Abstract

BackgroundIdentification and classification of highly similar microbial strains is a challenging issue in microbiology, ecology and evolutionary biology. Among various available approaches, gene content analysis is also at the core of microbial taxonomy. However, no threshold has been determined for grouping microorgnisms to different taxonomic levels, and it is still not clear that to what extent genomic fluidity should occur to form a microbial taxonomic group.ResultsBy taking advantage of the eggNOG database for orthologous groups, we calculated gene content dissimilarity among different microbial strains based on the orthologous gene profiles and tested the possibility of applying gene content dissimilarity as a quantitative index in classifying microbial taxonomic groups, as well as its potential application in subclassification of highly similar microbial strains. Evaluation of gene content dissimilarity to completed microbial genomes at different taxonomic levels suggested that cutoffs of 0.2 and 0.4 can be respectively used for species and family delineation, and that 0.2 gene content dissimilarity cutoff approximately corresponded to 98 % 16S rRNA gene identity and 94 % ANI for microbial species delineation. Furthermore, application of gene content dissimilarity to highly similar microbial strains suggested it as an effective approach in classifying closely related microorganisms into subgroups.ConclusionsThis approach is especially useful in identifying pathogens from commensals in clinical microbiology. It also provides novel insights into how genomic fluidity is linked with microbial taxonomy.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2991-9) contains supplementary material, which is available to authorized users.

Highlights

  • Identification and classification of highly similar microbial strains is a challenging issue in microbiology, ecology and evolutionary biology

  • Further application of gene content dissimilarity to highly similar microbial strains suggested it as an effective approach in classifying closely related microorganisms into subgroups

  • Overview of the framework microbial taxonomy at species and higher levels mainly rely on sequence identity approaches such as 16S rRNA gene identity and average nucleotide identity (ANI), identification and classification of highly similar microbial strains still require phenotypic properties of the isolated microorganisms [1]

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Summary

Introduction

Identification and classification of highly similar microbial strains is a challenging issue in microbiology, ecology and evolutionary biology. Traditional methods for identification and classification of microorganisms mainly rely on morphological, physiological and biochemical properties of isolated microorganisms [1] Characterizing these properties are experimentally very complicated and no quantitative standards can be applied for the obtained descriptive data. The DDH approach is experimentally tedious and hard to standardize between different laboratories in addition to several other problems, such as that the value obtained with the same pair of strains depends on which is used as probe and which as target [3]. Due to these reasons, 16S rRNA gene analysis has been mainly used in place

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