Delineating hierarchical cellular states, including rare intermediates and the networks of regulatory genes that orchestrate cell-type specification, are continuing challenges for developmental ...biology. Single-cell RNA sequencing is greatly accelerating such research, given its power to provide comprehensive descriptions of genomic states and their presumptive regulators. Haematopoietic multipotential progenitor cells, as well as bipotential intermediates, manifest mixed-lineage patterns of gene expression at a single-cell level. Such mixed-lineage states may reflect the molecular priming of different developmental potentials by co-expressed alternative-lineage determinants, namely transcription factors. Although a bistable gene regulatory network has been proposed to regulate the specification of either neutrophils or macrophages, the nature of the transition states manifested in vivo, and the underlying dynamics of the cell-fate determinants, have remained elusive. Here we use single-cell RNA sequencing coupled with a new analytic tool, iterative clustering and guide-gene selection, and clonogenic assays to delineate hierarchical genomic and regulatory states that culminate in neutrophil or macrophage specification in mice. We show that this analysis captured prevalent mixed-lineage intermediates that manifested concurrent expression of haematopoietic stem cell/progenitor and myeloid progenitor cell genes. It also revealed rare metastable intermediates that had collapsed the haematopoietic stem cell/progenitor gene expression programme, instead expressing low levels of the myeloid determinants, Irf8 and Gfi1 (refs 9, 10, 11, 12, 13). Genetic perturbations and chromatin immunoprecipitation followed by sequencing revealed Irf8 and Gfi1 as key components of counteracting myeloid-gene-regulatory networks. Combined loss of these two determinants 'trapped' the metastable intermediate. We propose that mixed-lineage states are obligatory during cell-fate specification, manifest differing frequencies because of their dynamic instability and are dictated by counteracting gene-regulatory networks.
Granulocyte-monocyte progenitors (GMPs) and monocyte-dendritic cell progenitors (MDPs) produce monocytes during homeostasis and in response to increased demand during infection. Both progenitor ...populations are thought to derive from common myeloid progenitors (CMPs), and a hierarchical relationship (CMP-GMP-MDP-monocyte) is presumed to underlie monocyte differentiation. Here, however, we demonstrate that mouse MDPs arose from CMPs independently of GMPs, and that GMPs and MDPs produced monocytes via similar but distinct monocyte-committed progenitors. GMPs and MDPs yielded classical (Ly6Chi) monocytes with gene expression signatures that were defined by their origins and impacted their function. GMPs produced a subset of “neutrophil-like” monocytes, whereas MDPs gave rise to a subset of monocytes that yielded monocyte-derived dendritic cells. GMPs and MDPs were also independently mobilized to produce specific combinations of myeloid cell types following the injection of microbial components. Thus, the balance of GMP and MDP differentiation shapes the myeloid cell repertoire during homeostasis and following infection.
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•GMPs and MDPs independently produce functionally distinct inflammatory monocytes•GMPs produce “neutrophil-like” inflammatory monocytes•MDPs produce monocyte-derived dendritic cells (moDCs)•Microbial stimuli differentially regulate monocyte production by GMPs and MDPs
Yáñez et al. show that functionally distinct inflammatory monocytes, including those producing monocyte-derived DCs and a “neutrophil-like” subset, arise from bone marrow progenitors via two independent pathways. Their analyses reveal that the repertoire of myeloid cells produced under steady-state and stress conditions depends on which progenitors are mobilized to differentiate.
•Interactive resource for bone marrow donor variation between cell populations.•Deep evaluation of Human Cell Atlas (HCA) data spanning eight donors and 100,000 cells.•Identification of 35 specified ...and novel progenitor populations and trajectories.•Hematopoietic stem cell (HSC) number and electron transport chain gene expression decrease with age.
The Human Cell Atlas (HCA) is expected to facilitate the creation of reference cell profiles, marker genes, and gene regulatory networks that will provide a deeper understanding of healthy and disease cell types from clinical biospecimens. The hematopoietic system includes dozens of distinct, transcriptionally coherent cell types, including intermediate transitional populations that have not been previously described at a molecular level. Using the first data release from the HCA bone marrow tissue project, we resolved common, rare, and potentially transitional cell populations from over 100,000 hematopoietic cells spanning 35 transcriptionally coherent groups across eight healthy donors using emerging new computational approaches. These data highlight novel mixed-lineage progenitor populations and putative trajectories governing granulocytic, monocytic, lymphoid, erythroid, megakaryocytic, and eosinophil specification. Our analyses suggest significant variation in cell-type composition and gene expression among donors, including biological processes affected by donor age. To enable broad exploration of these findings, we provide an interactive website to probe intra-cell and extra-cell population differences within and between donors and reference markers for cellular classification and cellular trajectories through associated progenitor states.
Granulocyte-colony stimulating factor receptor (G-CSFR) controls myeloid progenitor proliferation and differentiation to neutrophils. Mutations in CSF3R (encoding G-CSFR) have been reported in ...patients with chronic neutrophilic leukemia (CNL) and acute myeloid leukemia (AML); however, despite years of research, the malignant downstream signaling of the mutated G-CSFRs is not well understood. Here, we used a quantitative phospho-tyrosine analysis to generate a comprehensive signaling map of G-CSF induced tyrosine phosphorylation in the normal versus mutated (proximal: T618I and truncated: Q741x) G-CSFRs. Unbiased clustering and kinase enrichment analysis identified rapid induction of phospho-proteins associated with endocytosis by the wild type G-CSFR only; while G-CSFR mutants showed abnormal kinetics of canonical Stat3, Stat5, and Mapk phosphorylation, and aberrant activation of Bruton's Tyrosine Kinase (Btk). Mutant-G-CSFR-expressing cells displayed enhanced sensitivity (3-5-fold lower IC50) for ibrutinib-based chemical inhibition of Btk. Primary murine progenitor cells from G-CSFR-Q741x knock-in mice validated activation of Btk by the mutant receptor and retrovirally transduced human CD34
umbilical cord blood cells expressing mutant receptors displayed enhanced sensitivity to Ibrutinib. A significantly lower clonogenic potential was displayed by both murine and human primary cells expressing mutated receptors upon ibrutinib treatment. Finally, a dramatic synergy was observed between ibrutinib and ruxolinitib at lower dose of the individual drug. Altogether, these data demonstrate the strength of unsupervised proteomics analyses in dissecting oncogenic pathways, and suggest repositioning Ibrutinib for therapy of myeloid leukemia bearing CSF3R mutations. Phospho-tyrosine data are available via ProteomeXchange with identifier PXD009662.
Abstract
Motivation
While conventional flow cytometry is limited to dozens of markers, new experimental and computational strategies, such as Infinity Flow, allow for the generation and imputation of ...hundreds of cell surface protein markers in millions of cells. Here, we describe an end-to-end analysis workflow for Infinity Flow data in Python.
Results
pyInfinityFlow enables the efficient analysis of millions of cells, without down-sampling, through direct integration with well-established Python packages for single-cell genomics analysis. pyInfinityFlow accurately identifies both common and extremely rare cell populations which are challenging to define from single-cell genomics studies alone. We demonstrate that this workflow can nominate novel markers to design new flow cytometry gating strategies for predicted cell populations. pyInfinityFlow can be extended to diverse cell discovery analyses with flexibility to adapt to diverse Infinity Flow experimental designs.
Availability and implementation
pyInfinityFlow is freely available in GitHub (https://github.com/KyleFerchen/pyInfinityFlow) and on PyPI (https://pypi.org/project/pyInfinityFlow/). Package documentation with tutorials on a test dataset is available by Read the Docs (pyinfinityflow.readthedocs.io). The scripts and data for reproducing the results are available at https://github.com/KyleFerchen/pyInfinityFlow/tree/main/analysis_scripts, along with the raw flow cytometry input data.
The metabolic requirements of hematopoietic stem cells (HSCs) change with their cell cycle activity. However, the underlying role of mitochondria remains ill-defined. Here we found that, after ...mitochondrial activation with replication, HSCs irreversibly remodel the mitochondrial network and that this network is not repaired after HSC re-entry into quiescence, contrary to hematopoietic progenitors. HSCs keep and accumulate dysfunctional mitochondria through asymmetric segregation during active division. Mechanistically, mitochondria aggregate and depolarize after stress because of loss of activity of the mitochondrial fission regulator Drp1 onto mitochondria. Genetic and pharmacological studies indicate that inactivation of Drp1 causes loss of HSC regenerative potential while maintaining HSC quiescence. Molecularly, HSCs carrying dysfunctional mitochondria can re-enter quiescence but fail to synchronize the transcriptional control of core cell cycle and metabolic components in subsequent division. Thus, loss of fidelity of mitochondrial morphology and segregation is one type of HSC divisional memory and drives HSC attrition.
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•HSCs permanently remodel the mitochondrial network after replicative stress•HSCs keep dysfunctional mitochondria because of Drp1 loss, causing functional decline•HSCs accumulate dysfunctional mitochondria through asymmetric division•HSC attrition is due to asynchrony in cell cycle and biosynthetic gene expression
Hinge et al. show that mitochondria are permanently remodeled after HSC division despite re-entry into quiescence. HSCs keep dysfunctional mitochondria through asymmetric segregation during mitosis, which does not prevent reversible HSC quiescence and cell cycle progression but drives their functional decline via asynchrony in the cell cycle and biosynthetic gene expression.
Granulocyte-monocyte progenitors (GMPs) have been previously defined for their potential to generate various myeloid progenies such as neutrophils and monocytes. Although studies have proposed ...lineage heterogeneity within GMPs, it is unclear if committed progenitors already exist among these progenitors and how they may behave differently during inflammation. By combining single-cell transcriptomic and proteomic analyses, we identified the early committed progenitor within the GMPs responsible for the strict production of neutrophils, which we designate as proNeu1. Our dissection of the GMP hierarchy led us to further identify a previously unknown intermediate proNeu2 population. Similar populations could be detected in human samples. proNeu1s, but not proNeu2s, selectively expanded during the early phase of sepsis at the expense of monocytes. Collectively, our findings help shape the neutrophil maturation trajectory roadmap and challenge the current definition of GMPs.
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•GMPs are heterogeneous at the transcriptomic and proteomic level•An early committed neutrophil progenitor (proNeu1) exists within GMPs•proNeu1 gives rise to proNeu2, sequentially differentiating into mature neutrophil•proNeu1 specifically expands during emergency granulopoiesis
The daily production of circulating neutrophils depends on committed and proliferative progenitors, but the ontogenic pathway of neutrophil progenitors remains poorly defined. Integrating multiple single-cell-based technologies, Kwok et al. resolve GMP heterogeneity to identify an early committed neutrophil progenitor (proNeu1) and map out the entire neutrophil developmental pathway in steady state and emergency granulopoiesis.
Obesity is a chronic organismal stress that disrupts multiple systemic and tissue-specific functions. In this study, we describe the impact of obesity on the activity of the hematopoietic stem cell ...(HSC) compartment. We show that obesity alters the composition of the HSC compartment and its activity in response to hematopoietic stress. The impact of obesity on HSC function is progressively acquired but persists after weight loss or transplantation into a normal environment. Mechanistically, we establish that the oxidative stress induced by obesity dysregulates the expression of the transcription factor Gfi1 and that increased
expression is required for the abnormal HSC function induced by obesity. These results demonstrate that obesity produces durable changes in HSC function and phenotype and that elevation of Gfi1 expression in response to the oxidative environment is a key driver of the altered HSC properties observed in obesity. Altogether, these data provide phenotypic and mechanistic insight into durable hematopoietic dysregulations resulting from obesity.
Methods for single-cell RNA sequencing (scRNA-seq) have greatly advanced in recent years. While droplet- and well-based methods have increased the capture frequency of cells for scRNA-seq, these ...technologies readily produce technical artifacts, such as doublet cell captures. Doublets occurring between distinct cell types can appear as hybrid scRNA-seq profiles, but do not have distinct transcriptomes from individual cell states. We introduce DoubletDecon, an approach that detects doublets with a combination of deconvolution analyses and the identification of unique cell-state gene expression. We demonstrate the ability of DoubletDecon to identify synthetic, mixed-species, genetic, and cell-hashing cell doublets from scRNA-seq datasets of varying cellular complexity with a high sensitivity relative to alternative approaches. Importantly, this algorithm prevents the prediction of valid mixed-lineage and transitional cell states as doublets by considering their unique gene expression. DoubletDecon has an easy-to-use graphical user interface and is compatible with diverse species and unsupervised population detection algorithms.
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•DoubletDecon uses deconvolution to identify and remove doublets in scRNA-seq data•Retention of doublets can confound data analysis and cell population identification•DoubletDecon limits erroneous removal of transitional and progenitor cells•The algorithm identifies unique doublets relative to alternative approaches
Multiplets are a source of confounding gene expression in single-cell RNA sequencing (scRNA-seq) that result from the simultaneous capture of multiple cells in a droplet. DePasquale et al. introduce DoubletDecon to identify putative doublets and to consider unique gene expression inherent to transitional states and progenitors to “rescue” singlet captures from inaccurate classification.
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