Functional Basis of Microorganism Classification

Correctly identifying nearest "neighbors" of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is ex...

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Veröffentlicht in:PLoS computational biology 2015-08, Vol.11 (8), p.e1004472-e1004472
Hauptverfasser: Zhu, Chengsheng, Delmont, Tom O, Vogel, Timothy M, Bromberg, Yana
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creator Zhu, Chengsheng
Delmont, Tom O
Vogel, Timothy M
Bromberg, Yana
description Correctly identifying nearest "neighbors" of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with phylogenetic descent.
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subjects Bacteria - classification
Bacteria - genetics
Classification
Classification - methods
Computational Biology - methods
Electric power
Engineering Sciences
Gene expression
Genetic aspects
Genetic research
Genome, Bacterial - physiology
Genomes
Microbial colonies
Microbiological research
Microorganisms
Organisms
Phylogenetics
Quantitative trait loci
Software
Taxonomy
Vocabularies & taxonomies
title Functional Basis of Microorganism Classification
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