What can genome-scale metabolic network reconstructions do for prokaryotic systematics?

Abstract

It has recently been proposed that in addition to Nomenclature, Classification and Identification, Comprehending Microbial Diversity may be considered as the fourth tenet of microbial systematics [Staley JT (2010) The Bulletin of BISMiS, 1(1): 1-5]. As this fourth goal implies a fundamental understanding of microbial speciation, this perspective article argues that translation of bacterial genome sequences into metabolic features may contribute to the development of modern polyphasic taxonomic approaches. Genome-scale metabolic network reconstructions (GSMRs), which are the result of computationally predicted and experimentally confirmed stoichiometric matrices incorporating all enzyme and metabolite components encoded by a genome sequence, provide a platform that can illustrate bacterial speciation. As the topology and the composition of GSMRs are expected to be the result of adaptive evolution, the features of these networks may provide the prokaryotic taxonomist with novel tools for reaching the fourth tenet of microbial systematics. Through selected examples from the Actinobacteria, which have been inferred from GSMRs and experimentally confirmed after phenotypic characterisation, it will be shown that this level of information can be incorporated into modern polyphasic taxonomic approaches. In conclusion, three specific examples are illustrated to show how GSMRs will revolutionize prokaryotic systematics, as has previously occurred in many other fields of microbiology.

A novel taxonomic marker that discriminates between morphologically complex actinomycetes

“…This study is a tangible expression of this need as it has been shown that SsgA and SsgB proteins present in morphologically complex actinomycetes are the source of high-quality molecular data that can be used to resolve relationships between diverse genera classified in the class Actinobacteria [2]. Our work highlights the importance of combining molecular systematic and traditional taxonomic approaches, in accordance with the work of others [58,59], to identify chemotaxonomic and morphological markers as an excellent evidence-based way of distinguishing between closely related genera of actinomycetes, as exemplified by the distinction between Kitasatospora and Streptomyces . Additional comparative studies based on representatives of genera classified in taxa such as the orders Frankiales and Micromonosporales [11,51] can be expected to help resolve longstanding taxonomic enigmas.…”

The Antibiotic Resistant Target Seeker (ARTS), an exploration engine for antibiotic cluster prioritization and novel drug target discovery

“…In exploration mode for example, the detection algorithm includes genes that have been duplicated from central metabolism and have been repurposed for the biosynthesis of secondary metabolites. Indeed these gene expansions have been shown to be a valuable cluster detection technique as demonstrated with the EvoMining (11,32) method by highlighting clusters with potentially novel chemistries, such as the recent identification of arseno-organic natural products in the model actinomycetes Streptomyces coelicolor and Streptomyces lividans (11). …”

EvoMining reveals the origin and fate of natural products biosynthetic enzymes

“…Conserved sequences within the expanded EF were identified after bidirectional best hits (BBH) against the Enzyme DB. Expansions were defined as previously (15,16), and this information was presented as a heat plot, Fig. S1.…”

“…Only in the genus Streptomyces this has been estimated between 15% and 26% BGC per genome, which are actually different from those identified by antiSMASH (15). To address the problem of the limited novelty revealed by genome mining approaches based in sequence similarity searches, we have previously introduced the use of evolutionary principles driving the emergence of NP BGC (15,16). The latter gave place to EvoMining, which recapitulates enzyme evolutionary events as follows: any given enzyme family (EF) may undergo expansions (17) due to gene duplication, leading to paralogues, and/or horizontal gene transfer (HGT), leading to xenologues.…”

“…To date, EvoMining has been used to show the occurrence of conserved EF that fulfill related biochemical functions but yet with different physiological roles (16,20). It has also been used for the discovery of NP BGC that include unprecedented biosynthetic enzymes essential for the synthesis of arsenolipids in Streptomyces (15).…”