Machine learning predicts putative hematopoietic stem cells within large single-cell transcriptomics data sets.

Hematopoietic stem cells (HSCs) are an essential source and reservoir for normal hematopoiesis, and their function is compromised in many blood disorders. HSC research has benefitted from the recent development of single-cell molecular profiling technologies, where single-cell RNA sequencing (scRNA-seq) in particular has rapidly become an established method to profile HSCs and related hematopoietic populations. The classic definition of HSCs relies on transplantation assays, which have been used to validate HSC function for cell populations defined by flow cytometry. Flow cytometry information for single cells, however, is not available for many new high-throughput scRNA-seq methods, thus highlighting an urgent need for the establishment of alternative ways to pinpoint the likely HSCs within large scRNA-seq data sets. To address this, we tested a range of machine learning approaches and developed a tool, hscScore, to score single-cell transcriptomes from murine bone marrow based on their similarity to gene expression profiles of validated HSCs. We evaluated hscScore across scRNA-seq data from different laboratories, which allowed us to establish a robust method that functions across different technologies. To facilitate broad adoption of hscScore by the wider hematopoiesis community, we have made the trained model and example code freely available online. In summary, our method hscScore provides fast identification of mouse bone marrow HSCs from scRNA-seq measurements and represents a broadly useful tool for analysis of single-cell gene expression data.MRC, Wellcome Trust, Bloodwise, CRU

Charting the single-cell transcriptional landscape of haematopoiesis

High turnover in the haematopoietic system is sustained by stem and progenitor cells, which divide and mature to produce the range of cell types present in the blood. This complex system has long served as a model of differentiation in adult stem cell systems and its study has important clinical relevance. Maintaining a healthy blood system requires regulation of haematopoietic cell fate decisions, with severe dysregulation of these fate choices observed in diseases such as leukaemia. As transcriptional regulation is known to play a role in this regulation, the gene expression of many haematopoietic progenitors has been measured. However, many of the classic populations are actually extremely heterogeneous in both expression and function, highlighting the need for characterising the haematopoietic progenitor compartment at the level of individual cells. The first aim of this work was to chart the single-cell transcriptional landscape of the haematopoietic stem and progenitor cell (HSPC) compartment. To build a comprehensive map of this landscape, 1,654 HSPCs from mouse bone marrow were profiled using single-cell RNA-sequencing. Analysis of these data generated a useful resource, and reconstructed changes in gene expression, cell cycle and RNA content along differentiation trajectories to three blood lineages. To investigate how single-cell gene expression can be used to learn about regulatory relationships, data measuring the expression of 41 genes (including 31 transcription factors) in 2,167 stem and progenitor cells were used to construct Boolean gene regulatory network models describing the regulation of differentiation from stem cells to two different progenitor populations. The inferred relationships revealed positive regulation of Nfe2 and Cbfa2t3h by Gata2 that was unique to differentiation towards megakaryocyte-erythroid progenitors, which was subsequently experimentally validated. The next study focused on investigating the link between transcriptional and functional heterogeneity within blood progenitor populations. Single-cell profiles of human cord blood progenitors revealed a continuum of lympho-myeloid gene expression. Culture assays performed to assess the functional output of single cells found both unilineage and bilineage output and, by investigating the link between surface marker expression and function, a new sorting strategy was devised that was able to enrich for function within conventional lympho-myeloid progenitor sorting gates. The final project aimed to study changes to the HSPC compartment in a perturbed state. A droplet-based single-cell RNA-sequencing dataset of 44,802 cells was analysed to identify entry points to eight blood lineages and to characterise gene expression changes in this transcriptional landscape. Mapping single-cell data from W41/W41 Kit mutant mice highlighted quantitative shifts in progenitor populations such as a reduction in mast cell progenitors and an increase towards more mature progenitors along the erythroid trajectory. Differential gene expression identified upregulation of stress response and a reduction of apoptosis during erythropoiesis as potential compensatory mechanisms in the Kit mutant progenitors. Together this body of work characterises the HSPC compartment at single-cell level and provides methods for how single-cell data can be used to discover regulatory relationships, link expression heterogeneity to function, and investigate changes in the transcriptional landscape in a perturbed environment.This PhD studentship was funded by the Medical Research Counci

Using the Security Protocol Game to teach computer network security

The Security Protocol Game is a highly interactive game for teaching secure data communications protocols. Students use the game to simulate security protocols and explore possible attacks against them. The power of the game lies in the representation it provides for secret and public key cryptography – a unique combination of game rules and playing pieces has been devised that accurately represents the mathematical capabilities of cryptographic systems. Using pen and paper, envelopes and printed game pieces, students can simulate a wide range of computer network security protocols including well-known protocols such as SSL and Pretty Good Privacy. Such simulations enable students to gain a deep understanding of how the protocols operate and how protocol design affects security of the protocol. Student response to the game is positive and engaging. It has been successfully used with both information technology students and management students. This paper presents the game briefly followed by analysis and discussion of a recent survey of student response to the game

Mbd3/NuRD controls lymphoid cell fate and inhibits tumorigenesis by repressing a B cell transcriptional program

Differentiation of lineage-committed cells from multipotent progenitors requires establishment of accessible chromatin at lineage-specific transcriptional enhancers and promoters, which is mediated by pioneer transcription factors that recruit activating chromatin remodeling complexes. Here we show that the Mbd3/NuRD chromatin remodeling complex opposes this transcriptional pioneering during B cell programming of multipotent lymphoid progenitors by restricting chromatin accessibility at B cell enhancers and promoters. Mbd3/NuRD-deficient lymphoid progenitors therefore prematurely activate a B cell transcriptional program and are biased towards overproduction of pro-B cells at the expense of T cell progenitors. The striking reduction in early thymic T cell progenitors results in compensatory hyperproliferation of immature thymocytes and development of T cell lymphoma. Our results reveal that Mbd3/NuRD can regulate multilineage differentiation by constraining the activation of dormant lineage-specific enhancers and promoters. In this way, Mbd3/NuRD protects the multipotency of lymphoid progenitors, preventing B cell-programming transcription factors from prematurely enacting lineage commitment. Mbd3/NuRD therefore controls the fate of lymphoid progenitors, ensuring appropriate production of lineage-committed progeny and suppressing tumour formation.F.C. was supported by an EMBO long-term fellowship (1305-2015 and Marie Curie Actions LTFCOFUND2013/GA-2013-609409). Work in the Green lab is supported Cancer Research UK (grants refs. C1163/A12765 and C1163/A12526), Bloodwise (grant ref. 13003), and core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research (100140/Z/12/Z) and Wellcome Trust-MRC Cambridge Stem Cell Institute (097922/Z/11/Z)

Single-Cell RNA-Sequencing Reveals a Continuous Spectrum of Differentiation in Hematopoietic Cells.

The transcriptional programs that govern hematopoiesis have been investigated primarily by population-level analysis of hematopoietic stem and progenitor cells, which cannot reveal the continuous nature of the differentiation process. Here we applied single-cell RNA-sequencing to a population of hematopoietic cells in zebrafish as they undergo thrombocyte lineage commitment. By reconstructing their developmental chronology computationally, we were able to place each cell along a continuum from stem cell to mature cell, refining the traditional lineage tree. The progression of cells along this continuum is characterized by a highly coordinated transcriptional program, displaying simultaneous suppression of genes involved in cell proliferation and ribosomal biogenesis as the expression of lineage specific genes increases. Within this program, there is substantial heterogeneity in the expression of the key lineage regulators. Overall, the total number of genes expressed, as well as the total mRNA content of the cell, decreases as the cells undergo lineage commitment.The study was supported by Cancer Research UK grant number C45041/A14953 to A.C., C.L. and L.F and a core support grant from the Wellcome Trust and MRC to the Wellcome Trust–Medical Research Council Cambridge Stem Cell Institute. S.T would like to acknowledge the Lister Research Prize from the Lister Institute. The authors declare no competing financial interestsThis is the final version of the article. It first appeared from Cell Press via http://dx.doi.org/10.1016/j.celrep.2015.12.08