney, including the relative abundances of and interactions between intrinsic and immune cells, has long constrained the development of therapies for kidney disease. The small amount of tissue obtained by renal biopsy has previously limited the ability to use patient samples for discovery purposes. Imaging mass cytometry (IMC) is an ideal technology for quantitative interrogation of scarce samples, permitting concurrent analysis of more than 40 markers on a single tissue section. Using a validated panel of metal-conjugated antibodies designed to confer unique signatures on the structural and infiltrating cells comprising the human kidney, we performed simultaneous multiplexed imaging with IMC in 23 channels on 16 histopathologically normal human samples. We devised a machine-learning pipeline (Kidney-MAPPS) to perform single-cell segmentation, phenotyping, and quantification, thus creating a spatially preserved quantitative atlas of the normal human kidney. These data define selected baseline renal cell types, respective numbers, organization, and variability. We demonstrate the utility of IMC coupled to Kidney-MAPPS to qualitatively and quantitatively distinguish individual cell types and reveal expected as well as potentially novel abnormalities in diseased versus normal tissue. Our studies define a critical baseline data set for future quantitative analysis of human kidney disease.

Stromal Microenvironment Shapes the Intratumoral Architecture of Pancreatic Cancer

Single-cell technologies have described heterogeneity across tissues, but the spatial distribution and forces that drive single-cell phenotypes have not been well defined. Combining single-cell RNA and protein analytics in studying the role of stromal cancer-associated fibroblasts (CAFs) in modulating heterogeneity in pancreatic cancer (pancreatic ductal adenocarcinoma [PDAC]) model systems, we have identified significant single-cell population shifts toward invasive epithelial-to-mesenchymal transition (EMT) and proliferative (PRO) phenotypes linked with mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 3 (STAT3) signaling. Using high-content digital imaging of RNA in situ hybridization in 195 PDAC tumors, we quantified these EMT and PRO subpopulations in 319,626 individual cancer cells that can be classified within the context of distinct tumor gland "units." Tumor gland typing provided an additional layer of intratumoral heterogeneity that was associated with differences in stromal abundance and clinical outcomes. This demonstrates the impact of the stroma in shaping tumor architecture by altering inherent patterns of tumor glands in human PDAC.

TGF\u03b2-induced cytoskeletal remodeling mediates elevation of cell stiffness and invasiveness in NSCLC

Importance of growth factor (GF) signaling in cancer progression is widely acknowledged. Transforming growth factor beta (TGFβ) is known to play a key role in epithelial-to-mesenchymal transition (EMT) and metastatic cell transformation that are characterized by alterations in cell mechanical architecture and behavior towards a more robust and motile single cell phenotype. However, mechanisms mediating cancer type specific enhancement of cell mechanical phenotype in response to TGFβ remain poorly understood. Here, we combine high-throughput mechanical cell phenotyping, microarray analysis and gene-silencing to dissect cytoskeletal mediators of TGFβ-induced changes in mechanical properties of on-small-cell lung carcinoma (NSCLC) cells. Our experimental results show that elevation of rigidity and invasiveness of TGFβ-stimulated NSCLC cells correlates with upregulation of several cytoskeletal and motor proteins including vimentin, a canonical marker of EMT, and less-known unconventional myosins. Selective probing of gene-silenced cells lead to identification of unconventional myosin MYH15 as a novel mediator of elevated cell rigidity and invasiveness in TGFβ-stimulated NSCLC cells. Our experimental results provide insights into TGFβ-induced cytoskeletal remodeling of NSCLC cells and suggest that mediators of elevated cell stiffness and migratory activity such as unconventional cytoskeletal and motor proteins may represent promising pharmaceutical targets for restraining invasive spread of lung cancer.

A cellular model of Brugada syndrome with SCN10A variants using human-induced pluripotent stem cell-derived cardiomyocytes.

Brugada syndrome (BrS) is associated with a pronounced risk to develop sudden cardiac death (SCD). Up to 21% of patients are related to mutations in SCN5A. Studies identified SCN10A as a contributor of BrS. However, the investigation of the human cellular phenotype of BrS in the presence of SCN10A mutations remains lacking. The objective of this study was to establish a cellular model of BrS in presence of SCN10A mutations using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Dermal fibroblasts obtained from a BrS patient suffering from SCD harbouring the SCN10A double variants (c.3803G>A and c.3749G>A) and three independent healthy control subjects were reprogrammed to hiPSCs. Human-induced pluripotent stem cells were differentiated into cardiomyocytes (hiPSC-CMs).The hiPSC-CMs from the BrS patient showed a significantly reduced peak sodium channel current (INa) and a significantly reduced ATX II (sea anemone toxin, an enhancer of late INa) sensitive as well as A-887826 (a blocker of SCN10A channel) sensitive late sodium channel current (INa) when compared with the healthy control hiPSC-CMs, indicating loss-of-function of sodium channels. Consistent with reduced INa the action potential amplitude and upstroke velocity (Vmax) were significantly reduced, which may contribute to arrhythmogenesis of BrS. Moreover, Ajmaline effects on action potentials were stronger in BrS-hiPSC-CMs than in healthy control cells. This is in agreement with the higher susceptibility of patients to sodium channel blocking drugs in unmasking BrS. Patient-specific hiPSC-CMs are able to recapitulate single-cell phenotype features of BrS with SCN10A mutations and may provide novel opportunities to further elucidate the cellular disease mechanism.

Cell Shape and Population Migration Are Distinct Steps of Proteus mirabilis Swarming That Are Decoupled on High-Percentage Agar.

Swarming on rigid surfaces requires movement of cells as individuals and as a group of cells. For the bacterium Proteus mirabilis, an individual cell can respond to a rigid surface by elongating and migrating over micrometer-scale distances. Cells can form groups of transiently aligned cells, and the collective population is capable of migrating over centimeter-scale distances. To address how P. mirabilis populations swarm on rigid surfaces, we asked whether cell elongation and single-cell motility are coupled to population migration. We first measured the relationship between agar concentration (a proxy for surface rigidity), single-cell phenotypes, and swarm colony phenotypes. We find that cell elongation and single-cell motility are coupled with population migration on low-percentage hard agar (1% to 2.5%) and become decoupled on high-percentage hard agar (>2.5%). Next, we evaluate how disruptions in lipopolysaccharide (LPS), specifically the O-antigen components, affect responses to hard agar. We find that LPS is not essential for elongation and motility of individual cells, as predicted, and instead functions to broaden the range of agar concentrations on which cell elongation and motility are coupled with population migration. These findings demonstrate that cell elongation and motility are coupled with population migration under a permissive range of surface conditions; increasing agar concentration is sufficient to decouple these behaviors. Since swarm colonies cover greater distances when these steps are coupled than when they are not, these findings suggest that collective interactions among P. mirabilis cells might be emerging as a colony expands outwards on rigid surfaces.IMPORTANCE How surfaces influence cell size, cell-cell interactions, and population migration for robust swarmers like P. mirabilis is not fully understood. Here, we have elucidated how cells change length along a spectrum of sizes that positively correlates with increases in agar concentration, regardless of population migration. Single-cell phenotypes can be decoupled from collective population migration simply by increasing agar concentration. A cell's lipopolysaccharides function to broaden the range of agar conditions under which cell elongation and single-cell motility remain coupled with population migration. In eukaryotes, the physical environment, such as a surface matrix, can impact cell development, shape, and migration. These findings support the idea that rigid surfaces similarly act on swarming bacteria to impact cell shape, single-cell motility, and collective population migration.

Visualizing Engrafted Human Cancer and Therapy Responses in Immunodeficient Zebrafish

Xenograft cell transplantation into immunodeficient mice has become the gold standard for assessing pre-clinical efficacy of cancer drugs, yet direct visualization of single-cell phenotypes is difficult. Here, we report an optically-clear prkdc-/-, il2rga-/- zebrafish that lacks adaptive and natural killer immune cells, can engraft a wide array of human cancers at 37°C, and permits the dynamic visualization of single engrafted cells. For example, photoconversion cell-lineage tracing identified migratory and proliferative cell states in human rhabdomyosarcoma, a pediatric cancer of muscle. Additional experiments identified the preclinical efficacy of combination olaparib PARP inhibitor and temozolomide DNA-damaging agent as an effective therapy for rhabdomyosarcoma and visualized therapeutic responses using a four-color FUCCI cell-cycle fluorescent reporter. These experiments identified that combination treatment arrested rhabdomyosarcoma cells in the G2 cell cycle prior to induction of apoptosis. Finally, patient-derived xenografts could be engrafted into our model, opening new avenues for developing personalized therapeutic approaches in the future.

Quantitative Phase Imaging Flow Cytometry for Ultra-Large-Scale Single-Cell Biophysical Phenotyping.

Cellular biophysical properties are the effective label-free phenotypes indicative of differences in cell types, states, and functions. However, current biophysical phenotyping methods largely lack the throughput and specificity required in the majority of cell-based assays that involve large-scale single-cell characterization for inquiring the inherently complex heterogeneity in many biological systems. Further confounded by the lack of reported robust reproducibility and quality control, widespread adoption of single-cell biophysical phenotyping in mainstream cytometry remains elusive. To address this challenge, here we present a label-free imaging flow cytometer built upon a recently developed ultrafast quantitative phase imaging (QPI) technique, coined multi-ATOM, that enables label-free single-cell QPI, from which a multitude of subcellularly resolvable biophysical phenotypes can be parametrized, at an experimentally recorded throughput of >10,000 cells/s-a capability that is otherwise inaccessible in current QPI. With the aim to translate multi-ATOM into mainstream cytometry, we report robust system calibration and validation (from image acquisition to phenotyping reproducibility) and thus demonstrate its ability to establish high-dimensional single-cell biophysical phenotypic profiles at ultra-large-scale (>1,000,000 cells). Such a combination of throughput and content offers sufficiently high label-free statistical power to classify multiple human leukemic cell types at high accuracy (~92-97%). This system could substantiate the significance of high-throughput QPI flow cytometry in enabling next frontier in large-scale image-derived single-cell analysis applied in biological discovery and cost-effective clinical diagnostics. © 2019 International Society for Advancement of Cytometry.

Single-Cell and Neuronal Network Alterations in an In Vitro Model of Fragile X Syndrome.

The Fragile X mental retardation protein (FMRP) is involved in many cellular processes and it regulates synaptic and network development in neurons. Its absence is known to lead to intellectual disability, with a wide range of comorbidities including autism. Over the past decades, FMRP research focused on abnormalities both in glutamatergic and GABAergic signaling, and an altered balance between excitation and inhibition has been hypothesized to underlie the clinical consequences of absence of the protein. Using Fmrp knockout mice, we studied an in vitro model of cortical microcircuitry and observed that the loss of FMRP largely affected the electrophysiological correlates of network development and maturation but caused less alterations in single-cell phenotypes. The loss of FMRP also caused a structural increase in the number of excitatory synaptic terminals. Using a mathematical model, we demonstrated that the combination of an increased excitation and reduced inhibition describes best our experimental observations during the ex vivo formation of the network connections.

Clonal Composition and Single-Cell Characterization of T-Cell Infiltrates in Cardiac Allograft Vasculopathy

Purpose T-cells are implicated in the pathogenesis of cardiac allograft vasculopathy (CAV), yet their clonal composition and function are incompletely defined. We examined the T-cell receptor β (TCRβ) repertoire from explanted grafts with CAV and characterized their phenotype at the single-cell level. Methods TCRβ repertoire analysis was carried out in 4 cardiac explants with CAV by next generation sequencing using DNA extracted from 1) coronary artery (CA), 2) endomyocardium (endo) 3) peripheral blood and 4) cardiac biopsies from the same patients. Blood and intragraft T cells were also phenotyped at the single cell level using a strategy combining index sorting, 13-colour flow cytometry and single-cell RT/PCR for key cytokines, transcription markers and TCRβ chain sequencing. Unique TCRβ chain gene rearrangements were used to link single-cell and TCR repertoires. Results Overlap between intragraft and blood T cell repertoires was observed in all 4 cases with most high frequency rearrangements present in both compartments (Fig. 1a). The clonality index was higher in the blood compared to the graft. In contrast, there was minimal overlap in the B cell repertoire from the same samples (example in 1b). Strikingly, in each case, a common high frequency TCRβ in the blood was also amongst the top rearrangements in the CA, endo, and a previous biopsy (Quilty lesion or cellular rejection) obtained 2 to 6 years earlier (1c). Using their unique TCRβ sequence as a link to the single-cell phenotype data, we identified these clones as CD8+CD45RA+Tbet+ T-cells evocative of effector memory RA T cells (Temra). Conclusion Our studies demonstrated considerable overlap between the graft and blood TCR repertoire in CAV suggestive of a bystander T cell response in situ. However, these findings do not rule out the existence of individual clones being expanded in the graft. Moreover, the Temra phenotype of persistent high frequency clones offers a first indication of the type of T cells infiltrating cardiac allografts.

Biophysical phenotyping of single cells using a differential multiconstriction microfluidic device with self-aligned 3D electrodes

Precise measurement of mechanical and electrical properties of single cells can yield useful information on the physiological and pathological state of cells. In this work, we develop a differential multiconstriction microfluidic device with self-aligned 3D electrodes to simultaneously characterize the deformability, electrical impedance and relaxation index of single cells at a high throughput manner (>430 cell/min). Cells are pressure-driven to flow through a series of sequential microfluidic constrictions, during which deformability, electrical impedance and relaxation index of single cells are extracted simultaneously from impedance spectroscopy measurements. Mechanical and electrical phenotyping of untreated, Cytochalasin B treated and N-Ethylmaleimide treated MCF-7 breast cancer cells demonstrate the ability of our system to distinguish different cell populations purely based on these biophysical properties. In addition, we quantify the classification of different cell types using a back propagation neural network. The trained neural network yields the classification accuracy of 87.8% (electrical impedance), 70.1% (deformability), 42.7% (relaxation index) and 93.3% (combination of electrical impedance, deformability and relaxation index) with high sensitivity (93.3%) and specificity (93.3%) for the test group. Furthermore, we have demonstrated the cell classification of a cell mixture using the presented biophysical phenotyping technique with the trained neural network, which is in quantitative agreement with the flow cytometric analysis using fluorescent labels. The developed concurrent electrical and mechanical phenotyping provide great potential for high-throughput and label-free single cell analysis.

In-Depth Characterization of Monocyte-Derived Macrophages using a Mass Cytometry-Based Phagocytosis Assay

Phagocytosis is a process in which target cells or particles are engulfed and taken up by other cells, typically professional phagocytes; this process is crucial in many physiological processes and disease states. The detection of targets for phagocytosis is directed by a complex repertoire of cell surface receptors. Pattern recognition receptors directly detect targets for binding and uptake, while opsonic and complement receptors detect objects coated by soluble factors. However, the importance of single and combinatorial surface marker expression across different phenotypes of professional phagocytes is not known. Here we developed a novel mass cytometry-based phagocytosis assay that enables the simultaneous detection of phagocytic events in combination with up to 40 other protein markers. We applied this assay to distinct monocyte derived macrophage (MDM) populations and found that prototypic M2-like MDMs phagocytose more E. coli than M1-like MDMs. Surface markers such as CD14, CD206, and CD163 rendered macrophages phagocytosis competent, but only CD209 directly correlated with the amount of particle uptake. Similarly, M2-like MDMs also phagocytosed more cancer cells than M1-like MDMs but, unlike M1-like MDMs, were insensitive to anti-CD47 opsonization. Our approach facilitates the simultaneous study of single-cell phenotypes, phagocytic activity, signaling and transcriptional events in complex cell mixtures.

Patient-Specific and Gene-Corrected Induced Pluripotent Stem Cell-Derived Cardiomyocytes Elucidate Single-Cell Phenotype of Short QT Syndrome.

Short QT syndrome (SQT) is a rare but arrhythmogenic disorder featured by shortened ventricular repolarization and a propensity toward life-threatening ventricular arrhythmias and sudden cardiac death. This study aimed to investigate the single-cell mechanism of SQT using patient-specific and gene-corrected induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). One SQT patient carrying missense mutation T618I in potassium voltage-gated channel subfamily H member 2 ( KCNH2) was recruited as well as 2 healthy control subjects in this study. Control and SQT patient-specific iPSCs were generated from skin fibroblasts using nonintegrated Sendai virus. The KCNH2 T618I mutation was corrected by genome editing in SQT iPSC lines to generate isogenic controls. All iPSCs were differentiated into iPSC-CMs using monolayer-based differentiation protocol. SQT iPSC-CMs exhibited abnormal action potential phenotype featured by shortened action potential duration and increased beat-beat interval variability, when compared with control and gene-corrected iPSC-CMs. Furthermore, SQT iPSC-CMs showed KCNH2 gain-of-function with increased rapid delayed rectifying potassium current (IKr) density and enhanced membrane expression. Gene expression profiling of iPSC-CMs exhibited a differential cardiac ion-channel gene expression profile of SQT. Moreover, QTc of SQT patient and action potential durations of SQT iPSC-CMs were both normalized by quinidine, indicating that quinidine is beneficial to KCNH2 T618I of SQT. Importantly, shortened action potential duration phenotype observed in SQT iPSC-CMs was effectively rescued by a short-peptide scorpion toxin BmKKx2 with a mechanism of targeting KCNH2. We demonstrate that patient-specific and gene-corrected iPSC-CMs are able to recapitulate single-cell phenotype of SQT, which is caused by the gain-of-function mutation KCNH2 T618I. These findings will help elucidate the mechanisms underlying SQT and discover therapeutic drugs for treating the disease by using peptide toxins as lead compounds.

The Human Cell Atlas: making 'cell space' for disease.

ABSTRACTA single change in DNA, RNA, proteins or cellular images can be useful as a biomarker of disease onset or progression. With high-throughput molecular phenotyping of single cells, it is now conceivable that the molecular changes occurring across thousands, or tens of thousands, of individual cells could additionally be considered as a disease biomarker. Transition to a disease state would then be reflected by the shifts in cell numbers and locations across a multidimensional space that is defined by the molecular content of cells. Realising this ambition requires a robust formulation of such a multidimensional ‘cell space’. This is one of the goals of the recently launched Human Cell Atlas project. A second goal is to populate this ‘cell space’ with all cell types in the human body. Here, I consider the potential of the Human Cell Atlas project for improving our description and understanding of the cell-type specificity of disease.

Yeast Single-cell RNA-seq, Cell by Cell and Step by Step.

Single-cell RNA-seq (scRNA-seq) has become an established method for uncovering the intrinsic complexity within populations. Even within seemingly homogenous populations of isogenic yeast cells, there is a high degree of heterogeneity that originates from a compact and pervasively transcribed genome. Research with microorganisms such as yeast represents a major challenge for single-cell transcriptomics, due to their small size, rigid cell wall, and low RNA content per cell. Because of these technical challenges, yeast-specific scRNA-seq methodologies have recently started to appear, each one of them relying on different cell-isolation and library-preparation methods. Consequently, each approach harbors unique strengths and weaknesses that need to be considered. We have recently developed a yeast single-cell RNA-seq protocol (yscRNA-seq), which is inexpensive, high-throughput and easy-to-implement, tailored to the unique needs of yeast. yscRNA-seq provides a unique platform that combines single-cell phenotyping via index sorting with the incorporation of unique molecule identifiers on transcripts that allows to digitally count the number of molecules in a strand- and isoform-specific manner. Here, we provide a detailed, step-by-step description of the experimental and computational steps of yscRNA-seq protocol. This protocol will ease the implementation of yscRNA-seq in other laboratories and provide guidelines for the development of novel technologies.

IDH2 Mutations Induce Altered STAT Signaling and Cytokine Responses Which Are Restored By Enasidenib

Acute myeloid leukemia (AML) is a heterogeneous myeloid malignancy characterized by mutational and clonal heterogeneity. Mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2) are common, occurring in approximately 15-20% of patients, and actionable, with recently approved inhibitors for both mutations. These inhibitors lead to leukemia cell differentiation in vitro, in vivo and in patients. Healthy myeloid differentiation is governed by precise regulation of intracellular signaling, but this regulation is disrupted in AML. Given that signal transducer and activator of transcription (STAT) proteins are involved in both leukemogenesis and myeloid differentiation, we sought to determine the role of phosphorylated STATs and other signaling proteins in mIDH AML and inhibitor-induced differentiation of mIDH2 AML.To simultaneously dissect single cell signaling, differentiation and epigenetic changes, we employed fluorescence flow cytometry and mass cytometry to study an in vitro model of mIDH2R140Q leukemia, consisting of a parental TF-1 leukemia cell line and a CRISPR/Cas9 gene-edited mIDH2R140Q-mutated cell line. In order to generate provoked signaling profiles, we stimulated both the wild-type IDH2 and mutant IDH2 cells with nine cytokines. Additionally, we treated both cell lines and primary mIDH2 AML samples ex vivo with enasidenib and measured changes in high-dimensional single cell phenotype and phospho-protein expression via mass cytometry.mIDH2 leukemia cells displayed elevated basal pSTAT1, pSTAT3 and pNFkB-s529 expression, and concomitant low basal IkBa levels when compared to parental cells. Further, mIDH2 cells had increased PMA induced pS6 and IL1β induced pNFkB-s529 than the parental cell line, while wtIDH2 cells had higher levels of cytokine-induced pSTAT1, pSTAT3 and pSTAT5.After prolonged enasidenib treatment (28 days), model mIDH2 cells expressed lower basal pSTAT1, pSTAT3 and pNFkB-s529 than vehicle-treated mIDH2 cells. Further, when stimulated with GM-CSF, enasidenib-treated mIDH2 leukemia cells showed increased response at pSTAT3 and pSTAT5 as compared to vehicle-treated leukemia cells. We dissected enasidenib-induced differentiation using 18 cell surface markers and visualized results using t-distributed stochastic neighbor embedding (tSNE). Presence of mIDH2 leads to baseline expression differences including higher CD90 and CD71. Following treatment with enasidenib, mIDH2 leukemia cells had increased CD45 and CD11b expression as compared to vehicle-treated controls. Additionally, prolonged treatment with enasidenib increased proliferation as shown by increased Ki67 and decreased histone hypermethylation at suppressive histone marks, H3K27 and H3K9, while 7 days of enasidenib did not result in changes to these marks.We further explored the impact of mIDH2 in primary leukemia samples. First, we developed an ex vivo stromal co-culture system that allowed for treatment and expansion of four primary mIDH2 AML samples for 16 days. While the basal levels of signaling markers were sample dependent, consistently across all samples enasidenib-treated primary AML was more sensitive to IL-6 and GM-CSF-induced pSTAT1, pSTAT3 and pSTAT5 signaling. The enasidenib-treated AML also showed increased expression of mature myeloid markers, including CD33 and CD11c.Here we have shown the presence of mIDH2 mutations leads to decreased STAT signaling in response to cytokine stimulation as compared to wtIDH2 AML cells. We have also demonstrated increased response of pNFkB-s529 and pS6 to cytokine stimulation in mIDH2 AML cells as compared to wtIDH2 AML cells. Moreover, in both mIDH2 AML cell line and primary samples, IDH2 inhibitor-induced differentiation restored sensitivity to cytokine responses and reduced histone hypermethylation. Future work exploring these aberrant signaling events may reveal precise connections between mutated IDH, associated epigenetic changes, and intracellular signaling, potentially uncovering synergistic therapeutic strategies for mIDH AML. DisclosuresFerrell:Incyte: Research Funding.

Single-Cell Profiling Reveals Distinct Tumor Subtypes and Their Associated T-Cell Environments in Follicular Lymphoma

Follicular lymphoma (FL) is an indolent, but incurable malignancy as most patients eventually experience progressive disease. We hypothesized that clonal heterogeneity and patient-specific immune responses would contribute to variable clinical outcomes and that understanding the complexity of the entire tumor “ecosystem” would allow us to better match patients with specific types of tumor- and immune-targeted therapies.In this study, we performed 38-dimensional single-cell phenotyping by mass cytometry (CyTOF) to simultaneously characterize both the substructure of malignant B cell populations as well as the T cell microenvironment in a cohort of 77 diagnostic patient FL biopsies and 35 benign reactive LN (rLN) biopsies.We first applied the t-distributed Stochastic Neighbour Embedding (t-SNE) algorithm to explore intra- and inter- tumoral heterogeneity among malignant B cell populations. t-SNE mapping of individual samples showed that more than a third of FL samples contain at least two phenotypically distinct tumor subpopulations, supporting the notion of multi-clonal tumor architectures presumably due to ongoing clonal evolution. Batched analysis combining all 77 FL cases together with 35 rLN samples revealed two distinct tumor subtypes comprising about 25% (type “A”) and 10% (type “B”) of total FL samples, respectively, with individual tumors within each subtype showing highly similar and partially overlapping phenotypes. Mapping the same data using Uniform Manifold Approximation and Projection (UMAP), a dimensional reduction algorithm similar to t-SNE but preserves global structure more accurately, revealed that type A tumors localized in close proximity to normal germinal center (GC) B cells, thus fulfilling conventional expectations as to the histogenesis of FL. In contrast, type B tumors localized more closely to pre-GC B cells, implying the existence of an alternate histogenic path in FL. Importantly, we also performed single-cell RNA-Seq on a subset of FL cases which independently confirmed the type A vs type B distinction in whole transcriptomic space.We next analyzed matching T cell data using a modified Statistical Scaffold algorithm in order to place distinct subsets in context with conventionally defined normal T cell populations. Clustering analysis using multi-layer phenograph performed on T cells from all FL and rLN samples combined yielded hundreds of small, but phenotypically distinct populations that were then annotated according to the nearest conventionally defined T cell subset. These imputed designations were used as features to perform hierarchical clustering of samples which revealed 3 major clusters. Cluster1 was characterized by mostly naive T cell populations and contained the majority of rLN samples. Cluster2 was characterized by more differentiated effector T cell populations and was dominated by FL samples. Samples within Cluster2 could be further divided into Tfh, Treg and Th1-rich subgroups. Cluster3 was characterized by a diverse T cell environment including naive, memory and differentiated effector subsets and contained a mixture of rLN and FL samples. Integrative analysis correlating B- and T- cell features revealed type B FL tumors were associated with a Tfh-rich immune landscape.Taken together, these data reveal pervasive phenotypic heterogeneity in both malignant and immune cell compartments of patient FL samples and suggest that defining tumoral subtypes as well as the status of the local immune response within individual samples will support more refined diagnostic classification and highlight functional interactions most amenable to therapeutic targeting. DisclosuresGascoyne:NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies. Scott:Celgene: Consultancy, Honoraria; Roche: Research Funding; NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Janssen: Research Funding. Steidl:Juno Therapeutics: Consultancy; Seattle Genetics: Consultancy; Nanostring: Patents & Royalties: patent holding; Bristol-Myers Squibb: Research Funding; Tioma: Research Funding; Roche: Consultancy.

Quantification of somatic mutation flow across individual cell division events by lineage sequencing.

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon (POLE) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.

From Cellular Diversity to the Roots of Variability

From Cellular Diversity to the Roots of Variability

Towards Three-Dimensional Dynamic Regulation and In Situ Characterization of Single Stem Cell Phenotype Using Microfluidics

Mesenchymal stem cells and pluripotent stem cells are recognized as promising tools for tissue engineering, cell therapy, and drug screening. Their use in therapy requires the production of a sufficient number of cells committed to functional regenerative phenotypes. Time- and magnitude-controlled application of mechanical and biochemical cues is required to appropriately control the evolution of stem cell phenotype in 3D. The temporal monitoring of the impact of these cues on the diverse fates of individual stem cells is also needed to ensure the reliability of the differentiation processes. However, macro-scale bioreactors are limited in regulating stem environment and display limited capability to monitor heterogeneities at the single cell level. In turn, microfluidics devices are emerging as powerful tools for tightly controlling culture parameters and precisely monitoring stem cell behavior. This work summarizes recent advances in the applications of microfluidics for the dynamic regulation and characterization of stem cells in 3D.

PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling.

MotivationDue to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaBoSS) and multicellular behaviour using agent-based modelling (PhysiCell).ResultsPhysiBoSS provides a flexible and computationally efficient framework to explore the effect of environmental and genetic alterations of individual cells at the population level, bridging the critical gap from single-cell genotype to single-cell phenotype and emergent multicellular behaviour. PhysiBoSS thus becomes very useful when studying heterogeneous population response to treatment, mutation effects, different modes of invasion or isomorphic morphogenesis events. To concretely illustrate a potential use of PhysiBoSS, we studied heterogeneous cell fate decisions in response to TNF treatment. We explored the effect of different treatments and the behaviour of several resistant mutants. We highlighted the importance of spatial information on the population dynamics by considering the effect of competition for resources like oxygen.Availability and implementationPhysiBoSS is freely available on GitHub (https://github.com/sysbio-curie/PhysiBoSS), with a Docker image (https://hub.docker.com/r/gletort/physiboss/). It is distributed as open source under the BSD 3-clause license.Supplementary information Supplementary data are available at Bioinformatics online.