Isolation, identification, and characterization of antibiotic-producing microorganisms from soil

Abstract

The emergence and spread of antibiotic resistance in pathogenic bacteria have posed a serious concern in global healthcare. Highlighting a need for novel antimicrobial agents with diverse mechanisms of action to combat current pathogenic threats. Soil-borne bacteria are constantly exposed to various environmental stresses, which leads to the production of antimicrobial compounds as a strategy for their survival. In this context, soil-borne bacteria are key producers of antimicrobials with valuable applications in medicine, agriculture, and animal husbandry. The main aim of this study was to isolate, identify, and characterize microorganisms with the potential to produce antimicrobial compounds from soil. Preliminary screening was conducted using agar well diffusion, revealing that the bacterial isolates exhibited significant antimicrobial activity against the four pathogenic bacterial strains tested (Chapter 3). Furthermore, the use of 16S rRNA sequencing aided the identification of the active bacterial isolates at the molecular level, where isolates 1 and 2 were identified as strains of Bacillus pumilus, whilst isolate 3 was found to be Bacillus subtilis (Chapter 3). This study further explored the chemical composition of the bacterial extract using ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry and classical molecular networking. Computational metabolomic analysis revealed that metabolites from these soilborne Bacillus species are predominantly composed of peptides, dipeptides, benzenoids, organic acids, and derivatives. Interestingly, the methanolic crude extract of the Bacillus subtilis isolate was mainly characterized by the abundance of dipeptides and lipopeptides, such as surfactins, suggesting that the combination of cyclopeptides and lipopeptides together could be the attribute of the enhanced antimicrobial activity observed in agar well diffusion (Chapter 4). The current study further explored the applications of Whole Genome Sequencing (WGS) to enhance understanding of the overall distribution of genomic elements that contribute toward the adaptability and biosynthesis of antimicrobial compounds (Chapter 5). The results of the WGS showed that Bacillus species presented several genes for adaptability, such as genes that encode for motility, quorum sensing, stress response, desiccation tolerance, heavy metal tolerance, synthesis of siderophores, and most genes involved in antibiotic biosynthesis, such as NRPS, beta lactone, RiPP, and terpene gene clusters. Furthermore, the use of WGS aided a more precise taxonomic classification of the identities of the strains, highlighting the importance of WGS in the identification of bacterial isolates. Lastly, inspired by the diverse chemical composition and bioactivity of Bacillus subtilis, this study further explored the potential to enhance metabolite detection and expand the data coverage in the data-dependent acquisition (DDA) mode of the UHPLC-qTOF-MS technique (Chapter 6). Interestingly, using Central composite design (CCD), this study has demonstrated that even though both collision energy and intensity threshold independently enhance metabolite coverage, it is noteworthy that when both parameters are combined, the comprehensiveness in maximizing metabolome coverage is even greater. Therefore, revealing that to enhance exploration and maximize the potential of untargeted metabolomics, this study recommends future studies transitioning from single-point optimization to group-based optimization. Overall, contributes to the growing field of natural product discovery and provides insights into the biosynthetic pathways and insight into the chemical diversity of microbial secondary metabolites. Furthermore, these findings highlight the diverse potential of microbial-derived compounds as potential sources of new bioactive molecules.