Biology subjects

Zhang, G.

Publications and source records attributed to Zhang, G..

30 records · Page 2Linked to original sources

bioRxiv2018

Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here we perform a genome-wide prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.

cancer biology↗

bioRxiv2018

Efficient lentiviral transduction of different human and mouse cells

BackgroundLentiviral vectors (LVs) allowing efficient establishment of stable transgene overexpression mammalian and human cell lines are invaluable tools for genetic research. Currently, although LV transductions are broadly adopted, they are often limited due to their low titers for efficient transduction.\n\nResultsHere, we described a set of optimized, efficient techniques, which could produce sufficiently high LV titers, and, provide efficient transduction of cells. According to these optimizations, most of the mammalian and human cells, both primary cells and cell lines, could be transduced successfully with high levels of transgene stable expression, including both constitutive and induced expressions.\n\nConclusionsOur data demonstrated the highly usefulness of our optimized methods. Therefore, this study provided an efficient method for most of LV transduction experiments in vitro.

genetics↗

bioRxiv2018

Single Cell Molecular Alterations Reveal Pathogenesis and Targets of Concussive Brain Injury

The complex neuropathology of traumatic brain injury (TBI) is difficult to dissect in the hippocampus considering the convoluted hippocampal cytoarchitecture. As a major casualty of TBI, hippocampal dysfunction results in cognitive decline that may escalate to other neurological disorders, and the molecular basis is hidden in the genomic programs of individual hippocampal cells. Using the unbiased single cell sequencing method Drop-seq, we uncovered the hippocampal cell types most sensitive to concussive mild TBI (mTBI) as well as the vulnerable genes, pathways and cell-cell interactions predictive of disease pathogenesis in a cell-type specific manner, revealing hidden pathogenic mechanisms and potential targets. Targeting Ttr, encoding the thyroid hormone T4 transporter transthyretin, mitigated the genomic and behavioral abnormalities associated with mTBI. Single cell genomics provides unique evidence about altered circuits and pathogenic pathways, and pinpoints new targets amenable to therapeutics in mTBI and related disorders.

systems biology↗

bioRxiv2017

Airway IRF7hi versus IRF7lo molecular response patterns determine clinical phenotypes in children with acute wheezing

Asthma exacerbations are triggered by rhinovirus infections. We employed a systems biology approach to delineate upper airway gene network patterns underlying asthma exacerbation phenotypes in children. Cluster analysis unveiled distinct IRF7hi versus IRF7lo molecular phenotypes, the former exhibiting robust upregulation of Th1/type I interferon responses and the latter an alternative signature marked by upregulation of cytokine and growth factor signalling and downregulation of interferon gamma. The two phenotypes also produced distinct clinical phenotypes. For IRF7lo versus IRF7hi: symptom duration prior to hospital presentation was more than twice as long from initial symptoms (p=0.011) and nearly three times as long for cough (p<0.001); the odds ratio of admission to hospital was increased more than four-fold (p=0.018); and time to recurrence was shorter (p=0.015). In summary, our findings demonstrate that asthma exacerbations in children can be divided into IRF7hi versus IRF7lo phenotypes with associated differences in clinical phenotypes.\n\nAbbreviationsAHR, airway hyperresponsiveness; ARG1, Arginase 1, CSF3, Colony Stimulating Factor 3; CD38, Cluster of Differentiation 38; CD163, Cluster of Differentiation 163; cDCs, conventional (or myeloid) dendritic cells; DDX60, DExD/H-Box Helicase 60; ED, Emergency Department; EGF, Epidermal Growth Factor; ERK, Extracellular signal-Regulated Kinase; FCER1G, Fc Fragment Of IgE Receptor Ig; HMBS, Hydroxymethylbilane Synthase; IFNg, Interferon Gamma; IFNL1, Interferon Lambda 1; IL-1R2, Interleukin 1 Receptor Type 2; IRF7, Interferon Regulatory Factor 7; ISG15, Interferon-stimulated gene 15; MDA5, Melanoma Differentiation-Associated protein 5; MX1, Myxovirus Resistance Protein 1; NAD, nicotinamide adenine dinucleotide; NCR1, Natural cytotoxicity triggering receptor 1; OSM, Oncostatin M; PD-L1, Programmed Death-Ligand 1; PPIA, Peptidylprolyl Isomerase A; PPIB Peptidylprolyl Isomerase B; RSAD2, Radical S-adenosyl methionine domain-containing protein 2; RSV, respiratory syncytial virus; RT-qPCR, quantitative reverse transcription PCR; RV, rhinovirus; sPLA2, secretory Phospholipase A2; TGFb, Transforming Growth Factor beta; THBS1, Thrombospondin 1; TNF, Tumor Necrosis Factor; TLR2, Toll-like Receptor 2.

cell biology↗

bioRxiv2017

C24 sphingolipids play a surprising and central role in governing cholesterol and lateral organization of the live cell plasma membrane

Mammalian cell sphingolipids, primarily with C24 and C16 acyl chains, reside in the outer leaflet of the plasma membrane. Curiously, little is known how C24 sphingolipids impact cholesterol and membrane microdomains. Here, we generated giant unilamellar vesicles and live mammalian cells with C24 or C16 sphingomyelin exclusively in the outer leaflet and compared microdomain formation. In giant unilamellar vesicles, we observed that asymmetrically placed C24 sphingomyelin suppresses microdomains. Conversely, C16 sphingomyelin facilitates microdomains. Replacing endogenous sphingolipids with C24 or C16 sphingomyelin in live HeLa cells has a similar impact on microdomains, characterized by FRET between GPI-anchored proteins: C24, but not C16, sphingomyelin suppresses submicron domains in the plasma membrane. Molecular dynamics simulations indicated that, when in the outer leaflet, the acyl chain of C24 sphingomyelin interdigitates into the opposing leaflet, thereby favouring cholesterol in the inner leaflet. We indeed found that cholesterol prefers the inner over the outer leaflet of asymmetric unilamellar vesicles (80/20) when C24 sphingomyelin is in the outer leaflet. However, when C16 sphingomyelin is in the outer leaflet, cholesterol is evenly partitioned between leaflets (50/50). Interestingly, when a mixture of C24/C16 sphingomyelin is in the outer leaflet of unilamellar vesicles, cholesterol still prefers the inner leaflet (80/20). Indeed, in human erythrocyte plasma membrane, where a mixture of C24 and C16 sphingolipids are naturally in the outer leaflet, cholesterol prefers the cytoplasmic leaflet (80/20). Therefore, C24 sphingomyelin uniquely interacts with cholesterol and governs the lateral organization in asymmetric membranes, including the plasma membrane, potentially by generating cholesterol asymmetry.\n\nStatement of SignificanceThe plasma membrane bilayer of mammalian cells has distinct phospholipids between the outer and inner leaflet, with sphingolipids exclusively in the outer leaflet. A large portion of mammalian sphingolipids have very long acyl chains (C24). Little is known how C24 sphingolipids function in the outer leaflet. Mutations in the ceramide synthase 2 gene is found to decrease C24. This severely perturbs homeostasis in mice and humans. Here, we investigated unilamellar vesicles and mammalian cells with C24 sphingomyelin exclusively in the outer leaflet. We provide evidence that outer leaflet C24 sphingomyelin suppresses microdomains in model membranes and live cells by partitioning cholesterol into the inner leaflet. We propose that C24 sphingolipids are critical to the function of the plasma membrane.

cell biology↗

bioRxiv2017

A plant receptor-like kinase promotes cell-to-cell spread of RNAi and is targeted by a virus

RNA interference (RNAi) in plants can move from cell to cell, allowing for systemic spread of an anti-viral immune response. How this cell-to-cell spread of silencing is regulated is currently unknown. Here, we describe that the C4 protein from Tomato yellow leaf curl virus has the ability to inhibit the intercellular spread of RNAi. Using this viral protein as a probe, we have identified the receptor-like kinase (RLK) BARELY ANY MERISTEM 1 (BAM1) as a positive regulator of the cell-to-cell movement of RNAi, and determined that BAM1 and its closest homologue, BAM2, play a redundant role in this process. C4 interacts with the intracellular domain of BAM1 and BAM2 at the plasma membrane and plasmodesmata, the cytoplasmic connections between plant cells, interfering with the function of these RLKs in the cell-to-cell spread of RNAi. Our results identify BAM1 as an element required for the cell-to-cell spread of RNAi and highlight that signalling components have been co-opted to play multiple functions in plants.

plant biology↗

bioRxiv2017

Endosymbiont diversity and evolution across the weevil tree of life

As early as the time of Paul Buchner, a pioneer of endosymbionts research, it was shown that weevils host diverse bacterial endosymbionts, probably only second to the hemipteran insects. To date, there is no taxonomically broad survey of endosymbionts in weevils, which preclude any systematic understanding of the diversity and evolution of endosymbionts in this large group of insects, which comprise nearly 7% of described diversity of all insects. We gathered the largest known taxonomic sample of weevils representing four families and 17 subfamilies to perform a study of weevil endosymbionts. We found that the diversity of endosymbionts is exceedingly high, with as many as 44 distinct kinds of endosymbionts detected. We recovered an ancient origin of association of Nardonella with weevils, dating back to 124 MYA. We found repeated losses of this endosymbionts, but also cophylogeny with weevils. We also investigated patterns of coexistence and coexclusion.

evolutionary biology↗

bioRxiv2017

Karyotype stability and unbiased fractionation in the paleo-allotetraploid Cucurbita genomes

The Cucurbita genus contains several economically important species in the Cucurbitaceae family. Interspecific hybrids between C. maxima and C. moschata are widely used as rootstocks for other cucurbit crops. We report high-quality genome sequences of C. maxima and C. moschata and provide evidence supporting an allotetraploidization event in Cucurbita. We are able to partition the genome into two homoeologous subgenomes based on different genetic distances to melon, cucumber and watermelon in the Benincaseae tribe. We estimate that the two diploid progenitors successively diverged from Benincaseae around 31 and 26 million years ago (Mya), and the allotetraploidization happened earlier than 3 Mya, when C. maxima and C. moschata diverged. The subgenomes have largely maintained the chromosome structures of their diploid progenitors. Such long-term karyotype stability after polyploidization is uncommon in plant polyploids. The two subgenomes have retained similar numbers of genes, and neither subgenome is globally dominant in gene expression. Allele-specific expression analysis in the C. maxima x C. moschata interspecific F1 hybrid and the two parents indicates the predominance of trans-regulatory effects underlying expression divergence of the parents, and detects transgressive gene expression changes in the hybrid correlated with heterosis in important agronomic traits. Our study provides insights into plant genome evolution and valuable resources for genetic improvement of cucurbit crops.

genomics↗

bioRxiv2017

Insight Into The Mechanism Of Protein Thermostability Based On The Residue Interaction Degrees

Understanding the basis of protein thermostability raises a general question: which residue with specific interaction degrees is more important to the protein thermostability? A strictly selected dataset of 131 pairs of thermophilic (TPs) and mesophilic proteins (MPs) was constructed. There were 6.4% and 8.4% of the total residues in sequences did not interact with others in TPs and MPs. The amino acid contents in sequences are closest to those with the interaction degrees of 3 according to the Chi-squared distances. Only Glu, Gln and the amide residues showed significant differences in sequences, which was the same as identified at low residue interaction degrees. However, we observed significant Phe, Lys, Leu, Gln and the charged, aliphatic, aromatic, positive charged and small residues at high interaction degree. Among them, Phe was rarely reported previously although aromatic residues were well-known contributor to protein thermostability. Finally, we took aspartate transcarbamylases as an example to explain how a residue with various interaction degrees contributed differently to their thermostability. Our results clearly demonstrated the differences of amino acids in sequence between TPs and MPs could only represent those involved in low interaction degrees. Much more residues with significant differences existed at high interaction degrees even if they had few significant amino acids in sequences. The interaction degree-based method should be an alternative tool in extracting valuable eigenvalues for predicting proteins attributes in bioinformatics. It could also provide a new perspective for studying the thermostability of proteins and engineering novel thermostable proteins.\n\nList of abbreviations

bioinformatics↗

bioRxiv2017

Novel insights into the molecular heterogeneity of hepatocellularcarcinoma

Hepatocellular carcinoma (HCC) is influenced by numerous factors, which results in diverse genetic, epigenetic and transcriptional scenarios, thus posing obvious challenges for disease management. We scrutinized the molecular heterogeneity of HCC with a multi-omics approach in two small cohorts of resected and explanted livers. Whole-genome transcriptomics was conducted, including polyadenylated transcripts and micro (mi)-RNAs. Copy number variants (CNV) were inferred from whole genome low-pass sequencing data. Fifty-six cancer-related genes were screened using an oncology panel assay. HCC was associated with a dramatic transcriptional deregulation of hundreds of protein-coding genes suggesting downregulation of drugs catabolism, induction of inflammatory responses, and increased cell proliferation in resected livers. Moreover, several long non-coding RNAs and miRNAs not reported previously in the context of HCC were found deregulated. In explanted livers, downregulation of genes involved in energy-producing processes and upregulation of genes aiding in glycolysis were detected. Numerous CNV events were observed, with conspicuous hotspots on chromosomes 1 and 17. Amplifications were more common than deletions, and spanned regions containing genes potentially involved in tumorigenesis. CSF1R, FGFR3, FLT3, NPM1, PDGFRA, PTEN, SMO and TP53 were mutated in all tumors, while other 26 cancer-related genes were mutated with variable penetrance. Our results highlight a remarkable molecular heterogeneity between HCC tumors and reinforce the notion that precision medicine approaches are urgently needed for cancer treatment. We expect that our results will serve as a valuable dataset that will generate hypotheses for us or other researchers to evaluate to ultimately improve our understanding of HCC biology.

cancer biology↗

bioRxiv2017

BGDMdocker: an workflow base on Docker for analysis and visualization pan-genome and biosynthetic gene clusters of Bacterial

MotivationAt present Docker technology has received increasing level of attention throughout the bioinformatics community. However, its implementation details have not yet been mastered by most biologists and applied widely in biological researches. In order to popularizing this technology in the bioinformatics and sufficiently use plenty of public resources of bioinformatics tools (Dockerfile and image of scommunity, officially and privately) in Docker Hub Registry and other Docker sources based on Docker, we introduced full and accurate instance of a bioinformatics workflow based on Docker to analyse and visualize pan-genome and biosynthetic gene clusters of a bacteria in this article, provided the solutions for mining bioinformatics big data from various public biology databases. You could be guided step-by-step through the workflow process from docker file to build up your own images and run an container fast creating an workflow.\n\nResultsWe presented a BGDMdocker (bacterial genome data mining docker-based) workflow based on docker. The workflow consists of three integrated toolkits, Prokka v1.11, panX, and antiSMASH3.0. The dependencies were all written in Dockerfile, to build docker image and run container for analysing pan-genome of total 44 Bacillus amyloliquefaciens strains, which were retrieved from public? database. The pan-genome totally includes 172,432 gene, 2,306 Core gene cluster. The visualized pan-genomic data such as alignment, phylogenetic trees, maps mutations within that cluster to the branches of the tree, infers loss and gain of genes on the core-genome phylogeny for each gene cluster were presented. Besides, 997 known (MIBiG database) and 553 unknown (antiSMASH-predicted clusters and Pfam database) genes of biosynthesis gene clusters types and orthologous groups were mined in all strains. This workflow could also be used for other species pan-genome analysis and visualization. The display of visual data can completely duplicated as well as done in this paper. All result data and relevant tools and files can be downloaded from our website with no need to register. The pan-genome and biosynthetic gene clusters analysis and visualization can be fully reusable immediately in different computing platforms (Linux, Windows, Mac and deployed in the cloud), achieved cross platform deployment flexibility, rapid development integrated software package.\n\nAvailability and implementationBGDMdocker is available at http://42.96.173.25/bapgd/ and the source code under GPL license is available at https://github.com/cgwyx/debian_prokka_panx_antismash_biodocker.\n\nContactchenggongwyx@foxmail.com\n\nSupplementary informationSupplementary data are available at biorxiv online.

bioinformatics↗

bioRxiv2016

Genome sequence of a diabetes-prone desert rodent reveals a mutation hotspot around the ParaHox gene cluster

The sand rat Psammomys obesus is a gerbil native to deserts of North Africa and the Middle East1. Sand rats survive with low caloric intake and when given high carbohydrate diets can become obese and develop type II diabetes2 which, in extreme cases, leads to pancreatic failure and death3,4. Previous studies have reported inability to detect the Pdx1 gene or protein in gerbils5-7, suggesting that absence of this key insulin-regulating homeobox gene might underlie diabetes susceptibility. Here we report sequencing of the sand rat genome and discovery of an extensive, mutationally-biased GC-rich genomic domain encompassing many essential genes, including the elusive Pdx1. The sequence of Pdx1 has been grossly affected by GC-biased mutation leading to the highest divergence observed in the animal kingdom. In addition to molecular insights into restricted caloric intake in a desert species, the discovery that specific chromosomal regions can be subject to elevated mutation rate has widespread significance to evolution.

evolutionary biology↗