Understanding microbial community diversity metrics derived from metagenomes: performance evaluation using simulated datasets.
Summary of "Understanding microbial community diversity metrics derived from metagenomes: performance evaluation using simulated datasets."
Metagenomics holds the promise of greatly advancing the study of diversity in natural communities, but novel theoretical and methodological approaches must first be developed and adjusted for these datasets. We evaluated widely used macroecological metrics of taxonomic diversity on a simulated set of metagenomic samples, using phylogenetically-meaningful protein-coding genes as ecological proxies. To our knowledge, this is the first approach of this kind to evaluate taxonomic diversity metrics derived from metagenomic datasets. We demonstrate that abundance matrices derived from protein-coding marker genes reproduce more faithfully the structure of the original community than those derived from SSU-rRNA gene. We also found that the most commonly used diversity metrics are biased estimators of community structure and differ significantly from their corresponding real parameters, and that these biases are most likely caused by insufficient sampling and differences in community phylogenetic composition. Our results suggest that the ranking of samples using multidimensional metrics makes a good qualitative alternative for contrasting community structure, and that these comparisons can be greatly improved with the incorporation of metrics for both community structure and phylogenetic diversity. These findings will help to achieve a standardized framework for community diversity comparisons derived from metagenomic datasets. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
Affiliation
Dept. Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Apartado Postal, 70-275.
Journal Details
This article was published in the following journal.
Name: FEMS microbiology ecology
ISSN: 1574-6941
Pages:
Links
- PubMed Source: http://www.ncbi.nlm.nih.gov/pubmed/22554028
- DOI: http://dx.doi.org/10.1111/j.1574-6941.2012.01405.x
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Antibody Diversity
The phenomenon of immense variability characteristic of ANTIBODIES. It enables the IMMUNE SYSTEM to react specifically against the essentially unlimited kinds of ANTIGENS it encounters. Antibody diversity is accounted for by three main theories: (1) the Germ Line Theory, which holds that each antibody-producing cell has genes coding for all possible antibody specificities, but expresses only the one stimulated by antigen; (2) the Somatic Mutation Theory, which holds that antibody-producing cells contain only a few genes, which produce antibody diversity by mutation; and (3) the Gene Rearrangement Theory, which holds that antibody diversity is generated by the rearrangement of IMMUNOGLOBULIN VARIABLE REGION gene segments during the differentiation of the ANTIBODY-PRODUCING CELLS.
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Enumeration by direct count of viable, isolated bacterial, archaeal, or fungal CELLS or SPORES capable of growth on solid CULTURE MEDIA. Each colony (i.e., microbial colony-forming unit) represents the progeny of a single cell in the original inoculum. The method is used routinely by environmental microbiologists for quantifying organisms in AIR; FOOD; and WATER; by clinicians for measuring patients' microbial load; and in antimicrobial drug testing.
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A frequent complication of drug therapy for microbial infection. It may result from opportunistic colonization following immunosuppression by the primary pathogen and can be influenced by the time interval between infections, microbial physiology, or host resistance. Experimental challenge and in vitro models are sometimes used in virulence and infectivity studies.
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