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Results for “single cell RNA sequencing”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

Rectangle: robust and scalable multiscale deconvolution informed by single-cell RNA sequencing data

Bulk RNA-seq enables effective profiling of large cohorts and complex experimental designs, but current single-cell-informed deconvolution methods incompletely resolve closely related cell phenotypes, do not scale efficiently to large single-cell datasets, or fail to account for cellular content not represented in the reference. Here, we present Rectangle, an scverse Python framework for single-cell-informed deconvolution of bulk RNA-seq data. Rectangle combines multiscale deconvolution, capturing cellular composition across multiple resolution levels, with explicit modeling of unknown cellular content. In a diverse, cross-method benchmark, Rectangle achieved consistently strong performance across all evaluated metrics, demonstrating high accuracy, high resolution, low spillover, strong scalability and efficiency, and robustness to unknown cellular content. By bridging the resolution of single-cell transcriptomics with the scale and cost-efficiency of bulk RNA-seq, Rectangle enables cell-type and cell-state profiling at scale, supporting population-scale cellular biomarker discovery and tracking of cellular dynamics in settings impractical for comprehensive single-cell sequencing.

bioinformatics↗

bioRxiv2025

Single cell RNA sequencing reveals limited effects of Lrrk2 genotype in a mouse model of acute CNS inflammation

BACKGROUNDPrevious data implicates neuroinflammation in the pathogenesis of Parkinsons disease (PD). Of the genes associated with PD, Leucine rich repeat kinase 2 (LRRK2) has previously been proposed to play a role in neuroinflammation. However, the extent to which LRRK2 is involved in endogenous inflammatory signaling is unclear. OBJECTIVETo examine whether endogenous mutations in LRRK2 affect responses to neuroinflammation in vivo. METHODSWe injected cohorts of mice with knock-in mutations in Lrrk2, homologous to those causing human PD, with a single intrastriatal injection of lipopolysaccharide (LPS) or control. We used single cell RNA-Sequencing to examine cell type specific responses to treatment and genotype and validated key results with orthogonal approaches. RESULTSWe found that our chosen paradigm of acute LPS exposure evokes robust transcriptional changes consistent with a multicellular neuroinflammatory response. We also found evidence of peripheral immune cell recruitment into the brain and interaction with brain-resident microglia. However, the transcriptional effects of Lrrk2 mutations were limited to small numbers of genes, including down regulation of gene ontogeny terms related to lysosomes, in microglia. CONCLUSIONSOur data clearly demonstrate that many cells in the brain respond to a single inflammatory insult with strong transcriptional responses and that, even in a model focused on CNS injection, there is interaction between peripheral and central immune cells. In contrast, the quantitative effects of Lrrk2 mutations are modest at the transcriptional level, demonstrating that additional studies are needed to clarify whether Lrrk2 mutations affect neuroinflammation in an endogenous context.

neuroscience↗

bioRxiv2023

Single-cell RNA sequencing to explore the immune process difference between Kawasaki disease and febrile patients

BackgroundKawasaki disease (KD) is an acute systemic vasculitis that can lead to acquired heart disease in children mostly from in developed countries. The previous research showed that B cells in KD patients underwent a profound change in both the cell numbers and types after intravenous immunoglobulin (IVIG) therapy. MethodsWe performed the single-cell RNA-sequencing for the peripheral blood mononuclear cells (PBMCs) from three febrile patients and three KD patients to investigate the possible mechanism underlying B cell developmental dysfunction in KD. A previously published single-cell sequencing KD dataset (GSE168732) was also utilized in study for sample size expansion and validation. The comprehensive single-cell data analyses were applied for our dataset and GSE168732 dataset including single-cell trajectory analysis. To validate the immune disorders in KD, we measured immune-related indicators from 28 KD and 28 febrile patients. ResultOverall single-cell expression profiles show that the biological processes of immunity, B cell activation pathway and their related biological entities are repressed in KD patients before IVIG treatment compared to febrile patient and KD patients after IVIG treatment. The differentially expressed gene analyses further demonstrate that B cell signaling pathway is downregulated in B cells and plasma blast cells of KD patients before treatment while cell cycle genes and MYC gene are upregulated in dendritic cells (DCs) and hematopoietic stem and progenitor cells (HSPCs) of KD patients before treatment. The biological process of immune response is upregulated in the HSPCs of KD patients before treatment in our dataset while the biological process of inflammatory response is upregulated in the HSPCs of KD patients before treatment in GSE168732 dataset. Single-cell trajectory analyses demonstrate that KD patients before treatment have a shortened developmental path in which B cells and T cells are failed to differentiate into separate lineages. HSPD1 and HSPE1 genes show an elevated expression level in the early cell development stage of KD patients before treatment accompanied with the repression of MYC, SPI1, MT2A and UBE2C genes. Our analyses of all B cells from KD patients before treatment show most of B cells are arrested in a transitional state with an ill developmental path compared with febrile patients and KD patients after treatment. The percentage and absolute value of CD8 T cells in KD were lower than those in febrile patients. The ratio of CD4/CD8 in KD was higher than it in febrile patients. The serum levels of IgG and IgM in KD were lower than those in febrile patients. ConclusionsOur results indicate that the immune premature HSPCs accompanied with the abnormal expression dynamics of cell cycle and SPI1 genes are the mechanism underlying B cell developmental dysfunction in KD patients. FundingThis work is jointly supported by National Natural Science Foundation of China (82170518) and the Shanghai Science and Technology Committee research Funding (22Y11909700) and Shanghai Jinshan District medical key specialty Funding (JSZK2023A04).

immunology↗

bioRxiv2018

Generation of human neural retina transcriptome atlas by single cell RNA sequencing

The retina is a highly specialized neural tissue that senses light and initiates image processing. Although the functional organisation of specific cells within the retina has been well-studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile cell types in the human retina, we performed single cell RNA-sequencing on 20,009 cells obtained post-mortem from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct clusters representing all known retinal cells: rod photoreceptors, cone photoreceptors, Muller glia cells, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, retinal astrocytes and microglia. Notably, our data captured molecular profiles for healthy and early degenerating rod photoreceptors, and revealed a novel role of MALAT1 in putative rod degeneration. We also demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult Muller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to our understanding of retinal biology and disease.

systems biology↗

bioRxiv2017

Classifying Drosophila Olfactory Projection Neuron Subtypes by Single-cell RNA Sequencing

How a neuronal cell type is defined and how this relates to its transcriptome are still open questions. The Drosophila olfactory projection neurons (PNs) are among the best-characterized neuronal types: Different PN classes target dendrites to distinct olfactory glomeruli and PNs of the same class exhibit indistinguishable anatomical and physiological properties. Using single-cell RNA-sequencing, we comprehensively characterized the transcriptomes of 40 PN classes and unequivocally identified transcriptomes for 6 classes. We found a new lineage-specific transcription factor that instructs PN dendrite targeting. Transcriptomes of closely-related PN classes exhibit the largest difference during circuit assembly, but become indistinguishable in adults, suggesting that neuronal subtype diversity peaks during development. Genes encoding transcription factors and cell-surface molecules are the most differentially expressed, indicating their central roles in specifying neuronal identity. Finally, we show that PNs use highly redundant combinatorial molecular codes to distinguish subtypes, enabling robust specification of cell identity and circuit assembly.

genomics↗

bioRxiv2024

Single-cell RNA sequencing of mutant whole mouse embryos: from the epiblast to the end of gastrulation

Over the last decade, single-cell approaches have become the gold standard for studying gene expression dynamics, cell heterogeneity, and cell states within samples. Before single-cell advances, the feasibility of capturing the dynamic cellular landscape and rapid cell transitions during early development was limited. In this paper, we designed a robust pipeline to perform single-cell and nuclei analysis on mouse embryos from E6.5 to E8, corresponding to the onset and completion of gastrulation. Gastrulation is a fundamental process during development that establishes the three germinal layers: mesoderm, ectoderm, and endoderm, which are essential for organogenesis. Extensive literature is available on single-cell omics applied to WT perigastrulating embryos. However, single-cell analysis of mutant embryos is still scarce and often limited to FACS-sorted populations. This is partially due to the technical constraints associated with the need for genotyping, timed pregnancies, the count of embryos with desired genotypes per pregnancy, and the number of cells per embryo at these stages. Here, we present a methodology designed to overcome these limitations. This method establishes breeding and timed pregnancy guidelines to achieve a higher chance of synchronized pregnancies with desired genotypes. Optimization steps in the embryo isolation process coupled with FAST genotyping protocol (3 hours) allow for microdroplet-based single-cell to be performed on the same day, ensuring the high viability of cells and robust results. We also include guidelines for optimal nuclei isolations from embryos. Thus, these approaches increase the feasibility of single-cell approaches of mutant embryos at the gastrulation stage. We anticipate this method will facilitate the analysis of how mutations shape the cellular landscape of the gastrula. SUMMARYWe establish a pipeline for high-quality single-cell and nuclei suspensions of gastrulating mouse embryos for sequencing of single cells and nuclei.

developmental biology↗

bioRxiv2022

Ezh2 knockout in B cells impairs plasmablast differentiation and ameliorates lupus-like disease in MRL/lpr mice

ObjectivesEnhancer of zeste homolog 2 (EZH2) regulates B cell development and differentiation. We have previously demonstrated increased EZH2 expression in peripheral blood mononuclear cells isolated from lupus patients. The goal of this study was to evaluate the role of B cell EZH2 expression in lupus pathogenesis. MethodsWe generated an MRL/lpr mouse with floxed Ezh2, which was crossed with CD19-Cre mice to examine the effect of B cell EZH2 deficiency in MRL/lpr lupus-prone mice. Differentiation of B cells was assessed by flow cytometry. Single cell RNA sequencing and single cell B cell receptor sequencing were used to investigate compositional and functional changes of B cell subsets. In vitro B cell culture with an XBP1 inhibitor was performed. EZH2 and XBP1 mRNA levels in CD19+ B cells isolated from SLE patients and healthy controls were analyzed. ResultsWe show that Ezh2 deletion in B cells significantly decreased autoantibody production and improved glomerulonephritis. B cell development was altered in the bone marrow and spleen of EZH2-deficient mice. Differentiation of plasmablasts was impaired. Single cell RNA sequencing showed that XBP1, a key transcription factor in B cell development, is downregulated in the absence of EZH2. Inhibiting XBP1 in vitro impairs plasmablast development similar to EZH2-deficient mice. Single cell B cell receptor RNA sequencing revealed defective immunoglobulin class switch recombination in EZH2-deficient mice. In human lupus B cells, we observed a strong correlation between EZH2 and XBP1 mRNA expression levels. ConclusionEZH2 overexpression in B cells contributes to disease pathogenesis in lupus.

immunology↗

bioRxiv2022

Single-cell RNA sequencing implicates venous endothelial cells as a source of VEGF-mediated neo-angiogenesis in neuroinflammation

Histopathological studies of multiple sclerosis (MS), a demyelinating disease of the central nervous system (CNS), and its animal model, experimental autoimmune encephalomyelitis (EAE), have found newly formed leaky vessels in demyelinated acute and chronic plaques, in addition to blood-brain barrier (BBB) damage in existing vessels, that exacerbate disease pathology by increasing infiltration of immune cells. Which vessel subtypes and signaling pathways generate these aberrant vessels is poorly understood. Using single-cell RNA-sequencing and in vivo validation, we find that transcriptome signatures of neo-angiogenesis arise in venous endothelial cells in both acute and chronic EAE, and correlate with upregulation in VEGF-A signaling. These neo-angiogenic markers are also increased in acute and chronic MS lesions. Treatment with a VEGF-A blocking antibody diminishes neo-angiogenic transcriptomic signatures and vascular proliferation in vivo, but does not restore BBB function or ameliorate significantly EAE pathology. Therefore, anti-angiogenic therapies in combination with immunomodulatory therapies may benefit MS progression.

neuroscience↗

bioRxiv2021

Complexity and graded regulation of neuronal cell type-specific alternative splicing revealed by single-cell RNA sequencing

The enormous neuronal cellular diversity in the mammalian brain, which is highly prototypical and organized in a hierarchical manner, is dictated by cell type-specific gene regulatory programs at the molecular level. Although prevalent in the brain, contribution of alternative splicing (AS) to the molecular diversity across neuronal cell types is just starting to emerge. Here we systematically investigated AS regulation across over 100 transcriptomically defined neuronal types of the adult mouse cortex using deep single cell RNA-sequencing (scRNA-seq) data. We found distinct splicing programs between glutamatergic and GABAergic neurons and between subclasses within each neuronal class, consisting of overlapping sets of alternative exons showing differential splicing at multiple hierarchical levels. Using an integrative approach, our analysis suggests that RNA-binding proteins (RBPs) Celf1/2, Mbnl2 and Khdrbs3 are preferentially expressed and more active in glutamatergic neurons, while Elavl2 and Qk are preferentially expressed and more active in GABAergic neurons. Importantly, these and additional RBPs also contribute to differential splicing between neuronal subclasses at multiple hierarchical levels, and some RBPs drive splicing dynamics that do not conform to the hierarchical structure defined by the transcriptional profiles. Thus, our results suggest graded regulation of AS across neuronal cell types, which provides a molecular mechanism orthogonal to, rather than downstream of, transcriptional regulation in specifying neuronal identity and function. SignificanceAlternative splicing (AS) is extensively used in the mammalian brain, but its contribution to the molecular and cellular diversity across neuronal cell types remains poorly understood. Through systematic and integrative analysis of AS regulation across over 100 transcriptomically defined cortical neuronal types, we found neuronal subclass-specific splicing regulatory programs consists of overlapping alternative exons showing differential splicing at multiple hierarchical levels. This graded AS regulation is controlled by unique combinations of RNA-binding proteins (RBPs). Importantly, these RBPs also drive splicing dynamics across neuronal cell types that do not conform to the hierarchical taxonomy established based on transcriptional profiles, suggesting that the graded AS regulation provides a molecular mechanism orthogonal to transcriptional regulation in specifying neuronal identity and function.

neuroscience↗

bioRxiv2025

Single-cell RNA sequencing reveals distinct senotypes and a quiescence-senescence continuum at the transcriptome level following chemotherapy

Quiescence (reversible cell-cycle arrest) and senescence (irreversible arrest) are challenging to distinguish due to a lack of specific biomarkers, yet both arise simultaneously after chemotherapy. While senescence suppresses tumors by limiting proliferation and recruiting the immune system, quiescent cancer cells evade future therapies and may resume proliferation. Here, we pair time-lapse imaging of cell-cycle dynamics with single-cell RNA-sequencing after etoposide treatment to differentiate these states, linking heterogeneous cell-cycle phenotypes to the transcriptomic landscape. We identify diverse senescent types (senotypes) and link them to two arrest pathways - a gradual path arising after a standard mitosis-to-G0 transition, and a rarer but direct path driven by a mitotic slip. Using pseudotime trajectory analysis, we find that senescent phenotypes begin to manifest early and gradually along the first trajectory, even in shallow quiescent cells. These data support a model wherein, following chemotherapy, quiescence and senescence exist on a continuum of cell-cycle withdrawal at a transcriptome-wide level.

cell biology↗

bioRxiv2020

DUBStepR: correlation-based feature selection for clustering single-cell RNA sequencing data

Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. However, we found that the performance of existing feature selection methods was inconsistent across benchmark datasets, and occasionally even worse than without feature selection. Moreover, existing methods ignored information contained in gene-gene correlations. We therefore developed DUBStepR (Determining the Underlying Basis using Stepwise Regression), a feature selection algorithm that leverages gene-gene correlations with a novel measure of inhomogeneity in feature space, termed the Density Index (DI). Despite selecting a relatively small number of genes, DUBStepR substantially outperformed existing single-cell feature selection methods across diverse clustering benchmarks. In a published scRNA-seq dataset from sorted monocytes, DUBStepR sensitively detected a rare and previously invisible population of contaminating basophils. DUBStepR is scalable to over a million cells, and can be straightforwardly applied to other data types such as single-cell ATAC-seq. We propose DUBStepR as a general-purpose feature selection solution for accurately clustering single-cell data.

bioinformatics↗

bioRxiv2020

Combined transient ablation and single cell RNA sequencing reveals the development of medullary thymic epithelial cells

Medullary thymic epithelial cells (mTECs) play a critical role in central immune tolerance by mediating negative selection of autoreactive T cells through the collective expression of the peripheral self-antigen compartment, including tissue-specific antigens (TSAs). Recent work has shown that gene expression patterns within the mTEC compartment are remarkably heterogenous and include multiple differentiated cell states. To further define mTEC development and medullary epithelial lineage relationships, we combined lineage tracing and recovery from transient in vivo mTEC ablation with single cell RNA-sequencing. The combination of bioinformatic and experimental approaches revealed a non-stem transit-amplifying population of cycling mTECs that preceded Aire expression. Based on our findings, we propose a branching model of mTEC development wherein a heterogeneous pool of transit-amplifying cells gives rise to Aire- and Ccl21a-expressing mTEC subsets. We further use experimental techniques to show that within the Aire-expressing developmental branch, TSA expression peaked as Aire expression decreased, implying Aire expression must be established before TSA expression can occur. Collectively, these data provide a higher order roadmap of mTEC development and demonstrate the power of combinatorial approaches leveraging both in vivo models and high-dimensional datasets.

immunology↗

bioRxiv2020

Single-cell RNA sequencing of human, macaque, and mouse testes uncovers conserved and divergent features of mammalian spermatogenesis

Spermatogenesis is a highly regulated process that produces sperm to transmit genetic information to the next generation. Although extensively studied in mice, our current understanding of primate spermatogenesis is limited to populations defined by state-specific markers defined from rodent data. As between-species differences have been reported in the process duration and cellular differentiation hierarchy, it remains unclear how molecular markers and cell states are conserved or have diverged from mice to man. To address this challenge, we employ single-cell RNA-sequencing to identify transcriptional signatures of major germ and somatic cell-types of the testes in human, macaque and mice. This approach reveals differences in expression throughout spermatogenesis, including the stem/progenitor pool of spermatogonia, classical markers of differentiation, potential regulators of meiosis, the kinetics of RNA turnover during spermatid differentiation, and germ cell-soma communication. These datasets provide a rich foundation for future targeted mechanistic studies of primate germ cell development and in vitro gametogenesis.

genetics↗

bioRxiv2023

Single-cell RNA sequencing identifies KSHV-infected Mesenchymal stem cell subpopulations precursors of Kaposi's Sarcoma

Kaposis sarcoma (KS) may derive from Kaposis Sarcoma Herpesvirus (KSHV)-infected human Mesenchymal Stem Cells (hMSCs) migrating into an inflammatory and angiogenic site, enhancing KS initiation. KSHV infection of primary hMSCs uncovers specific cell subpopulations, mechanisms, and conditions involved in the first steps of the KSHV-induced transformation and reprogramming process toward KS progenitor cells. The pro-angiogenic environmental conditions allowed KSHV to reprogram hMSCs closer to KS gene expression profiles and points to KSHV infection as an important factor inducing the Mesenchymal-to-Endothelial (MEndT) transition of hMSC. Single-cell RNA-sequencing analysis revealed a subpopulation of infected cells growing in a pro-angiogenic environment with both viral and host oncogenes upregulation. This highlights the importance of this condition in boosting the KSHV-induced transformation and reprogramming of hMSC towards MEndT and closer to KS gene expression profiles, reinforcing the notion of these cell subpopulations as KS precursors.

microbiology↗

bioRxiv2024

Precision and Accuracy of Single-Cell/Nuclei RNA Sequencing Data

Single-cell and single-nucleus RNA sequencing (sc/snRNA-Seq) have become essential tools for profiling gene expression across different cell types in biomedical research. While factors like RNA integrity, cell count, and sequencing depth are known to influence data quality, quantitative benchmarks and actionable guidelines are lacking. This gap contributes to variability in study designs and inconsistencies in downstream analyses. In this study, we systematically evaluated quantitative precision and accuracy in expression measures across 23 sc/snRNA-Seq datasets comprising 3,682,576 cells from 339 samples. Precision was assessed using technical replicates based on pseudo-bulks created from subsampling. Accuracy was evaluated using sample-matched scRNA-Seq and pooled-cell RNA-Seq data of mononuclear phagocytes from four species. Our results show that precision and accuracy are generally low at the single-cell level, with reproducibility being strongly influenced by cell count and RNA quality. We establish data-driven thresholds for optimizing study design, recommending at least 500 cells per cell type per individual to achieve reliable quantification. Furthermore, we show that signal-to-noise ratio is a key metric for identifying reproducible differentially expressed genes. To support future research, we developed VICE (Variability In single-Cell gene Expressions), a tool that evaluates sc/snRNA-seq data quality and estimates the true positive rate of differential expression results based on sample size, observed noise levels, and expected effect size. These findings provide practical, evidence-based guidelines to enhance the reliability and reproducibility of sc/snRNA-seq studies.

genomics↗

bioRxiv2019

Single Cell Viewer (SCV): An interactive visualization data portal for single cell RNA sequence data

MotivationThanks to technological advances made in the last few years, we are now able to study transcriptomes from thousands of single cells. These have been applied widely to study various aspects of Biology. Nevertheless, comprehending and inferring meaningful biological insights from these large datasets is still a challenge. Although tools are being developed to deal with the data complexity and data volume, we do not have yet an effective visualizations and comparative analysis tools to realize the full value of these datasets.\n\nResultsIn order to address this gap, we implemented a single cell data visualization portal called Single Cell Viewer (SCV). SCV is an R shiny application that offers users rich visualization and exploratory data analysis options for single cell datasets.\n\nAvailabilitySource code for the application is available online at GitHub (http://www.github.com/neuhausi/single-cell-viewer) and there is a hosted exploration application using the same example dataset as this publication at http://periscopeapps.org/scv_tirosh.\n\nContactisaac.neuhaus@bms.com; kandasamy.ravi@bms.com

bioinformatics↗

bioRxiv2021

Single-Cell RNA Sequencing Characterizes the Molecular Heterogeneity of the Larval Zebrafish Optic Tectum

The optic tectum (OT) is a multilaminated midbrain structure that acts as the primary retinorecipient in the zebrafish brain. Homologous to the mammalian superior colliculus, the OT is responsible for the reception and integration of stimuli, followed by elicitation of salient behavioral responses. While the OT has been the focus of functional experiments for decades, less is known concerning specific cell types, microcircuitry, and their individual functions within the OT. Recent efforts have contributed substantially to the knowledge of tectal cell types; however, a comprehensive cell catalog is incomplete. Here we contribute to this growing effort by applying single-cell RNA-sequencing (scRNA-seq) to characterize the transcriptomic profiles of tectal cells labeled by the transgenic enhancer trap line y304Et(cfos:Gal4;UAS:Kaede). We sequenced 13,320 cells, a 4X cellular coverage, and identified 25 putative OT cell populations. Within those cells, we identified several mature and developing neuronal populations, as well as non-neuronal cell types including oligodendrocytes, microglia, and radial glia. Although most mature neurons demonstrate GABAergic activity, several glutamatergic populations are present, as well as one glycinergic population. We also conducted Gene Ontology analysis to identify enriched biological processes, and computed RNA velocity to infer current and future transcriptional cell states. Finally, we conducted in situ hybridization to validate our bioinformatic analyses and spatially map select clusters. In conclusion, the larval zebrafish OT is a complex structure containing at least 25 transcriptionally distinct cell populations. To our knowledge, this is the first time scRNA-seq has been applied to explore the OT alone and in depth.

neuroscience↗

bioRxiv2024

Comparison of Different Approaches to Single Cell RNA Sequencing of Cancer Associated Fibroblasts

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease with a poor prognosis. PDAC has a high propensity for metastasis, particularly to the lungs and liver. Cancer associated fibroblasts (CAFs) represent a major stromal component of PDAC with both tumor-promoting and restraining properties. Of note, CAFs play a significant role in the creation of an immunosuppressive tumor microenvironment (TME) and the metastasis of PDAC. Studies have demonstrated functional heterogeneity among different subpopulations of CAFs, highlighting the need to identify specific subpopulations when targeting CAFs. MethodsThe orthotopic model was used for both KPC-4545 and KPC-3403 cell lines, which were derived from the primary tumors of KPC mice with liver metastases and lung metastases only, respectively. In brief, 2x106 KPC cells were injected subcutaneously into the flanks of synergic female C57BI6 mice. Tumors were harvested and cut into 2-3 mm3 pieces before being implanted into the pancreas of new 6-8-week-old syngeneic female C57Bl/6 mice. Murine orthotopic tumors were dissected, mechanically and enzymatically processed with Miltenyi Tumor Dissociation Kit (Miltenyi Biotec) thirteen days after tumor implantation. Samples were filtered with a 100 {micro}m strainer, washed with T cell media, and centrifuged twice. Two different samples underwent single cell RNA-sequencing (scRNA-seq) for each cell line: an unenriched sample, which represents all cells following dissociation of the tumor, and a CAF-enriched sample. To further obtain the CAF-enriched sample, cells were then stained with CD45-AF657 (BioLegend clone 30-F11, 1:20), CD31-AF647 (BioLegend clone 390, 1:20), EPCAM-AF647 (BioLegend, clone G8.8, 1:20), and TER119-AF647 (BioLegend clone TER-119 1:20) for 30 minutes on ice. After two washes, CD45-, CD31-, EPCAM-, and TER119-negative cells, representing the CAF-enriched fraction, were obtained via cell sorting. scRNA-seq of both the unenriched and CAF-enriched fractions were performed using 10X Chromium microfluidic chips and data was analyzed using CellRanger v6.1.1, mm10 transcriptome reference, and 10X Loupe Browser. ResultsWe found that scRNA-seq of the unenriched whole tumor showed only one cluster of CAFs for both cells lines, making it difficult for studying CAF heterogeneity. Enriching for CAFs prior to scRNA-seq allowed for better capture of CAFs and provided more granularity on CAF heterogeneity for both KPC-4545 and KPC-3403. ConclusionsWhile enrichment provides more information on CAF heterogeneity, the process results in the loss of other cells within the TME. The need to capture CAF heterogeneity while studying cell-cell interaction between CAFs and other cells within the TME and identifying how distinct CAF populations respond differently to treatment warrants the use of other methods such as single-nuclear RNA-seq.

cancer biology↗