4.3 Article

Characterization of mucosa-associated bacterial communities of the mouse intestine by terminal restriction fragment length polymorphism: Utility of sampling strategies and methods to reduce single-stranded DNA artifacts

期刊

JOURNAL OF MICROBIOLOGICAL METHODS
卷 78, 期 2, 页码 175-180

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.mimet.2009.05.011

关键词

Intestine; Mucosa-associated bacteria; Single-stranded artifacts; T-RFLP; Statistical analyses

资金

  1. AAFC Peer Review Project
  2. Advanced Foods and Materials Network (AFMNet)

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Terminal restriction fragment length polymorphism (T-RFLP) is a molecular technique used for comparative analysis of microbial community structure and dynamics. We evaluated three sampling methods for recovering bacterial community DNA associated with intestinal mucosa of mice (i.e. mechanical agitation with PBS, hand washing with PBS containing Tween 80, and direct DNA extraction from mucosal plugs). In addition, the utility of two methods (i.e. Klenow fragment and mung-bean nuclease) to reduce single-stranded DNA artifacts was tested. T-RFLP analysis indicated that diverse communities of bacteria are associated with mucosa of the ileum, cecum, and descending colon of mice. Although there was no significant difference in bacterial community structure between the mechanical agitation and direct DNA extraction methods regardless of intestinal location, community diversity was reduced for the hand wash method in the colon. The use of Klenow fragment and mung-bean nuclease have been reported to eliminate single-stranded DNA artifacts (i.e. pseudo-T-restriction fragments), but neither method was beneficial for characterizing mucosa-associated bacterial communities of the mouse cecum. Our study showed that the mechanical agitation and direct plug extraction methods yielded equivalent bacterial community DNA from the mucosa of the small and large intestines of mice, but the latter method was superior for logistical reasons. We also applied a combination of different statistical approaches to analyze T-RFLP data, including statistical detection of true peaks, analysis of variance for peak number, and group significance test, which provided a quantitative improvement for the interpretation of the T-RFLP data. Crown Copyright (c) 2009 Published by Elsevier B.V. All rights reserved.

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