ArticlePLoS computational biology2015
Functional Basis of Microorganism Classification.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Pharms on farms: Variable impacts of veterinary pharmaceuticals on an arbuscular mycorrhizal symbiosis and soil microorganisms.Plant and soil · 2026Article
- Cutting-edge deep-learning based tools for metagenomic research.National science review · 2025Review
- A Comprehensive Study on Enhancing Microbicidal Activity of Pure and Ion-Exchanged Zeolites Through Structural and Chemical Determinants.IET nanobiotechnology · 2025Review
- Discovery of novel treponemes associated with pododermatitis in elk (Applied and environmental microbiology · 2024Article
- Rhizosphere Microorganisms Supply Availability of Soil Nutrients and Induce Plant Defense.Microorganisms · 2024Review
- Learning from the unknown: exploring the range of bacterial functionality.Nucleic acids research · 2023Article
- Standardized genome-wide function prediction enables comparative functional genomics: a new application area for Gene Ontologies in plants.GigaScience · 2022Article
- Sources and Assembly of Microbial Communities in Vineyards as a Functional Component of Winegrowing.Frontiers in microbiology · 2021Review
- Snow microbiome functional analyses reveal novel aspects of microbial metabolism of complex organic compounds.MicrobiologyOpen · 2020Article
- Quantifying stream periphyton assemblage responses to nutrient amendments with a molecular approach.Freshwater science (Print) · 2020Article
- Analysis of 1,000+ Type-Strain Genomes Substantially Improves Taxonomic Classification ofFrontiers in microbiology · 2020Article
- Genomic Analysis ofInternational journal of genomics · 2020Article
- Fingerprinting cities: differentiating subway microbiome functionality.Biology direct · 2019Article
- Exclusivity offers a sound yet practical species criterion for bacteria despite abundant gene flow.BMC genomics · 2018Article
- HFSP: high speed homology-driven function annotation of proteins.Bioinformatics (Oxford, England) · 2018Article
- fusionDB: assessing microbial diversity and environmental preferences via functional similarity networks.Nucleic acids research · 2018Article
- Linking pangenomes and metagenomes: thePeerJ · 2018Article
- COMPUTATIONAL APPROACHES TO STUDY MICROBES AND MICROBIOMES.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2016Article
- Phenotypic differentiation of gastrointestinal microbes is reflected in their encoded metabolic repertoires.Microbiome · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.