In silico genome mining of potential novel biosynthetic gene clusters for drug discovery from Burkholderia bacteria

Genome mining for ribosomally synthesized and post-translationally modified peptides (RiPPs) in Streptomyces bacteria

Ribosomally synthesized post-translationally modified peptides (RiPPs) are a novel category of bioactive natural products (NPs). Streptomyces bacteria are a potential source of many bioactive NPs. Limited opportunities are available to characterize all the bioactive NP gene clusters. In this study, 410 sequences of Streptomyces were analyzed for RiPPs through genome mining using the National Center for Biotechnology Information (NCBI), by combining BAGEL and anti-SMASH. A total of 4098 RiPPs were found; including both classified (lanthipeptide, RiPP-like, bacteriocin, LAPs, lassopeptide, thiopeptides) and nonclassified RiPPs. Soil was identified as a rich habitat for RiPPs. These data may offer alternative future remedies for various health issues.

A review on the diversity of antimicrobial peptides and genome mining strategies for their prediction

Antibiotic resistance has become one of the most serious threats to human health in recent years. In response to the increasing microbial resistance to the antibiotics currently available, it is imperative to develop new antibiotics or explore new approaches to combat antibiotic resistance. Antimicrobial peptides (AMPs) have shown considerable promise in this regard, as the microbes develop low or no resistance against them. The discovery and development of AMPs still confront numerous obstacles such as finding a target, developing assays, and identifying hits and leads, which are time-consuming processes, making it difficult to reach the market. However, with the advent of genome mining, new antibiotics could be discovered efficiently using tools such as BAGEL, antiSMASH, RODEO, etc., providing hope for better treatment of diseases in the future. Computational methods used in genome mining automatically detect and annotate biosynthetic gene clusters in genomic data, making it a useful tool in natural product discovery. This review aims to shed light on the history, diversity, and mechanisms of action of AMPs and the data on new AMPs identified by traditional as well as genome mining strategies. It further substantiates the various phases of clinical trials for some AMPs, as well as an overview of genome mining databases and tools built expressly for AMP discovery. In light of the recent advancements, it is evident that targeted genome mining stands as a beacon of hope, offering immense potential to expedite the discovery of novel antimicrobials.

Screening of core microorganisms in healthy and diseased peaches and effect evaluation of biocontrol bacteria (Burkholderia sp.)

Biological antagonists serve as the most important green alternatives to chemical fungicides, a class of microorganism that inhibits the growth of pathogenic fungi to reduce fruit incidence. In this paper, healthy and diseased peach fruit was selected for amplicon sequencing of the epiphytic microbiota on their surface to obtain a comprehensive understanding. Community structure, diversity and LefSe analysis were performed to screen Acetobacter, Muribaculaceae and Burkholderia as the core bacteria, Mycosphaerella, Penicillium and Alternaria as the core fungi, they showed significant differences and were highly enriched. Two strains fungi (Penicillium K3 and N1) and one strain antagonistic bacteria (Burkholderia J2) were isolated. The in intro test results indicated the bacterial suspension, fermentation broth and volatile organic compounds of antagonistic bacteria J2 were able to significantly inhibit pathogen growth. In vivo experiments, peach was stored at 28 °C for 6 days after different treatments, and samples were taken every day. It was found that Burkholderia J2 enhanced peach resistance by increasing the activities of antioxidant-related enzymes such as SOD, POD, PAL, PPO, GR, MDHAR, and DHAR. The results improved that Burkholderia J2 has great biocontrol potential and could be used as a candidate strain for green control of blue mold.

Comprehensive analysis of genomic variation, pan-genome and biosynthetic potential of Corynebacterium glutamicum strains

Corynebacterium glutamicum is a non-pathogenic species of the Corynebacteriaceae family. It has been broadly used in industrial biotechnology for the production of valuable products. Though it is widely accepted at the industrial level, knowledge about the genomic diversity of the strains is limited. Here, we investigated the comparative genomic features of the strains and pan-genomic characteristics. We also observed phylogenetic relationships among the strains based on average nucleotide identity (ANI). We found diversity between strains at the genomic and pan-genomic levels. Less than one-third of the C. glutamicum pan-genome consists of core genes and soft-core genes. Whereas, a large number of strain-specific genes covered about half of the total pan-genome. Besides, C. glutamicum pan-genome is open and expanding, which indicates the possible addition of new gene families to the pan-genome. We also investigated the distribution of biosynthetic gene clusters (BGCs) among the strains. We discovered slight variations of BGCs at the strain level. Several BGCs with the potential to express novel bioactive secondary metabolites have been identified. Therefore, by utilizing the characteristic advantages of C. glutamicum, different strains can be potential applicants for natural drug discovery.

In Silico Screening of Bacteriocin Gene Clusters within a Set of Marine Bacillota Genomes

Due to their potential application as an alternative to antibiotics, bacteriocins, which are ribosomally synthesized antimicrobial peptides produced by bacteria, have received much attention in recent years. To identify bacteriocins within marine bacteria, most of the studies employed a culture-based method, which is more time-consuming than the in silico approach. For that, the aim of this study was to identify potential bacteriocin gene clusters and their potential producers in 51 marine Bacillota (formerly Firmicutes) genomes, using BAGEL4, a bacteriocin genome mining tool. As a result, we found out that a majority of selected Bacillota (60.78%) are potential bacteriocin producers, and we identified 77 bacteriocin gene clusters, most of which belong to class I bacteriocins known as RiPPs (ribosomally synthesized and post-translationally modified peptides). The identified putative bacteriocin gene clusters are an attractive target for further in vitro research, such as the production of bacteriocins using a heterologous expression system.

Insights into group-specific pattern of secondary metabolite gene cluster in Burkholderia genus

Burkholderia is a versatile strain that has expanded into several genera. It has been steadily reported that the genome features of Burkholderia exhibit activities ranging from plant growth promotion to pathogenicity across various isolation areas. The objective of this study was to investigate the secondary metabolite patterns of 366 Burkholderia species through comparative genomics. Samples were selected based on assembly quality assessment and similarity below 80% in average nucleotide identity. Duplicate samples were excluded. Samples were divided into two groups using FastANI analysis. Group A included B. pseudomallei complex. Group B included B. cepacia complex. The limitations of MLST were proposed. The detection of genes was performed, including environmental and virulence-related genes. In the pan-genome analysis, each complex possessed a similar pattern of cluster for orthologous groups. Group A (n = 185) had 14,066 cloud genes, 2,465 shell genes, 682 soft-core genes, and 2,553 strict-core genes. Group B (n = 181) had 39,867 cloud genes, 4,986 shell genes, 324 soft-core genes, 222 core genes, and 2,949 strict-core genes. AntiSMASH was employed to analyze the biosynthetic gene cluster (BGC). The results were then utilized for network analysis using BiG-SCAPE and CORASON. Principal component analysis was conducted and a table was constructed using the results obtained from antiSMASH. The results were divided into Group A and Group B. We expected the various species to show similar patterns of secondary metabolite gene clusters. For in-depth analysis, a network analysis of secondary metabolite gene clusters was conducted, exemplified by BiG-SCAPE analysis. Depending on the species and complex, Burkholderia possessed several kinds of siderophore. Among them, ornibactin was possessed in most Burkholderia and was clustered into 4,062 clans. There was a similar pattern of gene clusters depending on the species. NRPS_04014 belonged to siderophore BGCs including ornibactin and indigoidine. However, it was observed that each family included a similar species. This suggests that, besides siderophores being species-specific, the ornibactin gene cluster itself might also be species-specific. The results suggest that siderophores are associated with environmental adaptation, possessing a similar pattern of siderophore gene clusters among species, which could provide another perspective on species-specific environmental adaptation mechanisms.

Comparative genomics with evolutionary lineage in Streptomyces bacteria reveals high biosynthetic potentials

Genome mining in silico approaches allow scientists to proficiently evaluate the genomic potency of secondary bioactive chemical producers and find new bioactive compounds in different bacteria. Streptomyces is one of the most ubiquitous bacterial genera in the environments, and well-known as prolific producers of diverse and valuable natural products (NPs) with significant biological activities. Mining and prioritizing of NP biosynthetic gene clusters (BGCs) would be the most important stage in the identification of novel compounds. Comparative genomics and genetic similarity network analysis of 62 Streptomyces public reference genomes demonstrated that individuals of these species exhibit a huge number of distinct NP BGCs, the most of which are cryptic and unconnected to any reported NPs with high phylogenetic variation among individuals. It was assumed that substantial heterogeneity across the varieties of species of Streptomyces drives outstanding biosynthetic and metabolic potential, making them plausible candidates for the identification of novel molecules.

Isolation, complete genome sequencing and in silico genome mining of Burkholderia for secondary metabolites

Recent years, Burkholderia species have emerged as a new source of natural products (NPs) with increasing attractions. Genome mining suggests the Burkholderia genomes include many natural product biosynthetic gene clusters (BGCs) which are new targets for drug discovery. In order to collect more Burkholderia, here, a strain S-53 was isolated from the soil samples on a mountain area in Changde, P.R. China and verified by comparative genetic analysis to belong to Burkholderia. The complete genome of Burkholderia strain S-53 is 8.2 Mbps in size with an average G + C content of 66.35%. Its taxonomy was both characterized by 16S rRNA- and whole genome-based phylogenetic trees. Bioinformatic prediction in silico revealed it has a total of 15 NP BGCs, some of which may encode unknown products. It is expectable that availability of these BGCs will speed up the identification of new secondary metabolites from Burkholderia and help us understand how sophisticated BGC regulation works.