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Title: Application of Sequence-based Methods in Human MicrobialEcology

Abstract

Ecologists studying microbial life in the environment have recognized the enormous complexity of microbial diversity for many years, and the development of a variety of culture-independent methods, many of them coupled with high-throughput DNA sequencing, has allowed this diversity to be explored in ever greater detail. Despite the widespread application of these new techniques to the characterization of uncultivated microbes and microbial communities in the environment, their application to human health and disease has lagged behind. Because DNA based-techniques for defining uncultured microbes allow not only cataloging of microbial diversity, but also insight into microbial functions, investigators are beginning to apply these tools to the microbial communities that abound on and within us, in what has aptly been called the second Human Genome Project. In this review we discuss the sequence-based methods for microbial analysis that are currently available and their application to identify novel human pathogens, improve diagnosis of known infectious diseases, and to advance understanding of our relationship with microbial communities that normally reside in and on the human body.

Authors:
; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Director. Office of Science. Office of Biological andEnvironmental Research, Lawrence Livermore National Laboratory, LosAlamos National Laboratory; National Institutes of HealthTHL007279F
OSTI Identifier:
889801
Report Number(s):
LBNL-58770
R&D Project: 626021; BnR: KP1103010; TRN: US200619%%851
DOE Contract Number:  
DE-AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Genome Research
Additional Journal Information:
Journal Volume: 16; Related Information: Journal Publication Date: 03/2006
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 60 APPLIED LIFE SCIENCES; COMMUNITIES; DIAGNOSIS; DISEASES; DNA; DNA SEQUENCING; ECOLOGY; INFECTIOUS DISEASES; PATHOGENS; Microbial diversity 16S ribosomal RNA gene metagenome

Citation Formats

Weng, Li, Rubin, Edward M, and Bristow, James. Application of Sequence-based Methods in Human MicrobialEcology. United States: N. p., 2005. Web.
Weng, Li, Rubin, Edward M, & Bristow, James. Application of Sequence-based Methods in Human MicrobialEcology. United States.
Weng, Li, Rubin, Edward M, and Bristow, James. 2005. "Application of Sequence-based Methods in Human MicrobialEcology". United States. https://www.osti.gov/servlets/purl/889801.
@article{osti_889801,
title = {Application of Sequence-based Methods in Human MicrobialEcology},
author = {Weng, Li and Rubin, Edward M and Bristow, James},
abstractNote = {Ecologists studying microbial life in the environment have recognized the enormous complexity of microbial diversity for many years, and the development of a variety of culture-independent methods, many of them coupled with high-throughput DNA sequencing, has allowed this diversity to be explored in ever greater detail. Despite the widespread application of these new techniques to the characterization of uncultivated microbes and microbial communities in the environment, their application to human health and disease has lagged behind. Because DNA based-techniques for defining uncultured microbes allow not only cataloging of microbial diversity, but also insight into microbial functions, investigators are beginning to apply these tools to the microbial communities that abound on and within us, in what has aptly been called the second Human Genome Project. In this review we discuss the sequence-based methods for microbial analysis that are currently available and their application to identify novel human pathogens, improve diagnosis of known infectious diseases, and to advance understanding of our relationship with microbial communities that normally reside in and on the human body.},
doi = {},
url = {https://www.osti.gov/biblio/889801}, journal = {Genome Research},
number = ,
volume = 16,
place = {United States},
year = {Mon Aug 29 00:00:00 EDT 2005},
month = {Mon Aug 29 00:00:00 EDT 2005}
}