Biology subjects

Ning, Z.

Publications and source records attributed to Ning, Z..

63 records · Page 4Linked to original sources

bioRxiv2019

Integrative framework of cross-module deep biomarker for the prognosis of clear cell renal cell carcinoma: A retrospective TCGA project

PurposeWe aimed to integrate cross-module data for predicting the prognosis of clear cell renal cell carcinoma (ccRCC) based on deep learning and to explore the relationship between deep features from images and eigengenes form gene data.\n\nExperimental designA total of 209 patients with ccRCC with computed tomography (CT), histopathological images and RNA sequences were enrolled. A deep biomarker-based integrative framework was proposed to construct a prognostic model. Deep features extracted from CT and histopathological images by using deep learning combined with eigengenes generated from functional genomic data were used to predict ccRCC prognosis. Furthermore, the relationship between deep features and eigengenes was explored, and two survival subgroups identified by integrative cross-module biomarkers were subjected to functional analysis.\n\nResultsThe model based on the integrative framework stratified two subgroups of patients with a significant prognostic difference (P = 6.51e-6, concordance index [C-index] = 0.808, 95% confidence interval [CI] = 0.728-0.888) and outperformed the prediction based on their individual biomarkers in the independent validation cohort (n = 70, gene data: C-index = 0.452, CI = 0.336-0.567; histopathological images: C-index = 0.677, CI = 0.577-0.776; CT images: C-index = 0.774, CI = 0.670-0.879). On the basis of statistical relationship, deep features correlated or complemented with eigengenes both enhanced the predictive performance of eigengenes (P = 0.439, correlated: C-index = 0.785, CI = 0.685-0.886; complemented: C-index = 0.778, CI = 0.683-0.872). The functional analysis of subgroups also exhibited reasonable results.\n\nConclusionThe model based on the integrative framework of cross-module deep biomarkers can efficiently predict ccRCC prognosis, and the framework with a code is shared to act as a reliable and powerful tool for further studies.

bioinformatics↗

bioRxiv2019

A Clostridia-rich microbiota contributes to increased excretion of bile acids in diarrhea-predominant irritable bowel syndrome

ObjectiveAn excess of fecal bile acids (BAs) is thought to be one of the mechanisms for diarrhea-predominant irritable bowel syndrome (IBS-D). However, the factors causing excessive BA excretion remains unclear. Given the importance of gut microbiota in BA metabolism, we hypothesized that gut dysbiosis might contribute to excessive BA excretion in IBS-D.\n\nDesignMetabolomic and metagenomic analyses were performed of specimens from 290 IBS-D patients and 89 healthy volunteers. By transplanting human microbiota and manipulating specific microbiome species in mice, the effects of microbiota on host BA metabolism were assessed at metabolic, genetic and protein levels. Effects of individual and mixed BAs on enterohepatic feedback pathways were also tested in vitro and in vivo.\n\nResultsTotal fecal BAs were excessively excreted in 24.5% of IBS-D patients. Their fecal metagenomes showed increased abundances of Clostridia and BA-transforming genes (hdhA and bais). The increases of Clostridia bacteria (e.g. C. scindens) were positively associated with the levels of fecal BAs and serum 7-hydroxy-4-cholesten-3-one (C4), while being negatively correlated with serum fibroblast growth factor 19 (FGF19). Both Clostridia-rich human microbiota and C. scindens enhanced levels of serum C4 and hepatic conjugated BAs in mice recipients and reduced ileal FGF19 expression. Inhibition of Clostridium species by vancomycin yielded opposite findings. Clostridia-derived BAs (e.g. conjugated and free ursodeoxycholic acid) significantly suppressed intestinal FGF19 expression.\n\nConclusionThe Clostridia-rich microbiota contributes to excessive BA excretion in IBS-D patients. This study provided the basis for more precise clinical diagnosis and management for IBS-D.

microbiology↗

bioRxiv2019

An in vitro model maintaining taxon-specific functional activities of the gut microbiome

The gut microbiome is a new target for therapeutics. In vitro high-throughput culture models could provide time-and-cost saving solutions to discover microbiome responses to drugs. Unfortunately, there has been no report of in vitro models capable of maintaining functional and compositional profiles resembling the in vivo gut microbiome. Here, we developed and validated a high-throughput culturing model named Mipro to maintain individuals microbiomes. The Mipro model quintupled viable bacteria count while maintained the functional and compositional profiles of individuals gut microbiomes. Comparison of taxon-specific functions between pre -and-post culture microbiomes showed Pearsons correlation coefficient r of 0.83 {+/-} 0.03. Moreover, the Mipro model also exhibited a high degree of in vitro - in vivo correlation (Pearsons r of 0.68 {+/-} 0.09) in microbial responses to metformin in mice fed a high-fat diet. Mipro provides a highly simulated gut microbiome for high-throughput investigation of drug-microbiome interactions.

microbiology↗

bioRxiv2019

RapidAIM: A culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

The gut microbiome has been associated with a growing list of diseases. Drugs and other compounds can affect the microbiome, but our understanding of drug-induced changes in individual microbiomes is limited due to a lack of rapid and effective high-throughput assay methods. We developed an approach named Rapid Assay of Individual Microbiome (RapidAIM) to screen xenobiotics against individual microbiomes. RapidAIM was evaluated by testing 43 compounds against five individual microbiomes using a metaproteomic approach. We show that our workflow enables quantitative profiling of the microbiome. The tested compounds significantly affected overall microbiome abundance, microbiome composition and functional pathways at multiple taxonomic levels. The microbiome responses to berberine, metformin, diclofenac, fructooligosaccharide and most antibiotics were consistent among most individuals. Interestingly, most of our tested NSAIDs, statins, and histamine-2 blockers induced strong and individually distinct responses. Our workflow offers an effective solution to systematically study the effects of many different compounds on individual microbiomes.

microbiology↗

bioRxiv2019

Therapeutic Targeting of Casein Kinase 1δ/ε in an Alzheimer's Disease Mouse Model

Sleep disturbances and memory impairment are common symptoms of Alzheimers disease (AD). Given that the circadian clock regulates sleep, hippocampal function, and neurodegeneration, it represents a therapeutic target against AD. Casein kinase 1{delta}/{varepsilon} (CK1{delta}/{varepsilon}) are clock regulators and overexpressed in AD brains, making them viable targets to improve sleep and cognition. We assessed the effects of a small molecule CK1{delta}/{varepsilon} inhibitor (PF-670462) in a cellular model of circadian clocks and in 3xTg-AD mice. Mass spectrometry-based proteomic analyses revealed that PF-670462 treatment in vitro upregulated multiple proteins that are downregulated in AD, while administration in 3xTg-AD mice reversed hippocampal proteomic alterations in diverse AD-associated and clock-regulated pathways, including synaptic plasticity and amyloid precursor protein processing. Furthermore, PF-670462 rescued working memory and normalized behavioural circadian rhythms in 3xTg-AD mice. Our study provides proof of concept for CK1{delta}/{varepsilon} inhibition and direct clock modulation against AD-related proteomic changes, memory impairment, and circadian disturbances.

biochemistry↗

bioRxiv2018

Genomic underpinnings of lifespan allow prediction and reveal basis in modern risks

We use a multi-stage genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near GADD45G, KCNK3, LDLR, POM121C, ZC3HC1, and ABO. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and tissue-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer -but not other cancers-explain the most variance, possibly reflecting modern susceptibilities, whilst cancer may act through many rare variants, or the environment. Resultant polygenic scores predict a mean lifespan difference of around five years of life across the deciles.

genomics↗

bioRxiv2018

The key lethal effect existed in the antibacterial behavior of short, medium, and long chain fatty acid monoglycerides on Escherichia coli

Monoglyceride is an amphiphilic molecule with promising antimicrobial activity for bacteria; however, the key lethal effect in its antibacterial behavior was still unknown. In the study, monobutyrate (MB), monolaurate (ML), monomyristate (MM) were selected to represent the short, medium, and long chain monoglycerides to compare their inhibitory effect against Escherichia coli, and a new dose-dependent inhibitory mechanism was proposed by the key lethal effect. The minimal inhibitory concentration and antibacterial curve showed a huge diversity existed in biology activity of MB, ML and MM. The results in scanning electron microscopy and flow cytometry assay indicated that the interference level of MB on cell membrane was obviously weaker than that of ML and MM, while the latter two had similar performance in increasing cell permeability at low doses. The results presented in UV-Vis spectroscopy, cell cycle and biomacromolecules synthesis inhibition assay showed that the cell cycle of Escherichia coli was obviously affected by three monoglycerides at doses near MIC, which was therefore regarded as the key lethal effect. The reason for the better biological activity of MM than ML was the stronger interference ability on bacterial cell cycle. In addition, an expanded antibacterial mode was raised that cell permeability increase at low doses was antimicrobial basis, cell cycle arrest at medium doses played the key lethal effect, and cell lysis at high doses was the result of combined action.

microbiology↗

bioRxiv2018

The identification of critical lethal action in antimicrobial mechanism of glycerol monomyristate against foodborne pathogens

Glycerol monomyristate (GMM) is a promising antimicrobial substance due to its broad antibacterial spectrum: however, the critical lethal action in its antimicrobial mechanism for foodborne pathogens remains unclear. In the present study, the inhibitory activities of GMM on Escherichia coli (E. coli), Staphylococcus aureus (S. aureus) and Candida albicans (C. albicans) were compared, and its membrane and intracellular action mechanism was investigated. The results showed that the susceptibility of E. coli to GMM was the highest, followed by S. aureus, and C. albicans being the poorest. Using flow cytometry, the GMM dose causing above 50% permeability ratio on E. coli was lower than that on S. aureus. The images from scanning electron microscope revealed no doses difference existed between the two strains when the obvious cell damage occurred. Furthermore, cell cycle and multiple fluorescent staining assays showed only the cell division of E. coli and S. aureus, excluding that of C. albicans, was obviously affected at 1/4 MIC and 1/2 MIC, indicating that the DNA interfere and subsequent cell division inhibition was likely to be the critical lethal action with doses near MIC, which can also explain the poor sensitivity of C. albicans.\n\nImportanceFoodborne pathogens, as a common source of biological pollution in the food industry, can cause millions of food poisoning incidents each year, which poses great risks to consumers health and safety. The use of monoglyceride as an edible surfactant to inhibit the growth of food-borne microorganisms has been a long time, but the relevant antibacterial mechanism is too broad to accurately grasp its key lethal effect and its action doses, which not only affects the antibacterial efficiency, but also may result in the abnormalities of food flavor when adding at overdoses. The significance of the study is to identify the key lethal effect and its action doses, which will greatly enhance the understanding of the response mechanism of different types of foodborne pathogens to monoglycerides, and provide a more reasonable reference for differential control and treatment of different gastrointestinal infections when combined with antibiotics in clinical.

microbiology↗

bioRxiv2017

Separating an allele associated with late flowering and slow maturation of Arabidopsis thaliana from population structure

Genome-wide association analysis is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of double-phenotype analysisto uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, acommon allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locusis co-selected with flowering-time-related genes. The discovered pleiotropic genotypephenotype map provides new insights into understanding the genetic correlation of complex traits.

genetics↗