Browsing by Subject "Genome-Wide Association Study"
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Item Chromobacterium spp. mediate their anti-Plasmodium activity through secretion of the histone deacetylase inhibitor romidepsin(Springer Nature, 2018-04-18) Saraiva, Raul G.; Huitt-Roehl, Callie R.; Tripathi, Abhai; Cheng, Yi-Qiang; Bosch, Jurgen; Townsend, Craig A.; Dimopoulos, GeorgeThe Chromobacterium sp. Panama bacterium has in vivo and in vitro anti-Plasmodium properties. To assess the nature of the Chromobacterium-produced anti-Plasmodium factors, chemical partition was conducted by bioassay-guided fractionation where different fractions were assayed for activity against asexual stages of P. falciparum. The isolated compounds were further partitioned by reversed-phase FPLC followed by size-exclusion chromatography; high resolution UPLC and ESI/MS data were then collected and revealed that the most active fraction contained a cyclic depsipeptide, which was identified as romidepsin. A pure sample of this FDA-approved HDAC inhibitor allowed us to independently verify this finding, and establish that romidepsin also has potent effect against mosquito stages of the parasite's life cycle. Genomic comparisons between C. sp. Panama and multiple species within the Chromobacterium genus further demonstrated a correlation between presence of the gene cluster responsible for romidepsin production and effective antiplasmodial activity. A romidepsin-null Chromobacterium spp. mutant loses its anti-Plasmodium properties by losing the ability to inhibit P. falciparum HDAC activity, and romidepsin is active against resistant parasites to commonly deployed antimalarials. This independent mode of action substantiates exploring a chromobacteria-based approach for malaria transmission-blocking.Item IPAD: the Integrated Pathway Analysis Database for Systematic Enrichment Analysis(Springer Nature, 2012) Zhang, Fan; Drabier, ReneeBackground: Next-Generation Sequencing (NGS) technologies and Genome-Wide Association Studies (GWAS) generate millions of reads and hundreds of datasets, and there is an urgent need for a better way to accurately interpret and distill such large amounts of data. Extensive pathway and network analysis allow for the discovery of highly significant pathways from a set of disease vs. healthy samples in the NGS and GWAS. Knowledge of activation of these processes will lead to elucidation of the complex biological pathways affected by drug treatment, to patient stratification studies of new and existing drug treatments, and to understanding the underlying anti-cancer drug effects. There are approximately 141 biological human pathway resources as of Jan 2012 according to the Pathguide database. However, most currently available resources do not contain disease, drug or organ specificity information such as disease-pathway, drug-pathway, and organ-pathway associations. Systematically integrating pathway, disease, drug and organ specificity together becomes increasingly crucial for understanding the interrelationships between signaling, metabolic and regulatory pathway, drug action, disease susceptibility, and organ specificity from high-throughput omics data (genomics, transcriptomics, proteomics and metabolomics). Results: We designed the Integrated Pathway Analysis Database for Systematic Enrichment Analysis (IPAD, http://bioinfo.hsc.unt.edu/ipad), defining inter-association between pathway, disease, drug and organ specificity, based on six criteria: 1) comprehensive pathway coverage; 2) gene/protein to pathway/disease/drug/organ association; 3) inter-association between pathway, disease, drug, and organ; 4) multiple and quantitative measurement of enrichment and inter-association; 5) assessment of enrichment and inter-association analysis with the context of the existing biological knowledge and a "gold standard" constructed from reputable and reliable sources; and 6) cross-linking of multiple available data sources. IPAD is a comprehensive database covering about 22,498 genes, 25,469 proteins, 1956 pathways, 6704 diseases, 5615 drugs, and 52 organs integrated from databases including the BioCarta, KEGG, NCI-Nature curated, Reactome, CTD, PharmGKB, DrugBank, PharmGKB, and HOMER. The database has a web-based user interface that allows users to perform enrichment analysis from genes/proteins/molecules and inter-association analysis from a pathway, disease, drug, and organ. Moreover, the quality of the database was validated with the context of the existing biological knowledge and a "gold standard" constructed from reputable and reliable sources. Two case studies were also presented to demonstrate: 1) self-validation of enrichment analysis and inter-association analysis on brain-specific markers, and 2) identification of previously undiscovered components by the enrichment analysis from a prostate cancer study. Conclusions: IPAD is a new resource for analyzing, identifying, and validating pathway, disease, drug, organ specificity and their inter-associations. The statistical method we developed for enrichment and similarity measurement and the two criteria we described for setting the threshold parameters can be extended to other enrichment applications. Enriched pathways, diseases, drugs, organs and their inter-associations can be searched, displayed, and downloaded from our online user interface. The current IPAD database can help users address a wide range of biological pathway related, disease susceptibility related, drug target related and organ specificity related questions in human disease studies.Item Patient genetics is linked to chronic wound microbiome composition and healing(PLOS, 2020-06-18) Tipton, Craig D.; Wolcott, Randall D.; Sanford, Nicholas E.; Miller, Clint; Pathak, Gita A.; Silzer, Talisa K.; Sun, Jie; Fleming, Derek; Rumbaugh, Kendra P.; Little, Todd D.; Phillips, Nicole; Phillips, Caleb D.The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection.