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Adult haematopoietic stem cells (HSCs) mainly reside in the bone marrow, where stromal and haematopoietic cells regulate their function. The steady state HSC niche has been extensively studied. In this Review, we focus on how bone marrow microenvironment components respond to different insults including inflammation, malignant haematopoiesis and chemotherapy. We highlight common and unique patterns among multiple cell types and their environment and discuss current limitations in our understanding of this complex and dynamic tissue.In this Review, Batsivari et al. discuss how cells in the bone marrow respond to inflammation, infection, leukaemia and chemotherapy.

Severe infections are a major stress on haematopoiesis, where the consequences for haematopoietic stem cells (HSCs) have only recently started to emerge. HSC function critically depends on the integrity of complex bone marrow (BM) niches; however, what role the BM microenvironment plays in mediating the effects of infection on HSCs remains an open question. Here, using a murine model of malaria and combining single-cell RNA sequencing, mathematical modelling, transplantation assays and intravital microscopy, we show that haematopoiesis is reprogrammed upon infection, whereby the HSC compartment turns over substantially faster than at steady-state and HSC function is drastically affected. Interferon is found to affect both haematopoietic and mesenchymal BM cells and we specifically identify a dramatic loss of osteoblasts and alterations in endothelial cell function. Osteo-active parathyroid hormone treatment abolishes infection-triggered HSC proliferation and—coupled with reactive oxygen species quenching—enables partial rescuing of HSC function.Haltalli et al. show that Plasmodium berghei infection induces interferon release, and affects haematopoietic stem cell proliferation and function, as well as osteoblasts and vascular integrity, in the bone marrow niche.

Niche hijack by malignant cells is considered to be a prominent cause of disease relapse. Barbier and colleagues uncover (E)-selectin as a novel mediator of malignant cell survival and regeneration which, upon blockade, has the potential to significantly improve therapeutic outcomes.

Haematopoiesis in the bone marrow (BM) maintains blood and immune cell production throughout postnatal life. Haematopoiesis first emerges in human BM at 11–12 weeks after conception 1 , 2 , yet almost nothing is known about how fetal BM (FBM) evolves to meet the highly specialized needs of the fetus and newborn. Here we detail the development of FBM, including stroma, using multi-omic assessment of mRNA and multiplexed protein epitope expression. We find that the full blood and immune cell repertoire is established in FBM in a short time window of 6–7 weeks early in the second trimester. FBM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell subsets emerging for the first time. The substantial expansion of B lymphocytes in FBM contrasts with fetal liver at the same gestational age. Haematopoietic progenitors from fetal liver, FBM and cord blood exhibit transcriptional and functional differences that contribute to tissue-specific identity and cellular diversification. Endothelial cell types form distinct vascular structures that we show are regionally compartmentalized within FBM. Finally, we reveal selective disruption of B lymphocyte, erythroid and myeloid development owing to a cell-intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in Down syndrome (trisomy 21). A single-cell atlas of human fetal bone marrow in healthy fetuses and fetuses with Down syndrome provides insight into developmental haematopoiesis in humans and the transcription and functional differences that occur in Down syndrome.

Recent lineage tracing based single-cell techniques (LT-scSeq), e.g., the Lineage And RNA RecoverY (LARRY) barcoding system, have enabled clonally resolved interpretation of differentiation trajectories. However, the heterogeneity of clone-specific kinetics remains understudied, both quantitatively and in terms of interpretability, thus limiting the power of barcoding systems to unravel how heterogeneous stem cell clones drive the overall cell population dynamics. Here, we present CLADES, a NeuralODE-based framework to faithfully estimate the clone and population-specific kinetics from both newly generated and publicly available LARRY LT-scSeq data. By incorporating a stochastic simulation algorithm (SSA) and differential expression gene (DEGs) analysis, CLADES yields the summary of cell division dynamics across differentiation time-courses and reconstructs the lineage tree of the progenitor cells in a quantitative way. Moreover, clone-level behaviors can be grouped into characteristic types by pooling individual clones into meta-clones for analyses at various resolutions. Finally, we show that meta-clone specific cellular behaviors identified by CLADES originate from hematopoietic stem and progenitor cells in distinct transcriptional states. In conclusion, we report a scalable approach to robustly quantify clone-specific differentiation kinetics of cellular populations for time-series systems with static barcoding designs. Recent studies have traced haematopoiesis at the clonal level but lack a way to extract dynamical information. Here, authors develop CLADES, a tool to estimate cellular kinetics and the number of divisions to produce mature cells for each clone, in human cord blood and adult mouse haematopoiesis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Recent lineage tracing single-cell techniques (LT-scSeq), e.g., the Lineage And RNA RecoverY (LARRY) barcoding system, have enabled clonally resolved interpretation of differentiation trajectories. However, the heterogeneity of clone-specific kinetics remains understudied, both quantitatively and in terms of interpretability, thus limiting the power of bar-coding systems to unravel how heterogeneous stem cell clones drive overall cell population dynamics. Here, we present CLADES, a NeuralODE-based framework to faithfully estimate clone-specific kinetics of cell states from newly generated and publicly available human cord blood LARRY LT-scSeq data. By incorporating a stochastic simulation algorithm (SSA) and differential expression gene (DEGs) analysis, CLADES yields cell division dynamics across differentiation timecourses and fate bias predictions for the early progenitor cells. Moreover, clone-level quantitative behaviours can be grouped into characteristic types by pooling individual clones into meta-clones. By benchmarking with CoSpar, we found that CLADES improves fate bias prediction accuracy at the meta-clone level. In conclusion, we report a broadly applicable approach to robustly quantify differentiation kinetics using meta-clones while providing valuable insights into the fate bias of cellular populations for any organ system maintained by a pool of heterogeneous stem and progenitor cells.

Acute myeloid leukemia (AML) continues to have a poor prognosis due to its ability to relapse following initial response to chemotherapy. While immunotherapies hold the promise to revolutionize cancer treatment, AML has been particularly challenging to target. It is therefore important to better understand the relationship between AML cells and immune cells within the bone marrow (BM) microenvironment, where this disease grows. Here we focus on non-malignant BM macrophages, and using a combination of intravital microscopy, flow cytometry, transcriptomics and functional analyses we identify a subpopulation of immunomodulatory BM macrophages (IMMs) with a unique profile and function during AML progression. While the majority of macrophages are already being lost at early infiltration, IMMs are locally enriched. They are capable of efferocytosis and support AML growth through inhibition of T cells. Enrichment of IMMs in the BM of patients developing early relapse indicates that future development of interventions that target IMMs’ development and function may improve AML patients’ outcome.

The paradigmatic tree model of hematopoiesis is increasingly recognized to be limited as it is based on heterogeneous populations and largely inferred from non-homeostatic cell fate assays. Here, we combine persistent labeling with time-series single-cell RNA-Seq to build the first real- time, quantitative model of in vivo tissue dynamics for any mammalian organ. We couple cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. The resulting explicit linkage between single cell molecular states and cellular behavior reveals widely varying self-renewal and differentiation properties across distinct lineages. Transplanted stem cells show strong acceleration of neutrophil differentiation, illustrating how the new model can quantify the impact of perturbations. Our reconstruction of dynamic behavior from snapshot measurements is akin to how a Kinetoscope allows sequential images to merge into a movie. We posit that this approach is broadly applicable to empower single cell genomics to reveal important tissue scale dynamics information. Cell flux analysis reveals high-resolution kinetics of native bone marrow hematopoiesis Quantitative model simulates cell behavior in real-time and connects it with gene expression patterns Distinct lineage-affiliated progenitors have unique self-renewal and differentiation properties Transplanted HSCs display accelerated stage- and lineage-specific differentiation

Abstract Acute myeloid leukemia (AML) is a blood cancer of the myeloid lineage. Its prognosis remains poor, highlighting the need for new therapeutic and precision medicine approaches. AML symptoms often include cytopenias, linked to loss of healthy hematopoietic stem and progenitor cells (HSPCs). The mechanism behind HSPC decline is complex and still poorly understood. Here, intravital microscopy (IVM) of a well-established experimental model of AML allows direct observation of the interactions between healthy and malignant cells in the bone marrow (BM), suggesting that physical dislodgment of healthy cells by AML through damaged vasculature may play an important role. Numerous human leukemia types, particularly MLL-AF9 samples, show high expression levels of multiple matrix metalloproteinases (MMPs). Therefore, we evaluate the therapeutic potential of the MMP inhibitor (MMPI) prinomastat. IVM analyses of treated mice reveal reduced vascular permeability and healthy cell clusters in circulation, and lower AML cell speed. Furthermore, treated mice have decreased BM infiltration, increased retention of healthy HSPCs in the BM and increased survival following chemotherapy. Overall, our results suggest that MMPIs could be a promising complementary therapy to reduce AML growth and limit the loss of HSPC and BM vascular damage caused by MLL-AF9 and possibly other AML subtypes. Competing Interest Statement The authors have declared no competing interest. Footnotes * The authors have declared that no conflict of interest exists.