Document Detail


Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.
MedLine Citation:
PMID:  18585806     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.
Authors:
Noha H Youssef; Mostafa S Elshahed
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2008-05-15
Journal Detail:
Title:  Journal of microbiological methods     Volume:  75     ISSN:  0167-7012     ISO Abbreviation:  J. Microbiol. Methods     Publication Date:  2008 Sep 
Date Detail:
Created Date:  2008-08-12     Completed Date:  2008-10-21     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8306883     Medline TA:  J Microbiol Methods     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  86-91     Citation Subset:  IM    
Affiliation:
Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, OK 74074, United States.
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MeSH Terms
Descriptor/Qualifier:
Bacteria / classification,  genetics,  isolation & purification*
Biodiversity*
DNA, Bacterial / genetics
DNA, Ribosomal / genetics
Gene Library
Models, Biological
Models, Statistical*
Molecular Sequence Data
RNA, Ribosomal, 16S / genetics
Soil Microbiology*
Chemical
Reg. No./Substance:
0/DNA, Bacterial; 0/DNA, Ribosomal; 0/RNA, Ribosomal, 16S

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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