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Microbiome data analysis with applications to pre-clinical studies using QIIME2: Statistical considerations

Genes & Diseases 2021年第2期8卷 215-223页

作者： shesh n.rai Chen Qian Jianmin Pan Jayesh P.rai Ming Song Juhi Bagaitkar Michael Merchant Matthew Cave nejat K.Egilmez Craig J.McClain Biostatistics and Bioinformatics Facility James Graham Brown Cancer CenterUniversity of LouisvilleLouisvilleKY40202USA Department of Biostatistics and Bioinformatics University of LouisvilleLouisvilleKY40202USA University of Louisville Alcohol Research Center University of LouisvilleLouisvilleKY40202USA University of Louisville Hepatobiology&Toxicology Center University of LouisvilleLouisvilleKY40202USA Department of Oral Immunology&Infectious Diseases University of LouisvilleLouisvilleKY40202USA Department of Medicine University of LouisvilleLouisvilleKY40202USA Robley Rex Louisville VAMC LouisvilleKY40206USA Department of Microbiology&Immunology University of LouisvilleLouisvilleKY40202USA

Diversity analysis and taxonomic profiles can be generated from marker-gene sequence data with the help of many available computational *** Quantitative Insights into Microbial Ecology Version 2(QIIME2)has been widely used for 16S rRnA data *** many articles have demonstrated the use of QIIME2 with suitable datasets,the application to preclinical data has rarely been talked *** issues involved in the pre-clinical data include the low-quality score and small sample size that should be addressed properly during *** addition,there are few articles that discuss the detailed statistical methods behind those alpha and beta diversity significance tests that researchers are eager to *** the program without knowing the logic behind it is extremely *** this article,we first provide a guideline for analyzing 16S rRnA data using *** we will talk about issues in pre-clinical data,and how they could impact the ***,we provide brief explanations of statistical methods such as group significance tests and sample size calculation.

关键词： 16S rRnA gene Alpha diversity AnOVA Beta diversity Bioinformatics Microbiome data QIIME Sample size calculation

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Proteomics and metabolic phenotyping define principal roles for the aryl hydrocarbon receptor in mouse liver

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Acta Pharmaceutica Sinica B 2021年第12期11卷 3806-3819页

作者： Jian Jin Banrida Wahlang Monika Thapa Kimberly Z.Head Josiah E.Hardesty Sudhir Srivastava Michael L.Merchant shesh n.rai Russell A.Prough Matthew C.Cave Department of Pharmacology&Toxicology theUniversity of Louisville School ofMedicineLouisvilleKY 40202USA Department of Endocrinology the Second Affiliated Hospital&Yuying Children’s HospitalWenzhou Medical UniversityWenzhou 325027China Division of Gastroenterology Hepatology&NutritionDepartment of Medicinethe University of Louisville School of MedicineLouisvilleKY 40202USA Superfund Research Center the University of LouisvilleLouisvilleKY 40202USA eDepartment of Biochemistry and Molecular Geneticsthe University of Louisville School of MedicineLouisvilleKY 40202USA Department of Bioinformatics and Biostatistics the School of Public Health and Information Sciencesthe University of LouisvilleLouisvilleKY 40202USA Centre for Agricultural Bioinformatics ICAR-Indian Agricultural Statistics Research InstituteNew Delhi 110012India The Center for Integrative Environmental Health Sciences University of LouisvilleLouisvilleKY 40202USA Division of nephrology&Hypertension Department of Medicinethe University of Louisville School of MedicineLouisvilleKY 40202USA The Hepatobiology and Toxicology Center University of LouisvilleLouisvilleKY 40202USA Alcohol Research Center University of LouisvilleLouisvilleKY 40202USA Biostatistics and Bioinformatics Facility James Graham Brown Cancer CenterLouisvilleKY 40202USA

Dioxin-like molecules have been associated with endocrine disruption and liver *** better understand aryl hydrocarbon receptor(AHR)biology,metabolic phenotyping and liver proteomics were performed in mice following ligand-activation or whole-body genetic ablation of this *** wild type(WT)and Ahr^(-/-) mice(Taconic)were fed a control diet and exposed to 3,3',4,4',5-pentachlorobiphenyl(PCB126)(61 nmol/kg by gavage)or vehicle for two ***126 increased expression of canonical AHR targets(Cyp1 a1 and Cyp1 a2)in WT but not Ahr^(-/-).Knockouts had increased adiposity with decreased glucose tolerance;smaller livers with increased steatosis and perilipin-2;and paradoxically decreased blood ***126 was associated with increased hepatic triglycerides in Ahr^(-/-).The liver proteome was impacted more so by Ahr^(-/-) genotype than ligandactivation,but top gene ontology(GO)processes were *** PCB126-associated liver proteome was *** principally regulated liver metabolism(e.g.,lipids,xenobiotics,organic acids)and bioenergetics,but it also impacted liver endocrine response(e.g.,the insulin receptor)and function,including the production of steroids,hepatokines,and pheromone binding *** effects could have been indirectly mediated by interacting transcription factors or *** biologic roles of the AHR and its ligands warrant more research in liver metabolic health and disease.

关键词： AHR Endocrine disruption Environmental liver disease nonalcoholic fatty liver disease Perilipin-2 Pheromones PCB126

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