Linking biosynthetic and chemical space to accelerate microbial secondary metabolite discovery

Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities

Microbial communities thrive through interactions and communication, which are challenging to study as most microorganisms are not cultivable. To address this challenge, researchers focus on the extracellular space where communication events occur. Exometabolomics and interactome analysis provide insights into the molecules involved in communication and the dynamics of their interactions. Advances in sequencing technologies and computational methods enable the reconstruction of taxonomic and functional profiles of microbial communities using high-throughput multi-omics data. Network-based approaches, including community flux balance analysis, aim to model molecular interactions within and between communities. Despite these advances, challenges remain in computer-assisted biosynthetic capacities elucidation, requiring continued innovation and collaboration among diverse scientists. This review provides insights into the current state and future directions of computer-assisted biosynthetic capacities elucidation in studying microbial communities.

Genome mining reveals secondary metabolites of Antarctic bacterium Streptomyces albidoflavus related to antimicrobial and antiproliferative activities

The urgent need for new antimicrobials arises from antimicrobial resistance. Actinobacteria, especially Streptomyces genus, are responsible for production of numerous clinical antibiotics and anticancer agents. Genome mining reveals the biosynthetic gene clusters (BGCs) related to secondary metabolites and the genetic potential of a strain to produce natural products. However, this potential may not be expressed under laboratory conditions. In the present study, the Antarctic bacterium was taxonomically affiliated as Streptomyces albidoflavus ANT_B131 (CBMAI 1855). The crude extracts showed antimicrobial activity against both fungi, Gram-positive and Gram-negative bacteria and antiproliferative activity against five human tumor cell lines. Whole-genome sequencing reveals a genome size of 6.96 Mb, and the genome mining identified 24 BGCs, representing 13.3% of the genome. The use of three culture media and three extraction methods reveals the expression and recovery of 20.8% of the BGCs. The natural products identified included compounds, such as surugamide A, surugamide D, desferrioxamine B + Al, desferrioxamine E, and ectoine. This study reveals the potential of S. albidoflavus ANT_B131 as a natural product producer. Yet, the diversity of culture media and extraction methods could enhance the BGCs expression and recovery of natural products, and could be a strategy to intensify the BGC expression of natural products.

Metabolome-guided genome mining of RiPP natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a chemically diverse class of metabolites. Many RiPPs show potent biological activities that make them attractive starting points for drug development. A promising approach for the discovery of new classes of RiPPs is genome mining. However, the accuracy of genome mining is hampered by the lack of signature genes shared across different RiPP classes. One way to reduce false-positive predictions is by complementing genomic information with metabolomics data. In recent years, several new approaches addressing such integrative genomics and metabolomics analyses have been developed. In this review, we provide a detailed discussion of RiPP-compatible software tools that integrate paired genomics and metabolomics data. We highlight current challenges in data integration and identify opportunities for further developments targeting new classes of bioactive RiPPs.

Secondary Metabolites Produced by the Blue-Cheese Ripening Mold Penicillium roqueforti; Biosynthesis and Regulation Mechanisms

Filamentous fungi are an important source of natural products. The mold Penicillium roqueforti, which is well-known for being responsible for the characteristic texture, blue-green spots, and aroma of the so-called blue-veined cheeses (French Bleu, Roquefort, Gorgonzola, Stilton, Cabrales, and Valdeón, among others), is able to synthesize different secondary metabolites, including andrastins and mycophenolic acid, as well as several mycotoxins, such as Roquefortines C and D, PR-toxin and eremofortins, Isofumigaclavines A and B, festuclavine, and Annullatins D and F. This review provides a detailed description of the biosynthetic gene clusters and pathways of the main secondary metabolites produced by P. roqueforti, as well as an overview of the regulatory mechanisms controlling secondary metabolism in this filamentous fungus.

An untargeted exometabolomics approach to characterize dissolved organic matter in groundwater of the Samail Ophiolite

The process of serpentinization supports life on Earth and gives rise to the habitability of other worlds in our Solar System. While numerous studies have provided clues to the survival strategies of microbial communities in serpentinizing environments on the modern Earth, characterizing microbial activity in such environments remains challenging due to low biomass and extreme conditions. Here, we used an untargeted metabolomics approach to characterize dissolved organic matter in groundwater in the Samail Ophiolite, the largest and best characterized example of actively serpentinizing uplifted ocean crust and mantle. We found that dissolved organic matter composition is strongly correlated with both fluid type and microbial community composition, and that the fluids that were most influenced by serpentinization contained the greatest number of unique compounds, none of which could be identified using the current metabolite databases. Using metabolomics in conjunction with metagenomic data, we detected numerous products and intermediates of microbial metabolic processes and identified potential biosignatures of microbial activity, including pigments, porphyrins, quinones, fatty acids, and metabolites involved in methanogenesis. Metabolomics techniques like the ones used in this study may be used to further our understanding of life in serpentinizing environments, and aid in the identification of biosignatures that can be used to search for life in serpentinizing systems on other worlds.

Metabologenomics analysis of Pseudomonas sp. So3.2b, an Antarctic strain with bioactivity against Rhizoctonia solani

Introduction

Phytopathogenic fungi are a considerable concern for agriculture, as they can threaten the productivity of several crops worldwide. Meanwhile, natural microbial products are acknowledged to play an important role in modern agriculture as they comprehend a safer alternative to synthetic pesticides. Bacterial strains from underexplored environments are a promising source of bioactive metabolites.

Methods

We applied the OSMAC (One Strain, Many Compounds) cultivation approach, in vitro bioassays, and metabolo-genomics analyses to investigate the biochemical potential of Pseudomonas sp. So3.2b, a strain isolated from Antarctica. Crude extracts from OSMAC were analyzed through HPLC-QTOF-MS/MS, molecular networking, and annotation. The antifungal potential of the extracts was confirmed against Rhizoctonia solani strains. Moreover, the whole-genome sequence was studied for biosynthetic gene clusters (BGCs) identification and phylogenetic comparison.

Results and Discussion

Molecular networking revealed that metabolite synthesis has growth media specificity, and it was reflected in bioassays results against R. solani. Bananamides, rhamnolipids, and butenolides-like molecules were annotated from the metabolome, and chemical novelty was also suggested by several unidentified compounds. Additionally, genome mining confirmed a wide variety of BGCs present in this strain, with low to no similarity with known molecules. An NRPS-encoding BGC was identified as responsible for producing the banamides-like molecules, while phylogenetic analysis demonstrated a close relationship with other rhizosphere bacteria. Therefore, by combining -omics approaches and in vitro bioassays, our study demonstrates that Pseudomonas sp. So3.2b has potential application to agriculture as a source of bioactive metabolites.

Specialized Metabolism of Gordonia Genus: An Integrated Survey on Chemodiversity Combined with a Comparative Genomics-Based Analysis

Members of the phylum Actinomycetota (formerly Actinobacteria) have historically been the most prolific providers of small bioactive molecules. Although the genus Streptomyces is the best-known member for this issue, other genera, such as Gordonia, have shown interesting potential in their specialized metabolism. Thus, we combined herein the result of a comprehensive literature survey on metabolites derived from Gordonia strains with a comparative genomic analysis to examine the potential of the specialized metabolism of the genus Gordonia. Thirty Gordonia-derived compounds of different classes were gathered (i.e., alkaloids, amides, phenylpropanoids, and terpenoids), exhibiting antimicrobial and cytotoxic activities, and several were also isolated from Streptomyces (e.g., actinomycin, nocardamin, diolmycin A1). With the genome data, we estimated an open pan-genome of 57,901 genes, most of them being part of the cloud genome. Regarding the BGCs content, 531 clusters were found, including Terpenes, RiPP-like, and NRPS clusters as the most frequent clusters. Our findings demonstrated that Gordonia is a poorly studied genus in terms of its specialized metabolism production and potential applications. Nevertheless, given their BGCs content, Gordonia spp. are a valuable biological resource that could expand the chemical spectrum of the phylum Actinomycetota, involving novel BGCs for inspiring innovative outlines for synthetic biology and further use in biotechnological initiatives. Therefore, further studies and more efforts should be made to explore different environments and evaluate other bioactivities.

An isotopic labeling approach linking natural products with biosynthetic gene clusters

Major advances in genome sequencing and large-scale biosynthetic gene cluster (BGC) analysis have prompted an age of natural product discovery driven by genome mining. Still, connecting molecules to their cognate BGCs is a substantial bottleneck for this approach. We have developed a mass-spectrometry-based parallel stable isotope labeling platform, termed IsoAnalyst, which assists in associating metabolite stable isotope labeling patterns with BGC structure prediction to connect natural products to their corresponding BGCs. Here we show that IsoAnalyst can quickly associate both known metabolites and unknown analytes with BGCs to elucidate the complex chemical phenotypes of these biosynthetic systems. We validate this approach for a range of compound classes, using both the type strain Saccharopolyspora erythraea and an environmentally isolated Micromonospora sp. We further demonstrate the utility of this tool with the discovery of lobosamide D, a new and structurally unique member of the family of lobosamide macrolactams.

Polyketide-derived macrobrevins from marine macroalga-associated Bacillus amyloliquefaciens as promising antibacterial agents against pathogens causing nosocomial infections

Marine heterotrophs are treasured bio-resources of antimicrobial metabolites, and herein we report the biosynthetic potential of Bacillus amyloliquefaciens (ex. Fukumoto) Priest et al. (Bacillaceae) strain MTCC 12713 isolated from an intertidal macroalga Kappaphycus alvarezii (Doty) L.M.Liao (Rhodophyta: Solieriaceae). The bacterium showed promising biological activities against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecalis. Genome mining of B. amyloliquefaciens MTCC 12713 predicted the gene clusters coding for biosynthesis of antibacterial metabolites. Bioactivity-guided purification was directed to isolate four homologous members of trans-acyltransferase polyketide synthase-derived antibiotics, which were classified as macrobrevin analogues. The compounds exhibited antibacterial activities against nosocomial pathogens, for example, methicillin-resistant S. aureus, vancomycin-resistant E. faecalis, Klebsiella pneumoniae and Pseudomonas aeruginosa with a range of MIC values from 1.56 to 6.25 μg/mL, although standard antibiotic chloramphenicol was active at 6.25-12.5 μg/mL. Conspicuously, the macrobrevin compound encompassing hexahydro-41-hydroxy-macrobrevin-31-acetate functionality, displayed considerably greater antagonistic activities against methicillin-resistant S. aureus, vancomycin-resistant E. faecalis, Vibrio parahaemolyticus, P. aeruginosa, K. pneumoniae, and Streptococcus pyogenes (MIC 1.56 μg/mL) compared to the positive controls and other macrobrevin analogues. Trans-AT polyketide synthase-stimulated biosynthetic pathway of macrobrevin compounds, through repetitive decarboxylative Claisen condensation between acetyl-S-KS domain and malonate-S-ACP units could corroborate the structural elucidation. In the genome mining study, among the 34 biosynthetic gene clusters, a hybrid trans-acyltransferase (trans-AT) pks/nrps gene cluster, which extends up to ∼81 Kb, was recognized in the genome of B. amyloliquefaciens MTCC 12713. The pks/nrps cluster revealed 46% similarity to trans-AT PKS-derived macrobrevin isolated from a mesophilic bacterium Brevibacillus sp. Leaf182 associated with the phyllosphere of the wild-type genotype of Arabidopsis thaliana. The binding positions for macrobrevins with S. aureus peptide deformylase showed docking score of larger than 14 kcal/mol, which was considerably greater than macrolactin N and actinonin (<10 kcal/mol). These present findings documented that the marine heterotrophic B. amyloliquefaciens MTCC 12713 could be used to develop prospective antibacterial agents belonging to macrobrevin analogues for biotechnological and pharmaceutical applications.

Bacillibactin class of siderophore antibiotics from a marine symbiotic Bacillus as promising antibacterial agents

Preliminary antibacterial metabolite production screening unveiled that B. amyloliquefaciens MTCC 12,713 associated with the intertidal red alga Kappaphycus alverezii exhibited potential inhibitory effects against drug-resistant pathogens methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus faecalis, Pseudomonas aeruginosa, and Klebsiella pneumoniae. Four homologous siderophore types of bacillibactins were isolated from a heterotrophic marine bacterium through bioactivity-guided purification. All detectable natural product gene clusters in B. amyloliquefaciens MTCC 12,713 were analyzed by sequencing the complete genome of the bacterium. The studied compounds displayed broad spectrum bactericidal activity against multidrug-resistant strains with a range of minimum inhibitory concentration values from 1.56 to 6.25 µg/mL, whereas standard antibiotic chloramphenicol was active at 6.25 to 12.5 µg/mL. Structure-bioactivity relationship assessment showed that higher electronic values were responsible for antibacterial properties against the nosocomial pathogens. The 2, 3-dihydroxybenzoate (dhb)-assisted biosynthetic pathway of catecholate-enclosed bacillibactins was proposed through the bacillibactin synthase multienzyme complex catalysis followed by dimerization of dhbACEBF operons with 16 genes (~ 12 kb bacterial genome). The present findings recognized an undescribed 4-methoxy-11'-pentanoyloxy-bacillibactin C as a source of potential antibacterial agent for use against drug-resistant pathogens for pharmaceutical applications. KEY POINTS: • Bacillus amyloliquefaciens in association with Kappaphycus alverezii was isolated • Four antibacterial bacillibactin analogs were identified from symbiotic bacterium • 4-Methoxy-11'-pentanoyloxy-bacillibactin C showed potential antibacterial activity.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

FunOrder: A robust and semi-automated method for the identification of essential biosynthetic genes through computational molecular co-evolution

Secondary metabolites (SMs) are a vast group of compounds with different structures and properties that have been utilized as drugs, food additives, dyes, and as monomers for novel plastics. In many cases, the biosynthesis of SMs is catalysed by enzymes whose corresponding genes are co-localized in the genome in biosynthetic gene clusters (BGCs). Notably, BGCs may contain so-called gap genes, that are not involved in the biosynthesis of the SM. Current genome mining tools can identify BGCs, but they have problems with distinguishing essential genes from gap genes. This can and must be done by expensive, laborious, and time-consuming comparative genomic approaches or transcriptome analyses. In this study, we developed a method that allows semi-automated identification of essential genes in a BGC based on co-evolution analysis. To this end, the protein sequences of a BGC are blasted against a suitable proteome database. For each protein, a phylogenetic tree is created. The trees are compared by treeKO to detect co-evolution. The results of this comparison are visualized in different output formats, which are compared visually. Our results suggest that co-evolution is commonly occurring within BGCs, albeit not all, and that especially those genes that encode for enzymes of the biosynthetic pathway are co-evolutionary linked and can be identified with FunOrder. In light of the growing number of genomic data available, this will contribute to the studies of BGCs in native hosts and facilitate heterologous expression in other organisms with the aim of the discovery of novel SMs.

The discovery and description of novel fungal secondary metabolites promises novel antibiotics, pharmaceuticals, and other useful compounds. A way to identify novel secondary metabolites is to express the corresponding genes in a suitable expression host. Consequently, a detailed knowledge or an accurate prediction of these genes is necessary. In fungi, the genes are co-localized in so-called biosynthetic gene clusters. Notably, the clusters may also contain genes that are not necessary for the biosynthesis of the secondary metabolites, so-called gap genes. We developed a method to detect co-evolved genes within the clusters and demonstrated that essential genes are co-evolving and can thus be differentiated from the gap genes. This adds an additional layer of information, which can support researchers with their decisions on which genes to study and express for the discovery of novel secondary metabolites.

Mining genomes to illuminate the specialized chemistry of life

All organisms produce specialized organic molecules, ranging from small volatile chemicals to large gene-encoded peptides, that have evolved to provide them with diverse cellular and ecological functions. As natural products, they are broadly applied in medicine, agriculture and nutrition. The rapid accumulation of genomic information has revealed that the metabolic capacity of virtually all organisms is vastly underappreciated. Pioneered mainly in bacteria and fungi, genome mining technologies are accelerating metabolite discovery. Recent efforts are now being expanded to all life forms, including protists, plants and animals, and new integrative omics technologies are enabling the increasingly effective mining of this molecular diversity.

Biotechnological applications of S-adenosyl-methionine-dependent methyltransferases for natural products biosynthesis and diversification

In the biosynthesis of natural products, methylation is a common and essential transformation to alter molecules' bioavailability and bioactivity. The main methylation reaction is performed by S-adenosylmethionine (SAM)-dependent methyltransferases (MTs). With advancements in genomic and chemical profiling technologies, novel MTs have been discovered to accept complex substrates and synthesize industrially valuable natural products. However, to achieve a high yield of small molecules in microbial hosts, many methyltransferase activities have been reported to be insufficient. Moreover, inadequate co-factor supplies and feedback inhibition of the by-product, S-adenosylhomocysteine (SAH), further limit MTs' activities. Here, we review recent advances in SAM-dependent MTs to produce and diversify natural products. First, we surveyed recently identified novel methyltransferases in natural product biosynthesis. Second, we summarized enzyme engineering strategies to improve methyltransferase activity, with a particular focus on high-throughput assay design and application. Finally, we reviewed innovations in co-factor regeneration and diversification, both in vitro and in vivo. Noteworthily, many MTs are able to accept multiple structurally similar substrates. Such promiscuous methyltransferases are versatile and can be tailored to design de novo pathways to produce molecules whose biosynthetic pathway is unknown or non-existent in nature, thus broadening the scope of biosynthesized functional molecules.

Mycopharmaceuticals and Nutraceuticals: Promising Agents to Improve Human Well-Being and Life Quality

Fungi, especially edible mushrooms, are considered as high-quality food with nutritive and functional values. They are of considerable interest and have been used in the synthesis of nutraceutical supplements due to their medicinal properties and economic significance. Specific fungal groups, including predominantly filamentous endophytic fungi from Ascomycete phylum and several Basidiomycetes, produce secondary metabolites (SMs) with bioactive properties that are involved in the antimicrobial and antioxidant activities. These beneficial fungi, while high in protein and important fat contents, are also a great source of several minerals and vitamins, in particular B vitamins that play important roles in carbohydrate and fat metabolism and the maintenance of the nervous system. This review article will summarize and discuss the abilities of fungi to produce antioxidant, anticancer, antiobesity, and antidiabetic molecules while also reviewing the evidence from the last decade on the importance of research in fungi related products with direct and indirect impact on human health.

Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions

Specialised metabolites from microbial sources are well-known for their wide range of biomedical applications, particularly as antibiotics. When mining paired genomic and metabolomic data sets for novel specialised metabolites, establishing links between Biosynthetic Gene Clusters (BGCs) and metabolites represents a promising way of finding such novel chemistry. However, due to the lack of detailed biosynthetic knowledge for the majority of predicted BGCs, and the large number of possible combinations, this is not a simple task. This problem is becoming ever more pressing with the increased availability of paired omics data sets. Current tools are not effective at identifying valid links automatically, and manual verification is a considerable bottleneck in natural product research. We demonstrate that using multiple link-scoring functions together makes it easier to prioritise true links relative to others. Based on standardising a commonly used score, we introduce a new, more effective score, and introduce a novel score using an Input-Output Kernel Regression approach. Finally, we present NPLinker, a software framework to link genomic and metabolomic data. Results are verified using publicly available data sets that include validated links.

Synthetic biology-inspired strategies and tools for engineering of microbial natural product biosynthetic pathways

Microbial-derived natural products (NPs) and their derivative products are of great importance and used widely in many fields, especially in pharmaceutical industries. However, there is an immediate need to establish innovative approaches, strategies, and techniques to discover new NPs with novel or enhanced biological properties, due to the less productivity and higher cost on traditional drug discovery pipelines from natural bioresources. Revealing of untapped microbial cryptic biosynthetic gene clusters (BGCs) using DNA sequencing technology and bioinformatics tools makes genome mining possible for NP discovery from microorganisms. Meanwhile, new approaches and strategies in the area of synthetic biology offer great potentials for generation of new NPs by engineering or creating synthetic systems with improved and desired functions. Development of approaches, strategies and tools in synthetic biology can facilitate not only exploration and enhancement in supply, and also in the structural diversification of NPs. Here, we discussed recent advances in synthetic biology-inspired strategies, including bioinformatics and genetic engineering tools and approaches for identification, cloning, editing/refactoring of candidate biosynthetic pathways, construction of heterologous expression hosts, fitness optimization between target pathways and hosts and detection of NP production.

Coupling Mass Spectral and Genomic Information to Improve Bacterial Natural Product Discovery Workflows

Bacterial natural products possess potent bioactivities and high structural diversity and are typically encoded in biosynthetic gene clusters. Traditional natural product discovery approaches rely on UV- and bioassay-guided fractionation and are limited in terms of dereplication. Recent advances in mass spectrometry, sequencing and bioinformatics have led to large-scale accumulation of genomic and mass spectral data that is increasingly used for signature-based or correlation-based mass spectrometry genome mining approaches that enable rapid linking of metabolomic and genomic information to accelerate and rationalize natural product discovery. In this mini-review, these approaches are presented, and discovery examples provided. Finally, future opportunities and challenges for paired omics-based natural products discovery workflows are discussed.

Comparative Metabologenomics Analysis of Polar Actinomycetes

Biosynthetic and chemical datasets are the two major pillars for microbial drug discovery in the omics era. Despite the advancement of analysis tools and platforms for multi-strain metabolomics and genomics, linking these information sources remains a considerable bottleneck in strain prioritisation and natural product discovery. In this study, molecular networking of the 100 metabolite extracts derived from applying the OSMAC approach to 25 Polar bacterial strains, showed growth media specificity and potential chemical novelty was suggested. Moreover, the metabolite extracts were screened for antibacterial activity and promising selective bioactivity against drug-persistent pathogens such as Klebsiella pneumoniae and Acinetobacter baumannii was observed. Genome sequencing data were combined with metabolomics experiments in the recently developed computational approach, NPLinker, which was used to link BGC and molecular features to prioritise strains for further investigation based on biosynthetic and chemical information. Herein, we putatively identified the known metabolites ectoine and chrloramphenicol which, through NPLinker, were linked to their associated BGCs. The metabologenomics approach followed in this study can potentially be applied to any large microbial datasets for accelerating the discovery of new (bioactive) specialised metabolites.

Linking genomics and metabolomics to chart specialized metabolic diversity

Microbial and plant specialized metabolites constitute an immense chemical diversity, and play key roles in mediating ecological interactions between organisms. Also referred to as natural products, they have been widely applied in medicine, agriculture, cosmetic and food industries. Traditionally, the main discovery strategies have centered around the use of activity-guided fractionation of metabolite extracts. Increasingly, omics data is being used to complement this, as it has the potential to reduce rediscovery rates, guide experimental work towards the most promising metabolites, and identify enzymatic pathways that enable their biosynthetic production. In recent years, genomic and metabolomic analyses of specialized metabolic diversity have been scaled up to study thousands of samples simultaneously. Here, we survey data analysis technologies that facilitate the effective exploration of large genomic and metabolomic datasets, and discuss various emerging strategies to integrate these two types of omics data in order to further accelerate discovery.

The Connection and Disconnection Between Microbiome and Metabolome: A Critical Appraisal in Clinical Research

Big data-driven omics research has led to a steep rise in investigations involving two of the most functional omes, the metabolome and microbiome. The former is touted as the closest to the phenotype, and the latter is implicated in general well-being and a plethora of human diseases. Although some research publications have integrated the concepts of the two domains, most focus their analyses on evidence solely originating from one or the other. With a growing interest in connecting the microbiome and metabolome in the context of disease, researchers must also appreciate the disconnect between the two domains. In the present review, drawing examples from the current literature, tools, and resources, I discuss the connections between the microbiome and metabolome and highlight challenges and opportunities in linking them together for the basic, translational, clinical, and nursing research communities.