Search bioRxiv⌕ Search

Biology subjects

Pe'er, D.

Publications and source records attributed to Pe'er, D..

At least 37 records · Page 2Linked to original sources

Single-cell analysis of bidirectional reprogramming between early embryonic states reveals mechanisms of differential lineage plasticities

Two distinct fates, pluripotent epiblast (EPI) and primitive (extra-embryonic) endoderm (PrE), arise from common progenitor cells, the inner cell mass (ICM), in mammalian embryos. To study how these sister identities are forged, we leveraged embryonic (ES) and eXtraembryonic ENdoderm (XEN) stem cells - in vitro counterparts of the EPI and PrE. Bidirectional reprogramming between ES and XEN coupled with single-cell RNA and ATAC-seq analyses uncovered distinct rates, efficiencies and trajectories of state conversions, identifying drivers and roadblocks of reciprocal conversions. While GATA4-mediated ES-to-iXEN conversion was rapid and nearly deterministic, OCT4, KLF4 and SOX2-induced XEN-to-iPS reprogramming progressed with diminished efficiency and kinetics. The dominant PrE transcriptional program, safeguarded by Gata4, and globally elevated chromatin accessibility of EPI underscored the differential plasticities of the two states. Mapping in vitro trajectories to embryos revealed reprogramming in either direction tracked along, and toggled between, EPI and PrE in vivo states without transitioning through the ICM.

developmental biology↗

Distinct tumor architectures for metastatic colonization of the brain

Brain metastasis is a dismal cancer complication, hinging on the initial survival and outgrowth of disseminated cancer cells. To understand these crucial early stages of colonization, we investigated two prevalent sources of cerebral relapse, triple-negative (TNBC) and HER2+ breast cancer (HER2BC). We show that these tumor types colonize the brain aggressively, yet with distinct tumor architectures, stromal interfaces, and autocrine growth programs. TNBC forms perivascular sheaths with diffusive contact with astrocytes and microglia. In contrast, HER2BC forms compact spheroids prompted by autonomous extracellular matrix components and segregating stromal cells to their periphery. Single-cell transcriptomic dissection reveals canonical Alzheimers disease-associated microglia (DAM) responses. Differential engagement of tumor-DAM signaling through the receptor AXL suggests specific pro-metastatic functions of the tumor architecture in both TNBC perivascular and HER2BC spheroidal colonies. The distinct spatial features of these two highly efficient modes of brain colonization have relevance for leveraging the stroma to treat brain metastasis.

cancer biology↗

Supervised discovery of interpretable gene programs from single-cell data

Factor analysis can drive biological discovery by decomposing single-cell gene expression data into a minimal set of gene programs that correspond to processes executed by cells in a sample. However, matrix factorization methods are prone to technical artifacts and poor factor interpretability. We have developed Spectra, an algorithm that identifies user-provided gene programs, modifies them to dataset context as needed, and detects novel programs that together best explain expression covariation. Spectra overcomes the dominance of cell-type signals by modeling cell-type-specific programs, and can characterize interpretable cell states along a continuum. We show that it outperforms existing approaches in challenging tumor immune contexts; Spectra finds factors that change under immune checkpoint therapy, disentangles the highly correlated features of CD8+ T-cell tumor reactivity and exhaustion, finds a novel program that explains continuous macrophage state changes under therapy, and identifies cell-type-specific immune metabolic programs.

bioinformatics↗

Chromosome 9p21.3 Coordinates Cell Intrinsic and Extrinsic Tumor Suppression

Somatic chromosomal deletions are prevalent in cancer, yet their functional contributions remain ill-defined. Among the most prominent of these events are deletions of chromosome 9p21.3, which disable a cell intrinsic barrier to tumorigenesis by eliminating the CDKN2A/B tumor suppressor genes. However, half of 9p21.3 deletions encompass a cluster of 16 type I interferons (IFNs) whose co-deletions have not been functionally characterized. To dissect how 9p21.3 and other genomic deletions impact cancer, we developed MACHETE (Molecular Alteration of Chromosomes with Engineered Tandem Elements), a genome engineering strategy that enables flexible modeling of megabase-sized deletions. Generation of 9p21.3-syntenic deletions in a mouse model of pancreatic cancer revealed that concomitant loss of Cdkn2a/b and the IFN cluster led to immune evasion and metastasis compared to Cdkn2a/b-only deletions. Mechanistically, IFN co-deletion disrupted type I IFN signaling, altered antigen-presenting cells, and facilitated escape from CD8+ T cell surveillance in a cell extrinsic manner requiring loss of interferon epsilon (Ifne). Our results establish co-deletions of the IFN cluster as a pervasive route to tumor immune evasion and metastasis, revealing how deletions can disable physically linked cell intrinsic and extrinsic tumor suppression. Our study establishes a framework to dissect the functions of genomic deletions in cancer and beyond.

cancer biology↗

Epigenetic plasticity cooperates with emergent cell-cell interactions to drive neoplastic tissue remodeling in the pancreas

The response to tumor-initiating inflammatory and genetic insults can vary amongst morphologically indistinguishable cells, suggesting yet uncharacterized roles for epigenetic plasticity during early neoplasia. To investigate the origins and impact of such plasticity, we perform single-cell analyses on normal, inflamed, pre-malignant and malignant tissues in autochthonous models of pancreatic cancer. We reproducibly identify heterogeneous cell-states that are primed for diverse late-emerging neoplastic fates and link these to chromatin remodeling at cell-cell communication loci. Using a new inference approach, we reveal signaling gene modules and tissue-level crosstalk, including a neoplasia-driving feedback loop between discrete epithelial and immune cell populations that we validate by genetic perturbation in mice. Our results uncover a neoplasia-specific tissue remodeling program that may be exploited for pancreas cancer interception. One-Sentence SummarySingle-cell analysis reveals that enhanced epigenetic plasticity drives pro-neoplastic crosstalk in early pancreatic cancer.

cancer biology↗

SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data

Metacells are cell groupings derived from single-cell sequencing data that represent highly granular, distinct cell states. Here, we present single-cell aggregation of cell-states (SEACells), an algorithm for identifying metacells; overcoming the sparsity of single-cell data, while retaining heterogeneity obscured by traditional cell clustering. SEACells outperforms existing algorithms in identifying accurate, compact, and well-separated metacells in both RNA and ATAC modalities across datasets with discrete cell types and continuous trajectories. We demonstrate the use of SEACells to improve gene-peak associations, compute ATAC gene scores and measure gene accessibility in each metacell. Metacell-level analysis scales to large datasets and are particularly well suited for patient cohorts, including facilitation of data integration. We use our metacells to reveal expression dynamics and gradual reconfiguration of the chromatin landscape during hematopoietic differentiation, and to uniquely identify CD4 T cell differentiation and activation states associated with disease onset and severity in a COVID-19 patient cohort.

bioinformatics↗

A lymphatic-stem cell interactome regulates intestinal stem cell activity

Barrier epithelia depend on resident stem cells for homeostasis, defense and repair. Intestinal stem cells (ISCs) of the small and large intestines respond to their local microenvironments (niches) to fulfill a continuous demand for tissue turnover, yet the complexity of their niches is still unfolding. Here, we report an extensive lymphatic network that intimately associates with ISCs within these niches. Devising a lymphatic:organoid coculture system, we show that lymphatic-secreted factors maintain ISCs while inhibiting precocious differentiation. Employing a new deconvolution algorithm, BayesPrism, to pair single-cell and spatial transcriptomics, we cartograph the lymphatic ligand:ISC receptor interactomes at high resolution. We unearth crypt lymphatics as a major source of WNT-signaling factors (WNT2, R-SPONDIN-3) known to drive ISC behavior, and REELIN, a hitherto unappreciated ISC regulator secreted by crypt lymphatics. Together, our studies expose lymphatics as a central hub for niche factors that govern the regenerative potential of ISCs.

cell biology↗

Dynamic structural cell responses in the thymus to acute injury, regeneration, and age

The thymus is essential for establishing adaptive immunity yet undergoes age-related atrophy leading to compromised immune responsiveness. The thymus is also extremely sensitive to acute insult and although capable of regeneration, this capacity declines with age. Focusing on non-hematopoietic stromal cells, and using single-cell and spatial transcriptomics, lineage-tracing, and advanced imaging, we discovered two atypical thymic epithelial cell (TEC) states that emerged with age. Age-associated (aa)TECs formed atypical high-density epithelial clusters that were devoid of thymocytes, an accretion of non-functional thymic tissue that worsened with age and exhibited features of partial epithelial-to-mesenchymal transition (EMT). In silico interaction analysis revealed that aaTEC emergence drew tonic signals from other TEC populations at baseline, acting as a sink for TEC growth factors. Following damage, aaTEC expanded substantially, further perturbing trophic pathways, and correlating with defective regeneration of the involuted thymus. These findings define a unique feature of thymic involution linked to immune aging.

immunology↗

Multilineage plasticity in prostate cancer through expansion of stem-like luminal epithelial cells with elevated inflammatory signaling

Lineage plasticity is a well-established mechanism of resistance to targeted therapies in lung and prostate cancer, where tumors transition from adenocarcinoma to small-cell or neuroendocrine carcinoma. Through single-cell analysis of a cohort of heavily-treated castration-resistant human prostate cancers (CRPC), we report a greater degree of plasticity than previously appreciated, with multiple distinct neuroendocrine (NEPC), mesenchymal (EMT-like), and other subpopulations detected within single biopsies. To explore the steps leading to this plasticity, we turned to two genetically engineered mouse models of prostate cancer that recapitulate progression from adenocarcinoma to neuroendocrine disease. Time course studies reveal expansion of stem-like luminal epithelial cells (Sca1+, Psca+, called L2) that, based on trajectories, gave rise to at least 4 distinct subpopulations, NEPC (Ascl1+), POU2F3 (Pou2f3+), TFF3 (Tff3+) and EMT-like (Vim+, Ncam1+)--these populations are also seen in human prostate and small cell lung cancers. Transformed L2-like cells express stem-like and gastrointestinal endoderm-like transcriptional programs, indicative of reemerging developmental plasticity programs, as well as elevated Jak/Stat and interferon pathway signaling. In sum, while the magnitude of multilineage heterogeneity, both within and across patients, raises considerable treatment challenges, the identification of highly plastic luminal cells as the likely source of this heterogeneity provides a target for more focused therapeutic intervention. One Sentence SummaryMultilineage plasticity results from expansion of stem-like luminal cells with JAK/STAT activation, serving as a therapeutic target.

cancer biology↗

Reversal of lineage plasticity in RB1/TP53-deleted prostate cancer through FGFR and Janus kinase inhibition

The inherent plasticity of tumor cells provides a mechanism of resistance to many molecularly targeted therapies, exemplified by adeno-to-neuroendocrine lineage transitions seen in prostate and lung cancer. Here we investigate the root cause of this lineage plasticity in a primary murine prostate organoid model that mirrors the lineage transition seen in patients. These cells lose luminal identity within weeks following deletion of Trp53 and Rb1, ultimately acquiring an Ar-negative, Syp+ phenotype after orthotopic in vivo transplantation. Single-cell transcriptomic analysis revealed progressive mixing of luminal-basal lineage features after tumor suppressor gene deletion, accompanied by activation of Jak/Stat and Fgfr pathway signaling and interferon-a and -g gene expression programs prior to any morphologic changes. Genetic or pharmacologic inhibition of Jak1/2 in combination with FGFR blockade restored luminal differentiation and sensitivity to antiandrogen therapy in models with residual AR expression. Collectively, we show lineage plasticity initiates quickly as a largely cell-autonomous process and, through newly developed computational approaches, identify a pharmacological strategy that restores lineage identity using clinical grade inhibitors.

cancer biology↗

Perturb-map enables CRISPR genomics with spatial resolution and identifies regulators of tumor immune composition

The cellular architecture of a tumor, particularly immune composition, has a major impact on cancer outcome, and thus there is an interest in identifying genes that control the tumor microenvironment (TME). While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying gene functions operating extracellularly or within a tissue context. To address this, we developed an approach for spatial functional genomics called Perturb-map, which utilizes protein barcodes (Pro-Code) to enable spatial detection of barcoded cells within tissue. We show >120 Pro-Codes can be imaged within a tumor, facilitating spatial mapping of 100s of cancer clones. We applied Perturb-map to knockout dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Additionally, we paired Perturb-map and spatial transcriptomics for unbiased molecular analysis of Pro-Code/CRISPR lesions. Our studies found in Tgfbr2 knockout lesions, the TME was converted to a mucinous state and T-cells excluded, which was concomitant with increased TGF{beta} expression and pathway activation, suggesting Tgfbr2 loss on lung cancer cells enhanced suppressive effects of TGF{beta} on the TME. These studies establish Perturb-map for functional genomics within a tissue at single cell-resolution with spatial architecture preserved.

immunology↗

Sparcle: assigning transcripts to cells in multiplexed images

BackgroundImaging-based spatial transcriptomics has the power to reveal patterns of single-cell gene expression by detecting mRNA transcripts as individually resolved spots in multiplexed images. However, molecular quantification has been severely limited by the computational challenges of segmenting poorly outlined, overlapping cells, and of overcoming technical noise; the majority of transcripts are routinely discarded because they fall outside the segmentation boundaries. This lost information leads to less accurate gene count matrices and weakens downstream analyses, such as cell type or gene program identification. ResultsHere, we present Sparcle, a probabilistic model that reassigns transcripts to cells based on gene covariation patterns and incorporates spatial features such as distance to nucleus. We demonstrate its utility on both multiplexed error-robust fluorescence in situ hybridization (MERFISH) and single-molecule FISH (smFISH) data. ConclusionsSparcle improves transcript assignment, providing more realistic per-cell quantification of each gene, better delineation of cell boundaries, and improved cluster assignments. Critically, our approach does not require an accurate segmentation and is agnostic to technological platform.

bioinformatics↗

Single cell profiling reveals novel tumor and myeloid subpopulations in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively), which are associated with distinct therapeutic vulnerabilities. To define the heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 54,523 cellular transcriptomes from 21 human biospecimens. Our single-cell SCLC atlas reveals tumor diversity exceeding lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discovered a PLCG2-high tumor cell population with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival, and manipulation of PLCG2 expression in cells confirms correlation with key metastatic markers. Treatment and subtype are associated with substantial phenotypic changes in the SCLC immune microenvironment, with greater T-cell dysfunction in SCLC-N than SCLC-A. Moreover, the recurrent, PLCG2-high subclone is associated with exhausted CD8+ T-cells and a pro-fibrotic, immunosuppressive monocyte/macrophage population, suggesting possible tumor-immune coordination to promote metastasis.

cancer biology↗

Counterfactual Hypothesis Testing of Tumor Microenvironment Scenarios Through Semantic Image Synthesis

AO_SCPLOWBSTRACTC_SCPLOWRecent multiplexed protein imaging technologies characterize cells, their spatial organization, and interactions within microenvironments at an unprecedented resolution. Although observational data can reveal spatial associations, it does not allow users to infer salient biological relationships and cellular interactions. To address this challenge, we develop a generative model that allows users to test hypotheses about the effect of cell-cell interactions on protein expression through in silico perturbation. Our Cell-Cell Interaction GAN (CCIGAN) model employs a generative adversarial network (GAN) architecture to generate high fidelity synthetic multiplexed images from semantic cell segmentations. Our approach is unique in that it learns relationships between all imaging channels simultaneously and yields biological insights from multiple imaging technologies in silico, capturing known tumor-immune cell interactions missed by other state-of-the-art GAN models.

cancer biology↗

Integrated Single Cell Atlas of Endothelial Cells of the Human Lung

BackgroundDespite its importance in health and disease, the cellular diversity of the lung endothelium has not been systematically characterized in humans. Here we provide a reference atlas of human lung endothelial cells (ECs), to facilitate a better understanding of the phenotypic diversity and composition of cells comprising the lung endothelium, both in health and disease. MethodsWe reprocessed control single cell RNA sequencing (scRNAseq) data from five datasets of whole lungs that were used for the analysis of pan-endothelial markers, we later included a sixth dataset of sorted control EC for the vascular subpopulation analysis. EC populations were characterized through iterative clustering with subsequent differential expression analysis. Marker genes were validated by immunohistochemistry and in situ hybridization. Signaling network between different lung cell types was studied using connectomic analysis. For cross species analysis we applied the same methods to scRNAseq data obtained from mouse lungs. ResultsThe six lung scRNAseq datasets were reanalyzed and annotated to identify over 15,000 vascular EC cells from 73 individuals. Differential expression analysis of EC revealed signatures corresponding to endothelial lineage, including pan-endothelial, pan-vascular and subpopulation-specific marker gene sets. Beyond the broad cellular categories of lymphatic, capillary, arterial and venous ECs we found previously indistinguishable subpopulations; among venous EC we identified two previously indistinguishable populations, pulmonary-venous ECs (COL15A1neg) localized to the lung parenchyma and systemic-venous ECs (COL15A1pos) localized to the airways and the visceral pleura; among capillary EC we confirmed their subclassification into recently discovered aerocytes characterized by EDNRB, SOSTDC1 and TBX2 and general capillary EC. We confirmed that all six endothelial cell types, including the systemic-venous EC and aerocytes are present in mice and identified endothelial marker genes conserved in humans and mice. Ligand-Receptor connectome analysis revealed important homeostatic crosstalk of EC with other lung resident cell types. Our manuscript is accompanied by an online data mining tool (www.LungEndothelialCellAtlas.com). ConclusionOur integrated analysis provides the comprehensive and well-crafted reference atlas of lung endothelial cells in the normal lung and confirms and describes in detail previously unrecognized endothelial populations across a large number of humans and mice.

cell biology↗

CellRank for directed single-cell fate mapping

Computational trajectory inference enables the reconstruction of cell-state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank (https://cellrank.org) for mapping the fate of single cells in diverse scenarios, including perturbations such as regeneration or disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, derived from ratios of spliced to unspliced reads. CellRank takes into account both the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in RNA velocity vectors. On data from pancreas development, we show that it automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. CellRank also predicts a novel dedifferentiation trajectory during regeneration after lung injury, which we follow up experimentally by confirming the existence of previously unknown intermediate cell states.

bioinformatics↗

A unified atlas of CD8 T cell dysfunctional states in cancer and infection

CD8 T cells play an essential role in defense against viral and bacterial infections and in tumor immunity. Deciphering T cell loss of functionality is complicated by the conspicuous heterogeneity of CD8 T cell states described across different experimental and clinical settings. By carrying out a unified analysis of over 300 ATAC-seq and RNA-seq experiments from twelve independent studies of CD8 T cell dysfunction in cancer and infection we defined a shared differentiation trajectory towards terminal dysfunction and its underlying transcriptional drivers and revealed a universal early bifurcation of functional and dysfunctional T cell activation states across models. Experimental dissection of acute and chronic viral infection using scATAC-seq and allele-specific scRNA-seq identified state-specific transcription factors and captured the early emergence of highly similar TCF1+ progenitor-like populations at an early branch point, at which epigenetic features of functional and dysfunctional T cells diverge. Our atlas of CD8 T cell states will facilitate mechanistic studies of T cell immunity and translational efforts.

genomics↗

Stag1 and Stag2 regulate cell fate decisions in hematopoiesis through non-redundant topological control

Transcriptional regulators, including the cohesin complex member STAG2, are recurrently mutated in cancer. The role of STAG2 in gene regulation, hematopoiesis, and tumor suppression remains unresolved. We show Stag2 deletion in hematopoietic stem/progenitor cells (HSPC) results in altered hematopoietic function, increased self-renewal, and impaired differentiation. ChIP-sequencing revealed that while Stag2 and Stag1 can bind the same loci, a component of Stag2 binding sites are unoccupied by Stag1 even in Stag2-deficient HSPCs. While concurrent loss of Stag2 and Stag1 abrogated hematopoiesis, Stag2 loss alone decreased chromatin accessibility and transcription of lineage-specification genes, including Ebf1 and Pax5, leading to blunted HSPC commitment to the B-cell lineage. Our data illustrate a role for Stag2 in transformation and transcriptional dysregulation distinct from its shared role with Stag1 in chromosomal segregation.\n\nOne Sentence SummaryStag1 rescues topologically associated domains in the absence of Stag2, but cannot restore chromatin architecture required for hematopoietic lineage commitment

cell biology↗