Biology subjects

Sun, Z.

Publications and source records attributed to Sun, Z..

At least 235 records · Page 13Linked to original sources

bioRxiv2021

Lactate Increases Stemness of CD8+ T Cells to Augment Anti-Tumor Immunity

Nutrients and metabolites play important roles in immune functions. Recent studies show lactate instead of glucose can serve as a primary carbon fuel source for most tissues. The role of lactate in tumor immunity is not well understood with immune suppressive functions reported for lactic acid, the conjugate acid form of lactate. In this study, we report lactate increases the stemness of CD8+ T cells and augments anti-tumor immunity. Subcutaneous administration of lactate but not glucose shows CD8+ T cell-dependent tumor growth inhibition. Single cell transcriptomics analysis revealed lactate treatment increased a subpopulation of stem-like TCF-1-expressing CD8+ T cells, which is further validated by ex vivo culture of CD8+ T cells from mouse splenocytes and human peripheral blood mononuclear cells. The inhibition of histone deacetylase activity by lactate increased acetylation in the histone H3K27 site at the Tcf7 super enhancer locus and increased the gene expression of Tcf7. Adoptive transfer of CD8+ T cells pretreated with lactate in vitro showed potent tumor growth inhibition in vivo. Our results elucidate the immune protective role of lactate in anti-tumor immunity without the masking effect of acid. These results may have broad implications for T cell therapy and the understanding of lactate in immune metabolism.

immunology↗

bioRxiv2021

Deep Learning Enables Design of Multifunctional Synthetic Human Gut Microbiome Dynamics

Predicting the dynamics and functions of microbiomes constructed from the bottom-up is a key challenge in exploiting them to our benefit. Current ordinary differential equation-based models fail to capture complex behaviors that fall outside of a predetermined ecological theory and do not scale well with increasing community complexity and in considering multiple functions. We develop and apply a long short-term memory (LSTM) framework to advance our understanding of community assembly and health-relevant metabolite production using a synthetic human gut community. A mainstay of deep learning, the LSTM learns a high dimensional data-driven non-linear dynamical system model used to design communities with desired metabolite profiles. We show that the LSTM model can outperform the widely used generalized Lotka-Volterra model. We build methods decipher microbe-microbe and microbe-metabolite interactions from an otherwise black-box model. These methods highlight that Actinobacteria, Firmicutes and Proteobacteria are significant drivers of metabolite production whereas Bacteroides shape community dynamics. We use the LSTM model to navigate a large multidimensional functional landscape to identify communities with unique health-relevant metabolite profiles and temporal behaviors. In sum, the accuracy of the LSTM model can be exploited for experimental planning and to guide the design of synthetic microbiomes with target dynamic functions.

systems biology↗

bioRxiv2021

A Statistical Framework for Data Purification with Application to Microbiome Data Analysis

Identification of disease-associated microbial species is of great biological and clinical interest. However, this investigation still remains challenges due to heterogeneity in microbial composition between individuals, data quality issues, and complex relationships among species. In this paper, we propose a novel data purification algorithm that allows elimination of noise observations, which leads to increased statistical power to detect disease-associated microbial species. We illustrate the proposed algorithm using the metagenomic data generated from colorectal cancer patients.

bioinformatics↗

bioRxiv2021

Accumulation of auranofin in white adipose tissues lowers leptin levels and exerts anti-diabetic effects

Low-grade, sustained inflammation in white adipose tissue (WAT) characterizes obesity and frequently coincides with insulin resistance and type 2 diabetes (T2D). However, pharmacological targeting of WAT inflammation lacks durable therapeutic effects. Through a computational screen, we identified the FDA-approved rheumatoid arthritis drug auranofin is a putative small molecule for obesity treatment. We discovered that allometrically scaled safe auranofin doses homed to WAT and improved insulin sensitivity in obese wild-type mice. Auranofin treatment also normalized other obesity-associated abnormalities, including hepatic steatosis and hyperinsulinemia. Surprisingly, the anti-diabetic effects of auranofin required leptin lowering and beta-adrenergic receptors in WAT. These metabolic benefits of leptin reduction were superior to any immune impacts of auranofin in WAT. Our studies reveal important metabolic properties of anti-inflammatory treatments and contribute to the notion that leptin reduction in the periphery can be accomplished to treat obesity and T2D.

physiology↗

bioRxiv2021

rRNA Biogenesis Regulates Mouse 2C-like State by 3D Structure Reorganization of Peri-Nucleolar Heterochromatin

Nucleolus is the organelle for ribosome biogenesis and for sensing various types of stress. Its role in regulating stem cell fate is unclear. Here, we present multiple lines of evidence that nucleolar stress induced by interfering rRNA biogenesis can drive 2-cell stage embryo-like (2C-like) transcriptional program and induce an expanded 2C-like cell population in mouse embryonic stem (mES) cells. Mechanistically, the nucleolar integrity mediated by rRNA biogenesis maintains the normal liquid-liquid phase separation (LLPS) of nucleolus and the formation of peri-nucleolar heterochromatin (PNH). Upon rRNA biogenesis defect, the natural LLPS of nucleolus is disrupted, causing dissociation of NCL/TRIM28 complex from PNH and changes of epigenetic states and reorganization of the 3D structure of PNH, which leads to Dux, a 2C program transcription factor gene, to be released from the PNH region and activation of 2C-like program. Correspondingly, embryos with rRNA biogenesis defect are incompatible to develop from 2-cell (2C) to 4-cell embryos, with delayed repression of 2C/ERV genes and a transcriptome skewed toward earlier cleavage embryo signatures. Our results highlight that rRNA-mediated nucleolar integrity and 3D structure reshaping of PNH compartment regulates the fate transition of mES cells to 2C-like cells, and that rRNA biogenesis is a critical regulator during the 2-cell-to-4-cell transition of murine pre-implantation embryo development.

cell biology↗

bioRxiv2021

COVID-ONE-humoral immune: The One-stop Database for COVID-19-specific Antibody Responses and Clinical Parameters

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.

microbiology↗

bioRxiv2021

LENG8 regulation of mRNA processing, is responsible for the control of mitochondrial activity

The processing of mRNA is essential for the maintenance of cellular and tissue homeostasis. However, the precise regulation of this process in mammalian cells, remains largely unknown. Here we have found that LENG8 represents the mammalian orthologue of the yeast mRNA processing factor Thp3 and Sac3. We go on to demonstrate that LENG8 binds to mRNAs, associates with components of mRNA processing machinery (the TREX complex) and contributes to mRNA nuclear export to the cytoplasm. Loss of LENG8, leads to aberrant accumulation of poly (A)+ RNA in the nucleus, in both Hela cells and murine fibroblasts. Furthermore, the precipitation of LENG8, is associated with an enrichment of both mRNAs and lncRNAs, and approximately half of these are also bound by the TREX component, THOC1. However, LENG8 preferentially binds mRNAs encoding for mitochondrial proteins and depletion of this processing factor, causes a dramatic breakdown in mitochondrial ultrastructure and a reduction in mitochondrial respiratory activity. Conditional deletion of Leng8 in mouse adipose tissues lead to a decreased body weight, and increased adipose thermogenesis. Our work has found an evolutionarily conserved mRNA processing factor that can control mitochondrial activity.

cell biology↗

bioRxiv2021

Complete depletion of Arabidopsis linker histones impairs the correlations among chromatin compartmentalization, DNA methylation and gene expression

In eukaryotic cells, linker histone H1 anchors in and out ends of nucleosome DNA to promote chromatin to fold into the 30 nm fiber. However, if H1 plays a role in coordinating the three-dimensional (3D) chromatin architecture, DNA methylation, and transcriptional regulation is not clear. We engineered H1 knockout mutants in Arabidopsis thaliana which shows pleiotropic phenotypes. Using High-throughput Chromosome Conformation Capture (Hi-C), we found that H1 complete depletion dampens inter- and intra-chromosomal interactions, as well as intra- and inter-chromosomal arm interactions. MNase accessibility assays followed by sequencing (MNase-seq) showed that the nucleosome density decreases in centromeric regions and increases in chromosome arms. In contrast, DNA methylation level in CHG and CHH contexts increases in centromeric regions and decreases in chromosome arms as revealed by whole genome bisulfite sequencing (WGBS) in h1 mutant. Importantly, the functional link between DNA methylation and gene transcription is defected, and the extensive switches between chromatin compartment A and B are uncoupled from genome-wide DNA methylation and most of gene transcriptions upon H1 depletion. These results suggested that linker histone H1 works as linkers among chromatin compartmentalization, DNA methylation and transcription.

plant biology↗

bioRxiv2021

An immune-related E2F gene expression signature provides prognostic information in patients with hepatocellular

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies. E2F transcription factors play an important role in the tumorigenesis and progression of HCC, mainly through the RB/E2F pathway. Prognostic models for HCC based on gene signatures have been developed rapidly in recent years; however, their discriminating ability at the single cell level remains elusive, which could reflect the underlying mechanisms driving the sample bifurcation. In this study, we constructed and validated a predictive model based on E2F expression, successfully stratifying HCC patients into two groups with different survival risks. Then we used a single-cell dataset to test the discriminating ability of the predictive model on infiltrating T cells, demonstrating remarkable cellular heterogeneity as well as altered cell fates. We identified distinct cell subpopulations with diverse molecular characteristics. We also found that the distribution of cell subpopulations varied considerably across onset stages among patients, providing fundamental basis for patient-oriented precision evaluation. Moreover, single-sample gene set enrichment analysis revealed that subsets of CD8+ T cells with significantly different cell adhesion level could be associated with different patterns of tumor cell dissemination. Therefore, our findings linked the conventional prognostic gene signature to the immune microenvironment and cellular heterogeneity at the single-cell level, thereby providing deeper insights into the understanding of HCC tumorigenesis.

bioinformatics↗

bioRxiv2021

Live-Cell Imaging of (p)ppGpp with RNA-based Fluorescent Sensors

Guanosine tetra- and pentaphosphate, (p)ppGpp, are important alarmone nucleotides that regulate bacterial survival in stressful environment. A direct detection of (p)ppGpp in living cells is critical for our understanding of the mechanism of bacterial stringent response. However, it is still challenging to directly image and measure cellular (p)ppGpp. Here, we report a type of RNA-based fluorescent sensors for live-cell imaging of (p)ppGpp. Our sensor is engineered by conjugating a recently identified (p)ppGpp-specific riboswitch with a fluorogenic RNA aptamer, Broccoli. These sensors can be genetically encoded and enable direct monitoring of cellular (p)ppGpp accumulation. Unprecedented information on cell-to-cell variation and cellular dynamics of (p)ppGpp levels can now be obtained under different nutritional conditions. We predict that these RNA-based sensors will be broadly adapted to study bacterial stringent response.

cell biology↗

bioRxiv2021

The Arabidopsis thaliana PeptideAtlas; harnessing world-wide proteomics data for a comprehensive community proteomics resource

We developed a new resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis proteome, such as the significance of protein splice forms, post-translational modifications (PTMs), or simply obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) analyses collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical and biological metadata. Nearly 40 million out of [~]143 million MSMS spectra were matched to the reference genome Araport11, identifying [~]0.5 million unique peptides and 17858 uniquely identified proteins (only isoform per gene) at the highest confidence level (FDR 0.0004; 2 non-nested peptides [≥] 9 aa each), assigned canonical proteins, and 3543 lower confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified, generated from pseudogenes, alternative start, stops and/or splice variants and sORFs; these features should be considered for updates to the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. This new PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS data. One sentence summaryA new web resource providing the global community with mass spectrometry-based Arabidopsis proteome information and its spectral, technical and biological metadata integrated with TAIR and JBrowse

plant biology↗

bioRxiv2021

Deep learning identifies pathological abnormalities predictive of graft loss in kidney transplant biopsies

BackgroundInterstitial fibrosis, tubular atrophy, and inflammation are major contributors to renal allograft failure. Here we seek an objective, quantitative pathological assessment of these lesions to improve predictive utility. MethodsWe constructed a deep-learning-based pipeline recognizing normal vs. abnormal kidney tissue compartments and mononuclear leukocyte (MNL) infiltrates from Periodic acid-Schiff (PAS) stained slides of transplant biopsies (training: n=60, testing: n=33) that quantified pathological lesions specific for interstitium, tubules and MNL infiltration. The pipeline was applied to 789 whole slide images (WSI) from baseline (n=478, pre-implantation) and 12-month post-transplant (n=311) protocol biopsies in two independent cohorts (GoCAR: 404 patients, AUSCAD: 212 patients) of transplant recipients to correlate composite lesion features with graft loss. ResultsOur model accurately recognized kidney tissue compartments and MNLs. The digital features significantly correlated with Banff scores, but were more sensitive to subtle pathological changes below the thresholds in Banff scores. The Interstitial and Tubular Abnormality Score (ITAS) in baseline samples was highly predictive of 1-year graft loss (p=2.8e-05), while a Composite Damage Score (CDS) in 12-month post-transplant protocol biopsies predicted later graft loss (p=7.3e-05). ITAS and CDS outperformed Banff scores or clinical predictors with superior graft loss prediction accuracy. High/intermediate risk groups stratified by ITAS or CDS also demonstrated significantly higher incidence of eGFR decline and subsequent graft damage. ConclusionsThis deep-learning approach accurately detected and quantified pathological lesions from baseline or post-transplant biopsies, and demonstrated superior ability for prediction of posttransplant graft loss with potential application as a prevention, risk stratification or monitoring tool.

pathology↗

bioRxiv2021

Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation

Mass spectrometry-based phosphoproteomics allows large-scale generation of phosphorylation site data. However, analytical pipelines need to be carefully designed and optimised to minimise incorrect identification of phosphopeptide sequences or wrong localisation of phosphorylation sites within those peptides. Public databases such as PhosphoSitePlus (PSP) and PeptideAtlas (PA) compile results from published papers or openly available MS data, but to our knowledge, there is no database-level control for false discovery of sites, subsequently leading to the likely overestimation of true phosphosites. It is therefore difficult for researchers to assess which phosphosites are "real" and which are likely to be artefacts of data processing. By profiling the human phosphoproteome, we aimed to estimate the false discovery rate (FDR) of phosphosites based on available evidence in PSP and/or PA and predict a more realistic count of true phosphosites. We ranked sites into phosphorylation likelihood sets based on layers of accumulated evidence and then analysed them in terms of amino acid conservation across 100 species, sequence properties and functional annotations of associated proteins. We demonstrated significant differences between the sets and developed a method for independent phosphosite FDR estimation. Remarkably, we estimated a false discovery rate of 86.1%, 95.4% and 82.2% within sets of described phosphoserine (pSer), phosphothreonine (pThr) and phosphotyrosine (pTyr) sites respectively for which only a single piece of identification evidence is available (the vast majority of sites in PSP). Overall, we estimate that [~]56,000 Ser, 10,000 Thr and 12,000 Tyr phosphosites in the human proteome have truly been identified to date, based on evidence in PSP and/or PA, which is lower than most published estimates. Furthermore, our analysis estimated [~]91,000 Ser, 49,000 Thr and 26,000 Tyr sites that are likely to represent false-positive phosphosite identifications. We conclude that researchers should be aware of the significant potential for false positive sites to be present in public databases and should evaluate the evidence behind the phosphosites used in their research.

bioinformatics↗

bioRxiv2021

scAMACE: Model-based approach to the joint analysis of single-cell data on chromatin accessibility, gene expression and methylation

The advancement in technologies and the growth of available single-cell datasets motivate integrative analysis of multiple single-cell genomic datasets. Integrative analysis of multimodal single-cell datasets combines complementary information offered by single-omic datasets and can offer deeper insights on complex biological process. Clustering methods that identify the unknown cell types are among the first few steps in the analysis of single-cell datasets, and they are important for downstream analysis built upon the identified cell types. We propose scAMACE for the integrative analysis and clustering of single-cell data on chromatin accessibility, gene expression and methylation. We demonstrate that cell types are better identified and characterized through analyzing the three data types jointly. We develop an efficient expectation-maximization (EM) algorithm to perform statistical inference, and evaluate our methods on both simulation study and real data applications. We also provide the GPU implementation of scAMACE, making it scalable to large datasets. The software and datasets are available at https://github.com/cuhklinlab/scAMACE_py (python implementation) and https://github.com/cuhklinlab/scAMACE (R implementation).

bioinformatics↗

bioRxiv2021

Restriction of RecG translocation by DNA mispairing

The RecG DNA helicase plays a crucial role in stalled replication fork rescue as the guardian of the bacterial genome. We have recently demonstrated that single-strand DNA binding protein (SSB) promotes binding of RecG to the stalled replication fork by remodeling RecG, enabling the helicase to translocate ahead of the fork. We also hypothesized that mispairing of DNA could limit such translocation of RecG, which plays the role of roadblocks for the fork movement. Here, we used atomic force microscopy (AFM) to directly test this hypothesis and investigate how sensitive RecG translocation is to different types of mispairing. We found that a C-C mismatch at a distance of 30 bp away from the fork position prevents translocation of RecG over this mispairing. A G-bulge placed at the same distance also has a similar roadblock efficiency. However, a C-C mismatch 10 bp away from the fork does not prevent RecG translocation, as 10 bp from fork is within the distance of footprint of RecG on fork DNA. Our findings suggest that retardation of RecG translocation ahead of the replication fork can be a mechanism for the base pairing control for DNA replication machinery.

biophysics↗

bioRxiv2021

Neutralization of European, South African, and United States SARS-CoV-2 mutants by a human antibody and antibody domains

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) transmission with several emerging variants remain uncontrolled in many countries, indicating the pandemic remains severe. Recent studies showed reduction of neutralization against these emerging SARS-CoV-2 variants by vaccine-elicited antibodies. Among those emerging SARS-CoV-2 variants, a panel of amino acid mutations was characterized including those in the receptor-binding domain (RBD) of the SARS-CoV-2 spike (S) glycoprotein. In the present study, we evaluated our previously identified antibody and antibody domains for binding to these RBD variants with the emerging mutations, and neutralization of pseudo typed viruses carrying spike proteins with such mutations. Our results showed that one previously identified antibody domain, ab6, can bind 32 out of 35 RBD mutants tested in an ELISA assay. All three antibodies and antibody domains can neutralize pseudo typed B.1.1.7 (UK variant), but only the antibody domain ab6 can neutralize the pseudo typed virus with the triple mutation (K417N, E484K, N501Y). This domain and its improvements have potential for therapy of infections caused by SARS-CoV-2 mutants.

immunology↗

bioRxiv2021

A low sugar diet enhances Drosophila body size in males and females via sex-specific mechanisms

In Drosophila, changes to dietary protein elicit different body size responses between the sexes. Whether this sex difference in nutrient-dependent body size regulation extends to other nutrients, such as dietary sugar, remains unclear. Here, we show that reducing dietary sugar enhanced body size in Drosophila male and female larvae. Indeed, the largest body size was found in larvae reared in a diet without added sugar. Despite the equivalent body size effects of a low sugar diet between males and females, we detected sex-specific changes to the insulin/insulin-like growth factor (IIS) and target of rapamycin (TOR) signaling pathways. Further, we show that the metabolic changes observed in larvae reared on a low sugar diet differ between the sexes. Thus, despite identical phenotypic responses to dietary sugar in males and females, distinct changes to cell signaling pathways and whole-body metabolism were associated with the increased body size in each sex. This highlights the importance of including both sexes in all mechanistic studies on larval growth, as males and females may use different molecular and metabolic mechanisms to achieve similar phenotypic outcomes.

physiology↗

bioRxiv2021

Sulfur limitation increases duckweed starch accumulation without compromising growth

Duckweeds contain relatively high levels of starch and are a potential biomass feedstock for biofuel production. Here, the biomass and starch yield of duckweed under three different nutrient-limited conditions were analyzed to investigate possible ways of further increasing the efficiency of starch production. The results showed that sulfur limitation resulted in the highest starch yield, which was 42% and 73% higher than in nitrogen or phosphorus limitation, respectively. The high yield of sulfur-limited duckweed is largely due to the combinations of little effects on biomass and high accumulations of starch. Although nitrogen limitation led to higher starch content (67.4%), it severely reduced biomass production. The photosynthetic performance indicator Fv/Fm was a simple and sensitive indicator of starch content in nutrient-limited duckweed. Taken together, this study demonstrates that sulfur limitation is a simple and efficient way to increase starch yield, highlighting the great potential of duckweed for biofuel production. We report that sulfur limitation is a practical approach to increase starch yields in duckweed without affecting growth or biomass. HighlightsO_LISulfur limitation induces starch production in a duckweed specie. C_LIO_LINitrogen limitation triggers the highest starch content, but limits growth. C_LIO_LISulfur limitation results in the highest starch yield. C_LIO_LIFv/Fm is a rapid and robust proxy of starch content in nutrient-limited duckweed. C_LI

plant biology↗