Biology subjects

Zheng, R.

Publications and source records attributed to Zheng, R..

81 records · Page 5Linked to original sources

bioRxiv2020

Bacteroidetes contribute to the carbon and nutrient cycling of deep sea through breaking down diverse glycans

Bacteroidetes are thought to be specialized for the degradation of algae-derived ocean polysaccharides and are a major contributor to the marine carbon and nutrient cycling. Here, we first show Bacteroidetes are the second most abundant phylum bacteria in deep-sea cold seep and possess more genes associated with polysaccharides degradation than other bacteria through metagenomics methods. We further isolate a novel Bacteroidetes species, Maribellus comscasis WC007T, which can efficiently degrade numerous different polysaccharides including: cellulose, pectin, fucoidan, mannan, xylan and starch. These results are verified by transcriptomic analyses and growth assays. Notably, we find cellulose promotes abundant bacterial growth, and using transcriptomics and metabolomics we finally report on the underlying mechanisms of cellulose degradation and utilization, as well as potential contributions to the carbon cycling. Overall, our results suggest Bacteroidetes play key roles in the deep-sea carbon and nutrient cycling, likely due to their high abundance and prominent polysaccharide degradation capabilities. One Sentence SummaryBacteroidetes contribute to ocean carbon and nutrient cycle.

microbiology↗

bioRxiv2020

ViMIC: A Database of Human Disease-related Virus Mutations, Integration Sites and Cis-effects

Molecular mechanisms of virus-related diseases involve multiple factors, including viral mutation accumulation and integration of a viral genome into the host DNA. With increasing attention being paid to virus-mediated pathogenesis and the development of many useful technologies to identify virus mutations (VMs) and viral integration sites (VISs), abundant literatures on these topics are available in PubMed. However, knowledge of VMs and VISs is widely scattered in numerous published papers, and the association of VMs with VISs in the viral genome or the functional annotation of VISs still lacks integration and curation. To address these challenges, we built a database of human disease-related Virus Mutations, Integration sites and Cis-effects (ViMIC), which specialize in three features: virus mutation sites, viral integration sites and target genes. In total, the ViMIC provides information on 6,461 VMs, 79,089 VISs, and 15,056 viral target genes of 8 viruses in 65 human diseases obtained from literatures. Furthermore, in ViMIC, users are allowed to explore the cis-effects of virus-host interactions by surveying 78 histone modifications, binding of 1,358 transcription regulators, and chromatin accessibility on these VISs. We believe ViMIC will become a valuable resource for the virus research community. The database is available at http://bmtongji.cn/ViMIC/index.php.

bioinformatics↗

bioRxiv2020

Derivation of human extended pluripotent stem cells in feeder-free condition

Human extended pluripotent stem cells (EPSCs), with bidirectional chimeric ability to contribute to both embryonic and extra-embryonic lineages, can be obtained and maintained by converting embryonic stem cells (ESCs) using chemicals. However, the transition system is based on inactivated mouse fibroblast, which greatly hinders the mechanistic studies of extended pluripotency and further applications. Here we reported a Matrigel-based feeder-free method to convert human ESCs and iPSCs into EPSCs and demonstrated the extended pluripotency in terms of molecular features, chimeric ability, and transcriptome. We further improved the protocol by applying chemicals targeting glycolysis and histone methyltransferase. Altogether, our data established a feeder-free system to generate human EPSCs and provided additional insights into the acquisition of extended pluripotency.

developmental biology↗

bioRxiv2020

TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment

Cancer immunotherapy targeting co-inhibitory pathways by checkpoint blockade shows remarkable efficacy in a variety of cancer types. However, only a minority of patients respond to treatment due to the stochastic heterogeneity of tumor microenvironment (TME). Recent advances in single-cell RNA-seq technologies enabled comprehensive characterization of the immune system heterogeneity in tumors, but also posed computational challenges on how to integrate and utilize the massive published datasets to inform immunotherapy. Here, we present Tumor Immune Single Cell Hub (TISCH, http://tisch.comp-genomics.org), a large-scale curated database that integrates single-cell transcriptomic profiles of nearly two million cells from 76 high-quality tumor datasets across 28 cancer types. All the data were uniformly processed with a standardized workflow, including quality control, batch effect removal, malignant cell classification, cell clustering, cell-type annotation, differential expression analysis, and functional enrichment analysis. TISCH provides interactive gene expression visualization across multiple datasets at the single-cell level or cluster level, allowing systematic comparison between different cell-types, patients, tissue origins, treatment and response groups, and even different cancer-types. In summary, TISCH provides a user-friendly interface for systematically visualizing, searching, and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the TME.

bioinformatics↗

bioRxiv2020

SSRE: Cell Type Detection Based on Sparse Subspace Representation and Similarity Enhancement

Accurate identification of cell types from single-cell RNA sequencing (scRNA-seq) data plays a critical role in a variety of scRNA-seq analysis studies. It corresponds to solving an unsupervised clustering problem, in which the similarity measurement between cells in a high dimensional space affects the result significantly. Although many approaches have been proposed recently, the accuracy of cell type identification still needs to be improved. In this study, we proposed a novel single-cell clustering framework based on similarity learning, called SSRE. In SSRE, we model the relationships between cells based on subspace assumption and generate a sparse representation of the cell-to-cell similarity, which retains the most similar neighbors for each cell. Besides, we adopt classical pairwise similarities incorporated with a gene selection and enhancement strategy to further improve the effectiveness of SSRE. For performance evaluation, we applied SSRE in clustering, visualization, and other exploratory data analysis processes on various scRNA-seq datasets. Experimental results show that SSRE achieves superior performance in most cases compared to several state-of-the-art methods.

bioinformatics↗

bioRxiv2020

Maternal vitamin D deficiency increases the risk of obesity in male mice offspring by affecting the immune response

Recently, many epidemiological and animal studies have indicated that obesity have their origin in the early stages of life including the inappropriate balance of some nutrients, the objective of this study is to determine the risk of obesity in male mice offspring as a consequence of maternal VD deficiency-mediated disordering of the immune response. Four-week-old C57BL/6J female mice were fed VD-deficient or normal reproductive diets during pregnancy and lactation. Their male offspring were weighted and euthanized after being fed control and high-fat diets (HFD) for 16 weeks starting at the weaning. The serum was collected for biochemical analyses. Epididymal (eWAT) and inguinal (iWAT) white adipose tissues were excised for histological examination, immunohistochemistry, gene expressions of inflammatory factors, and for determining the proportions of immune cells by flow cytometry. Insufficient maternal VD intake exacerbated the development of obesity both in non-obese and obese male offspring as evidenced by larger adipose cells and abnormal glucose and lipid metabolisms. Also, the expression of proinflammatory cytokine genes was increased and that of anti-inflammatory cytokines was decreased in maternal VD-deficient groups in the eWAT and/or iWAT. This was accompanied by higher levels of TNF- or/and INF-{beta}, and lower levels of IL-4 and IL-10. Insufficient maternal VD intake was also observed to induce a shift in the profiles of immune cells in the eWAT and/or iWAT, resulting in increased percentages of M1 macrophage, ATDCs, and CD4+ and CD8+ T cells, but caused a significant decrease in the percentage of M2 macrophages, both in non-obese and obese male offspring. All these changes in the immune cell profile were more obvious in the eWAT than in the iWAT. These results indicated that insufficient maternal VD intake promoted the development of obesity in male offspring by modulating the immune cell populations and causing a polarization in the adipose depots. ImportanceEvidence in this study has indicated that insufficient maternal VD intake promotes the development of obesity in the male offspring by modulating the recruitment of immune cell populations and their polarization as well as the expression and secretion of proinflammatory adipokines in the adipose depots in a weight-independent manner, which is more obvious in eWAT than that in the iWAT.

immunology↗

bioRxiv2019

Inferring transcriptional regulators through integrative modeling ofpublic chromatin accessibility and ChIP-seq data

We developed Lisa (http://lisa.cistrome.org) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses compendia of public histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Then using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes, and outperformed alternative methods in identifying the perturbed TRs.

bioinformatics↗

bioRxiv2019

Determinants of transcription factor regulatory range

To characterize the genomic distances over which transcription factors (TFs) influence gene expression, we examined thousands of TF and histone modification ChIP-seq datasets and thousands of gene expression profiles. A model integrating these data revealed two classes of TF: one with short-range regulatory influence, the other with long-range regulatory influence. The two TF classes also had distinct chromatin-binding preferences and auto-regulatory properties. The regulatory range of a single TF bound within different topologically associating domains (TADs) depended on intrinsic TAD properties such as local gene density and G/C content, but also on the TAD chromatin state in specific cell types. Our results provide evidence that most TFs belong to one of these two functional classes, and that the regulatory range of long-range TFs is chromatin-state dependent. Thus, consideration of TF type, distance-to-target, and chromatin context is likely important in identifying TF regulatory targets and interpreting GWAS and eQTL SNPs.

genomics↗

bioRxiv2018

Inherited defects in natural killer cells shape tumor immune microenvironment, clinical outcome and immunotherapy response

Tumor immune microenvironment (TIME) plays an important role in metastasis and immunotherapy. However, it has been not much known how to classify TIMEs and how TIMEs are genetically regulated. Here we showed that tumors were classified into TIME-rich, -intermediate and -poor subtypes which had significant differences in clinical outcomes, abundances of tumor-infiltrating lymphocytes (TILs), the degree of key immune programs activation, and immunotherapy response across 13 common cancer types (n= [~]6,000). Furthermore, TIME-intermediate/-poor patients had significantly more inherited genetic defects (i.e., functional germline variants) in natural killer (NK) cells, antigen processing and presentation (APP) and Wnt signaling pathways than TIME-rich patients, and so did cancer patients than non-cancer individuals (n=4,500). These results suggested that individuals who had more inherited defects in NK cells, APP and Wnt pathways had a higher risk of developing cancers. Moreover, in the 13 common cancers the number of inheritably defected genes of NK cells was significantly negative-correlated with patients survival, TILs abundance in TIMEs and immunotherapy response, suggesting that inherited defects in NK cells alone were sufficient to shape TILs recruitment, clinical outcome, and immunotherapy response, highlighting that NK cell activation was required in the 13 cancer types to drive the recruitment of immune troops into TIMEs. Thus, we proposed that cancer was a disease of NK cell inherited deficiencies. These results had implications in identifying of high-risk individuals based on germline genomes, implementing precision cancer prevention by adoptive transfer of healthy NK cells, and improving existing immunotherapies by combining of adoptive NK cell transfer (i.e., converting TIME-intermediate/-poor tumors into TIME-rich tumors) and anti-PD-1 or CAR-T therapy.\n\nContactEW (edwin.wang@ucalgary.ca)

cancer biology↗