Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 1,549 records · Page 86Linked to original sources

bioRxiv2019

Soil and vegetation conditions changes following the different sand dune restoration measures on the Zoige Plateau

Restoration of alpine sand dunes has been increasingly attracting the attention of ecologists due to their difficulty and importance among the mountain-river-forest-farmland-lake-grass system (referred as meta-ecosystem) restoration. Alpine sand dunes are suffered from unstable soil and lack of plants. Efficient restoration measures are vital to guide the sand dune restoration. Whether the engineering materials co-applied with seeding could achieve considerable restoration in such areas? Here, sandbag and wicker as environmental friendly materials combined with Elymus nutans seeding were implemented on the Zoige Plateau sand dune, comparing with the control treatment that only seeding. We assessed the topsoil conditions by sampled the surface soil and measured the water capacity and nutrients. We also utilized interspecific relationship and population niche to analyse the plant community structure variances among different restoration measures. Results showed that the soil conditions got clearly improved in sandbag area than that in wicker area when compared with that in control area. The community in control area was the least structured, while the species showed the closest related in sandbag area. In addition, average population niche overlap showed a control (0.26) < wicker (0.32) < sandbag (0.39) ranking. Thus, we suggested that sandbag or wicker co-applied with indigenous grass seeding is a practical and quick restoration approach in alpine sand dunes, and the sandbag may surpasses the wicker. Moreover, soil amending measures including nutrient improvement, and microbial fertilizer addition may further accelerate sand dune restoration.

ecology↗

bioRxiv2019

coMethDMR: Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies

Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying differentially methylated regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the regions that contain consecutive highly significantly differentially methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic regions, and is available as an open-source R package.

bioinformatics↗

bioRxiv2019

Angiocrine FSTL1 insufficiency leads to atrial and vein wall fibrosis via SMAD3 activation

Angiocrine factors, mediating the endothelial-mural cell interaction in vascular wall construction as well as maintenance, are incompletely characterized. Here we show that loss of follistatin-like protein 1 (FSTL1) in endothelial cells (Fstl1ECKO) led to an increase of pulmonary vascular resistance, resulting in the heart regurgitation especially with tricuspid valves. However, this abnormality was not detected in mutant mice with Fstl1 deletion in smooth muscle cells or hematopoietic cells. We further showed that there was excessive alpha-smooth muscle actin (SMA) associated with atrial endocardia, heart valves, veins and microvessels after the endothelial FSTL1 deletion. Consistently, there was an increase of collagen deposition as demonstrated in livers of Fstl1ECKO mutants. The SMAD3 phosphorylation was significantly enhanced and pSMAD3 staining was colocalized with SMA in vein walls, suggesting the activation of TGF{beta} signaling in vascular mural cells of Fstl1ECKO mice. The findings imply that endothelial FSTL1 is critical for the homeostasis of atria and veins and its insufficiency may favor cardiovascular fibrosis leading to heart failure.

developmental biology↗

bioRxiv2019

Effects of sugars and lipids on the growth and development of Caenorhabditis elegans

Excessive intake of carbohydrates and fats causes over-nutrition, leading to a variety of diseases and complications. Here, we characterized the effects of different types of sugar and lipids on the growth and development of Caenorhabditis elegans. We measured the lifespan, reproductive capacity, and length of nematodes after sugars and lipids treatment alone and co-treatment of sugars and lipids. Furthermore, by using transcriptome sequencing technology, we studied the mechanisms underlying the damaged caused by high-sucrose and high-stearic acid on C. elegans. The results showed that a certain concentration of sugar and lipid promoted the growth and development of nematodes. However, excessive sugars and lipids shortened the lifespan and length of nematodes and destroyed their reproductive capacity. Based on the results of the orthogonal test, we selected 400 mmol/L sucrose and 500 g/mL stearic acid to model a high-sugar and high-lipid diet for C. elegans. High-sugar and high-lipid intake altered the expression of genes involved in biofilm synthesis, genes that catalyze the synthesis and degradation of endogenous substances, and genes involved in innate immunity, resulting in physiological damage.

genetics↗

bioRxiv2019

Multilayered N-glycoproteomics reveals impaired N-glycosylation promoting Alzheimer’s disease

Alzheimers disease (AD) is one of the most common neurodegenerative diseases that currently lacks clear pathogenesis and effective treatment. Protein glycosylation is ubiquitous in brain tissue and site-specific analysis of N-glycoproteome, which is technically challenging, can advance our understanding of the glycoproteins role in AD. In this study, we profiled the multilayered variations in proteins, N-glycosites, N-glycans, and in particular site-specific N-glycopeptides in the APP/PS1 and wild type mouse brain through combining pGlyco 2.0 strategy with other quantitative N-glycoproteomic strategies. The comprehensive brain N-glycoproteome landscape was constructed, and rich details of the heterogeneous site-specific protein N-glycosylations were exhibited. Quantitative analyses explored generally downregulated N-glycosylation involving proteins such as glutamate receptors, as well as fucosylated and oligo-mannose type glycans in APP/PS1 mice versus wild type mice. Moreover, our preliminary functional study revealed that N-glycosylation was crucial for the membrane localization of NCAM1 and for maintaining the excitability and viability of neuron cells. Our work offered a panoramic view of the N-glycoproteomes in Alzheimers disease and revealed that generally impaired N-glycosylation promotes Alzheimers disease progression.

systems biology↗

bioRxiv2019

TRIM21-SERPINB5 aids GMPS repression to protect nasopharyngeal carcinoma cells from radiation-induced apoptosis

Nasopharyngeal carcinoma (NPC) is the most prevalent head and neck malignancy in South China and Southeast Asia. The main NPC treatment strategy is radiotherapy. However, recurrence resulting from radioresistance is a leading clinical bottleneck. Revealing the mechanism of NPC radioresistance would help improve the therapeutic effect. Here, our work reveals that TRIM21 (tripartite motif-containing 21) functions as an oncogene in NPC progression, and its ablation increases NPC cell radiosensitivity. Further analysis indicated that TRIM21 represses TP53 expression by mediating GMPS (guanine monophosphate synthase) ubiquitination and degradation after ionizing radiation. Mass spectrometry and co-immunoprecipitation showed that SERPINB5 (serpin family B member 5) interacts with both TRIM21 and GMPS. Epistatic analysis showed that SERPINB5 acts as an adaptor to recruit GMPS and introduce TRIM21 for ubiquitination. The in vitro and in vivo results validated the finding that SERPINB5 promotes NPC cell radioresistance. Furthermore, immunohistochemistry indicated that radioresistant patients have higher SERPINB5 expression. Overall, our data show that TRIM21-SERPINB5-mediated GMPS degradation facilitates TP53 repression, which promotes the radioresistance of NPC cells.

cancer biology↗

bioRxiv2019

Dynamic changes in the urine proteome in two ovarian cancer rat models

Ovarian cancer is the most lethal gynecological malignancy in women, and it is likely to metastasize and has a poor prognosis. The early and reliable diagnosis and monitoring of ovarian cancer is very important. Without a homeostasis mechanism, urine can reflect early systemic changes in the body and has a great potential to be used for the early detection of cancer. This study tested whether early changes could be detected in two ovarian cancer rat models. Two rat models were established by either intraperitoneal (i.p.) or orthotopic (o.t.) injection of NuTu-19 ovarian cancer cells in female Fischer344 rats. Urine samples from ovarian cancer rats were collected at five time points during cancer development, and urinary proteins from the rats were profiled by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Compared with pre-injection samples, 49 differential proteins that have human orthologues were significantly changed in the orthotopically injected model. Among them, 24 of the differential proteins have previously been reported to be associated with ovarian cancer, six of which were reported to be biomarkers of ovarian cancer. On the 7th day after orthotopic injection, four differential proteins (APOA1, OX2G, CHMP5, HEXB) were identified before obvious metastases appeared. In the intraperitoneal injection model, 76 differential proteins were changed during the course of ovarian cancer development. The results show that urine proteins could enable the early detection and monitoring of ovarian cancer progression and could lay a foundation for further exploration of the biomarkers of ovarian cancer.

biochemistry↗

bioRxiv2019

Performance of bitumen coating sheet using biomass pyrolysis oil

The \"green\" production of bitumen has raised increasing interest in recent years to reduce the environmental, energy and petro-based concerns. Bio-oil, prepared by biomass pyrolysis, can be used as substitute for petro-based bitumen in bitumen or bitumen-based coatings, for its similar properties of good adhesion and anti-corrosion characteristics. Although biomass is a renewable and widespread chemicals resource, its value-added utilization is still difficult. Several studies have qualitatively demonstrated the use of bio-bitumen in practical applications. The present study investigates the effects and properties and the incorporation of bio-bitumen shown to improve the performance of traditional petro-bitumen to some extent. Bio-bitumen was prepared from biomass pyrolysis oil and applied to self-adhesive and doped hot-melt sheets. Resulting physical properties demonstrate that bio-bitumen is a potential substitute in bitumen coating sheet.\n\nIMPLICATIONSThis paper is intended to verify the effect of pyrolyzed bio-oil from wheat straw on the performance of bitumen, as well as the feasibility of application in the coating sheet. Up to now, the research on bio-bitumen is mainly in pavement bitumen. In the present research, bio-bitumen was applied to the coating sheet in different proportions. Interestingly, the prepared coating sheet exhibited higher adhesion. Other performances, such as temperature stability, mechanical strength and temperature flexibility of coating sheet showed improvement in the presence of bio- oil, which indicated the suitability of bio-oil in coating sheet bitumen.

bioengineering↗

bioRxiv2019

Circular RNA profiling in the oocyte and cumulus cells reveals that circARMC4 is essential for porcine oocyte maturation

Thousands of circular RNAs (circRNAs) have been recently discovered in cumulus cells and oocytes from several species. However, the expression and function of circRNA during porcine oocyte meiotic maturation have been never examined. Here, we separately identified 7,067 and 637 circRNAs in both the cumulus cell and the oocyte via deep sequencing and bioinformatic analysis. Further analysis revealed that a faction of circRNAs is differentially expressed (DE) in a developmental stage-specific manner. The host genes of DE circRNAs are markedly enriched to multiple signaling pathways associated with cumulus cell function and oocyte maturation. Additionally, most DE circRNAs harbor several miRNA targets, suggesting that these DE circRNAs potentially act as miRNA sponge. Importantly, we found that maternal circARMC4 knockdown by siRNA microinjection caused a severely impaired chromosome alignment, and significantly inhibited first polar body extrusion and early embryo development. Taken together, these results demonstrate for the first time that circRNAs are abundantly and dynamically expressed in a developmental stage-specific manner in cumulus cells and oocytes, and maternally expressed circARMC4 is essential for porcine oocyte meiotic maturation and early embryo development.

developmental biology↗

bioRxiv2019

Multiplatform Biomarker Identification using a Data-driven Approach Enables Single-sample Classification

High-throughput gene expression profiles have allowed discovery of potential biomarkers enabling early diagnosis, prognosis and developing individualized treatment. However, it remains a challenge to identify a set of reliable and reproducible biomarkers across various gene expression platforms and laboratories for single sample diagnosis and prognosis. We address this need with our Data-Driven Reference (DDR) approach, which employs stably expressed housekeeping genes as references to eliminate platform-specific biases and non-biological variabilities. Our method identifies biomarkers with \"built-in\" features, and these features can be interpreted consistently regardless of profiling technology, which enable classification of single-sample independent of platforms. Validation with RNA-seq data of blood platelets shows that DDR achieves the superior performance in classification of six different tumor types as well as molecular target statuses (such as MET or HER2-positive, and mutant KRAS, EGFR or PIK3CA) with smaller sets of biomarkers. We demonstrate on the three microarray datasets that our method is capable of identifying robust biomarkers for subgrouping medulloblastoma samples with data perturbation due to different microarray platforms. In addition to identifying the majority of subgroup-specific biomarkers in Code-Set of nanoString, some potential new biomarkers for subgrouping medulloblastoma were detected by our method. Our results show that the DDR method contributes significantly to single-sample classification of disease and shed light on personalized medicine.

bioinformatics↗

bioRxiv2019

De novo Identification of Essential Protein Domains from CRISPR/Cas9 Tiling-sgRNA Knockout Screens

High-throughput CRISPR/Cas9 knockout screens using a tiling-sgRNA design permit in situ evaluation of protein domain function. To facilitate de novo identification of essential protein domains from such screens, we developed ProTiler, a computational method for the robust mapping of CRISPR knockout hyper-sensitive (CKHS) regions, which refers to the protein regions that are associated with strong sgRNA dropout effect in the screens. We used ProTiler to analyze a published CRISPR tiling screen dataset, and identified 175 CKHS regions in 83 proteins. Of these CKHS regions, more than 80% overlapped with annotated Pfam domains, including all of the 15 known drug targets in the dataset. ProTiler also revealed unannotated essential domains, including the N-terminus of the SWI/SNF subunit SMARCB1, which we validated experimentally. Surprisingly, the CKHS regions were negatively correlated with phosphorylation and acetylation sites, suggesting that protein domains and post-translational modification sites have distinct sensitivities to CRISPR/Cas9 mediated amino acids loss.

bioinformatics↗

bioRxiv2019

CytoGPS: A Web-Enabled Karyotype Analysis Tool for Cytogenetics

Karyotype data are the most common form of genetic data that is regularly used clinically. They are collected as part of the standard of care in many diseases, particularly in pediatric and cancer medicine contexts. Karyotypes are represented in a unique text-based format, with a syntax defined by the International System for human Cytogenetic Nomenclature (ISCN). While human-readable, ISCN is not intrinsically machine-readable. This limitation has prevented the full use of complex karyotype data in discovery science use cases. To enhance the utility and value of karyotype data, we developed a tool named CytoGPS. CytoGPS first parses ISCN karyotypes into a machine-readable format. It then converts the ISCN karyotype into a binary Loss-Gain-Fusion (LGF) model, which represents all cytogenetic abnormalities as combinations of loss, gain, or fusion events, in a format that is analyzable using modern computational methods. Such data is then made available for comprehensive \"downstream\" analyses that previously were not feasible.\n\nAvailability and ImplementationFreely available at https://cytogps.org\n\nContactprpayne@wustl.edu\n\nSupplementary informationNot applicable

bioinformatics↗

bioRxiv2019

A failed top-down control from prefrontal cortex to amygdala in generalized anxiety disorder: evidence from resting-state fMRI with Granger causality analysis

ObjectiveIn generalized anxiety disorder (GAD), abnormal top-down control from prefrontal cortex (PFC) to amygdala is a widely accepted hypothesis through which \"emotional dysregulation model\" may be explained. However, whether and how the PFC directly exerted abnormal top-down control on amygdala remained largely unknown. We aim to investigate the amygdala-based effective connectivity by using Granger causality analysis (GCA).\n\nMethodsThirty-five drug-naive patients with GAD and thirty-six healthy controls (HC) underwent resting-state functional MR imaging. We used seed-based Granger causality analysis to examine the effective connectivity between the bilateral amygdala and the whole brain. The amygdala-based effective connectivity was compared between the two groups.\n\nResultsIn HC, the left middle frontal gyrus exerted inhibitory influence on the right amygdala, while in GAD group, this influence was disrupted (single voxel P < 0.001, Gaussian random field corrected with P < 0.01).\n\nConclusionOur finding might provide new insight into the \"insufficient top-down control\" hypothesis in GAD.

neuroscience↗

bioRxiv2019

Conserving unprotected important coastal habitats in the Yellow Sea: shorebird occurrence, distribution and food resources at Lianyungang

The authors have withdrawn their manuscript since this preprint contain errors which have been corrected in the version published in the journal Global Ecology and Conservation (doi: 10.1016/j.gecco.2019.e00724). Therefore, the authors do not wish this preprint to be cited as reference for the project. If you have any questions, please contact the corresponding author.

ecology↗

bioRxiv2019

MetaMLP: A fast word embedding based classifier to profile target gene databases in metagenomic samples

The functional profile of metagenomic samples allows the understanding of the role of the microbes in their environment. Such analysis consists of assigning short sequencing reads to a particular functional category. Normally, manually curated databases are used for functional assignment where genes are arranged into different classes. Sequence alignment has been widely used to profile metagenomic samples against curated databases. However, this method is time consuming and requires high computing resources. Although several alignment free methods based on k-mer composition have been developed in the recent years, they still require a large amount of memory. In this paper, MetaMLP (Metagenomics Machine Learning Profiler) a machine learning method that represents sequences into numerical vectors (embeddings) and uses a simple one hidden layer neural network to profile functional categories is proposed. Unlike other methods, MetaMLP enables partial matching by using a reduced alphabet to build sequence embeddings from full and partial kmers. MetaMLP is able to identify a slightly larger number of reads compared to Diamond (one of the fastest sequence alignment method) as well as to perform accurate predictions with 0.99 precision and 0.99 recall. MetaMLP can process 100M reads in around 10 minutes in a laptop computer which is 50x faster than Diamond. MetaMLP is free for use, available at https://bitbucket.org/gaarangoa/metamlp/src/master/.

bioinformatics↗

bioRxiv2019

EPIC: MHC-I epitope prediction integrating mass spectrometry derived motifs and tissue-specific expression profiles

BackgroundAccurate prediction of epitopes presented by human leukocyte antigen (HLA) is crucial for personalized cancer immunotherapies targeting T cell epitopes. Mass spectrometry (MS) profiling of eluted HLA ligands, which provides high-throughput measurements of HLA associated peptides in vivo, can be used to faithfully model the presentation of epitopes on the cell surface. In addition, gene expression profiles measured by RNA-seq data in a specific cell/tissue type can significantly improve the performance of epitope presentation prediction. However, although large amount of high-quality MS data of HLA-bound peptides is being generated in recent years, few provide matching RNA-seq data, which makes incorporating gene expression into epitope prediction difficult. MethodsWe collected publicly available HLA peptidome and matching RNA-seq data of 34 cell lines derived from various sources. We built position score specific matrixes (PSSMs) for 21 HLA-I alleles based on these MS data, then used logistic regression (LR) to model the relationship among PSSM score, gene expression and peptide length to predict whether a peptide could be presented in each of the cell line. We further built a universal LR model, termed Epitope Presentation Integrated Prediction (EPIP), based on more than 180,000 unique HLA ligands collected from public sources and ~3,000 HLA ligands generated by ourselves, to predict epitope presentation for 66 common HLA-I alleles. ResultsWhen evaluating EPIP on large, independent HLA eluted ligand datasets, it performed substantially better than other popular methods, including MixMHCpred (v2.0), NetMHCpan (v4.0), and MHCflurry (v1.2.2), with an average 0.1% positive predictive value (PPV) of 52.01%, compared to 37.24%, 36.96%, 24.90% and 23.76% achieved by MixMHCpred, NetMHCpan-4.0 (EL), NetMHCpan-4.0 (BA) and MHCflurry, respectively. It is also comparable to EDGE, a recent deep learning-based model that is not publicly available, on predicting epitope presentation and selecting immunogenic cancer neoantigens. However, the simplicity and flexibility of EPIP makes it easier to be applied in diverse situations, and we demonstrated this by generating MS data for the HCC4006 cell line and adding the support of HLA-A*33:03 to EPIP. EPIP is publicly available as a web tool < http://epip.genomics.cn/>. Conclusionswe have developed an easy to use, publicly available epitope prediction tool, EPIP, that incorporates information from both MS and RNA-seq data, and demonstrated its superior performance over existing public methods.

bioinformatics↗

bioRxiv2019

Unexpected higher resilience to distraction during visual working memory in schizophrenia

Visual working memory (VWM) and distractibility are two core executive functions in human cognition. It has been suggested that schizophrenia (SZ) patients exhibit worse VWM performance and lower resilience to distraction compared with healthy control (HC) subjects. Previous studies, however, have largely investigated these two functions separately. It still remains unclear what are the mechanisms of the deficits, especially the interactions between the two cognitive domains. Here we modify the standard delay-estimation task in VWM and explicitly add distractors in the task so as to examine the two domains simultaneously. We find that SZ indeed exhibit worse performance compared with HC in almost all VWM load and distraction levels, a result consistent with most prior experimental findings. But adding distractors does not selectively impose larger impacts on SZ performance. Furthermore, unlike most previous studies that only focused on behavioral performance, we use the variable precision model to disentangle the distraction effect on different computational components of VWM (resources and resources allocation variability etc.). Surprisingly, adding distractors significantly elevates resources allocation variability--a parameter describing the heterogeneity of resource allocation across different targets--in HC but not in SZ. This counterintuitive result suggests that the internal VWM process in SZ is less interfered by the distractors. However, this unexpected higher resilience to distraction might be associated with less flexible cognitive control mechanisms. In sum, our work demonstrates that multiple cognitive functions might jointly contribute to dysfunctions in SZ and their interactions might manifest differently from merely summing their independent effects.

neuroscience↗

bioRxiv2019

Transcriptome Profiling of Mouse Brain and Lung under Dip2A Regulation Using RNA-Sequencing

Disconnected interacting 2 homolog A (DIP2A) gene is highly expressed in nervous system and respiratory system of developing embryos. However, genes regulated by Dip2a in developing brain and lung have not been systemically studied. Transcriptome of brain and lung in embryonic 19.5 day (E19.5) were compared between wild type and Dip2a-/- mice. Total RNAs were extracted from brain and lung of E19.5 embryos for RNA-Seq. Clean reads were mapped to mouse reference sequence (mm9) using Tophat and assembled into transcripts by Cufflinks. Edge R and DESeq were applied to identify differentially expressed genes (DEGs) and annotated under GO, COG, KEGG and TF. An average of 50 million reads per sample was mapped to the reference sequence. A total of 214 DEGs were detected in brain (82 up and 132 down) and 1900 DEGs in lung (1259 up and 641 down). GO enrichment analysis indicated that DEGs in both Brain and Lung were mainly enriched in biological processes DNA-templated transcription and Transcription from RNA polymerase II promoter, multicellular organism development, cell differentiation and apoptotic process. In addition, COG classification showed that both were mostly involved in Replication, Recombination and Repair, Signal transduction and mechanism, Translation, Ribosomal structure and Biogenesis and Transcription. KEGG enrichment analysis showed that brain was mainly enriched in Thryoid cancer pathway whereas lung in Complement and Coagulation Cascades pathway. Transcription factor (TF) annotation analysis identified Zinc finger domain containing (ZF) proteins were mostly regulated in lung and brain. Interestingly, study identified genes Skor2, Gpr3711, Runx1, Erbb3, Frmd7, Fut10, Sox11, Hapln1, Tfap2c and Plxnb3 from brain that play important roles in neuronal cell maturation, differentiation and survival; genes Hoxa5, Eya1, Ctsh, Erff1, Lama1, Lama2, Rspo2, Sox11, Spry4, Shh, Igf1 and Wnt7a from lung are important in lung development and morphogenesis. Expression levels of the candidate genes were validated by qRT-PCR. Genome wide transcriptional analysis using wild type and Dip2a knockout mice in brain and lung at embryonic day 19.5 (E19.5) provided a genetic basis of molecular function of these genes.

genetics↗