| 1. |
- Chng, Kern Rei, et al.
(författare)
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Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment
- 2020
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 26, s. 941-951
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Tidskriftsartikel (refereegranskat)abstract
- Although disinfection is key to infection control, the colonization patterns and resistomes of hospital-environment microbes remain underexplored. We report the first extensive genomic characterization of microbiomes, pathogens and antibiotic resistance cassettes in a tertiary-care hospital, from repeated sampling (up to 1.5 years apart) of 179 sites associated with 45 beds. Deep shotgun metagenomics unveiled distinct ecological niches of microbes and antibiotic resistance genes characterized by biofilm-forming and human-microbiome-influenced environments with corresponding patterns of spatiotemporal divergence. Quasi-metagenomics with nanopore sequencing provided thousands of high-contiguity genomes, phage and plasmid sequences (>60% novel), enabling characterization of resistome and mobilome diversity and dynamic architectures in hospital environments. Phylogenetics identified multidrug-resistant strains as being widely distributed and stably colonizing across sites. Comparisons with clinical isolates indicated that such microbes can persist in hospitals for extended periods (>8 years), to opportunistically infect patients. These findings highlight the importance of characterizing antibiotic resistance reservoirs in hospitals and establish the feasibility of systematic surveys to target resources for preventing infections. Spatiotemporal characterization of microbial diversity and antibiotic resistance in a tertiary-care hospital reveals broad distribution and persistence of antibiotic-resistant organisms that could cause opportunistic infections in a healthcare setting.
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| 2. |
- Feng, Helian, et al.
(författare)
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Cross-cancer cross-tissue Transcriptome-wide Association Study (TWAS) of 11 cancers identifies 56 novel genes
- 2020
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 44:5, s. 481-481
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Though heterogeneous, multiple tumor types share hallmark mechanisms. Thus, identifying genes associated with multiple cancer types may shed light on general oncogenic mechanisms and identify genes missed in single‐cancer analyses. TWAS have been successful in testing whether genetically‐predicted tissue‐specific gene expression is associated with cancer risk. Although cross‐cancer genome‐wide association studies (GWAS) analyses have been performed previously, no cross‐cancer TWAS has been conducted to date. Here, we implement a pipeline to perform cross‐cancer, cross‐tissue TWAS analysis. We use newly‐developed multi‐trait TWAS test statistics to integrate the TWAS results for association between 11 separated cancers and predicted gene expression in 43 GTEx tissues, including a “sum” test and a “variance components” test, analogous to fixed‐ and random‐effects meta‐analyses. We then integrated the results across different tissues using the Aggregated Cauchy Association Test (ACAT) combined test.A total of 403 genes were significantly associated with at least one cancer type for at least one tissue; 96 additional genes were identified when combining test results across cancers; and 35 additional genes when further combining test results across tissue. Among these significant genes, 70 were not near previously‐published GWAS index variants. 14 of the 70 novel genes were identified from the single‐cancer single‐tissue test; an additional 43 were identified with the cross‐cancer test; and another 13 were identified when further combined across tissues. The newly identified genes, including RBBP8 and TP53BP , are involved in chromatin structure, tumorigenesis, apoptosis, transcriptional regulation, DNA repair, immune system, oxidative damage and cell‐cycle, proliferation, progression, shape, structure, and migration.
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