2017 ; Vol.27-12: 2089~2093
|Author||Bo-Ra Kim, Jiwon Shin, Robin B. Guevarra, Jun Hyung Lee, Doo Wan Kim, Kuk-Hwan Seol, Ju-Hoon Lee, Hyeun Bum Kim, Richard E. Isaacson|
|Place of duty||Department of Animal Resources Science, Dankook University, Cheonan 31116, Republic of Korea|
|Title||Deciphering Diversity Indices for a Better Understanding of Microbial Communities|
J. Microbiol. Biotechnol.2017 ;
|Abstract||The past decades have been a golden era during which great tasks were accomplished in the
field of microbiology, including food microbiology. In the past, culture-dependent methods
have been the primary choice to investigate bacterial diversity. However, using cultureindependent
high-throughput sequencing of 16S rRNA genes has greatly facilitated studies
exploring the microbial compositions and dynamics associated with health and diseases.
These culture-independent DNA-based studies generate large-scale data sets that describe the
microbial composition of a certain niche. Consequently, understanding microbial diversity
becomes of greater importance when investigating the composition, function, and dynamics of
the microbiota associated with health and diseases. Even though there is no general agreement
on which diversity index is the best to use, diversity indices have been used to compare the
diversity among samples and between treatments with controls. Tools such as the Shannon-
Weaver index and Simpson index can be used to describe population diversity in samples. The
purpose of this review is to explain the principles of diversity indices, such as Shannon-
Weaver and Simpson, to aid general microbiologists in better understanding bacterial
communities. In this review, important questions concerning microbial diversity are
addressed. Information from this review should facilitate evidence-based strategies to explore
|Key_word||Microbiota, microbial diversity, microbial ecology, diversity index|
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