Accounting for Errors in Data Improves Divergence Time Estimates in Single-cell Cancer Evolution

Single-cell sequencing provides a new way to explore the evolutionary history of cells. Compared to traditional bulk sequencing, where a population of heterogeneous cells is pooled to form a single observation, single-cell sequencing isolates and amplifies genetic material from individual cells, thereby preserving the information about the origin of the sequences. However, single-cell data are more error-prone than bulk sequencing data due to the limited genomic material available per cell. Here, we present error and mutation models for evolutionary inference of single-cell data within a mature and extensible Bayesian framework, BEAST2. Our framework enables integration with biologically informative models such as relaxed molecular clocks and population dynamic models. Our simulations show that modeling errors increase the accuracy of relative divergence times and substitution parameters. We reconstruct the phylogenetic history of a colorectal cancer patient and a healthy patient from single-cell DNA sequencing data. We find that the estimated times of terminal splitting events are shifted forward in time compared to models which ignore errors. We observed that not accounting for errors can overestimate the phylogenetic diversity in single-cell DNA sequencing data. We estimate that 30–50% of the apparent diversity can be attributed to error. Our work enables a full Bayesian approach capable of accounting for errors in the data within the integrative Bayesian software framework BEAST2.     

Integrating multiple references for single-cell assignment

Efficient single-cell assignment is essential for single-cell sequencing data analysis. With the explosive growth of single-cell sequencing data, multiple single-cell sequencing data sources are available for the same kind of tissue, which can be integrated to further improve single-cell assignment; however, an efficient integration strategy is still lacking due to the great challenges of data heterogeneity existing in multiple references. To this end, we present mtSC, a flexible single-cell assignment framework that integrates multiple references based on multitask deep metric learning designed specifically for cell type identification within tissues with multiple single-cell sequencing data as references. We evaluated mtSC on a comprehensive set of publicly available benchmark datasets and demonstrated its state-of-the-art effectiveness for integrative single-cell assignment with multiple references.     

A Genetic Bottleneck of Mitochondrial DNA During Human Lymphocyte Development

Mitochondria are essential organelles in eukaryotic cells that provide critical support for energetic and metabolic homeostasis. Although the elimination of pathogenic mitochondrial DNA (mtDNA) mutations in somatic cells has been observed, the mechanisms to maintain proper functions despite their mtDNA mutation load are poorly understood. In this study, we analyzed somatic mtDNA mutations in more than 30,000 single human peripheral and bone marrow mononuclear cells. We observed a significant overrepresentation of homoplasmic mtDNA mutations in B, T, and natural killer (NK) lymphocytes. Intriguingly, their overall mutational burden was lower than that in hematopoietic progenitors and myeloid cells. This characteristic mtDNA mutational landscape indicates a genetic bottleneck during lymphoid development, as confirmed with single-cell datasets from multiple platforms and individuals. We further demonstrated that mtDNA replication lags behind cell proliferation in both pro-B and pre-B progenitor cells, thus likely causing the genetic bottleneck by diluting mtDNA copies per cell. Through computational simulations and approximate Bayesian computation (ABC), we recapitulated this lymphocyte-specific mutational landscape and estimated the minimal mtDNA copies as <30 in T, B, and NK lineages. Our integrative analysis revealed a novel process of a lymphoid-specific mtDNA genetic bottleneck, thus illuminating a potential mechanism used by highly metabolically active immune cells to limit their mtDNA mutation load.     

Delineating spatiotemporal and hierarchical development of human fetal innate lymphoid cells

Whereas the critical roles of innate lymphoid cells (ILCs) in adult are increasingly appreciated, their developmental hierarchy in early human fetus remains largely elusive. In this study, we sorted human hematopoietic stem/progenitor cells, lymphoid progenitors, putative ILC progenitor/precursors and mature ILCs in the fetal hematopoietic, lymphoid and non-lymphoid tissues, from 8 to 12 post-conception weeks, for single-cell RNA-sequencing, followed by computational analysis and functional validation at bulk and single-cell levels. We delineated the early phase of ILC lineage commitment from hematopoietic stem/progenitor cells, which mainly occurred in fetal liver and intestine. We further unveiled interleukin-3 receptor as a surface marker for the lymphoid progenitors in fetal liver with T, B, ILC and myeloid potentials, while IL-3RA^– lymphoid progenitors were predominantly B-lineage committed. Notably, we determined the heterogeneity and tissue distribution of each ILC subpopulation, revealing the proliferating characteristics shared by the precursors of each ILC subtype. Additionally, a novel unconventional ILC2 subpopulation (CRTH2^– CCR9⁺ ILC2) was identified in fetal thymus. Taken together, our study illuminates the precise cellular and molecular features underlying the stepwise formation of human fetal ILC hierarchy with remarkable spatiotemporal heterogeneity.Subject terms: Innate immunity, Haematopoietic stem cells     

Single-cell transcriptomics analysis reveals intratumoral heterogeneity and identifies a gene signature associated with prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) tumors exhibit high heterogeneity. However, current understanding of tumor cell heterogeneity of HCC and the association with prognosis remains very limited. In the present study, we collected and examined tumor tissue from one HCC patient by single-cell RNA sequencing (scRNA-seq). We identified 5753 cells and 16 clusters including hepatocytes/cancer cells, T cells, macrophages, endothelial cells, fibroblasts, NK cells, neutrophils, and B cells. In six tumor cell subclusters, we identified a cluster of proliferative tumor cells associated with poor prognosis. We downloaded scRNA-seq data of {"type":"entrez-geo","attrs":{"text":"GSE125449","term_id":"125449"}}GSE125449 from the NCBI-GEO as validation dataset, and found that a cluster of hepatocytes exhibited high proliferation activity in HCC. Furthermore, we identified a gene signature related to the proliferation of HCC cells. This gene signature is efficient to classify HCC patients into two groups with distinct prognosis in both TCGA and ICGC database cohorts. Our results reveal the intratumoral heterogeneity of HCC at single cell level and identify a gene signature associated with HCC prognosis.     

Primitive AML progenitors from most CD34(+) patients lack CD33 expression but progenitors from many CD34(-) AML patients express CD33

BACKGROUND: AML blast populations are heterogeneous in their phenotype and functional properties, and contain a small subset of cells that regenerate leukemia in immunocompromised mice or produce clonogenic progeny in long-term cultures. This suggests the existence of a hierarchy of AML progenitor cells. CD33 is a myeloid marker absent on normal hematopoietic stem cells but expressed in about 75% of AML patients, and has been used for BM purging strategies and Ab-targeted therapies. These CD33 Ab therapies benefit only a minority of AML patients, suggesting that AML stem cells are heterogeneous in their CD33 expression. METHODS: In order to evaluate this question, we determined expression levels of CD34 and CD33 on AML progenitors with long-term in vitro proliferative ability and NOD/SCID engrafting ability. RESULTS: The CD34(+) CD33(-) subfraction contained the majority of progenitors detected in vitro and most often engrafted the mice. This proliferation was leukemic from the CD34(+) AML patients, however from the CD34(-) AML patients only normal progenitors were detected in this fraction in some cases. DISCUSSION: These data suggest that most leukemic progenitors of CD34(+) patients do not express CD33. In contrast, CD34(-) AML primitive leukemic progenitors may be CD33(+). CD34(-) AML patients could potentially benefit most from CD33-targeted therapies or purging.     

Identification of a plastid-specific ribosomal protein in the 30 S subunit of chloroplast ribosomes and isolation of the cDNA clone encoding its cytoplasmic precursor

We describe the isolation and characterization of a chloroplast ribosomal protein and a clone of its cDNA. This protein has no homology to any Escherichia coli ribosomal protein or to any known proteins. Due to this novel finding we propose it be called PSrp-1, i.e. a plastid-specific ribosomal protein. The precursor form of PSrp-1, deduced from the cDNA sequence, is 302-amino acid residues long. The mature PSrp-1, identified by amino-terminal sequencing, is a protein of 236 residues. The NH2-terminal 66 amino acids form the transit peptide that targets PSrp-1 into the chloroplast. We show that PSrp-1 is a protein of the chloroplast 30 S ribosomal subunit by Western blotting and sequencing the excised protein after two-dimensional gel electrophoresis. The possible evolutionary origin of PSrp-1 from the nucleated host cell of the endosymbiont theory is discussed.     

Knockdown of SALL4 Protein Enhances All-trans Retinoic Acid-induced Cellular Differentiation in Acute Myeloid Leukemia Cells

All-trans retinoic acid (ATRA) is a differentiation agent that revolutionized the treatment of acute promyelocytic leukemia. However, it has not been useful for other types of acute myeloid leukemia (AML). Here we explored the effect of SALL4, a stem cell factor, on ATRA-induced AML differentiation in both ATRA-sensitive and ATRA-resistant AML cells. Aberrant SALL4 expression has been found in nearly all human AML cases, whereas, in normal bone marrow and peripheral blood cells, its expression is only restricted to hematopoietic stem/progenitor cells. We reason that, in AMLs, SALL4 activation may prevent cell differentiation and/or protect self-renewal that is seen in normal hematopoietic stem/progenitor cells. Indeed, our studies show that ATRA-mediated myeloid differentiation can be largely blocked by exogenous expression of SALL4, whereas ATRA plus SALL4 knockdown causes significantly increased AML differentiation and cell death. Mechanistic studies indicate that SALL4 directly associates with retinoic acid receptor α and modulates ATRA target gene expression. SALL4 is shown to recruit lysine-specific histone demethylase 1 (LSD1) to target genes and alter the histone methylation status. Furthermore, coinhibition of LSD1 and SALL4 plus ATRA treatment exhibited the strongest anti-AML effect. These findings suggest that SALL4 plays an unfavorable role in ATRA-based regimes, highlighting an important aspect of leukemia therapy.     

Lung microvascular endothelium is enriched with progenitor cells that exhibit vasculogenic capacity

Endothelial progenitor cells (EPCs) have been isolated postnatally from bone marrow, blood, and both the intima and adventitia of conduit vessels. However, it is unknown whether EPCs can be isolated from the lung microcirculation. Thus we sought to determine whether the microvasculature possesses EPCs capable of de novo vasculogenesis. Rat pulmonary artery (PAEC) and microvascular (PMVEC) endothelial cells were isolated and selected by using a single-cell clonogenic assay. Whereas the majority of PAECs (approximately 60%) were fully differentiated, the majority of PMVECs (approximately 75%) divided, with approximately 50% of the single cells giving rise to large colonies (>2,000 cells/colony). These highly proliferative cells exhibited the capacity to reconstitute the entire proliferative hierarchy of PMVECs, unveiling the existence of resident microvascular endothelial progenitor cells (RMEPCs). RMEPCs expressed endothelial cell markers (CD31, CD144, endothelial nitric oxide synthase, and von Willenbrand factor) and progenitor cell antigens (CD34 and CD309) but did not express the leukocyte marker CD45. Consistent with their origin, RMEPCs interacted with Griffonia simplicifolia and displayed restrictive barrier properties. In vitro and in vivo Matrigel assays revealed that RMEPCs possess vasculogenic capacity, forming ultrastructurally normal de novo vessels. Thus the pulmonary microcirculation is enriched with EPCs that display vasculogenic competence while maintaining functional endothelial microvascular specificity.