Biosynthetic potential of the global ocean microbiome.

Natural microbial communities are phylogenetically and metabolically diverse. In addition to underexplored organismal groups1, this diversity encompasses a rich discovery potential for ecologically and biotechnologically relevant enzymes and biochemical compounds2,3. However, studying this diversity to identify genomic pathways for the synthesis of such compounds4 and assigning them to their respective hosts remains challenging. The biosynthetic potential of microorganisms in the open ocean remains largely uncharted owing to limitations in the analysis of genome-resolved data at the global scale. Here we investigated the diversity and novelty of biosynthetic gene clusters in the ocean by integrating around 10,000 microbial genomes from cultivated and single cells with more than 25,000 newly reconstructed draft genomes from more than 1,000 seawater samples. These efforts revealed approximately 40,000 putative mostly new biosynthetic gene clusters, several of which were found in previously unsuspected phylogenetic groups. Among these groups, we identified a lineage rich in biosynthetic gene clusters ('Candidatus Eudoremicrobiaceae') that belongs to an uncultivated bacterial phylum and includes some of the most biosynthetically diverse microorganisms in this environment. From these, we characterized the phospeptin and pythonamide pathways, revealing cases of unusual bioactive compound structure and enzymology, respectively. Together, this research demonstrates how microbiomics-driven strategies can enable the investigation of previously undescribed enzymes and natural products in underexplored microbial groups and environments.

Ribosomally derived lipopeptides containing distinct fatty acyl moieties.

Lipopeptides represent a large group of microbial natural products that include important antibacterial and antifungal drugs and some of the most-powerful known biosurfactants. The vast majority of lipopeptides comprise cyclic peptide backbones N-terminally equipped with various fatty acyl moieties. The known compounds of this type are biosynthesized by nonribosomal peptide synthetases, giant enzyme complexes that assemble their products in a non-gene-encoded manner. Here, we report the genome-guided discovery of ribosomally derived, fatty-acylated lipopeptides, termed selidamides. Heterologous reconstitution of three pathways, two from cyanobacteria and one from an arctic, ocean-derived alphaproteobacterium, allowed structural characterization of the probable natural products and suggest that selidamides are widespread over various bacterial phyla. The identified representatives feature cyclic peptide moieties and fatty acyl units attached to (hydroxy)ornithine or lysine side chains by maturases of the GCN5-related N-acetyltransferase superfamily. In contrast to nonribosomal lipopeptides that are usually produced as congener mixtures, the three selidamides are selectively fatty acylated with C10, C12, or C16 fatty acids, respectively. These results highlight the ability of ribosomal pathways to emulate products with diverse, nonribosomal-like features and add to the biocatalytic toolbox for peptide drug improvement and targeted discovery.

Microbial Biocatalysis within Us: The Underexplored Xenobiotic Biotransformation Potential of the Urinary Tract Microbiota.

Enzymatic biotransformation of xenobiotics by the human microbiota mediates diet-drug-microbe-host interactions and affects human health. Most research on xenobiotics has focused on the gut microbiota while neglecting other body sites, yet over two-thirds of pharmaceuticals are primarily excreted in urine. As a result, the urinary microbiota is exposed to many xenobiotics in much higher concentrations than in the gut. Microbial xenobiotic biocatalysis in the bladder has implications for urinary tract infections and the emergence of antibiotic resistance. However, we have limited knowledge of biotransformations catalyzed by the urinary microbiota. In this perspective, we investigated differences in physicochemical conditions and microbial community composition between the gut and urinary tract. We used a comparative enzyme class mining approach to profile the distribution of xenobiotic-transforming enzyme homologs in genomes of urinary bacteria. Our analysis revealed a discontinuous distribution of enzyme classes even among closely related organisms. We detected diverse amidase homologs involved in pharmaceutical and dietary additive biotransformation pathways, pinpointing microbial candidates to validate for their involvement in xenobiotic transformations in urine. Overall, we highlight the biocatalytic potential of urinary tract bacteria as a lens to study how the human microbiota may respond and adapt to xenobiotic inputs.

MIBiG 2.0: a repository for biosynthetic gene clusters of known function.

Fueled by the explosion of (meta)genomic data, genome mining of specialized metabolites has become a major technology for drug discovery and studying microbiome ecology. In these efforts, computational tools like antiSMASH have played a central role through the analysis of Biosynthetic Gene Clusters (BGCs). Thousands of candidate BGCs from microbial genomes have been identified and stored in public databases. Interpreting the function and novelty of these predicted BGCs requires comparison with a well-documented set of BGCs of known function. The MIBiG (Minimum Information about a Biosynthetic Gene Cluster) Data Standard and Repository was established in 2015 to enable curation and storage of known BGCs. Here, we present MIBiG 2.0, which encompasses major updates to the schema, the data, and the online repository itself. Over the past five years, 851 new BGCs have been added. Additionally, we performed extensive manual data curation of all entries to improve the annotation quality of our repository. We also redesigned the data schema to ensure the compliance of future annotations. Finally, we improved the user experience by adding new features such as query searches and a statistics page, and enabled direct link-outs to chemical structure databases. The repository is accessible online at https://mibig.secondarymetabolites.org/.

A procedure for removal of cyanuric acid in swimming pools using a cell-free thermostable cyanuric acid hydrolase.

Cyanuric acid (CYA) is used commercially for maintaining active chlorine to inactivate microbial and viral pathogens in swimming pools and hot tubs. Repeated CYA addition can cause a lack of available chlorine and adequate disinfection. Acceptable CYA levels can potentially be restored via cyanuric acid hydrolases (CAH), enzymes that hydrolyze CYA to biuret under mild conditions. Here we describe a previously unknown CAH enzyme from Pseudolabrys sp. Root1462 (CAH-PR), mined from public databases by bioinformatic analysis of potential CAH genes, which we show to be suitable in a cell-free form for industrial applications based upon favorable enzymatic and physical properties, combined with high-yield expression in aerobic cell culture. The kinetic parameters and modeled structure were similar to known CAH enzymes, but the new enzyme displayed a surprising thermal and storage stability. The new CAH enzyme was applied, following addition of inexpensive sodium sulfite, to hydrolyze CYA to biuret. At the desired endpoint, hypochlorite addition inactivated remaining enzyme and oxidized biuret to primarily dinitrogen and carbon dioxide gases. The mechanism of biuret oxidation with hypochlorite under conditions relevant to recreational pools is described.

Widespread soil bacterium that oxidizes atmospheric methane.

The global atmospheric level of methane (CH4), the second most important greenhouse gas, is currently increasing by ∼10 million tons per year. Microbial oxidation in unsaturated soils is the only known biological process that removes CH4 from the atmosphere, but so far, bacteria that can grow on atmospheric CH4 have eluded all cultivation efforts. In this study, we have isolated a pure culture of a bacterium, strain MG08 that grows on air at atmospheric concentrations of CH4 [1.86 parts per million volume (p.p.m.v.)]. This organism, named Methylocapsa gorgona, is globally distributed in soils and closely related to uncultured members of the upland soil cluster α. CH4 oxidation experiments and 13C-single cell isotope analyses demonstrated that it oxidizes atmospheric CH4 aerobically and assimilates carbon from both CH4 and CO2 Its estimated specific affinity for CH4 (a0s) is the highest for any cultivated methanotroph. However, growth on ambient air was also confirmed for Methylocapsa acidiphila and Methylocapsa aurea, close relatives with a lower specific affinity for CH4, suggesting that the ability to utilize atmospheric CH4 for growth is more widespread than previously believed. The closed genome of M. gorgona MG08 encodes a single particulate methane monooxygenase, the serine cycle for assimilation of carbon from CH4 and CO2, and CO2 fixation via the recently postulated reductive glycine pathway. It also fixes dinitrogen and expresses the genes for a high-affinity hydrogenase and carbon monoxide dehydrogenase, suggesting that atmospheric CH4 oxidizers harvest additional energy from oxidation of the atmospheric trace gases carbon monoxide (0.2 p.p.m.v.) and hydrogen (0.5 p.p.m.v.).

Global analysis of adenylate-forming enzymes reveals ß-lactone biosynthesis pathway in pathogenic Nocardia.

Enzymes that cleave ATP to activate carboxylic acids play essential roles in primary and secondary metabolism in all domains of life. Class I adenylate-forming enzymes share a conserved structural fold but act on a wide range of substrates to catalyze reactions involved in bioluminescence, nonribosomal peptide biosynthesis, fatty acid activation, and ß-lactone formation. Despite their metabolic importance, the substrates and functions of the vast majority of adenylate-forming enzymes are unknown without tools available to accurately predict them. Given the crucial roles of adenylate-forming enzymes in biosynthesis, this also severely limits our ability to predict natural product structures from biosynthetic gene clusters. Here we used machine learning to predict adenylate-forming enzyme function and substrate specificity from protein sequences. We built a web-based predictive tool and used it to comprehensively map the biochemical diversity of adenylate-forming enzymes across >50,000 candidate biosynthetic gene clusters in bacterial, fungal, and plant genomes. Ancestral phylogenetic reconstruction and sequence similarity networking of enzymes from these clusters suggested divergent evolution of the adenylate-forming superfamily from a core enzyme scaffold most related to contemporary CoA ligases toward more specialized functions including ß-lactone synthetases. Our classifier predicted ß-lactone synthetases in uncharacterized biosynthetic gene clusters conserved in >90 different strains of Nocardia. To test our prediction, we purified a candidate ß-lactone synthetase from Nocardia brasiliensis and reconstituted the biosynthetic pathway in vitro to link the gene cluster to the ß-lactone natural product, nocardiolactone. We anticipate that our machine learning approach will aid in functional classification of enzymes and advance natural product discovery.

A roadmap for metagenomic enzyme discovery.

Covering: up to 2021Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.

Analysis and modeling of Blastomyces dermatitidis environmental prevalence in Minnesota using soil collected to compare basal and outbreak levels.

Outbreaks of blastomycosis, caused by the fungus Blastomyces dermatitidis, occur in endemic areas of the United States and Canada but the geographic range of blastomycosis is expanding. Previous studies inferred the location of B. dermatitidis through epidemiologic data associated with outbreaks because culture of B. dermatitidis from the environment is often unsuccessful. In this study, we used a culture-independent, PCR-based method to identify B. dermatitidis DNA in environmental samples using the BAD1 promoter region. We tested 250 environmental samples collected in Minnesota, either associated with blastomycosis outbreaks or environmental samples collected from high- and low-endemic regions to determine basal prevalence of B. dermatitidis in the environment. We identified a fifth BAD1 promoter haplotype of B. dermatitidis prevalent in Minnesota. Ecological niche analysis identified latitude, longitude, elevation, and site classification as environmental parameters associated with the presence of B. dermatitidis Using this analysis, a Random Forest model predicted B. dermatitidis presence in basal environmental samples with 75% accuracy. These data support use of culture-independent, PCR-based environmental sampling to track spread into new regions and to characterize the unknown B. dermatitidis environmental niche.Importance Upon inhalation of spores from the fungus Blastomyces dermatitidis from the environment, humans and animals can develop the disease blastomycosis. Based on disease epidemiology, B. dermatitidis is known to be endemic in the United States and Canada around the Great Lakes and in the Ohio and Mississippi River Valleys but is starting to emerge in other areas. B. dermatitidis is extremely difficult to culture from the environment so little is known about the environmental reservoirs for this pathogen. We used a culture-independent PCR-based assay to identify the presence of B. dermatitidis DNA in soil samples from Minnesota. By combining molecular data with ecological niche modeling, we were able to predict the presence of B. dermatitidis in environmental samples with 75% accuracy and to define characteristics of the B. dermatitidis environmental niche. Importantly, we showed the effectiveness of using a PCR-based assay to identify B. dermatitidis in environmental samples.

The ever-expanding limits of enzyme catalysis and biodegradation: polyaromatic, polychlorinated, polyfluorinated, and polymeric compounds.

Biodegradation is simply the metabolism of anthropogenic, or otherwise unwanted, chemicals in our environment, typically by microorganisms. The metabolism of compounds commonly found in living things is limited to several thousand metabolites whereas ∼100 million chemical substances have been devised by chemical synthesis, and ∼100 000 are used commercially. Since most of those compounds are not natively found in living things, and some are toxic or carcinogenic, the question arises as to whether there is some organism somewhere with the enzymes that can biodegrade them. Repeatedly, anthropogenic chemicals have been denoted 'non-biodegradable,' only to find they are reactive with one or more enzyme(s). Enzyme reactivity has been organized into categories of functional group transformations. The discovery of new functional group transformations has continually expanded our knowledge of enzymes and biodegradation. This expansion of new-chemical biodegradation is driven by the evolution and spread of newly evolved enzymes. This review describes the biodegradation of widespread commercial chemicals with a focus on four classes: polyaromatic, polychlorinated, polyfluorinated, and polymeric compounds. Polyaromatic hydrocarbons include some of the most carcinogenic compounds known. Polychlorinated compounds include polychlorinated biphenyls (PCBs) and many pesticides of the twentieth century. Polyfluorinated compounds are a major focus of bioremediation efforts today. Polymers are clogging landfills, killing aquatic species in the oceans and increasingly found in our bodies. All of these classes of compounds, each thought at one time to be non-biodegradable, have been shown to react with natural enzymes. The known limits of enzyme catalysis, and hence biodegradation, are continuing to expand.

Cyanuric Acid Biodegradation via Biuret: Physiology, Taxonomy, and Geospatial Distribution.

Cyanuric acid is an industrial chemical produced during the biodegradation of s-triazine pesticides. The biodegradation of cyanuric acid has been elucidated using a single model system, Pseudomonas sp. strain ADP, in which cyanuric acid hydrolase (AtzD) opens the s-triazine ring and AtzEG deaminates the ring-opened product. A significant question remains as to whether the metabolic pathway found in Pseudomonas sp. ADP is the exception or the rule in bacterial genomes globally. Here, we show that most bacteria utilize a different pathway, metabolizing cyanuric acid via biuret. The new pathway was determined by reconstituting the pathway in vitro with purified enzymes and by mining more than 250,000 genomes and metagenomes. We isolated soil bacteria that grow on cyanuric acid as a sole nitrogen source and showed that the genome from a Herbaspirillum strain had a canonical cyanuric acid hydrolase gene but different flanking genes. The flanking gene trtB encoded an enzyme that we show catalyzed the decarboxylation of the cyanuric acid hydrolase product, carboxybiuret. The reaction generated biuret, a pathway intermediate further transformed by biuret hydrolase (BiuH). The prevalence of the newly defined pathway was determined by cooccurrence analysis of cyanuric acid hydrolase genes and flanking genes. Here, we show the biuret pathway was more than 1 order of magnitude more prevalent than the original Pseudomonas sp. ADP pathway. Mining a database of over 40,000 bacterial isolates with precise geospatial metadata showed that bacteria with concurrent cyanuric acid and biuret hydrolase genes were distributed throughout the United States.IMPORTANCE Cyanuric acid is produced naturally as a contaminant in urea fertilizer, and it is used as a chlorine stabilizer in swimming pools. Cyanuric acid-degrading bacteria are used commercially in removing cyanuric acid from pool water when it exceeds desired levels. The total volume of cyanuric acid produced annually exceeds 200 million kilograms, most of which enters the natural environment. In this context, it is important to have a global understanding of cyanuric acid biodegradation by microbial communities in natural and engineered systems. Current knowledge of cyanuric acid metabolism largely derives from studies on the enzymes from a single model organism, Pseudomonas sp. ADP. In this study, we obtained and studied new microbes and discovered a previously unknown cyanuric acid degradation pathway. The new pathway identified here was found to be much more prevalent than the pathway previously established for Pseudomonas sp. ADP. In addition, the types of environment, taxonomic prevalences, and geospatial distributions of the different cyanuric acid degradation pathways are described here.

Biosynthesis and chemical diversity of ß-lactone natural products.

Covering: up to 2018 ß-Lactones are strained rings that are useful organic synthons and pharmaceutical warheads. Over 30 core scaffolds of ß-lactone natural products have been described to date, many with potent bioactivity against bacteria, fungi, or human cancer cell lines. ß-Lactone natural products are chemically diverse and have high clinical potential, but production of derivatized drug leads has been largely restricted to chemical synthesis partly due to gaps in biochemical knowledge about ß-lactone biosynthesis. Here we review recent discoveries in enzymatic ß-lactone ring closure via ATP-dependent synthetases, intramolecular cyclization from seven-membered rings, and thioesterase-mediated cyclization during release from nonribosomal peptide synthetase assembly lines. We also comprehensively cover the diversity and taxonomy of source organisms for ß-lactone natural products including their isolation from bacteria, fungi, plants, insects, and marine sponges. This work identifies computational and experimental bottlenecks and highlights future directions for genome-based discovery of biosynthetic gene clusters that may produce novel compounds with ß-lactone rings.

Mechanism of a Standalone ß-Lactone Synthetase: New Continuous Assay for a Widespread ANL Superfamily Enzyme.

Enzyme-catalyzed ß-lactone formation from ß-hydroxy acids is a crucial step in bacterial biosynthesis of ß-lactone natural products and membrane hydrocarbons. We developed a novel, continuous assay for ß-lactone synthetase activity using synthetic ß-hydroxy acid substrates with alkene or alkyne moieties. ß-Lactone formation is followed by rapid decarboxylation to form a conjugated triene chromophore for real-time evaluation by UV/Vis spectroscopy. The assay was used to determine steady-state kinetics of a long-chain ß-lactone synthetase, OleC, from the plant pathogen Xanthomonas campestris. Site-directed mutagenesis was used to test the involvement of conserved active site residues in Mg2+ and ATP binding. A previous report suggested OleC adenylated the substrate hydroxy group. Here we present several lines of evidence, including hydroxylamine trapping of the AMP intermediate, to demonstrate the substrate carboxyl group is adenylated prior to making the ß-lactone final product. A panel of nine substrate analogues were used to investigate the substrate specificity of X. campestris OleC by HPLC and GC-MS. Stereoisomers of 2-hexyl-3hydroxyoctanoic acid were synthesized and OleC preferred the (2R,3S) diastereomer consistent with the stereo-preference of upstream and downstream pathway enzymes. This biochemical knowledge was used to guide phylogenetic analysis of the ß-lactone synthetases to map their functional diversity within the acyl-CoA synthetase, NRPS adenylation domain, and luciferase superfamily.

Microbial biodegradation of biuret: defining biuret hydrolases within the isochorismatase superfamily.

Biuret is a minor component of urea fertilizer and an intermediate in s-triazine herbicide biodegradation. The microbial metabolism of biuret has never been comprehensively studied. Here, we enriched and isolated bacteria from a potato field that grew on biuret as a sole nitrogen source. We sequenced the genome of the fastest-growing isolate, Herbaspirillum sp. BH-1 and identified genes encoding putative biuret hydrolases (BHs). We purified and characterized a functional BH enzyme from Herbaspirillum sp. BH-1 and two other bacteria from divergent phyla. The BH enzymes reacted exclusively with biuret in the range of 2-11 µmol min-1 mg-1 protein. We then constructed a global protein superfamily network to map structure-function relationships in the BH subfamily and used this to mine > 7000 genomes. High-confidence BH sequences were detected in Actinobacteria, Alpha- and Beta-proteobacteria, and some fungi, archaea and green algae, but not animals or land plants. Unexpectedly, no cyanuric acid hydrolase homologs were detected in > 90% of genomes with BH homologs, suggesting BHs may have arisen independently of s-triazine ring metabolism. This work links genotype to phenotype by enabling accurate genome-mining to predict microbial utilization of biuret. Importantly, it advances understanding of the microbial capacity for biuret biodegradation in agricultural systems.

Gene transcription ontogeny of hypothalamic-pituitary-thyroid axis development in early-life stage fathead minnow and zebrafish.

The hypothalamic-pituitary-thyroid (HPT) axis is known to play a crucial role in the development of teleost fish. However, knowledge of endogenous transcription profiles of thyroid-related genes in developing teleosts remains fragmented. We selected two model teleost species, the fathead minnow (Pimephales promelas) and the zebrafish (Danio rerio), to compare the gene transcription ontogeny of the HPT axis. Control organisms were sampled at several time points during embryonic and larval development until 33 days post-fertilization. Total RNA was extracted from pooled, whole fish, and thyroid-related mRNA expression was evaluated using quantitative polymerase chain reaction. Gene transcripts examined included: thyrotropin-releasing hormone receptor (trhr), thyroid-stimulating hormone receptor (tshr), sodium-iodide symporter (nis), thyroid peroxidase (tpo), thyroglobulin (tg), transthyretin (ttr), deiodinases 1, 2, 3a, and 3b (dio1, dio2, dio3a and 3b), and thyroid hormone receptors alpha and beta (thrα and ß). A loess regression method was successful in identifying maxima and minima of transcriptional expression during early development of both species. Overall, we observed great similarities between the species, including maternal transfer, at least to some extent, of almost all transcripts (confirmed in unfertilized eggs), increasing expression of most transcripts during hatching and embryo-larval transition, and indications of a fully functional HPT axis in larvae. These data will aid in the development of hypotheses on the role of certain genes and pathways during development. Furthermore, this provides a background reference dataset for designing and interpreting targeted transcriptional expression studies both for fundamental research and for applications such as toxicology.

OleB from Bacterial Hydrocarbon Biosynthesis Is a ß-Lactone Decarboxylase That Shares Key Features with Haloalkane Dehalogenases.

OleB is an α/ß-hydrolase found in bacteria that biosynthesize long-chain olefinic hydrocarbons, but its function has remained obscure. We report that OleB from the Gram-negative bacterium Xanthomonas campestris performs an unprecedented ß-lactone decarboxylation reaction, to complete cis-olefin biosynthesis. OleB reactions monitored by 1H nuclear magnetic resonance spectroscopy revealed a selectivity for decarboxylating cis-ß-lactones and no discernible activity with trans-ß-lactones, consistent with the known configuration of pathway intermediates. Protein sequence analyses showed OleB proteins were most related to haloalkane dehalogenases (HLDs) and retained the canonical Asp-His-Asp catalytic triad of HLDs. Unexpectedly, it was determined that an understudied subfamily, denoted as HLD-III, is comprised mostly of OleB proteins encoded within oleABCD gene clusters, suggesting a misannotation. OleB from X. campestris showed very low dehalogenase activity only against haloalkane substrates with long alkyl chains. A haloalkane substrate mimic alkylated wild-type X. campestris OleB but not OleBD114A, implicating this residue as the active site nucleophile as in HLDs. A sequence-divergent OleB, found as part of a natural OleBC fusion and classified as an HLD-III, from the Gram-positive bacterium Micrococcus luteus was demonstrated to have the same activity, stereochemical preference, and dependence on the proposed Asp nucleophile. H218O studies with M. luteus OleBC suggested that the canonical alkyl-enzyme intermediate of HLDs is hydrolyzed differently by OleB enzymes, as 18O is not incorporated into the nucleophilic aspartic acid. This work defines a previously unrecognized reaction in nature, functionally identifies some HLD-III enzymes as ß-lactone decarboxylases, and posits an enzymatic mechanism of ß-lactone decarboxylation.

Substrate promiscuity of xenobiotic-transforming hydrolases from stream biofilms impacted by treated wastewater.

Organic contaminants enter aquatic ecosystems from various sources, including wastewater treatment plant effluent. Freshwater biofilms play a major role in the removal of organic contaminants from receiving water bodies, but knowledge of the molecular mechanisms driving contaminant biotransformations in complex stream biofilm (periphyton) communities remains limited. Previously, we demonstrated that biofilms in experimental flume systems grown at higher ratios of treated wastewater (WW) to stream water displayed an increased biotransformation potential for a number of organic contaminants. We identified a positive correlation between WW percentage and biofilm biotransformation rates for the widely-used insect repellent, N,N-diethyl-meta-toluamide (DEET) and a number of other wastewater-borne contaminants with hydrolyzable moieties. Here, we conducted deep shotgun sequencing of flume biofilms and identified a positive correlation between WW percentage and metagenomic read abundances of DEET hydrolase (DH) homologs. To test the causality of this association, we constructed a targeted metagenomic library of DH homologs from flume biofilms. We screened our complete metagenomic library for activity with four different substrates, including DEET, and a subset thereof with 183 WW-related organic compounds. The majority of active hydrolases in the metagenomic library preferred aliphatic and aromatic ester substrates while, remarkably, only a single reference enzyme was capable of DEET hydrolysis. Of the 626 total enzyme-substrate combinations tested, approximately 5% were active enzyme-substrate pairs. Metagenomic DH family homologs revealed a broad substrate promiscuity spanning 22 different compounds when summed across all enzymes tested. We biochemically characterized the most promiscuous and active enzymes identified based on metagenomic analysis from uncultivated Rhodospirillaceae and Planctomycetaceae. In addition to characterizing new DH family enzymes, we exemplified a framework for linking metagenome-guided hypothesis generation with experimental validation. Overall, this study expands the scope of known enzymatic contaminant biotransformations for metagenomic hydrolases from WW-receiving stream biofilm communities.

Structure-guided metagenome mining to tap microbial functional diversity.

Scientists now have access to millions of accurate three-dimensional (3D) models of protein structures. How do we leverage 3D structural models to learn about microbial functions encoded in metagenomes? Here, we review recent developments using protein structural features to mine metagenomes from diverse environments ranging from the human gut to soil and ocean viromes. We compare 3D protein structural methods to characterize antibiotic resistance phenotypes, nutrient cycling, and host-drug-microbe interactions. Broadly, we encourage the scientific community to look beyond global sequence and structure alignments by considering fine-grained descriptors such as distance to ligand, active site, and tertiary interactions between amino acid residues scaling to microbiomes. Finally, we highlight structure-inspired approaches to chart new areas of microbial protein-coding sequence space.

Artificial intelligence for microbial biotechnology: beyond the hype.

It has been a landmark year for artificial intelligence (AI) and biotechnology. Perhaps the most noteworthy of these advances was Google DeepMind's AlphaFold2 algorithm which smashed records in protein structure prediction (Jumper et al., 2021, Nature, 596, 583) complemented by progress made by other research groups around the globe (Baek et al., 2021, Science, 373, 871; Zheng et al., 2021, Proteins). For the first time in history, AI achieved protein structure models rivalling the accuracy of experimentally determined structures. The power of accurate protein structure prediction at our fingertips has countless implications for drug discovery, de novo protein design and fundamental research in chemical biology. While acknowledging the significance of these breakthroughs, this perspective aims to cut through the hype and examine some key limitations using AlphaFold2 as a lens to consider the broader implications of AI for microbial biotechnology for the next 15 years and beyond.