The expression of ZAP-70 in a subset of CLL patients strongly correlates with a more aggressive clinical course, though the exact underlying mechanisms remain elusive. The ability of ZAP-70 to enhance B cell receptor (BCR) signaling, independently of its kinase function, is considered to contribute. Here we employed RNA-sequencing and proteomic analyses of primary cells differing only in their expression of ZAP-70 to further define how ZAP-70 increases aggressiveness of CLL. We identified that ZAP-70 is directly required for cell survival in the absence of an overt BCR signal, which can compensate for ZAP-70 deficiency as an anti-apoptotic signal. In addition, the expression of ZAP-70 regulates the transcription of factors regulating recruitment and activation of T cells, such as CCL3, CCL4 and IL4I1. Quantitative mass spectrometry of double-cross linked ZAP-70 complexes further demonstrated constitutive and direct protein-protein interactions between ZAP-70 and BCR-signaling components. Unexpectedly, ZAP-70 also binds to ribosomal proteins, which is not dependent on, but further increased by BCR-stimulation. Importantly, decreased expression of ZAP-70 significantly reduced MYC-expression and global protein synthesis, providing evidence that ZAP-70 contributes to translational dysregulation in CLL. In conclusion, ZAP-70 constitutively promotes cell survival, microenvironment-interactions and protein synthesis in CLL cells, likely to improve cellular fitness and to further drive disease progression.
Platelet deficiency, known as thrombocytopenia, can cause hemorrhage and is treated with platelet transfusions. We developed a system for the production of platelet precursor cells, megakaryocytes, from pluripotent stem cells. These cultures can be maintained for >100 days, implying culture renewal by megakaryocyte progenitors (MKPs). However, it is unclear whether the MKP state in vitro mirrors the state in vivo, and MKPs cannot be purified using conventional surface markers. We performed single-cell RNA sequencing throughout in vitro differentiation and mapped each state to its equivalent in vivo. This enabled the identification of five surface markers that reproducibly purify MKPs, allowing us insight into their transcriptional and epigenetic profiles. Last, we performed culture optimization, increasing MKP production. Together, this study has mapped parallels between the MKP states in vivo and in vitro and allowed the purification of MKPs, accelerating the progress of in vitro–derived transfusion products toward the clinic.
The transition from bulk to single-cell analyses refocused the computational challenges for high-throughput sequencing data-processing. The core of single-cell pipelines is partitioning cells and assigning cell-identities; extensive consequences derive from this step; generating robust and reproducible outputs is essential. From benchmarking established single-cell pipelines, we observed that clustering results critically depend on algorithmic choices (e.g. method, parameters) and technical details (e.g. random seeds). We present ClustAssess, a suite of tools for quantifying clustering robustness both within and across methods. The tools provide fine-grained information enabling (a) the detection of optimal number of clusters, (b) identification of regions of similarity (and divergence) across methods, (c) a data driven assessment of optimal parameter ranges. The aim is to assist practitioners in evaluating the robustness of cell-identity inference based on the partitioning, and provide information for choosing robust clustering methods and parameters. We illustrate its use on three case studies: a single-cell dataset of in-vivo hematopoietic stem and progenitors (10x Genomics scRNA-seq), in-vitro endoderm differentiation (SMART-seq), and multimodal in-vivo peripheral blood (10x RNA+ATAC). The additional checks offer novel viewpoints on clustering stability, and provide a framework for consistent decision-making on preprocessing, method choice, and parameters for clustering.
Over the past two decades, the advances in high throughput sequencing (HTS) enabled the characterisation of biological processes at an unprecedented level of detail; as a result the vast majority of hypotheses in molecular biology rely on analyses of HTS data. However, achieving increased robustness and reproducibility of results remains one of the main challenges across analyses. Although variability in results may be introduced at various stages, such as alignment, summarisation or detection of differences in expression, one source of variability has been systematically omitted: the consequences of choices that influence the sequencing design which propagate through analyses and introduce an additional layer of technical variation. In this study, we illustrate qualitative and quantitative differences in results arising from the splitting of samples across lanes, on bulk and single cell sequencing outputs. For bulk mRNAseq data, we focus on differential expression and enrichment analyses; for bulk ChIPseq data, we investigate the effect on peak calling, and the peaks' properties. At single cell level, we concentrate on the identification of cell subpopulations (cells clustered based on their expression profiles). We rely on the identity of markers used for assigning cell identities; both smartSeq and 10x data are presented. We conclude that the observed reduction in the number of unique sequenced fragments reduces the level of detail on which the different prediction approaches depend. Further, the sequencing stochasticity adds in a weighting bias corroborated with variable sequencing depths.
The advances in high-throughput sequencing (HTS) have enabled the characterisation of biological processes at an unprecedented level of detail; most hypotheses in molecular biology rely on analyses of HTS data. However, achieving increased robustness and reproducibility of results remains a main challenge. Although variability in results may be introduced at various stages, e.g., alignment, summarisation or detection of differential expression, one source of variability was systematically omitted: the sequencing design, which propagates through analyses and may introduce an additional layer of technical variation. We illustrate qualitative and quantitative differences arising from splitting samples across lanes on bulk and single-cell sequencing. For bulk mRNAseq data, we focus on differential expression and enrichment analyses; for bulk ChIPseq data, we investigate the effect on peak calling and the peaks’ properties. At the single-cell level, we concentrate on identifying cell subpopulations. We rely on markers used for assigning cell identities; both smartSeq and 10× data are presented. The observed reduction in the number of unique sequenced fragments limits the level of detail on which the different prediction approaches depend. Furthermore, the sequencing stochasticity adds in a weighting bias corroborated with variable sequencing depths and (yet unexplained) sequencing bias. Subsequently, we observe an overall reduction in sequencing complexity and a distortion in the biological signal across technologies, experimental contexts, organisms and tissues.
SummaryPlatelet deficiency, known as thrombocytopenia, can cause haemorrhage and is treated with platelet transfusions. We developed a system for the production of platelet precursor cells, megakaryocytes, from pluripotent stem cells. These cultures can be maintained for >100 days, implying culture renewal by megakaryocyte progenitors (MKPs). However, it is unclear whether the MKP state in vitro mirrors the state in vivo, and MKPs cannot be purified using conventional surface markers. We performed single cell RNA sequencing throughout in vitro differentiation and mapped each state to its equivalent in vivo. This enabled the identification of 5 surface markers which reproducibly purify MKPs, allowing us an insight into their transcriptional and epigenetic profiles. Finally, we performed culture optimisation, increasing MKP production. Altogether, this study has mapped parallels between the MKP states in vivo and in vitro and allowed the purification of MKPs, accelerating the progress of in vitro-derived transfusion products towards the clinic.
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