The challenge of discriminating between phylogenetically similar but functionally distinct bacterial lineages is particularly relevant to the development of technologies seeking to exploit the metabolic or physiological characteristics of specific… Click to show full abstract
The challenge of discriminating between phylogenetically similar but functionally distinct bacterial lineages is particularly relevant to the development of technologies seeking to exploit the metabolic or physiological characteristics of specific members of bacterial genera. A computational approach was developed to expedite screening of potential genetic markers among phylogenetically affiliated bacteria. ABSTRACT As a group, the genus Dehalococcoides dehalogenates a wide range of organohalide pollutants, but the range of organohalide compounds that can be utilized for reductive dehalogenation differs among Dehalococcoides strains. Dehalococcoides lineages cannot be reliably disambiguated in mixed communities using typical phylogenetic markers, which often confounds bioremediation efforts. Here, we describe a computational approach to identify Dehalococcoides genetic markers with improved discriminatory resolution. Screening core genes from the Dehalococcoides pangenome for degree of similarity and frequency of 100% identity found a candidate genetic marker encoding a bacterial neuraminidase repeat (BNR)-containing protein of unknown function. This gene exhibits the fewest completely identical amino acid sequences and has among the lowest average amino acid sequence identity in the core pangenome. Primers targeting BNR could effectively discriminate between 40 available BNR sequences (in silico) and 10 different Dehalococcoides isolates (in vitro). Amplicon sequencing of BNR fragments generated from 22 subsurface soil samples revealed a total of 109 amplicon sequence variants, suggesting a high diversity of Dehalococcoides distributed in the environment. Therefore, the BNR gene can serve as an alternative genetic marker to differentiate strains of Dehalococcoides in complicated microbial communities. IMPORTANCE The challenge of discriminating between phylogenetically similar but functionally distinct bacterial lineages is particularly relevant to the development of technologies seeking to exploit the metabolic or physiological characteristics of specific members of bacterial genera. A computational approach was developed to expedite screening of potential genetic markers among phylogenetically affiliated bacteria. Using this approach, a gene encoding a bacterial neuraminidase repeat (BNR)-containing protein of unknown function was selected and evaluated as a genetic marker to differentiate strains of Dehalococcoides, an environmentally relevant genus of bacteria whose members can transform and detoxify a range of halogenated organic solvents and persistent organic pollutants, in complex microbial communities to demonstrate the validity of the approach. Moreover, many apparently phylogenetically distinct, currently uncharacterized Dehalococcoides were detected in environmental samples derived from contaminated sites.
               
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