Needles in haystacks: reevaluating old paradigms for the discovery of bacterial secondary metabolites

Diving into freshwater microbial metabolites: Pioneering research and future prospects

In practically every facet of life, especially nutrition, agriculture, and healthcare, microorganisms offer a prospective origin for abundant natural substances and products. Among these microorganisms, bacteria also possess the capability to rapidly acclimate to diverse environments, utilize varied resources, and effectively respond to environmental fluctuations, including those influenced by human activities like pollution and climate change. The ever-changing environment of freshwater bodies influences bacterial communities, offering opportunities for improving health and environmental conservation that remain unexplored. Herein, the study discusses the bacterial taxa along with specialised metabolites with antioxidant, antibacterial, and anticancer activity that have been identified from freshwater environments, thus achieving Sustainable Development Goals addressing health and wellbeing (SDG-3), economic growth (SDG-8) along with industrial development (SDG-9). The present review is intended as a compendium for research teams working in the fields of medicinal chemistry, organic chemistry, clinical research, and natural product chemistry.

BGCFlow: systematic pangenome workflow for the analysis of biosynthetic gene clusters across large genomic datasets

Genome mining is revolutionizing natural products discovery efforts. The rapid increase in available genomes demands comprehensive computational platforms to effectively extract biosynthetic knowledge encoded across bacterial pangenomes. Here, we present BGCFlow, a novel systematic workflow integrating analytics for large-scale genome mining of bacterial pangenomes. BGCFlow incorporates several genome analytics and mining tools grouped into five common stages of analysis such as: (i) data selection, (ii) functional annotation, (iii) phylogenetic analysis, (iv) genome mining, and (v) comparative analysis. Furthermore, BGCFlow provides easy configuration of different projects, parallel distribution, scheduled job monitoring, an interactive database to visualize tables, exploratory Jupyter Notebooks, and customized reports. Here, we demonstrate the application of BGCFlow by investigating the phylogenetic distribution of various biosynthetic gene clusters detected across 42 genomes of the Saccharopolyspora genus, known to produce industrially important secondary/specialized metabolites. The BGCFlow-guided analysis predicted more accurate dereplication of BGCs and guided the targeted comparative analysis of selected RiPPs. The scalable, interoperable, adaptable, re-entrant, and reproducible nature of the BGCFlow will provide an effective novel way to extract the biosynthetic knowledge from the ever-growing genomic datasets of biotechnologically relevant bacterial species.

Global Map of Specialized Metabolites Encoded in Prokaryotic Plasmids

Plasmids are the main mobile elements responsible for horizontal gene transfer (HGT) in microorganisms. These replicons extend the metabolic spectrum of their host cells by carrying functional genes. However, it is still unknown to what extent plasmids carry biosynthetic gene clusters (BGCs) related to the production of secondary or specialized metabolites (SMs). Here, we analyzed 9,183 microbial plasmids to unveil their potential to produce SMs, finding a large diversity of cryptic BGCs in a few varieties of prokaryotic host taxa. Some of these plasmids harbored 15 or more BGCs, and many others were exclusively dedicated to mobilizing BGCs. We found an occurrence pattern of BGCs within groups of homologous plasmids shared by a common taxon, mainly in host-associated microbes (e.g., Rhizobiales, Enterobacteriaceae members). Our results add to the knowledge of the ecological functions and potential industrial uses of plasmids and shed light on the dynamics and evolution of SMs in prokaryotes. IMPORTANCE Plasmids are mobile DNA elements that can be shared among microbial cells, and they are useful for bringing to fruition some microbial ecological traits. However, it is not known to what extent plasmids harbor genes related to the production of specialized/secondary metabolites (SMs). In microbes, these metabolites are frequently useful for defense purposes, signaling, etc. In addition, these molecules usually have biotechnological and clinical applications. Here, we analyzed the content, dynamics, and evolution of genes related to the production of SMs in >9,000 microbial plasmids. Our results confirm that some plasmids act as a reservoir of SMs. We also found that some families of biosynthetic gene clusters are exclusively present in some groups of plasmids shared among closely related microbes. Host-associated bacteria (e.g., plant and human microbes) harbor the majority of specialized metabolites encoded in plasmids. These results provide new knowledge about microbial ecological traits and might enable the discovery of novel metabolites.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

New trends in synthetic drugs and natural products targeting 20S proteasomes in cancers

Cancer is a global health challenge that remains to be a field of extensive research aiming to find new anticancer therapeutics. The 20S proteasome complex is one of the targets of anticancerdrugs, as it is correlated with several cancer types. Herein, we aim to discuss the 20S proteasome subunits and investigatethe currently studied proteasome inhibitors targeting the catalytically active proteasome subunits. In this review, we summarize the proteindegradation mechanism of the 20S proteasome complex and compareit with the 26S proteasome complex. Afterwards, the localization of the 20S proteasome is summarized as well as its use as a diagnosticandprognostic marker. The FDA-approved proteasome inhibitors (PIs) under clinical trials are summarized and their current limited use in solid tumors is also reviewed in addition to the expression of theβ5 subunit in differentcell lines. The review discusses in-silico analysis of the active subunit of the 20S proteasome complex. For development of new proteasome inhibitor drugs, the natural products inhibiting the 20S proteasome are summarized, as well as novel methodologies and challenges for the natural product discovery and current information about the biosynthetic gene clusters encoding them. We herein briefly summarize some resistancemechanismsto the proteasomeinhibitors. Additionally, we focus on the three main classes of proteasome inhibitors: 1] boronic acid, 2] beta-lactone and 3] epoxide inhibitor classes, as well as other PI classes, and their IC₅₀ values and their structure-activity relationship (SAR). Lastly,we summarize several future prospects of developing new proteasome inhibitors towards the treatment of tumors, especially solid tumors.

Evolutionary investigations of the biosynthetic diversity in the skin microbiome using lsaBGC

Bacterial secondary metabolites, synthesized by enzymes encoded in biosynthetic gene clusters (BGCs), can underlie microbiome homeostasis and serve as commercialized products, which have historically been mined from a select group of taxa. While evolutionary approaches have proven beneficial for prioritizing BGCs for experimental characterization efforts to uncover new natural products, dedicated bioinformatics tools designed for comparative and evolutionary analysis of BGCs within focal taxa are limited. We thus developed lineage specific analysis of BGCs (lsaBGC; https://github.com/Kalan-Lab/lsaBGC) to aid exploration of microdiversity and evolutionary trends across homologous groupings of BGCs, gene cluster families (GCFs), in any bacterial taxa of interest. lsaBGC enables rapid and direct identification of GCFs in genomes, calculates evolutionary statistics and conservation for BGC genes, and builds a framework to allow for base resolution mining of novel variants through metagenomic exploration. Through application of the suite to four genera commonly found in skin microbiomes, we uncover new insights into the evolution and diversity of their BGCs. We show that the BGC of the virulence-associated carotenoid staphyloxanthin in Staphylococcus aureus is ubiquitous across the genus Staphylococcus . While one GCF encoding the biosynthesis of staphyloxanthin showcases evidence for plasmid-mediated horizontal gene transfer (HGT) between species, another GCF appears to be transmitted vertically amongst a sub-clade of skin-associated Staphylococcus . Further, the latter GCF, which is well conserved in S. aureus , has been lost in most Staphylococcus epidermidis , which is the most common Staphylococcus species on human skin and is also regarded as a commensal. We also identify thousands of novel single-nucleotide variants (SNVs) within BGCs from the Corynebacterium tuberculostearicum sp. complex, a narrow, multi-species clade that features the most prevalent Corynebacterium in healthy skin microbiomes. Although novel SNVs were approximately 10 times as likely to correspond to synonymous changes when located in the top five percentile of conserved sites, lsaBGC identified SNVs that defied this trend and are predicted to underlie amino acid changes within functionally key enzymatic domains. Ultimately, beyond supporting evolutionary investigations of BGCs, lsaBGC also provides important functionalities to aid efforts for the discovery or directed modification of natural products.

Diversity and taxonomic distribution of bacterial biosynthetic gene clusters predicted to produce compounds with therapeutically relevant bioactivities

Bacteria have long been a source of natural products with diverse bioactivities that have been developed into therapeutics to treat human disease. Historically, researchers have focused on a few taxa of bacteria, mainly Streptomyces and other actinomycetes. This strategy was initially highly successful and resulted in the golden era of antibiotic discovery. The golden era ended when the most common antibiotics from Streptomyces had been discovered. Rediscovery of known compounds has plagued natural product discovery ever since. Recently, there has been increasing interest in identifying other taxa that produce bioactive natural products. Several bioinformatics studies have identified promising taxa with high biosynthetic capacity. However, these studies do not address the question of whether any of the products produced by these taxa are likely to have activities that will make them useful as human therapeutics. We address this gap by applying a recently developed machine learning tool that predicts natural product activity from biosynthetic gene cluster (BGC) sequences to determine which taxa are likely to produce compounds that are not only novel but also bioactive. This machine learning tool is trained on a dataset of BGC-natural product activity pairs and relies on counts of different protein domains and resistance genes in the BGC to make its predictions. We find that rare and understudied actinomycetes are the most promising sources for novel active compounds. There are also several taxa outside of actinomycetes that are likely to produce novel active compounds. We also find that most strains of Streptomyces likely produce both characterized and uncharacterized bioactive natural products. The results of this study provide guidelines to increase the efficiency of future bioprospecting efforts.

ONE-SENTENCE SUMMARY

This paper combines several bioinformatics workflows to identify which genera of bacteria are most likely to produce novel natural products with useful bioactivities such as antibacterial, antitumor, or antifungal activity.

Bioprospecting the microbiome of Red Sea Atlantis II brine pool for peptidases and biosynthetic genes with promising antibacterial activity

Background

The search for novel antimicrobial agents is crucial as antibiotic-resistant pathogens continue to emerge, rendering the available antibiotics no longer effective. Likewise, new anti-cancer drugs are needed to combat the emergence of multi-drug resistant tumors. Marine environments are wealthy sources for natural products. Additionally, extreme marine environments are interesting niches to search for bioactive natural compounds. In the current study, a fosmid library of metagenomic DNA isolated from Atlantis II Deep Lower Convective Layer (ATII LCL), was functionally screened for antibacterial activity as well as anticancer effects.

Results

Two clones exhibited antibacterial effects against the marine Bacillus Cc6 strain, namely clones 102-5A and 88-1G and they were further tested against eleven other challenging strains, including six safe relatives of ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter  spp.), a safe relative to Mycobacterium tuberculosis and four resistant clinical isolates. Clone 88-1G resulted in clear zones of inhibition against eight bacterial strains, while clone 102-5A resulted in zones of inhibition against five bacterial strains. The whole cell lysates of clone 88-1G showed 15% inhibition of Mtb ClpP protease -Mycobacterium tuberculosis drug target-, while whole cell lysates of clone 102-5A showed 19% inhibition of Mtb ClpP protease. Whole cell lysates from the selected clones exhibited anticancer effects against MCF-7 breast cancer cells (cell viability at 50% v/v was 46.2% ± 9.9 for 88-1G clone and 38% ± 7 for 102-5A clone), U2OS osteosarcoma cells (cell viability at 50% v/v was 64.6% ± 12.3 for 88-1G clone and 28.3% ± 1.7 for 102-5A clone) and 1BR hTERT human fibroblast cells (cell viability at 50% v/v was 74.4% ± 5.6 for 88-1G clone and 57.6% ± 8.9 for 102-5A clone). Sequencing of 102-5A and 88-1G clones, and further annotation detected putative proteases and putative biosynthetic genes in clones 102-5A and 88-1G, respectively.

Conclusions

The ATII LCL metagenome hosts putative peptidases and biosynthetic genes that confer antibiotic and anti-cancer effects. The tested clones exhibited promising antibacterial activities against safe relative strains to ESKAPE pathogens and Mycobacterium tuberculosis. Thus, searching the microbial dark matter of extreme environments is a promising approach to identify new molecules with pharmaceutical potential use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01835-z.

Nutrient Availability Shifts the Biosynthetic Potential of Soil-Derived Microbial Communities

Secondary metabolites produced by microorganisms are the main source of antimicrobials and other pharmaceutical drugs. Soil microbes have been the primary discovery source for these secondary metabolites, often producing complex organic compounds with specific biological activities. Research suggests that secondary metabolism broadly shapes microbial ecological interactions, but little is known about the factors that shape the abundance, distribution, and diversity of biosynthetic gene clusters in the context of microbial communities. In this study, we investigate the role of nutrient availability on the abundance of biosynthetic gene clusters in soil-derived microbial consortia. Soil microbial consortia enriched in high sugar medium (150 mg/L of glucose and 200 mg/L of trehalose) had more biosynthetic gene clusters and higher inhibitory activity than those enriched in low sugar medium (15 mg/L of glucose + 20 mg/L of trehalose). Our results demonstrate that experimental microbial communities are a promising tool to study the ecology of specialized metabolites.