Exploring the role of antimicrobials in the selective growth of purple phototrophic bacteria through genome mining and agar spot assays

Abstract

Purple non-sulphur bacteria (PNSB) are an emerging group of microbes attractive for applied microbiology applications such as wastewater treatment, plant biostimulants, microbial protein, polyhydroxyalkanoates and H₂ production. These photoorganoheterotrophic microbes have the unique ability to grow selectively on organic carbon in anaerobic photobioreactors. This so-called selectivity implies that the microbial community will have a low diversity and a high abundance of a particular PNSB species. Recently, it has been shown that certain PNSB strains can produce antimicrobials, yet it remains unclear whether these contribute to competitive inhibition. This research aimed to understand which type of antimicrobial PNSB produce and identify whether these compounds contribute to their selective growth. Mining 166 publicly-available PNSB genomes using the computational tool BAGEL showed that 59% contained antimicrobial encoding regions, more specifically biosynthetic clusters of bacteriocins and non-ribosomal peptide synthetases. Inter- and intra-species inhibition was observed in agar spot assays for Rhodobacter blasticus EBR2 and Rhodopseudomonas palustris EBE1 with inhibition zones of, respectively, 5.1 and 1.5-5.7 mm. Peptidomic analysis detected a peptide fragment in the supernatant (SVLQLLR) that had a 100% percentage identity match with a known non-ribosomal peptide synthetase with antimicrobial activity.

Keywords: alternative protein; animal feed; antibiotics; antimicrobial peptide; bacteriocin; probiotic; purple phototrophic bacteria.

Figure 1

Areas of interest for secondary metabolites with an occurrence over 20% mined in purple non‐sulphur bacteria genomes through antiSMASH. The dominant antimicrobial encoding regions were related to bacteriocins, non‐ribosomal peptide synthetases and type 1 polyketide synthases.

Figure 2

Analysis of 166 publically‐available purple non‐sulphur bacteria genomes using the BActeriocin GEne mining tooL (BAGEL) showing ribosomally synthesized and post‐translationally modified peptides (RiPPs) identified based on biochemical structures and bacteriocins identified through a core peptide hit.

Figure 3

Liquid culture competitive growth experiment showing the relative abundance of Rhodobacter blasticus EBR2 (■) and the Rhodopseudomonas palustris EBE1 () at time (t) 0 h, 72 h and through the growth model. The PNSB abundancies in the growth model were calculated using the equation N = N0*e^{μmax* (tfinal−tlag)} without considering competitive inhibition. The abundance was corrected for 16S gene copies per genome.