Dataset Information

Microbiology of bacterial translocation in humans.

ABSTRACT: BACKGROUND: Gut translocation of bacteria has been shown in both animal and human studies. Evidence from animal studies that links bacteria translocation to the development of postoperative sepsis and multiple organ failure has yet to be confirmed in humans. AIMS: To examine the spectrum of bacteria involved in translocation in surgical patients undergoing laparotomy and to determine the relation between nodal migration of bacteria and the development of postoperative septic complications. METHODS: Mesenteric lymph nodes (MLN), serosal scrapings, and peripheral blood from 448 surgical patients undergoing laparotomy were analysed using standard microbiological techniques. RESULTS: Bacterial translocation was identified in 69 patients (15.4%). The most common organism identified was Escherichia coli (54%). Both enteric bacteria, typical of indigenous intestinal flora, and non-enteric bacteria were isolated. Postoperative septic complications developed in 104 patients (23%). Enteric organisms were responsible in 74% of patients. Forty one per cent of patients who had evidence of bacterial translocation developed sepsis compared with 14% in whom no organisms were cultured (p < 0.001). Septic morbidity was more frequent when a greater diversity of bacteria resided within the MLN, but this was not statistically significant. CONCLUSION: Bacterial translocation is associated with a significant increase in the development of postoperative sepsis in surgical patients. The organisms responsible for septic morbidity are similar in spectrum to those observed in the mesenteric lymph nodes. These data strongly support the gut origin hypothesis of sepsis in humans.

SUBMITTER: O'Boyle CJ

PROVIDER: S-EPMC1726947 | biostudies-other | 1998 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:The latest generation of benchtop DNA sequencing platforms can provide an accurate whole-genome sequence (WGS) for a broad range of bacteria in less than a day. These could be used to more effectively contain the spread of multidrug-resistant pathogens.To compare WGS with standard clinical microbiology practice for the investigation of nosocomial outbreaks caused by multidrug-resistant bacteria, the identification of genetic determinants of antimicrobial resistance, and typing of other clinically important pathogens.A laboratory-based study of hospital inpatients with a range of bacterial infections at Cambridge University Hospitals NHS Foundation Trust, a secondary and tertiary referral center in England, comparing WGS with standard diagnostic microbiology using stored bacterial isolates and clinical information.Specimens were taken and processed as part of routine clinical care, and cultured isolates stored and referred for additional reference laboratory testing as necessary. Isolates underwent DNA extraction and library preparation prior to sequencing on the Illumina MiSeq platform. Bioinformatic analyses were performed by persons blinded to the clinical, epidemiologic, and antimicrobial susceptibility data.We investigated 2 putative nosocomial outbreaks, one caused by vancomycin-resistant Enterococcus faecium and the other by carbapenem-resistant Enterobacter cloacae; WGS accurately discriminated between outbreak and nonoutbreak isolates and was superior to conventional typing methods. We compared WGS with standard methods for the identification of the mechanism of carbapenem resistance in a range of gram-negative bacteria (Acinetobacter baumannii, E cloacae, Escherichia coli, and Klebsiella pneumoniae). This demonstrated concordance between phenotypic and genotypic results, and the ability to determine whether resistance was attributable to the presence of carbapenemases or other resistance mechanisms. Whole-genome sequencing was used to recapitulate reference laboratory typing of clinical isolates of Neisseria meningitidis and to provide extended phylogenetic analyses of these.The speed, accuracy, and depth of information provided by WGS platforms to confirm or refute outbreaks in hospitals and the community, and to accurately define transmission of multidrug-resistant and other organisms, represents an important advance.

Dataset Information

Microbiology of bacterial translocation in humans.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets