Leveraging Microbial Genomes and Genomic Context for Chemical Discovery

Context matters: assessing the impacts of genomic background and ecology on microbial biosynthetic gene cluster evolution

Encoded within many microbial genomes, biosynthetic gene clusters (BGCs) underlie the synthesis of various secondary metabolites that often mediate ecologically important functions. Several studies and bioinformatics methods developed over the past decade have advanced our understanding of both microbial pangenomes and BGC evolution. In this minireview, we first highlight challenges in broad evolutionary analysis of BGCs, including delineation of BGC boundaries and clustering of BGCs across genomes. We further summarize key findings from microbial comparative genomics studies on BGC conservation across taxa and habitats and discuss the potential fitness effects of BGCs in different settings. Afterward, recent research showing the importance of genomic context on the production of secondary metabolites and the evolution of BGCs is highlighted. These studies draw parallels to recent, broader, investigations on gene-to-gene associations within microbial pangenomes. Finally, we describe mechanisms by which microbial pangenomes and BGCs evolve, ranging from the acquisition or origination of entire BGCs to micro-evolutionary trends of individual biosynthetic genes. An outlook on how expansions in the biosynthetic capabilities of some taxa might support theories that open pangenomes are the result of adaptive evolution is also discussed. We conclude with remarks about how future work leveraging longitudinal metagenomics across diverse ecosystems is likely to significantly improve our understanding on the evolution of microbial genomes and BGCs.

Insights into Functions of Universal Stress Proteins Encoded by Genomes of Gastric Cancer Pathogen Helicobacter pylori and Related Bacteria

The genes that encode the universal stress protein (USP) family domain (pfam00582) aid the survival of bacteria in specific host or habitat-induced stress conditions. Genome sequencing revealed that the genome of Helicobacter pylori, a gastric cancer pathogen, typically contains one USP gene, while related helicobacters have one or two distinct USP genes. However, insights into the functions of Helicobacteraceae (Helicobacter and Wolinella) USP genes are still limited to inferences from large-scale genome sequencing. Thus, we have combined bioinformatics and visual analytics approaches to conduct a more comprehensive data investigation of a set of 1045 universal stress protein sequences encoded in 1014 genomes including 785 Helicobacter pylori genomes. The study generated a representative set of 183 USP sequences consisting of 180 Helicobacter sequences, two Wolinella succinogenes sequences, and a sequence from a related campylobacteria. We used the amino acid residues and positions of the 12 possible functional sites in 1030 sequences to identify 25 functional sites patterns for guiding studies on functional interactions of Helicobacteraceae USPs with ATP and other molecules. Genomic context searches and analysis identified USP genes of gastric and enterohepatic helicobacters that are adjacent or in operons with genes for proteins responsive to DNA-damaging oxidative stress (ATP-dependent proteases: ClpS and ClpA); and DNA uptake proteins (natural competence for transformation proteins: ComB6, ComB7, ComB8, ComB9, ComB10, ComBE, and conjugative transfer signal peptidase TraF). Since transcriptomic evidence indicates that oxidative stress and the presence of virulence-associated genes regulate the transcription of H. pylori USP gene, we recommend further research on Helicobacter USP genes and their neighboring genes in oxidative stress response and virulence of helicobacters. To facilitate the reuse of data and research, we produced interactive analytics resources of a dataset composed of values for variables including phylogeography of H. pylori strains, protein sequence features, and gene neighborhood.

The right tool for the job: Chemical biology and microbiome science

Microbiomes exist in ecological niches ranging from the ocean and soil to inside of larger organisms like plants and animals. Within these niches, microbes play key roles in biochemical processes that impact larger phenomena, such as biogeochemical cycling or health. By understanding of how these processes occur at the molecular level, it may be possible to develop new interventions to address global problems. The complexity of these systems poses challenges to more traditional techniques. Chemical biology can help overcome these challenges by providing tools that are broadly applicable and can obtain molecular-level information about complex systems. This primer is intended to serve as a brief introduction to chemical biology and microbiome science, to highlight some of the ways that these two disciplines complement each other, and to encourage dialog and collaboration between these fields.

Metatranscriptomics-guided discovery and characterization of a polyphenol-metabolizing gut microbial enzyme

Gut microbial catechol dehydroxylases are a largely uncharacterized family of metalloenzymes that potentially impact human health by metabolizing dietary polyphenols. Here, we use metatranscriptomics (MTX) to identify highly transcribed catechol-dehydroxylase-encoding genes in human gut microbiomes. We discover a prevalent, previously uncharacterized catechol dehydroxylase (Gp Hcdh) from Gordonibacter pamelaeae that dehydroxylates hydrocaffeic acid (HCA), an anti-inflammatory gut microbial metabolite derived from plant-based foods. Further analyses suggest that the activity of Gp Hcdh may reduce anti-inflammatory benefits of polyphenol-rich foods. Together, these results show the utility of combining MTX analysis and biochemical characterization for gut microbial enzyme discovery and reveal a potential link between host inflammation and a specific polyphenol-metabolizing gut microbial enzyme.

Heterologous expression of lasso peptides with apparent participation in the morphological development in Streptomyces

Lasso peptides, ribosomally synthesized and post-translationally modified peptides, are primarily produced by bacteria and some archaea. Streptomyces lasso peptides have been known for their antimicrobial, anticancer, and antiviral properties. However, understanding their role in the morphology and production of secondary metabolites remains limited. We identified a previously unknown lasso peptide gene cluster in the genome of Streptomyces sp. L06. This gene cluster (LASS) produces two distinct lasso peptides, morphosin-1 and - 2. Notably, morphosin-2 is a member of a new subfamily of lasso peptides, with BGCs exhibiting a similar structure. When LASS was expressed in different Streptomyces hosts, it led to exciting phenotypic changes, including the absence of spores and damage in aerial mycelium development. In one of the hosts, LASS even triggered antibiotic formation. These findings open up a world of possibilities, suggesting the potential role of morphosins in shaping Streptomyces' morphological and biochemical development.

Genomic language model predicts protein co-regulation and function

Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function paradigm from massive protein sequence datasets. However, to date, limited attempts have been made in extending this continuum to include higher order genomic context information. Evolutionary processes dictate the specificity of genomic contexts in which a gene is found across phylogenetic distances, and these emergent genomic patterns can be leveraged to uncover functional relationships between gene products. Here, we train a genomic language model (gLM) on millions of metagenomic scaffolds to learn the latent functional and regulatory relationships between genes. gLM learns contextualized protein embeddings that capture the genomic context as well as the protein sequence itself, and encode biologically meaningful and functionally relevant information (e.g. enzymatic function, taxonomy). Our analysis of the attention patterns demonstrates that gLM is learning co-regulated functional modules (i.e. operons). Our findings illustrate that gLM's unsupervised deep learning of the metagenomic corpus is an effective and promising approach to encode functional semantics and regulatory syntax of genes in their genomic contexts and uncover complex relationships between genes in a genomic region.

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.

Comparative Metagenomic Analysis of Biosynthetic Diversity across Sponge Microbiomes Highlights Metabolic Novelty, Conservation, and Diversification

Marine sponges and their microbial symbiotic communities are rich sources of diverse natural products (NPs) that often display biological activity, yet little is known about the global distribution of NPs and the symbionts that produce them. Since the majority of sponge symbionts remain uncultured, it is a challenge to characterize their NP biosynthetic pathways, assess their prevalence within the holobiont, and measure the diversity of NP biosynthetic gene clusters (BGCs) across sponge taxa and environments. Here, we explore the microbial biosynthetic landscapes of three high-microbial-abundance (HMA) sponges from the Atlantic Ocean and the Mediterranean Sea. This data set reveals striking novelty, with <1% of the recovered gene cluster families (GCFs) showing similarity to any characterized BGC. When zooming in on the microbial communities of each sponge, we observed higher variability of specialized metabolic and taxonomic profiles between sponge species than within species. Nonetheless, we identified conservation of GCFs, with 20% of sponge GCFs being shared between at least two sponge species and a GCF core comprised of 6% of GCFs shared across all species. Within this functional core, we identified a set of widespread and diverse GCFs encoding nonribosomal peptide synthetases that are potentially involved in the production of diversified ether lipids, as well as GCFs putatively encoding the production of highly modified proteusins. The present work contributes to the small, yet growing body of data characterizing NP landscapes of marine sponge symbionts and to the cryptic biosynthetic potential contained in this environmental niche. IMPORTANCE Marine sponges and their microbial symbiotic communities are a rich source of diverse natural products (NPs). However, little is known about the sponge NP global distribution landscape and the symbionts that produce them. Here, we make use of recently developed tools to perform untargeted mining and comparative analysis of sponge microbiome metagenomes of three sponge species in the first study considering replicate metagenomes of multiple sponge species. We present an overview of the biosynthetic diversity across these sponge holobionts, which displays extreme biosynthetic novelty. We report not only the conservation of biosynthetic and taxonomic diversity but also a core of conserved specialized metabolic pathways. Finally, we highlight several novel GCFs with unknown ecological function, and observe particularly high biosynthetic potential in Acidobacteriota and Latescibacteria symbionts. This study paves the way toward a better understanding of the marine sponge holobionts' biosynthetic potential and the functional and ecological role of sponge microbiomes.

Kinetic Characteristics of Curcumin and Germacrone in Rat and Human Liver Microsomes: Involvement of CYP Enzymes

Curcumin and germacrone, natural products present in the Zingiberaceae family of plants, have several biological properties. Among these properties, the anti-NSCLC cancer action is noteworthy. In this paper, kinetics of the two compounds in rat liver microsomes (RLMs), human liver microsomes (HLMs), and cytochrome P450 (CYP) enzymes (CYP3A4, 1A2, 2E1, and 2C19) in an NADPH-generating system in vitro were evaluated by UP-HPLC–MS/MS (ultrahigh-pressure liquid chromatography–tandem mass spectrometry). The contents of four cytochrome P450 (CYP) enzymes, adjusting by the compounds were detected using Western blotting in vitro and in vivo. The t1/2 of curcumin was 22.35 min in RLMs and 173.28 min in HLMs, while 18.02 and 16.37 min were gained for germacrone. The Vmax of curcumin in RLMs was about 4-fold in HLMs, meanwhile, the Vmax of germacrone in RLMs was similar to that of HLMs. The single enzyme t1/2 of curcumin was 38.51 min in CYP3A4, 301.4 min in 1A2, 69.31 min in 2E1, 63.01 min in 2C19; besides, as to the same enzymes, t1/2 of germacrone was 36.48 min, 86.64 min, 69.31 min, and 57.76 min. The dynamic curves were obtained by reasonable experimental design and the metabolism of curcumin and germacrone were selected in RLMs/HLMs. The selectivities in the two liver microsomes differed in degradation performance. These results meant that we should pay more attention to drugs in clinical medication–drug and drug–enzyme interactions.

Exploration of Chemical Biology Approaches to Facilitate the Discovery and Development of Novel Antibiotics

Approximately 2.8 million people worldwide are infected with bacteria that are deemed resistant to clinically relevant antibiotics. This accounts for 700,000 deaths every year and represents a major public health threat that has been on the rise for the past two decades. In contrast, the pace of antibiotic discovery to treat these resistant pathogens has significantly decreased. Most antibiotics are complex natural products that were isolated from soil microorganisms during the golden era of antibiotic discovery (1940s to 1960s) employing the “Waksman platform”. After the collapse of this discovery platform, other strategies and approaches emerged, including phenotype- or target-based screenings of large synthetic compound libraries. However, these methods have not resulted in the discovery and/or development of new drugs for clinical use in over 30 years. A better understanding of the structure and function of the molecular components that constitute the bacterial system is of paramount importance to design new strategies to tackle drug-resistant pathogens. Herein, we review the traditional approaches as well as novel strategies to facilitate antibiotic discovery that are chemical biology-focused. These include the design and application of chemical probes that can undergo bioorthogonal reactions, such as copper (I)-catalyzed azide-alkyne cycloadditions (CuAAC). By specifically interacting with bacterial proteins or being incorporated in the microorganism’s metabolism, chemical probes are powerful tools in drug discovery that can help uncover new drug targets and investigate the mechanisms of action and resistance of new antibacterial leads.