Understanding the molecular programs that guide differentiation during development is a major challenge. Here, we introduce Waddington-OT, an approach for studying developmental time courses to infer ...ancestor-descendant fates and model the regulatory programs that underlie them. We apply the method to reconstruct the landscape of reprogramming from 315,000 single-cell RNA sequencing (scRNA-seq) profiles, collected at half-day intervals across 18 days. The results reveal a wider range of developmental programs than previously characterized. Cells gradually adopt either a terminal stromal state or a mesenchymal-to-epithelial transition state. The latter gives rise to populations related to pluripotent, extra-embryonic, and neural cells, with each harboring multiple finer subpopulations. The analysis predicts transcription factors and paracrine signals that affect fates and experiments validate that the TF Obox6 and the cytokine GDF9 enhance reprogramming efficiency. Our approach sheds light on the process and outcome of reprogramming and provides a framework applicable to diverse temporal processes in biology.
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•Optimal transport analysis recovers trajectories from 315,000 scRNA-seq profiles•Induced pluripotent stem cell reprogramming produces diverse developmental programs•Regulatory analysis identifies a series of TFs predictive of specific cell fates•Transcription factor Obox6 and cytokine GDF9 increase reprogramming efficiency
Application of a new analytical approach to examine developmental trajectories of single cells offers insight into how paracrine interactions shape reprogramming.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Stroma is a poorly defined non-parenchymal component of virtually every organ with key roles in organ development, homeostasis, and repair. Studies of the bone marrow stroma have defined individual ...populations in the stem cell niche regulating hematopoietic regeneration and capable of initiating leukemia. Here, we use single-cell RNA sequencing (scRNA-seq) to define a cellular taxonomy of the mouse bone marrow stroma and its perturbation by malignancy. We identified seventeen stromal subsets expressing distinct hematopoietic regulatory genes spanning new fibroblastic and osteoblastic subpopulations including distinct osteoblast differentiation trajectories. Emerging acute myeloid leukemia impaired mesenchymal osteogenic differentiation and reduced regulatory molecules necessary for normal hematopoiesis. These data suggest that tissue stroma responds to malignant cells by disadvantaging normal parenchymal cells. Our taxonomy of the stromal compartment provides a comprehensive bone marrow cell census and experimental support for cancer cell crosstalk with specific stromal elements to impair normal tissue function and thereby enable emergent cancer.
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•A single-cell bone marrow stromal cell atlas at steady-state and emergent leukemia•A portal for comparative cell and molecular analyses of bone marrow stromal cells•Distinction among putative niche cells and types of osteolineage differentiation•Leukemia remodeling of stroma to the disadvantage of normal hematopoietic cells
Molecular definition of the cell populations comprising bone marrow stroma is provided with single-cell resolution. Seventeen distinct cell subsets with new mesenchymal, pericyte, fibroblast, and endothelial subpopulations, new inferred osteolineage differentiation trajectories, and distinctions among Lepr, Nestin, and NG2-expressing HSC niche populations are defined. The changes imposed by an emergent AML indicate impaired stromal differentiation among mesenchymal cells and decreased expression of hematopoietic regulatory genes consistent with cancer cells indirectly impairing the normal hematopoietic cells with whom they must compete.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Massively parallel single-cell and single-nucleus RNA sequencing has opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so is the need ...for computational pipelines for scaled analysis. Here we developed Cumulus-a cloud-based framework for analyzing large-scale single-cell and single-nucleus RNA sequencing datasets. Cumulus combines the power of cloud computing with improvements in algorithm and implementation to achieve high scalability, low cost, user-friendliness and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies.
Biologistics provides data for quantitative analysis of transport (diffusion) processes and their spatio-temporal correlations in cells. Mobility of proteins is one of the few parameters necessary to ...describe reaction rates for gene regulation. Although understanding of diffusion-limited biochemical reactions in vivo requires mobility data for the largest possible number of proteins in their native forms, currently, there is no database that would contain the complete information about the diffusion coefficients (DCs) of proteins in a given cell type.
We demonstrate a method for the determination of in vivo DCs for any molecule--regardless of its molecular weight, size and structure--in any type of cell. We exemplify the method with the database of in vivo DC for all proteins (4302 records) from the proteome of K12 strain of Escherichia coli, together with examples of DC of amino acids, sugars, RNA and DNA. The database follows from the scale-dependent viscosity reference curve (sdVRC). Construction of sdVRC for prokaryotic or eukaryotic cell requires ~20 in vivo measurements using techniques such as fluorescence correlation spectroscopy (FCS), fluorescence recovery after photobleaching (FRAP), nuclear magnetic resonance (NMR) or particle tracking. The shape of the sdVRC would be different for each organism, but the mathematical form of the curve remains the same. The presented method has a high predictive power, as the measurements of DCs of several inert, properly chosen probes in a single cell type allows to determine the DCs of thousands of proteins. Additionally, obtained mobility data allow quantitative study of biochemical interactions in vivo.
rholyst@ichf.edu.pl.
Supplementary data are available at Bioinformatics Online.
During postnatal life, thymopoiesis depends on the continuous colonization of the thymus by bone-marrow-derived hematopoietic progenitors that migrate through the bloodstream. The current ...understanding of the nature of thymic immigrants is largely based on data from pre-clinical models. Here, we employed single-cell RNA sequencing (scRNA-seq) to examine the immature postnatal thymocyte population in humans. Integration of bone marrow and peripheral blood precursor datasets identified two putative thymus seeding progenitors that varied in expression of CD7; CD10; and the homing receptors CCR7, CCR9, and ITGB7. Whereas both precursors supported T cell development, only one contributed to intrathymic dendritic cell (DC) differentiation, predominantly of plasmacytoid dendritic cells. Trajectory inference delineated the transcriptional dynamics underlying early human T lineage development, enabling prediction of transcription factor (TF) modules that drive stage-specific steps of human T cell development. This comprehensive dataset defines the expression signature of immature human thymocytes and provides a resource for the further study of human thymopoiesis.
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•scRNA-seq and CITE-seq identify two thymus seeding progenitors in human postnatal thymus•The human thymus is colonized by distinct T and non-T lineage precursors•Immature thymocytes differentiate mainly into T and DC lineage cells•Transcriptional dynamics reveal regulatory networks similar to and distinct from mouse
T cell development is dependent on the migration of precursor cells from the bone marrow toward the thymus, but their nature has remained unclear in human. Using scRNA-seq and data integration across tissues, Lavaert et al. identify two distinct precursor subsets that can colonize the thymus to support postnatal T cell development.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Bimodality of gene expression, as a mechanism contributing to phenotypic diversity, enhances the survival of cells in a fluctuating environment. To date, the bimodal response of a gene regulatory ...system has been attributed to the cooperativity of transcription factor binding or to feedback loops. It has remained unclear whether noncooperative binding of transcription factors can give rise to bimodality in an open-loop system. We study a theoretical model of gene expression in a two-step cascade (a deterministically monostable system) in which the regulatory gene produces transcription factors that have a nonlinear effect on the activity of the target gene. We show that a unimodal distribution of transcription factors over the cell population can generate a bimodal steadystate output without cooperative transcription factor binding. We introduce a simple method of geometric construction that allows one to predict the onset of bimodality. The construction only involves the parameters of bursting of the regulatory gene and the dose—response curve of the target gene. Using this method, we show that the gene expression may switch between unimodal and bimodal as the concentration of inducers or corepressors is varied. These findings may explain the experimentally observed bimodal response of cascades consisting of a fluorescent protein reporter controlled by the tetracycline repressor. The geometric construction provides a useful tool for designing experiments and for interpretation of their results. Our findings may have important implications for understanding the strategies adopted by cell populations to survive in changing environments.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
This paper deals with the recent phenomenological model of the motion of nanoscopic objects (colloidal particles, proteins, nanoparticles, molecules) in complex liquids. We analysed motion in ...polymer, micellar, colloidal and protein solutions and the cytoplasm of living cells using the length-scale dependent viscosity model. Viscosity monotonically approaches macroscopic viscosity as the size of the object increases and thus gives a single, coherent picture of motion at the nano and macro scale. The model includes interparticle interactions (solvent-solute), temperature and the internal structure of a complex liquid. The depletion layer ubiquitously occurring in complex liquids is also incorporated into the model. We also discuss the biological aspects of crowding in terms of the length-scale dependent viscosity model.
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•The viscosity is length-scale dependent.•Discussed model is valid in polymers, colloids and living cells.•The model unifies motion at all length-scales.•The model includes interparticle interactions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when ...processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.
The dimeric motor protein kinesin-1 moves processively along microtubules against forces of up to 7 pN. However, the mechanism of force generation is still debated. Here, we point to the crucial ...importance of diffusion of the tethered motor domain for the stepping of kinesin-1: small crowders stop the motor at a viscosity of 5 mPa·s-corresponding to a hydrodynamic load in the sub-fN (~10^{-4} pN) range-whereas large crowders have no impact even at viscosities above 100 mPa·s. This indicates that the scale-dependent, effective viscosity experienced by the tethered motor domain is a key factor determining kinesin's functionality. Our results emphasize the role of diffusion in the kinesin-1 stepping mechanism and the general importance of the viscosity scaling paradigm in nanomechanics.
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CMK, CTK, FMFMET, IJS, NUK, PNG, UM
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