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Persistent organic pollutants and plasma microRNAs: A community-based profiling analysis

ENVIRONMENT INTERNATIONAL 2025年 197卷 109328页

作者： Qu, Jingli Li, Wending Jia, Chengyong Jiang, Qin Tang, Rui Yin, Yu Wang, Xi Long, Pinpin Wu, Tangchun Yuan, Yu Huazhong Univ Sci & Technol Tongji Med Coll Dept Occupat & Environm Hlth Sch Publ HlthMinist EducKey Lab Environm & Hlth Wuhan 430030 Peoples R China Huazhong Univ Sci & Technol Tongji Med Coll Sch Publ Hlth State Key Lab Environm Hlth Incubating Wuhan 430030 Peoples R China Columbia Univ Mailman Sch Publ Hlth Dept Environm Hlth Sci New York NY 10032 USA

Background: Whether exposure to persistent organic pollutants (POPs) may incur microRNAs (miRNAs) dysregulation remains largely unclear. Objectives: We aim to identify the miRNA signature and related pathways of low-level POPs exposure in a community-based population. Methods: We used general linear regression to model the association of POPs with plasma miRNAs, adjusting for age, gender, smoking, alcohol consumption, body mass index, triglyceride, and total cholesterol levels. We performed pathway enrichment analysis based on 11 experimentally validated and prediction-based databases, and performed tissue specificity analysis. Results: We identified 19 POPs significantly associated with 23 miRNAs at false discovery rate-adjusted P value < 0.2, most of which were related to organophosphorus and organochlorine pesticides. Pathway enrichment of the associated miRNAs highlighted chromosome segregation, RNA splicing, autophagy regulation, lipid metabolism, cell growth, development and differentiation, cell cycle regulation, neural network construction, and signal transduction. Notably, 13 POPs were positively associated with miR-6810-3p, a miRNA enriched in temporal lobe with high tissue specificity (Tissue Specificity Index = 0.78). Pathway analysis revealed that miR-6810-3p contributes to the positive regulation of autophagy and multiple cellular functions related to the nervous system such as transport along microtubules, maintenance of cell polarity, and synaptic transmission. Conclusion: In conclusion, we identified POPs-related miRNA signatures in community-dwelling adults, and highlighted miR-6810-3p in association with multiple POPs, with a potential role in nervous system regulation.

关键词： Persistent organic pollutants MicroRNAs Pathway enrichment gene ontology enrichment analysis Neurological function

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Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality

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BMC BIOINFORMATICS 2019年第1期20卷 1-9页

作者： Rendleman, Michael C. Buatti, John M. Braun, Terry A. Smith, Brian J. Nwakama, Chibuzo Beichel, Reinhard R. Brown, Bart Casavant, Thomas L. Univ Iowa Ctr Bioinformat & Computat Biol Dept Elect & Comp Engn Seamans Ctr 5017 Iowa City IA 52242 USA Univ Iowa Carver Coll Med Dept Radiat Oncol LL W Pomerantz Family Pavil200 Hawkins Dr Iowa City IA 52242 USA Univ Iowa Ctr Bioinformat & Computat Biol Dept Biomed Engn Seamans Ctr 5017 Iowa City IA 52242 USA Univ Iowa Dept Biostat 145 N Riverside Dr100 CPHB Iowa City IA 52242 USA Univ Iowa Ctr Bioinformat & Computat Biol Seamans Ctr 5017 Iowa City IA 52242 USA Univ Iowa Dept Internal Med Dept Elect & Comp Engn Iowa Inst Biomed Imaging Iowa City IA 52242 USA 3312 Seamans Ctr Engn Arts & Sci Iowa City IA 52242 USA

BackgroundIn the era of precision oncology and publicly available datasets, the amount of information available for each patient case has dramatically increased. From clinical variables and PET-CT radiomics measures to DNA-variant and RNA expression profiles, such a wide variety of data presents a multitude of challenges. Large clinical datasets are subject to sparsely and/or inconsistently populated fields. Corresponding sequencing profiles can suffer from the problem of high-dimensionality, where making useful inferences can be difficult without correspondingly large numbers of instances. In this paper we report a novel deployment of machine learning techniques to handle data sparsity and high dimensionality, while evaluating potential biomarkers in the form of unsupervised transformations of RNA data. We apply preprocessing, MICE imputation, and sparse principal component analysis (SPCA) to improve the usability of more than 500 patient cases from the TCGA-HNSC dataset for enhancing future oncological decision support for Head and Neck Squamous Cell Carcinoma (HNSCC).ResultsImputation was shown to improve prognostic ability of sparse clinical treatment variables. SPCA transformation of RNA expression variables reduced runtime for RNA-based models, though changes to classifier performance were not significant. gene ontology enrichment analysis of gene sets associated with individual sparse principal components (SPCs) are also reported, showing that both high- and low-importance SPCs were associated with cell death pathways, though the high-importance gene sets were found to be associated with a wider variety of cancer-related biological *** imputation allowed us to impute missing values for clinically informative features, improving their overall importance for predicting two-year recurrence-free survival by incorporating variance from other clinical variables. Dimensionality reduction of RNA expression profiles via SPCA reduced both computat

关键词： Machine learning hnscc tcga Dimensionality reduction gene ontology enrichment analysis Decision support Unsupervised transformation

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Bioinformatics analysis of ferroptosis in spinal cord injury

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Neural Regeneration Research 2023年第3期18卷 626-633页

作者： Jin-Ze Li Bao-You Fan Tao Sun Xiao-Xiong Wang Jun-Jin Li Jian-Ping Zhang Guang-Jin Gu Wen-Yuan Shen De-Rong Liu Zhi-Jian Wei Shi-Qing Feng International Cooperation Base of Spinal Cord Injury Tianjin Key Laboratory of Spine and Spinal Cord InjuryDepartment of OrthopedicsTianjin Medical University General HospitalTianjinChina Department of Orthopedics Qilu Hospital of Shandong UniversityJinanShandong ProvinceChina Shandong University Centre for Orthopedics Advanced Medical Research InstituteCheeloo College of MedicineShandong UniversityJinanShandong ProvinceChina

Ferroptosis plays a key role in aggravating the progression of spinal cord injury(SCI),but the specific mechanism remains *** this study,we constructed a rat model of T10 SCI using a modified Allen *** identified 48,44,and 27 ferroptosis genes that were differentially expressed at 1,3,and 7 days after SCI *** with the sham group and other SCI subgroups,the subgroup at 1 day after SCI showed increased expression of the ferroptosis marker acyl-CoA synthetase long-chain family member 4 and the oxidative stress marker malondialdehyde in the injured spinal cord while glutathione in the injured spinal cord was *** findings with our bioinformatics results suggested that 1 day after SCI was the important period of ferroptosis *** analysis identified the following top ten hub ferroptosis genes in the subgroup at 1 day after SCI:STAT3,JUN,TLR4,ATF3,HMOX1,MAPK1,MAPK9,PTGS2,VEGFA,and ***-time polymerase chain reaction on rat spinal cord tissue confirmed that STAT3,JUN,TLR4,ATF3,HMOX1,PTGS2,and RELA mRNA levels were up-regulated and VEGFA,MAPK1 and MAPK9 mRNA levels were *** potential compounds were predicted using the DSigDB database as potential drugs or molecules targeting ferroptosis to repair *** also constructed a ferroptosis-related mRNA-miRNA-lncRNA network in SCI that included 66 lncRNAs,10 miRNAs,and 12 *** results help further the understanding of the mechanism underlying ferroptosis in SCI.

关键词： bioinformatics drug ferroptosis gene ontology enrichment analysis gene-miRNA network Kyoto Encyclopedia of genes and Genomes pathway mRNA-miRNA-lncRNA network progression spinal cord injury

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Salivary Proteome Patterns Affecting Human Salt Taste Sensitivity

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JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2017年第42期65卷 9275-9286页

作者： Stolle, Theresa Grondinger, Freya Dunkel, Andreas Meng, Chen Medard, Guillaume Kuster, Bernhard Hofmann, Thomas Tech Univ Munich Chair Food Chem & Mol Sensory Sci Lise Meitner Str 34 D-85354 Freising Weihenstephan Germany Tech Univ Munich Chair Prote & Bioanalyt Emil Erlenmeyer Forum 5 D-85354 Freising Weihenstephan Germany

To investigate the role of perireceptor events in inter-individual variability in salt taste sensitivity, 31 volunteers were monitored in their detection functions for sodium chloride (NaCl) arid classified into sensitive (0.6-1.7 mmol/L), medium-sensitive (1.8-6.9 mmol/L), and nonsensitive (7.0-11.2 mmol/L) subjects. Chemosensory intervention of NaCl-sensitive (S+) and nonsensitive (S-) panellists with potassium chloride, ammonium chloride, and sodium gluconate showed the salt taste sensitivity to be specific for NaCl. As no significant differences were found between S+ and S- subjects in salivary sodium and protein Content, salivary proteome differences and their stimulus-induced dynamic changes were analyzed by tryptic digestion, iTRAQ labeling, and liquid chromatography-tandem mass spectrometry analysis. Differences in the salivary proteome between S+ and S- subjects were found primarily in resting saliva and were largely independent of the dynamic alterations observed upon salt stimulation. gene ontology enrichment analysis of key proteins, i.e., immunoglobulin heavy constant y1, myeloblastin, cathepsin G, and kallikrein, revealed significantly increased serine-type endopeptidase activity for the S+ group, while the S- group exhibited augmented cysteine-type endopeptidase inhibitor activity by increased abundances in lipocalin-1 and cystatin-D,-S, and -SN, respectively. As proteases have been, suggested, to facilitate transepithelial sodium transport by cleaving the y-subunit of the epithelial sodium channel (ENaC) and protease inhibitors have been Shown to reduce ENac-mediated sodium transport, the differentially modulated proteolytic activity patterns observed in vivo for S+ and S- subjects show evidence of them playing a crucial role in affecting human NaCl sensitivity.

关键词： salt taste taste Sensitivity saliva salivary proteome sodium chloride gene ontology enrichment analysis

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Prediction of the anti-inflammatory mechanisms of curcumin by module-based protein interaction network analysis

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Acta Pharmaceutica Sinica B 2015年第6期5卷 590-595页

作者： Yanxiong Gan Shichao Zheng Jan P.A.Baak Silei Zhao Yongfeng Zheng Nini Luo Wan Liao Chaomei Fu State Key Laboratory Breeding Base of Systematic Research Development and Utilization of Chinese Medicine ResourcesSchool of PharmacyChengdu University of Traditional Chinese Medicine School of Chinese Pharmacy Beijing University of Chinese Medicine Faculty of Sports Sciences and Medicine Technical University Munich

Curcumin, the medically active component from Curcuma Tonga (Turmeric), is widely used to treat inflammatory diseases. Protein interaction network (PIN) analysis was used to predict its mechanisms of molecular action. Targets of curcumin were obtained based on ChEMBL and STITCH databases. Protein protein interactions (PPIs) were extracted from the String database. The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology (GO) enrichment analysis based on molecular complex detection (MCODE). A PIN of curcumin with 482 nodes and 1688 interactions was constructed, which has scale-free, small world and modular properties. Based on analysis of these function modules, the mechanism of curcumin is proposed. Two modules were found to be intimately associated with inflammation. With function modules analysis, the anti-inflammatory effects of curcumin were related to SMAD, ERG and mediation by the TLR family. TLR9 may be a potential target of curcumin to treat inflammation. (C) 2015 Chinese Pharmaceutical Association and Institute of Materia Medica, Chinese Academy of Medical Sciences. Production and hosting by Elsevier B.V.

关键词： Curcumin Protein interaction network Module Anti-inflamatory Molecular mechanism gene ontology enrichment analysis Molecular complex detection Cytoseape

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Identification of Soybean genes Related to Soybean Seed Protein Content Based on Quantitative Trait Loci Collinearity analysis

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JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2019年第1期67卷 258-274页

作者： Huang, Shiyu Yu, Jingyao Li, Yingying Wang, Jingxin Wang, Xinyu Qi, Huidong Xu, Mingyue Qin, Hongtao Yin, Zhengong Mei, Hongyao Chang, Huilin Gao, Hongxiu Liu, Shanshan Zhang, Zhenguo Zhang, Shuli Zhu, Rongsheng Liu, Chunyan Wu, Xiaoxia Jiang, Hongwei Hu, Zhenbang Xin, Dawei Chen, Qingshan Qi, Zhaoming Northeast Agr Univ Coll Agr Harbin 150030 Heilongjiang Peoples R China Heilongjiang Acad Agr Sci Inst Wuchang Rice Res Wuchang 150229 Heilongjiang Peoples R China

Increasing the protein content of soybean seeds through a higher ratio of glycinin is important for soybean breeding and food processing;therefore, the integration of different quantitative trait loci (QTLs) is of great significance. In this study, we investigated the collinearity of seed protein QTLs. We identified 192 collinear protein QTLs that formed six hotspot regions. The two most important regions had seed protein 36-10 and seed protein 36-20 as hub nodes. We used a chromosome segment substitution line (CSSL) population for QTL validation and identified six CSSL materials with collinear QTLs. Five materials with higher protein and glycinin contents in comparison to the recurrent parent were analyzed. A total of 13 candidate genes related to seed protein from the QTL hotspot intervals were detected, 8 of which had high expression in mature soybean seeds. These results offer a new analysis method for molecular-assisted selection (MAS) and improvement of soybean product quality.

关键词： soybean protein QTLs collinearity analysis candidate genes QTL validation SDS-PAGE analysis qRT-PCR verification gene ontology enrichment analysis

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RNA-seq analysis reveals a key role of brassinolide-regulated pathways in NaCl-stressed cotton

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BIOLOGIA PLANTARUM 2017年第4期61卷 667-674页

作者： Shu, H. M. Guo, S. Q. Gong, Y. Y. Jiang, L. Zhu, J. W. Ni, W. C. Jiangsu Acad Agr Sci Inst Ind Crops Key Lab Cotton & Rapeseed Minist Agr Nanjing 210014 Jiangsu Peoples R China

Brassinolide (BL) alleviates salt injury in cotton seedlings;however, little is known about the molecular mechanisms of this response. In this study, digital gene expression analysis was performed to better understand the regulatory pathways of BL in NaCl-stressed cotton (Gossypium hirsutum L.). Compared with control plants (CK), a total of 1 162 and 7 659 differentially expressed genes (DEGs) were detected in the leaves and roots of NaCl-treated plants, respectively. Most of the DEGs in NaCl-treated plants, compared to CK, were regulated by BL. Moreover, expression patterns of DEGs in BL+NaCl treated plants were similar to those in CK plants;however, the responses of DEGs in the leaves and roots of NaCl-treated plants to BL differed. In the roots, BL-regulated DEGs were involved in protein biosynthesis, whereas in the leaves, BL promoted photosynthesis in NaCl-stressed cotton. BL treatment also significantly increased the overall biomass, chlorophyll a + b content in leaves, and the protein content in roots in NaCl-stressed cotton. The downregulation of stress-responsive genes in BL+NaCl-stressed leaves was also found. These results suggest that BL can alleviate NaCl injury in cotton plants.

关键词： chlorophyll differentially expressed genes gene ontology enrichment analysis photosynthesis proteins

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Prediction of a Cell-Class-Specific Mouse Mesoconnectome Using gene Expression Data

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NEUROINFORMATICS 2020年第4期18卷 611-626页

作者： Timonidis, Nestor Bakker, Rembrandt Tiesinga, Paul Radboud Univ Nijmegen Donders Ctr Neurosci Neuroinformat Dept Heyendaalseweg 135 NL-6525 AJ Nijmegen Netherlands Julich Res Ctr Inst Neurosci & Med INM 6 Wilhelm Johnen Str D-52425 Julich Germany Julich Res Ctr Inst Adv Simulat IAS 6 Wilhelm Johnen Str D-52425 Julich Germany Julich Res Ctr JARA BRAIN Inst 1 Wilhelm Johnen Str D-52425 Julich Germany

Reconstructing brain connectivity at sufficient resolution for computational models designed to study the biophysical mechanisms underlying cognitive processes is extremely challenging. For such a purpose, a mesoconnectome that includes laminar and cell-class specificity would be a major step forward. We analyzed the ability of gene expression patterns to predict cell-class and layer-specific projection patterns and assessed the functional annotations of the most predictive groups of genes. To achieve our goal we used publicly available volumetric gene expression and connectivity data and we trained computational models to learn and predict cell-class and layer-specific axonal projections using gene expression data. Predictions were done in two ways, namely predicting projection strengths using the expression of individual genes and using the co-expression of genes organized in spatial modules, as well as predicting binary forms of projection. For predicting the strength of projections, we found that ridge (L2-regularized) regression had the highest cross-validated accuracy with a median r(2) score of 0.54 which corresponded for binarized predictions to a median area under the ROC value of 0.89. Next, we identified 200 spatial gene modules using a dictionary learning and sparse coding approach. We found that these modules yielded predictions of comparable accuracy, with a median r(2) score of 0.51. Finally, a gene ontology enrichment analysis of the most predictive gene groups resulted in significant annotations related to postsynaptic function. Taken together, we have demonstrated a prediction workflow that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.

关键词： Spatial gene co-expression Connectomics Machine learning Predictive models Mouse brain Axonal projection gene expression gene ontology enrichment analysis Ridge regression Dictionary learning Sparse coding ROC analysis Cellularly resolved connectome

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Pop's Pipes: poplar gene expression data analysis pipelines

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TREE geneTICS & GENOMES 2014年第4期10卷 1093-1101页

作者： Li, Xiang Gunasekara, Chathura Guo, Yufeng Zhang, Hang Lei, Liang Tunlaya-Anukit, Sermsawat Busov, Victor Chiang, Vincent Wei, Hairong Michigan Technol Univ Dept Comp Sci Houghton MI 49931 USA Michigan Technol Univ Comp Sci & Engn Program Houghton MI 49931 USA Chongqing Univ Sci & Technol Dept Comp Technol Chongqing Peoples R China N Carolina State Univ Dept Forestry & Environm Resources Forest Biotechnol Grp Raleigh NC 27695 USA Michigan Technol Univ Sch Forest Resources & Environm Sci Houghton MI 49931 USA Michigan Technol Univ Biotechnol Res Ctr Houghton MI 49931 USA Northeast Forestry Univ State Key Lab Forest Tree Genet & Breeding Harbin 150040 Heilongjiang Peoples R China

We developed multiple gene expression pipelines and assembled them into a web-based tool called Pop's Pipes to facilitate preprocessing and analysis of substantial poplar gene expression data. The input data can be spatiotemporal microarray and RNA-seq data from comparable tissues, time points, or treatment-vs-control conditions. Pop's Pipes can be used to identify differentially expressed genes between one or multiple paired tissues, time points, or treatment-vs-control conditions in a single in silico analysis. The differentially expressed genes (DEGs) obtained for each comparison will be automatically analyzed by Pop's Pipes for identifying significantly enriched gene ontologies and interpro protein domains. Also, significantly changed metabolic pathways across all input data sets will be identified. We also integrated a pipeline into Pop's Pipes for constructing any of three type gene ontology trees when a short list of gene ontologies from biological processes, molecular functions, or cellular components is used as an input. The resulting information from Pop's Pipes enables scrutiny to create spatiotemporal models and hypotheses to understand how poplar develops and functions. Pop's Pipes can analyze a microarray or RNA-seq data set with 10 time points in 4-10 h, with each time point containing three replicates of treatments and three controls. Such a data set usually takes a bioinformatician a few months to a year to analyze. Pop's Pipes can thus save users tremendous amounts of research time when large numbers of comparative data need to be analyzed.

关键词： Poplar Microarray RNA-seq data Differentially expressed genes Pathway enrichment analysis gene ontology enrichment analysis Protein domain enrichment analysis Pipeline gene ontology tree

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Celiac disease biomarkers identified by transcriptome analysis of small intestinal biopsies

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CELLULAR AND MOLECULAR LIFE SCIENCES 2018年第23期75卷 4385-4401页

作者： Bragde, Hanna Jansson, Ulf Fredrikson, Mats Grodzinsky, Ewa Soderman, Jan Ryhov Cty Hosp Lab Med Bldg E3Level 4 S-55185 Jonkoping Sweden Linkoping Univ Dept Clin & Expt Med Fac Med & Hlth Sci Linkoping Sweden Ryhov Cty Hosp Dept Pediat Jonkoping Sweden Linkoping Univ Dept Clin & Expt Med & Forum Ostergotland Fac Med & Hlth Sci Linkoping Sweden Natl Board Forens Med Div Forens Genet & Forens Toxicol Linkoping Sweden Linkoping Univ Dept Med & Hlth Fac Med & Hlth Sci Linkoping Sweden

Establishing a celiac disease (CD) diagnosis can be difficult, such as when CD-specific antibody levels are just above cutoff or when small intestinal biopsies show low-grade injuries. To investigate the biological pathways involved in CD and select potential biomarkers to aid in CD diagnosis, RNA sequencing of duodenal biopsies from subjects with either confirmed Active CD (n=20) or without any signs of CD (n=20) was performed. gene enrichment and pathway analysis highlighted contexts, such as immune response, microbial infection, phagocytosis, intestinal barrier function, metabolism, and transportation. Twenty-nine potential CD biomarkers were selected based on differential expression and biological context. The biomarkers were validated by real-time polymerase chain reaction of eight RNA sequencing study subjects, and further investigated using an independent study group (n=43) consisting of subjects not affected by CD, with a clear diagnosis of CD on either a gluten-containing or a gluten-free diet, or with low-grade intestinal injury. Selected biomarkers were able to classify subjects with clear CD/non-CD status, and a subset of the biomarkers (CXCL10, GBP5, IFI27, IFNG, and UBD) showed differential expression in biopsies from subjects with no or low-grade intestinal injury that received a CD diagnosis based on biopsies taken at a later time point. A large number of pathways are involved in CD pathogenesis, and gene expression is affected in CD mucosa already in low-grade intestinal injuries. RNA sequencing of low-grade intestinal injuries might discover pathways and biomarkers involved in early stages of CD pathogenesis.

关键词： RNA-seq RNA sequencing Molecular biomarkers gene expression profiling gene ontology enrichment analysis

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