Genome Mining of Biosynthetic Gene Clusters in Indigenous Environmental Bacteria Using Culture-Dependent and Independent Approaches

Abstract

Genome mining is considered a powerful approach to explore the potential of environmental bacteria for bioactive secondary metabolites biosynthesis. In the current study, 342 bacterial isolates were isolated from various localities of Pakistan and evaluated for the synthesis of bioactive metabolites. Among these, 27 isolates were found to antagonize the growth of at least two American Type Culture Collection (ATCC) bacterial strains. Based on their antimicrobial activities and diversity, five strains were selected and subjected to Illumina sequencing. These strains SF-4, RS10, ES-1, SD-4 and MW-6 were identified as Bacillus pumilus, Bacillus subtilis, Bacillus paralicheniformis, Bacillus sp. and Chryseobacterium cucmeris, respectively. Overall, these strains harbor relatively large genome (>4 Mbps) size, small core genome, and numerous strain-specific gene content. Genome mining revealed several diverse secondary metabolites biosynthetic gene clusters (BGCs), indicating a high potential to synthesize antimicrobial metabolites. Non-ribosomal peptides (NRPs), polyketides (PKs), and terpenes are the major secondary metabolites BGCs identified in these strains. While some of the secondary metabolites BGCs coding for NRPs, ribosomal synthesized post translationally modified peptides (RiPPs), T3PKs, and hybrid NRP/PK are strain specific. The strain SF-4, RS10, and ES-1 also revealed in vitro plant growth-promoting traits, including de-nitrification, iron acquisition, phosphate solubilization, and nitrogen metabolism. Comparative genome analysis indicates an open pan-genome for all species. Average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values are above the threshold (95% and 70%, respectively) for all sequenced strains except SD 4, which indicates potential novel species. The strain RS10 was identified as a novel sequence type (ST) within B. subtilis species and the new sequence type number, ST 176 was obtained from the PubMLST database. Further, metagenome analysis of 5 samples isolated from hot spring Tattapani (n=4) Azad Kashmir and salt mine (n=1) Jhelum were conducted. Prokaryotic diversity was assessed based on the 16S rRNA gene sequence analysis. Proteobacteria was found to be the most abundant (17–50%) phyla in all samples, except HSS (2%), which had the highest abundance (16%) of phylum Chloroflexi. Chloroflexi was also found at 5% in the HSB sample. On the other side, Cyanobacteria (39%) was found most predominantly in HSB sample. Firmicutes were also observed abundantly in all samples (6–18%). While Actinobacteriota was observed abundantly only in HSWh (37%), other hot spring water samples contained <3% Abstract xxii Acidobacteriota. The thermophilic phylum TA06 was only found in HSS sample (9%) and HSWl sample (1%). The prokaryotic community in the salt mine sample (SMW) comprises 14% bacteria and 9% archaea. Alpha-proteobacteria, Gamma-proteobacteria and Rhodothermia were the principal phyla found among bacteria, while Halobacteria and Nanosalinia were found abundantly among Archaea. A total of 26%, 24%, 23%, 17%, and 77% of prokaryotic taxa were identified as unclassified in hot spring sediment (HSS), hot spring biofilm, hot spring water outlet (HSWl), hot spring pond (HSWh) and salt mine water (SMW), respectively. Functional annotations were performed to gain insights into the metabolic potential of microbiome found in hot springs and salt lake using COG database. The HSWh carries a maximum of 45% genes for metabolism, followed by HSS and SMW samples which contain 44 and 42% genes for metabolism, respectively. The HSWh sample also carries the highest 21% genes for cellular processing and signaling, while the lowest 18% genes were observed in SMW. Additionally, 113 metagenome-assembled genomes (MAGs) and four single amplified genomes (SAGs) were obtained and analyzed. The four SAGs were identified, belong to a recently described candidate phylum White Oak River (WOR)-3. All the SAGs showed completeness of more than 70%; however, one SAG, SFM2 contained a high (59.56%) contamination. Genome mining unraveled 180 secondary metabolites BGCs including rarely found antimicrobial/antitumor lankacidin and antioxidative resorcinol in 53 high quality MAGs. Further, 63% of predicted BGCs were found unique and do not show any similarity with known metabolite cluster which indicate that the indigenous microbiomes are capable to synthesis several novel metabolites. SAGs revealed two unique BGCs, NRPS-like and NRPS, in the SFO9 genome. The MIBiG database comparison showed that the NRPS-like cluster exhibit some similarity (Score 0.75) with the sunscreen compound Shinorine (BGC0000427.1). While the NRPS BGC was found to encode an antimicrobial and anti-tumor agent, rhizomide. The COGs categories C (energy production and conversion), J (Translation), and S (function unknown) are found to have relatively higher percentages in all four SAGs