RESUMO
Tumor metastasis requires systemic remodeling of distant organ microenvironments that impacts immune cell phenotypes, population structure, and intercellular communication. However, our understanding of immune phenotypic dynamics in the metastatic niche remains incomplete. Here, we longitudinally assayed lung immune transcriptional profiles in the polyomavirus middle T antigen (PyMT) and 4T1 metastatic breast cancer models from primary tumorigenesis, through pre-metastatic niche formation, to the final stages of metastatic outgrowth at single-cell resolution. Computational analyses of these data revealed a TLR-NFκB inflammatory program enacted by both peripherally derived and tissue-resident myeloid cells that correlated with pre-metastatic niche formation and mirrored CD14+ "activated" myeloid cells in the primary tumor. Moreover, we observed that primary tumor and metastatic niche natural killer (NK) cells are differentially regulated in mice and human patient samples, with the metastatic niche featuring elevated cytotoxic NK cell proportions. Finally, we identified cell-type-specific dynamic regulation of IGF1 and CCL6 signaling during metastatic progression that represents anti-metastatic immunotherapy candidate pathways.
Assuntos
Neoplasias da Mama , Células Matadoras Naturais , Neoplasias Pulmonares , Microambiente Tumoral , Animais , Feminino , Humanos , Camundongos , Neoplasias Pulmonares/imunologia , Neoplasias Pulmonares/secundário , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/genética , Neoplasias da Mama/imunologia , Neoplasias da Mama/patologia , Neoplasias da Mama/genética , Células Matadoras Naturais/imunologia , Microambiente Tumoral/imunologia , Progressão da Doença , Linhagem Celular Tumoral , Pulmão/imunologia , Pulmão/patologia , Camundongos Endogâmicos BALB C , Metástase Neoplásica , Fator de Crescimento Insulin-Like I/metabolismo , Regulação Neoplásica da Expressão Gênica , Células Mieloides/imunologia , Células Mieloides/metabolismo , Quimiocinas CC/metabolismo , Quimiocinas CC/genética , Transdução de SinaisRESUMO
Tissue folds are structural motifs critical to organ function. In the intestine, bending of a flat epithelium into a periodic pattern of folds gives rise to villi, finger-like protrusions that enable nutrient absorption. However, the molecular and mechanical processes driving villus morphogenesis remain unclear. Here, we identify an active mechanical mechanism that simultaneously patterns and folds the intestinal epithelium to initiate villus formation. At the cellular level, we find that PDGFRA+ subepithelial mesenchymal cells generate myosin II-dependent forces sufficient to produce patterned curvature in neighboring tissue interfaces. This symmetry-breaking process requires altered cell and extracellular matrix interactions that are enabled by matrix metalloproteinase-mediated tissue fluidization. Computational models, together with in vitro and in vivo experiments, revealed that these cellular features manifest at the tissue level as differences in interfacial tensions that promote mesenchymal aggregation and interface bending through a process analogous to the active dewetting of a thin liquid film.
Assuntos
Matriz Extracelular , Mucosa Intestinal , Animais , Camundongos , Mucosa Intestinal/metabolismo , Mucosa Intestinal/citologia , Matriz Extracelular/metabolismo , Miosina Tipo II/metabolismo , Mesoderma/metabolismo , Mesoderma/citologia , Células-Tronco Mesenquimais/metabolismo , Células-Tronco Mesenquimais/citologia , Receptor alfa de Fator de Crescimento Derivado de Plaquetas/metabolismo , Morfogênese , Metaloproteinases da Matriz/metabolismoRESUMO
A key aspect of nutrient absorption is the exquisite division of labour across the length of the small intestine, with individual nutrients taken up at different proximal:distal positions. For millennia, the small intestine was thought to comprise three segments with indefinite borders: the duodenum, jejunum and ileum. By examining the fine-scale longitudinal transcriptional patterns that span the mouse and human small intestine, we instead identified five domains of nutrient absorption that mount distinct responses to dietary changes, and three regional stem cell populations. Molecular domain identity can be detected with machine learning, which provides a systematic method to computationally identify intestinal domains in mice. We generated a predictive model of transcriptional control of domain identity and validated the roles of Ppar-δ and Cdx1 in patterning lipid metabolism-associated genes. These findings represent a foundational framework for the zonation of absorption across the mammalian small intestine.
Assuntos
Duodeno , Intestino Delgado , Humanos , Camundongos , Animais , Intestino Delgado/metabolismo , Duodeno/metabolismo , Intestinos , Jejuno/metabolismo , Íleo/metabolismo , MamíferosRESUMO
A key aspect of nutrient absorption is the exquisite division of labor across the length of the small intestine, with individual classes of micronutrients taken up at different positions. For millennia, the small intestine was thought to comprise three segments with indefinite borders: the duodenum, jejunum, and ileum. By examining fine-scale longitudinal segmentation of the mouse and human small intestines, we identified transcriptional signatures and upstream regulatory factors that define five domains of nutrient absorption, distinct from the three traditional sections. Spatially restricted expression programs were most prominent in nutrient-absorbing enterocytes but initially arose in intestinal stem cells residing in three regional populations. While a core signature was maintained across mice and humans with different diets and environments, domain properties were influenced by dietary changes. We established the functions of Ppar-Ạand Cdx1 in patterning lipid metabolism in distal domains and generated a predictive model of additional transcription factors that direct domain identity. Molecular domain identity can be detected with machine learning, representing the first systematic method to computationally identify specific intestinal regions in mice. These findings provide a foundational framework for the identity and control of longitudinal zonation of absorption along the proximal:distal small intestinal axis.
RESUMO
Tissue folding generates structural motifs critical to organ function. In the intestine, bending of a flat epithelium into a periodic pattern of folds gives rise to villi, the numerous finger-like protrusions that are essential for nutrient absorption. However, the molecular and mechanical mechanisms driving the initiation and morphogenesis of villi remain a matter of debate. Here, we identify an active mechanical mechanism that simultaneously patterns and folds intestinal villi. We find that PDGFRA+ subepithelial mesenchymal cells generate myosin II-dependent forces sufficient to produce patterned curvature in neighboring tissue interfaces. At the cell-level, this occurs through a process dependent upon matrix metalloproteinase-mediated tissue fluidization and altered cell-ECM adhesion. By combining computational models with in vivo experiments, we reveal these cellular features manifest at the tissue-level as differences in interfacial tensions that promote mesenchymal aggregation and interface bending through a process analogous to the active de-wetting of a thin liquid film.
RESUMO
Tumor metastasis requires systemic remodeling of distant organ microenvironments which impacts immune cell phenotypes, population structure, and intercellular communication networks. However, our understanding of immune phenotypic dynamics in the metastatic niche remains incomplete. Here, we longitudinally assayed lung immune cell gene expression profiles in mice bearing PyMT-driven metastatic breast tumors from the onset of primary tumorigenesis, through formation of the pre-metastatic niche, to the final stages of metastatic outgrowth. Computational analysis of these data revealed an ordered series of immunological changes that correspond to metastatic progression. Specifically, we uncovered a TLR-NFκB myeloid inflammatory program which correlates with pre-metastatic niche formation and mirrors described signatures of CD14+ 'activated' MDSCs in the primary tumor. Moreover, we observed that cytotoxic NK cell proportions increased over time which illustrates how the PyMT lung metastatic niche is both inflammatory and immunosuppressive. Finally, we predicted metastasis-associated immune intercellular signaling interactions involving Igf1 and Ccl6 which may organize the metastatic niche. In summary, this work identifies novel immunological signatures of metastasis and discovers new details about established mechanisms that drive metastatic progression. In brief: McGinnis et al. report a longitudinal scRNA-seq atlas of lung immune cells in mice bearing PyMT-driven metastatic breast tumors and identify immune cell transcriptional states, shifts in population structure, and rewiring of cell-cell signaling networks which correlate with metastatic progression. Highlights: Longitudinal scRNA-seq reveals distinct stages of immune remodeling before, during, and after metastatic colonization in the lungs of PyMT mice.TLR-NFκB inflammation correlates with pre-metastatic niche formation and involves both tissue-resident and bone marrow-derived myeloid cell populations. Inflammatory lung myeloid cells mirror 'activated' primary tumor MDSCs, suggesting that primary tumor-derived cues induce Cd14 expression and TLR-NFκB inflammation in the lung. Lymphocytes contribute to the inflammatory and immunosuppressive lung metastatic microenvironment, highlighted by enrichment of cytotoxic NK cells in the lung over time. Cell-cell signaling network modeling predicts cell type-specific Ccl6 regulation and IGF1-IGF1R signaling between neutrophils and interstitial macrophages.
RESUMO
Gene regulatory networks within cells modulate the expression of the genome in response to signals and changing environmental conditions. Reconstructions of gene regulatory networks can reveal the information processing and control principles used by cells to maintain homeostasis and execute cell-state transitions. Here, we introduce a computational framework, D-SPIN, that generates quantitative models of gene-regulatory networks from single-cell mRNA-seq data sets collected across thousands of distinct perturbation conditions. D-SPIN models the cell as a collection of interacting gene-expression programs, and constructs a probabilistic model to infer regulatory interactions between gene-expression programs and external perturbations. Using large Perturb-seq and drug-response datasets, we demonstrate that D-SPIN models reveal the organization of cellular pathways, sub-functions of macromolecular complexes, and the logic of cellular regulation of transcription, translation, metabolism, and protein degradation in response to gene knockdown perturbations. D-SPIN can also be applied to dissect drug response mechanisms in heterogeneous cell populations, elucidating how combinations of immunomodulatory drugs can induce novel cell states through additive recruitment of gene expression programs. D-SPIN provides a computational framework for constructing interpretable models of gene-regulatory networks to reveal principles of cellular information processing and physiological control.
RESUMO
The rise and fall of estrogen and progesterone across menstrual cycles and during pregnancy regulates breast development and modifies cancer risk. How these hormones impact each cell type in the breast remains poorly understood because they act indirectly through paracrine networks. Using single-cell analysis of premenopausal breast tissue, we reveal a network of coordinated transcriptional programs representing the tissue-level response to changing hormone levels. Our computational approach, DECIPHER-seq, leverages person-to-person variability in breast composition and cell state to uncover programs that co-vary across individuals. We use differences in cell-type proportions to infer a subset of programs that arise from direct cell-cell interactions regulated by hormones. Further, we demonstrate that prior pregnancy and obesity modify hormone responsiveness through distinct mechanisms: obesity reduces the proportion of hormone-responsive cells, whereas pregnancy dampens the direct response of these cells to hormones. Together, these results provide a comprehensive map of the cycling human breast.
Assuntos
Mama , Progesterona , Mama/metabolismo , Comunicação Celular , Estrogênios/metabolismo , Feminino , Humanos , Obesidade/metabolismo , Gravidez , Progesterona/metabolismoRESUMO
Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.
Assuntos
Neoplasias , Animais , Genes ras , Camundongos , Neoplasias/genética , Filogenia , Sequenciamento do ExomaRESUMO
Enhancers integrate transcription factor signaling pathways that drive cell fate specification in the developing brain. We paired enhancer labeling and single-cell RNA-sequencing (scRNA-seq) to delineate and distinguish specification of neuronal lineages in mouse medial, lateral, and caudal ganglionic eminences (MGE, LGE, and CGE) at embryonic day (E)11.5. We show that scRNA-seq clustering using transcription factors improves resolution of regional and developmental populations, and that enhancer activities identify specific and overlapping GE-derived neuronal populations. First, we mapped the activities of seven evolutionarily conserved brain enhancers at single-cell resolution in vivo, finding that the selected enhancers had diverse activities in specific progenitor and neuronal populations across the GEs. We then applied enhancer-based labeling, scRNA-seq, and analysis of in situ hybridization data to distinguish transcriptionally distinct and spatially defined subtypes of MGE-derived GABAergic and cholinergic projection neurons and interneurons. Our results map developmental origins and specification paths underlying neurogenesis in the embryonic basal ganglia and showcase the power of scRNA-seq combined with enhancer-based labeling to resolve the complex paths of neuronal specification underlying mouse brain development.
Assuntos
Gânglios da Base , Neurônios Colinérgicos , Elementos Facilitadores Genéticos , Neurônios GABAérgicos , Neurogênese , Animais , Gânglios da Base/citologia , Gânglios da Base/embriologia , Linhagem da Célula/genética , Neurônios Colinérgicos/metabolismo , Neurônios GABAérgicos/metabolismo , Camundongos , Neurogênese/genética , RNA-Seq , Análise de Célula Única , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismoRESUMO
Microglia are resident macrophages in the brain that emerge in early development and respond to the local environment by altering their molecular and phenotypic states. Fundamental questions about microglia diversity and function during development remain unanswered because we lack experimental strategies to interrogate their interactions with other cell types and responses to perturbations ex vivo. We compared human microglia states across culture models, including cultured primary and pluripotent stem cell-derived microglia. We developed a "report card" of gene expression signatures across these distinct models to facilitate characterization of their responses across experimental models, perturbations, and disease conditions. Xenotransplantation of human microglia into cerebral organoids allowed us to characterize key transcriptional programs of developing microglia in vitro and reveal that microglia induce transcriptional changes in neural stem cells and decrease interferon signaling response genes. Microglia additionally accelerate the emergence of synchronized oscillatory network activity in brain organoids by modulating synaptic density.
Assuntos
Células-Tronco Pluripotentes Induzidas , Células-Tronco Neurais , Encéfalo , Diferenciação Celular , Humanos , Microglia , Modelos Teóricos , OrganoidesRESUMO
Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater than two uniquely aligned reads across the genome to effectively detect multiplets. We evaluate the method by generating snATAC-seq data in the human blood and pancreatic islet samples. AMULET has high precision, estimated via donor-based multiplexing, and high recall, estimated via simulated multiplets, compared to alternatives and identifies multiplets most effectively when a certain read depth of 25K median valid reads per nucleus is achieved.
Assuntos
Sequenciamento de Cromatina por Imunoprecipitação , Software , Idoso , DNA/genética , Humanos , Leucócitos Mononucleares/metabolismo , Funções Verossimilhança , Transposases/metabolismoRESUMO
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) provides high-dimensional measurements of transcript counts in individual cells. However, high assay costs and artifacts associated with analyzing samples across multiple sequencing runs limit the study of large numbers of samples. Sample multiplexing technologies such as MULTI-seq and antibody hashing using single-cell multiplexing kit (SCMK) reagents (BD Biosciences) use sample-specific sequence tags to enable individual samples to be sequenced in a pooled format, markedly lowering per-sample processing and sequencing costs while minimizing technical artifacts. Critically, however, pooling samples could introduce new artifacts, partially negating the benefits of sample multiplexing. In particular, no study to date has evaluated whether pooling peripheral blood mononuclear cells (PBMCs) from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures. RESULTS: Here, we applied the 10x Genomics scRNA-seq platform to MULTI-seq and/or SCMK-labeled PBMCs from a single donor with and without pooling with PBMCs from unrelated donors for 30 min at 4 °C. We did not detect any alloreactivity signal between mixed and unmixed PBMCs across a variety of metrics, including alloreactivity marker gene expression in CD4+ T cells, cell type proportion shifts, and global gene expression profile comparisons using Gene Set Enrichment Analysis and Jensen-Shannon Divergence. These results were additionally mirrored in publicly-available scRNA-seq data generated using a similar experimental design. Moreover, we identified confounding gene expression signatures linked to PBMC preparation method (e.g., Trima apheresis), as well as SCMK sample classification biases against activated CD4+ T cells which were recapitulated in two other SCMK-incorporating scRNA-seq datasets. CONCLUSIONS: We demonstrate that (i) mixing PBMCs from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) does not cause an allogeneic response, and (ii) that Trima apheresis and PBMC sample multiplexing using SCMK reagents can introduce undesirable technical artifacts into scRNA-seq data. Collectively, these observations establish important benchmarks for future cross-sectional immunological scRNA-seq experiments.
Assuntos
Leucócitos Mononucleares/metabolismo , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Transcriptoma , Humanos , Manejo de EspécimesRESUMO
Sample multiplexing facilitates scRNA-seq by reducing costs and identifying artifacts such as cell doublets. However, universal and scalable sample barcoding strategies have not been described. We therefore developed MULTI-seq: multiplexing using lipid-tagged indices for single-cell and single-nucleus RNA sequencing. MULTI-seq reagents can barcode any cell type or nucleus from any species with an accessible plasma membrane. The method involves minimal sample processing, thereby preserving cell viability and endogenous gene expression patterns. When cells are classified into sample groups using MULTI-seq barcode abundances, data quality is improved through doublet identification and recovery of cells with low RNA content that would otherwise be discarded by standard quality-control workflows. We use MULTI-seq to track the dynamics of T-cell activation, perform a 96-plex perturbation experiment with primary human mammary epithelial cells and multiplex cryopreserved tumors and metastatic sites isolated from a patient-derived xenograft mouse model of triple-negative breast cancer.
Assuntos
Lipídeos/química , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Animais , Sequência de Bases , Células HEK293 , Sequenciamento de Nucleotídeos em Larga Escala , HumanosRESUMO
Single-cell RNA sequencing (scRNA-seq) data are commonly affected by technical artifacts known as "doublets," which limit cell throughput and lead to spurious biological conclusions. Here, we present a computational doublet detection tool-DoubletFinder-that identifies doublets using only gene expression data. DoubletFinder predicts doublets according to each real cell's proximity in gene expression space to artificial doublets created by averaging the transcriptional profile of randomly chosen cell pairs. We first use scRNA-seq datasets where the identity of doublets is known to show that DoubletFinder identifies doublets formed from transcriptionally distinct cells. When these doublets are removed, the identification of differentially expressed genes is enhanced. Second, we provide a method for estimating DoubletFinder input parameters, allowing its application across scRNA-seq datasets with diverse distributions of cell types. Lastly, we present "best practices" for DoubletFinder applications and illustrate that DoubletFinder is insensitive to an experimentally validated kidney cell type with "hybrid" expression features.
Assuntos
RNA-Seq/métodos , Análise de Célula Única/métodos , Software , Humanos , RNA-Seq/normas , Análise de Célula Única/normasRESUMO
Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or "tipping point" at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations.