Biology subjects

Yao, K.

Publications and source records attributed to Yao, K..

3 recordsLinked to original sources

bioRxiv2018

Retrospective whole-genome sequencing analysis distinguished PFGE and drug resistance matched retail meat and clinical Salmonella isolates

Non-typhoidal Salmonella are a leading cause of outbreak and sporadic-associated foodborne illnesses in the U.S. These infections have been associated with a range of foods, including retail meats. Traditionally, pulsed-field gel electrophoresis (PFGE) and antibiotic susceptibility testing (AST) have been used to facilitate public health investigations of Salmonella infections. However, whole-genome sequencing (WGS) has emerged as an alternative tool that can be routinely implemented. To assess its potential in enhancing integrated surveillance in Pennsylvania, WGS was used to directly compare the genetic characteristics of 7 retail meat and 43 clinical historic Salmonella isolates, subdivided into three subsets based on PFGE and AST results, to retrospectively resolve their genetic relatedness and identify antimicrobial resistance (AMR) determinants. Single nucleotide polymorphism (SNP) analyses revealed the retail meat isolates within S. Heidelberg, S. Typhimurium var. O5- subset 1, and S. Typhimurium var. O5- subset 2 were separated from each primary PFGE pattern-matched clinical isolate by 6-12, 41-96, and 21-81 SNPs, respectively. Fifteen resistance genes were identified across all isolates, including fosA7, a gene only recently found in a limited number of Salmonella and a [≥] 95% phenotype to genotype correlation was observed for all tested antimicrobials. Moreover, AMR was primarily plasmid-mediated in S. Heidelberg and S. Typhimurium var. O5- subset 2; whereas, AMR was chromosomally-carried in S. Typhimurium var. O5- subset 1. Similar plasmids were identified in both the retail meat and clinical isolates. Collectively, these data highlight the utility of WGS in retrospective analyses and enhancing integrated surveillance of Salmonella from multiple sources.

microbiology↗

bioRxiv2018

Whole genome sequence analysis of 91 Salmonella Enteritidis isolates from mice caught on poultry farms in the mid 1990s

Salmonella enterica serovar Enteritidis (SE), the most commonly reported serovar of human salmonellosis, has been frequently associated with poultry farms, eggs and egg products. Mice are known vectors of SE contamination in these facilities. The objective of this study was to use whole-genome sequencing (WGS) to analyze SE from mice obtained at poultry farms in Pennsylvania. Documenting pathogen diversity can identify reliable biomarkers for rapid detection and speed up outbreak investigations. We sequenced 91 SE isolates from 83 mice (62 spleen isolates, 29 intestinal isolates) caught at 15 poultry farms between 1995-1998 using an Illumina NextSeq 500. We identified 742 single nucleotide polymorphisms (SNPs) capable of distinguishing each isolate from one another. Isolates were divided into two major clades: there were more SNPs differences within Clade B than counterparts in Clade A. All isolates containing antimicrobial resistance genes belong to Subgroup B2. Clade-defining SNPs provided biomarkers distinguishing isolates from 12 individual subgroups, which were separated by farm location or year of collection. Nonsynonymous changes from the clade-defining SNPs proffered a better understanding of possible genetic variations among these isolates. For a broader view of SE diversity, we included data from NCBI Pathogen Detection Isolates Browser, in which subgroups in Clade B formed new SNP Clusters.\n\nImportanceWGS and SNPs analyses are excellent and powerful tools for investigating SE phylogenies. Identifying the evolutionary relationships among SE isolates from mouse, poultry, environmental, and clinical isolates, along with patterns of genetic diversity, advances understanding of SE and the role mice may play in SE contamination and spread among poultry population. Our data was able to identify SE isolates from different farms or years of collection. Moreover, the annotations of clade-defining SNPs provided information about possible protein functions among these SE isolates from each subgroup. Clade-defining or farm-unique biomarkers were useful for rapid detection and outbreak investigations.

genomics↗

bioRxiv2017

PGC-1α coordinates with Bcl-2 to control cell cycle in U251 cells through reducing ROS

B-cell lymphoma 2 (Bcl-2) has a dual function, acting both as an oncogene and an anti-tumor gene. It is well known that Bcl-2 exerts its tumor promoting function through the mitochondrial pathway. However, the mechanism by which Bcl-2 suppresses tumor formation is not well understood. We have previously shown that Bcl-2 inhibits cell cycle progression from the G0/G1 to the S phase after serum starvation, and that quiescent Bcl-2 expressing cells maintained a significant lower level of mitochondrial reactive oxygen species (ROS) than the control cells. Based on the fact that ROS mediate cell cycle progression, and are controlled by peroxisome proliferator-activated receptor-{gamma} co-activator 1 (PGC-1), a key molecule induced by prolonged starvation and involved in mitochondrial metabolism, we hypothesized that PGC-1 might be related with the cell cycle function of Bcl-2. Here, we showed that PGC-1 was upregulated upon Bcl-2 overexpression and downregulated following Bcl-2 knockdown during serum starvation. Knockdown of PGC-1 activated Bcl-2 expression. Taken together, our results suggest that after serum depletion, PGC-la might coordinate with Bcl-2 to reduce ROS, which in turn delay cell cycle progression.\n\nSummary statementPGC-1 coordinate with Bcl-2 delay cell cycle progression to reduce ROS after serum depletion in human glioma U251 cells.

biochemistry↗