Discovery of new enzymes and metabolic pathways by using structure and genome context

Genome Mining for New Enzyme Chemistry

A revolution in the field of biocatalysis has enabled scalable access to compounds of high societal values using enzymes. The construction of biocatalytic routes relies on the reservoir of available enzymatic transformations. A review of uncharacterized proteins predicted from genomic sequencing projects shows that a treasure trove of enzyme chemistry awaits to be uncovered. This Review highlights enzymatic transformations discovered through various genome mining methods and showcases their potential future applications in biocatalysis.

AnnoView enables large-scale analysis, comparison, and visualization of microbial gene neighborhoods

The analysis and comparison of gene neighborhoods is a powerful approach for exploring microbial genome structure, function, and evolution. Although numerous tools exist for genome visualization and comparison, genome exploration across large genomic databases or user-generated datasets remains a challenge. Here, we introduce AnnoView, a web server designed for interactive exploration of gene neighborhoods across the bacterial and archaeal tree of life. Our server offers users the ability to identify, compare, and visualize gene neighborhoods of interest from 30 238 bacterial genomes and 1672 archaeal genomes, through integration with the comprehensive Genome Taxonomy Database and AnnoTree databases. Identified gene neighborhoods can be visualized using pre-computed functional annotations from different sources such as KEGG, Pfam and TIGRFAM, or clustered based on similarity. Alternatively, users can upload and explore their own custom genomic datasets in GBK, GFF or CSV format, or use AnnoView as a genome browser for relatively small genomes (e.g. viruses and plasmids). Ultimately, we anticipate that AnnoView will catalyze biological discovery by enabling user-friendly search, comparison, and visualization of genomic data. AnnoView is available at http://annoview.uwaterloo.ca.

The Complex GH32 Enzyme Orchestra from Priestia megaterium Holds the Key to Better Discriminate Sucrose-6-phosphate Hydrolases from Other β-Fructofuranosidases in Bacteria

Inulin is widely used as a prebiotic and emerging as a priming compound to counteract plant diseases. We isolated inulin-degrading strains from the lettuce phyllosphere, identified as Bacillus subtilis and Priestia megaterium, species hosting well-known biocontrol organisms. To better understand their varying inulin degradation strategies, three intracellular β-fructofuranosidases from P. megaterium NBRC15308 were characterized after expression in Escherichia coli: a predicted sucrose-6-phosphate (Suc6P) hydrolase (SacAP1, supported by molecular docking), an exofructanase (SacAP2), and an invertase (SacAP3). Based on protein multiple sequence and structure alignments of bacterial glycoside hydrolase family 32 enzymes, we identified conserved residues predicted to be involved in binding phosphorylated (Suc6P hydrolases) or nonphosphorylated substrates (invertases and fructanases). Suc6P hydrolases feature positively charged residues near the structural catalytic pocket (histidine, arginine, or lysine), whereas other β-fructofuranosidases contain tryptophans. This correlates with our phylogenetic tree, grouping all predicted Suc6P hydrolases in a clan associated with genomic regions coding for transporters involved in substrate phosphorylation. These results will help to discriminate between Suc6P hydrolases and other β-fructofuranosidases in future studies and to better understand the interaction of B. subtilis and P. megaterium endophytes with sucrose and/or fructans, sugars naturally present in plants or exogenously applied in the context of defense priming.

Discovery of a non-canonical prototype long-chain monoacylglycerol lipase through a structure-based endogenous reaction intermediate complex

The identification and characterization of enzyme function is largely lacking behind the rapidly increasing availability of large numbers of sequences and associated high-resolution structures. This is often hampered by lack of knowledge on in vivo relevant substrates. Here, we present a case study of a high-resolution structure of an unusual orphan lipase in complex with an endogenous C18 monoacylglycerol ester reaction intermediate from the expression host, which is insoluble under aqueous conditions and thus not accessible for studies in solution. The data allowed its functional characterization as a prototypic long-chain monoacylglycerol lipase, which uses a minimal lid domain to position the substrate through a hydrophobic tunnel directly to the enzyme's active site. Knowledge about the molecular details of the substrate binding site allowed us to modulate the enzymatic activity by adjusting protein/substrate interactions, demonstrating the potential of our findings for future biotechnology applications.

A cellular platform for production of C4 monomers

Living organisms carry out a wide range of remarkable functions, including the synthesis of thousands of simple and complex chemical structures for cellular growth and maintenance. The manipulation of this reaction network has allowed for the genetic engineering of cells for targeted chemical synthesis, but it remains challenging to alter the program underlying their fundamental chemical behavior. By taking advantage of the unique ability of living systems to use evolution to find solutions to complex problems, we have achieved yields of up to ∼95% for three C4 commodity chemicals, n-butanol, 1,3-butanediol, and 4-hydroxy-2-butanone. Genomic sequencing of the evolved strains identified pcnB and rpoBC as two gene loci that are able to alter carbon flow by remodeling the transcriptional landscape of the cell, highlighting the potential of synthetic pathways as a tool to identify metabolic control points.

AI-driven pan-proteome analyses reveal insights into the biohydrometallurgical properties of Acidithiobacillia

Microorganism-mediated biohydrometallurgy, a sustainable approach for metal recovery from ores, relies on the metabolic activity of acidophilic bacteria. Acidithiobacillia with sulfur/iron-oxidizing capacities are extensively studied and applied in biohydrometallurgy-related processes. However, only 14 distinct proteins from Acidithiobacillia have experimentally determined structures currently available. This significantly hampers in-depth investigations of Acidithiobacillia's structure-based biological mechanisms pertaining to its relevant biohydrometallurgical processes. To address this issue, we employed a state-of-the-art artificial intelligence (AI)-driven approach, with a median model confidence of 0.80, to perform high-quality full-chain structure predictions on the pan-proteome (10,458 proteins) of the type strain Acidithiobacillia. Additionally, we conducted various case studies on de novo protein structural prediction, including sulfate transporter and iron oxidase, to demonstrate how accurate structure predictions and gene co-occurrence networks can contribute to the development of mechanistic insights and hypotheses regarding sulfur and iron utilization proteins. Furthermore, for the unannotated proteins that constitute 35.8% of the Acidithiobacillia proteome, we employed the deep-learning algorithm DeepFRI to make structure-based functional predictions. As a result, we successfully obtained gene ontology (GO) terms for 93.6% of these previously unknown proteins. This study has a significant impact on improving protein structure and function predictions, as well as developing state-of-the-art techniques for high-throughput analysis of large proteomic data.

Identification of Cytochrome P450 2E1 as a Novel Target in Glioma and Development of Its Inhibitor as an Anti-Tumor Agent

Glioblastoma (GBM) is a devastating inflammation-related cancer for which novel therapeutic targets are urgently required. Previous studies of the authors indicate Cytochrome P450 2E1 (CYP2E1) as a novel inflammatory target and develop a specific inhibitor Q11. Here it is demonstrated that CYP2E1 overexpression is closely related to higher malignancy in GBM patients. CYP2E1 activity is positively correlated with tumor weight in GBM rats. Significantly higher CYP2E1 expression accompanied by increased inflammation is detected in a mouse GBM model. Q11, 1-(4-methyl-5-thialzolyl) ethenone, a newly developed specific inhibitor of CYP2E1 here remarkably attenuates tumor growth and prolongs survival in vivo. Q11 does not directly affect tumor cells but blocks the tumor-promoting effect of microglia/macrophage (M/Mφ) in the tumor microenvironment through PPARγ-mediated activation of the STAT-1 and NF-κB pathways and inhibition of the STAT-3 and STAT-6 pathways. The effectiveness and safety of targeting CYP2E1 in GBM are further supported by studies with Cyp2e1 knockout rodents. In conclusion, a pro-GBM mechanism in which CYP2E1-PPARγ-STAT-1/NF-κB/STAT-3/STAT-6 axis fueled tumorigenesis by reprogramming M/Mφ and Q11 as a promising anti-inflammatory agent for GBM treatment is uncovered.

Decipher enzymes from human microbiota for drug discovery and development

The human microbiota plays an important role in human health and contributes to the metabolism of therapeutic drugs affecting their potency. However, the current knowledge on human gut bacterial metabolism is limited and lacks an understanding of the underlying mechanisms of observed drug biotransformations. Despite the complexity of the gut microbial community, genomic and metagenomic sequencing provides insights into the diversity of chemical reactions that can be carried out by the microbiota and poses new challenges to functionally annotate thousands of bacterial enzymes. Here, we outline methods to systematically address the structural and functional space of the human microbiome, highlighting a combination of in silico and in vitro approaches. Systematic knowledge about microbial enzymes could eventually be applied for personalized therapy, the development of prodrugs and modulators of unwanted bacterial activity, and the further discovery of new antibiotics.

Discovery and Enzymatic Screening of Genome-Mined Microbial Levanases to Produce Second-Generation β-(2,6)-Fructooligosaccharides: Catalytic Properties

Evidence suggests that β-(2,6)-levan-type fructooligosaccharides (FOSs) possess higher prebiotic potential and selectivity than their β-(2,1)-inulin-type counterparts. The focus of the present work was to develop an enzymatic approach for the synthesis of levan-type FOSs, employing levanases (EC 3.2.1.65), specifically those performing endo-hydrolysis on levans. To identify new levanases, a selection of candidates was obtained via in silico exploration of the levanase family biodiversity through a sequence-driven approach. A collection of 113 candidates was screened according to their specific activities on low- and high-molecular-weight (MW) levan as well as thermal stability. The most active levanases were able to hydrolyze both types of levan with similar efficiency. This ultimately revealed 10 active, highly evolutionary distant and diverse candidate levanases, which demonstrated preferential hydrolysis of levan over inulin. The end-product profile differed significantly depending on levanase with levanbiose, levantriose, and levantetraose being the major FOSs. Among them, the catalytic properties of 5 selected potential new levanases (LEV9 from Belliella Baltica, LEV36 from Dyadobacter fermentans, LEV37 from Capnocytophaga ochracea, LEV79 from Vibrio natriegens, LEV91 from Paenarthrobacter aurescens) were characterized, especially in terms of pH and temperature profiles, thermal stability, and kinetic parameters. The identification of these novel levanases is expected to contribute to the production of levan-type FOSs with properties surpassing those of commercial preparations.

Stable isotope-assisted metabolite profiling reveals new insights into L-tryptophan chemotrophic metabolism of Rubrivivax benzoatilyticus

Anoxygenic photosynthetic bacteria (APB) are metabolically versatile, capable of surviving with an extended range of carbon and nitrogen sources. This group of phototrophic bacteria have remarkable metabolic plasticity in utilizing an array of organic compounds as carbon source/electron donors and nitrogen sources with sophisticated growth modes. Rubrivivax benzoatilyticus JA2 is one such photosynthetic bacterium utilizes L-tryptophan as nitrogen source under phototrophic growth mode and produces an array of indolic compounds of biotechnological significance. However, chemotrophic L-tryptophan metabolism is largely unexplored and studying L-tryptophan metabolism under chemotrophic mode would provide new insights into metabolic potential of strain JA2. In the present study, we employed stable-isotopes assisted metabolite profiling to unravel the L-tryptophan catabolism in Rubrivivax benzoatilyticus strain JA2 under chemotrophic (dark aerobic) conditions. Utilization of L-tryptophan as a nitrogen source for growth and simultaneous production of indole derivatives was observed in strain JA2. Liquid chromatography mass spectrometry (LC-MS) analysis of exo-metabolite profiling of carbon labeled L-tryptophan (¹³C₁₁) fed cultures of strain JA2 revealed at least seventy labeled metabolites. Of these, only fourteen metabolites were confirmed using standards, while sixteen were putative and forty metabolites remained unidentified. L-tryptophan chemotrophic catabolism revealed multiple catabolic pathways and distinct differential catabolism of L-tryptophan under chemotropic state as compared to photo-catabolism of L-tryptophan in strain JA2.

Expanding the viewpoint: Leveraging sequence information in enzymology

The use of protein sequence to inform enzymology in terms of structure, mechanism, and function has burgeoned over the past two decades. Referred to as genomic enzymology, the utilization of bioinformatic tools such as sequence similarity networks and phylogenetic analyses has allowed the identification of new substrates and metabolites, novel pathways, and unexpected reaction mechanisms. The holistic examination of superfamilies can yield insight into the origins and paths of evolution of enzymes and the range of their substrates and mechanisms. Herein, we highlight advances in the use of genomic enzymology to address problems which the in-depth analyses of a single enzyme alone could not enable.

Activity-based annotation: the emergence of systems biochemistry

Current tools to annotate protein function have failed to keep pace with the speed of DNA sequencing and exponentially growing number of proteins of unknown function (PUFs). A major contributing factor to this mismatch is the historical lack of high-throughput methods to experimentally determine biochemical activity. Activity-based methods, such as activity-based metabolite and protein profiling, are emerging as new approaches for unbiased, global, biochemical annotation of protein function. In this review, we highlight recent experimental, activity-based approaches that offer new opportunities to determine protein function in a biologically agnostic and systems-level manner.

Sequence Conservation Does Not Always Signify a Functional Imperative as Observed in the Nitroreductase Superfamily

Consensus sequences have the potential to help classify the structure and function of proteins and highlight key regions that may contribute to their biological properties. Often, the level of significance will track with the extent of sequence conservation, but this should not be considered universal. Arg and Lys dominate a position adjacent to the N1 and C2 carbonyl of flavin mononucleotide (FMN) bound in the proteins of the nitroreductase superfamily. Although this placement satisfies expectations for stabilizing the reduced form of FMN, the substitution of these residues in three subfamilies promoting distinct reactions demonstrates their importance to catalysis as only modest. Replacing Arg34 with Lys, Gln, or Glu enhances FMN binding to a flavin destructase (BluB) by twofold and diminishes FMN turnover by no more than 25%. Similarly, replacing Lys14 with Arg, Gln, or Glu in a nitroreductase (NfsB) does not perturb the binding of the substrate nitrofurazone. The catalytic efficiency does decrease by 21-fold for the K14Q variant, but no change in the midpoint potential of FMN was observed with any of the variants. Equivalent substitution at Arg38 in iodotyrosine deiodinase (IYD) affects catalysis even more modestly (<10-fold). While the Arg/Lys to Glu substitution inactivates NfsB and IYD, this change also stabilizes one-electron transfer in IYD contrary to predictions based on other classes of flavoproteins. Accordingly, functional correlations developed in certain structural superfamilies may not necessarily translate well to other superfamilies.

Second-Shell Amino Acid R266 Helps Determine N-Succinylamino Acid Racemase Reaction Specificity in Promiscuous N-Succinylamino Acid Racemase/o-Succinylbenzoate Synthase Enzymes

Catalytic promiscuity is the coincidental ability to catalyze nonbiological reactions in the same active site as the native biological reaction. Several lines of evidence show that catalytic promiscuity plays a role in the evolution of new enzyme functions. Thus, studying catalytic promiscuity can help identify structural features that predispose an enzyme to evolve new functions. This study identifies a potentially preadaptive residue in a promiscuous N-succinylamino acid racemase/o-succinylbenzoate synthase (NSAR/OSBS) enzyme from Amycolatopsis sp. T-1-60. This enzyme belongs to a branch of the OSBS family which includes many catalytically promiscuous NSAR/OSBS enzymes. R266 is conserved in all members of the NSAR/OSBS subfamily. However, the homologous position is usually hydrophobic in other OSBS subfamilies, whose enzymes lack NSAR activity. The second-shell amino acid R266 is close to the catalytic acid/base K263, but it does not contact the substrate, suggesting that R266 could affect the catalytic mechanism. Mutating R266 to glutamine in Amycolatopsis NSAR/OSBS profoundly reduces NSAR activity but moderately reduces OSBS activity. This is due to a 1000-fold decrease in the rate of proton exchange between the substrate and the general acid/base catalyst K263. This mutation is less deleterious for the OSBS reaction because K263 forms a cation-π interaction with the OSBS substrate and/or the intermediate, rather than acting as a general acid/base catalyst. Together, the data explain how R266 contributes to NSAR reaction specificity and was likely an essential preadaptation for the evolution of NSAR activity.

The minimal structure for iodotyrosine deiodinase function is defined by an outlier protein from the thermophilic bacterium Thermotoga neapolitana

The nitroreductase superfamily of enzymes encompasses many flavin mononucleotide (FMN)-dependent catalysts promoting a wide range of reactions. All share a common core consisting of an FMN-binding domain, and individual subgroups additionally contain one to three sequence extensions radiating from defined positions within this core to support their unique catalytic properties. To identify the minimum structure required for activity in the iodotyrosine deiodinase subgroup of this superfamily, attention was directed to a representative from the thermophilic organism Thermotoga neapolitana (TnIYD). This representative was selected based on its status as an outlier of the subgroup arising from its deficiency in certain standard motifs evident in all homologues from mesophiles. We found that TnIYD lacked a typical N-terminal sequence and one of its two characteristic sequence extensions, neither of which was found to be necessary for activity. We also show that TnIYD efficiently promotes dehalogenation of iodo-, bromo-, and chlorotyrosine, analogous to related deiodinases (IYDs) from humans and other mesophiles. In addition, 2-iodophenol is a weak substrate for TnIYD as it was for all other IYDs characterized to date. Consistent with enzymes from thermophilic organisms, we observed that TnIYD adopts a compact fold and low surface area compared with IYDs from mesophilic organisms. The insights gained from our investigations on TnIYD demonstrate the advantages of focusing on sequences that diverge from conventional standards to uncover the minimum essentials for activity. We conclude that TnIYD now represents a superior starting structure for future efforts to engineer a stable dehalogenase targeting halophenols of environmental concern.

The Birth of Genomic Enzymology: Discovery of the Mechanistically Diverse Enolase Superfamily

Enzymes are categorized into superfamilies by sequence, structural, and mechanistic similarities. The evolutionary implications can be profound. Until the mid-1990s, the approach was fragmented largely due to limited sequence and structural data. However, in 1996, Babbitt et al. published a paper in Biochemistry that demonstrated the potential power of mechanistically diverse superfamilies to identify common ancestry, predict function, and, in some cases, predict specificity. This Perspective describes the findings of the original work and reviews the current understanding of structure and mechanism in the founding family members. The outcomes of the genomic enzymology approach have reached far beyond the functional assignment of members of the enolase superfamily, inspiring the study of superfamilies and the adoption of sequence similarity networks and genome context and yielding fundamental insights into enzyme evolution.

Discovery and mining of enzymes from the human gut microbiome

Advances in technological and bioinformatics approaches have led to the generation of a plethora of human gut metagenomic datasets. Metabolomics has also provided substantial data regarding the small metabolites produced and modified by the microbiota. Comparatively, the microbial enzymes mediating the transformation of metabolites have not been intensively investigated. Here, we discuss the recent efforts and technologies used for discovering and mining enzymes from the human gut microbiota. The wealth of knowledge on metabolites, reactions, genome sequences, and structures of proteins, may drive the development of strategies for enzyme mining. Ongoing efforts to annotate gut microbiota enzymes will explain catalytic mechanisms that may guide the clinical applications of the gut microbiome for diagnostic and therapeutic purposes.

Methodological Advances to Study Contaminant Biotransformation: New Prospects for Understanding and Reducing Environmental Persistence?

Complex microbial communities in environmental systems play a key role in the detoxification of chemical contaminants by transforming them into less active metabolites or by complete mineralization. Biotransformation, i.e., transformation by microbes, is well understood for a number of priority pollutants, but a similar level of understanding is lacking for many emerging contaminants encountered at low concentrations and in complex mixtures across natural and engineered systems. Any advanced approaches aiming to reduce environmental exposure to such contaminants (e.g., novel engineered biological water treatment systems, design of readily degradable chemicals, or improved regulatory assessment strategies to determine contaminant persistence a priori) will depend on understanding the causal links among contaminant removal, the key driving agents of biotransformation at low concentrations (i.e., relevant microbes and their metabolic activities), and how their presence and activity depend on environmental conditions. In this Perspective, we present the current understanding and recent methodological advances that can help to identify such links, even in complex environmental microbiomes and for contaminants present at low concentrations in complex chemical mixtures. We discuss the ensuing insights into contaminant biotransformation across varying environments and conditions and ask how much closer we have come to designing improved approaches to reducing environmental exposure to contaminants.

Accelerating biological insight for understudied genes

The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The vast majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.

Comparative analysis of the chemical and biochemical synthesis of keto acids

Keto acids are essential organic acids that are widely applied in pharmaceuticals, cosmetics, food, beverages, and feed additives as well as chemical synthesis. Currently, most keto acids on the market are prepared via chemical synthesis. The biochemical synthesis of keto acids has been discovered with the development of metabolic engineering and applied toward the production of specific keto acids from renewable carbohydrates using different metabolic engineering strategies in microbes. In this review, we provide a systematic summary of the types and applications of keto acids, and then summarize and compare the chemical and biochemical synthesis routes used for the production of typical keto acids, including pyruvic acid, oxaloacetic acid, α-oxobutanoic acid, acetoacetic acid, ketoglutaric acid, levulinic acid, 5-aminolevulinic acid, α-ketoisovaleric acid, α-keto-γ-methylthiobutyric acid, α-ketoisocaproic acid, 2-keto-L-gulonic acid, 2-keto-D-gluconic acid, 5-keto-D-gluconic acid, and phenylpyruvic acid. We also describe the current challenges for the industrial-scale production of keto acids and further strategies used to accelerate the green production of keto acids via biochemical routes.

Influence of domestication on specialized metabolic pathways in fruit crops

During the process of plant domestication, the selection and traditional breeding for desired characters such as flavor, juiciness and nutritional value of fruits, probably have resulted in gain or loss of specialized metabolites contributing to these traits. Their appearance in fruits is likely due to the acquisition of novel and specialized metabolic pathways and their regulation, driven by systematic molecular evolutionary events facilitated by traditional breeding. Plants change their armory of specialized metabolism to adapt and survive in diverse ecosystems. This may occur through molecular evolutionary events, such as single nucleotide polymorphism, gene duplication and transposition, leading to convergent or divergent evolution of biosynthetic pathways producing such specialized metabolites. Breeding and selection for improved specific and desired traits (fruit size, color, taste, flavor, etc.) in fruit crops through conventional breeding approaches may further alter content and profile of specialized metabolites. Biosynthetic routes of these metabolites have been studied in various plants. Here, we explore the influence of plant domestication and breeding processes on the selection of biosynthetic pathways of favorable specialized metabolites in fruit crops. An orderly clustered arrangement of genes associated with their production is observed in many fruit crops. We further analyzed selection-based acquisition of specialized metabolic pathways comparing first the metabolic profiles and genes involved in their biosynthesis, followed by the genomic organization of such genes between wild and domesticated horticultural crops. Domestication of crop plants favored the acquisition and retention of metabolic pathways that enhanced the fruit value while eliminated those which produced toxic or unfavorable metabolites. Interestingly, unintentional reorganization of complex metabolic pathways by selection and traditional breeding processes has endowed us with flavorful, juicy and nutritionally rich fruits.

Engineering Plant Cytochrome P450s for Enhanced Synthesis of Natural Products: Past Achievements and Future Perspectives

Cytochrome P450s (P450s) are the most versatile catalysts and are widely used by plants to synthesize a vast array of structurally diverse specialized metabolites that not only play essential ecological roles but also constitute a valuable resource for the development of new drugs. To accelerate the metabolic engineering of these high-value metabolites, it is imperative to identify and characterize pathway P450s, and to further improve their activities through protein engineering. In this review, we focus on P450 engineering and summarize the major strategies for enhancing the stability and activity of P450s and successful cases of P450 engineering. Studies in which the functions of P450s were altered to create de novo metabolic pathways or novel compounds are discussed as well. We also overview emerging tools, specifically DNA synthesis, machine learning, and de novo protein design, as well as the evolutionary patterns of P450s unveiled from a massive number of DNA sequences that could be integrated to accelerate the engineering of these enzymes. These approaches would greatly aid in the exploitation of plant-specialized metabolites or derivatives for various uses including medical applications.

Computationally Guided Discovery and Experimental Validation of Indole-3-acetic Acid Synthesis Pathways

Elucidating the interaction networks associated with secondary metabolite production in microorganisms is an ongoing challenge made all the more daunting by the rate at which DNA sequencing technology reveals new genes and potential pathways. Developing the culturing methods, expression conditions, and genetic systems needed for validating pathways in newly discovered microorganisms is often not possible. Therefore, new tools and techniques are needed for defining complex metabolic pathways. Here, we describe an in vitro computationally assisted pathway description approach that employs bioinformatic searches of genome databases, protein structural modeling, and protein-ligand-docking simulations to predict the gene products most likely to be involved in a particular secondary metabolite production pathway. This information is then used to direct in vitro reconstructions of the pathway and subsequent confirmation of pathway activity using crude enzyme preparations. As a test system, we elucidated the pathway for biosynthesis of indole-3-acetic acid (IAA) in the plant-associated microbe Pantoea sp. YR343. This organism is capable of metabolizing tryptophan into the plant phytohormone IAA. BLAST analyses identified a likely three-step pathway involving an amino transferase, an indole pyruvate decarboxylase, and a dehydrogenase. However, multiple candidate enzymes were identified at each step, resulting in a large number of potential pathway reconstructions (32 different enzyme combinations). Our approach shows the effectiveness of crude extracts to rapidly elucidate enzymes leading to functional pathways. Results are compared to affinity purified enzymes for select combinations and found to yield similar relative activities. Further, in vitro testing of the pathway reconstructions revealed the "underground" nature of IAA metabolism in Pantoea sp. YR343 and the various mechanisms used to produce IAA. Importantly, our experiments illustrate the scalable integration of computational tools and cell-free enzymatic reactions to identify and validate metabolic pathways in a broadly applicable manner.

Systematic prediction of functionally linked genes in bacterial and archaeal genomes

Functionally linked genes in bacterial and archaeal genomes are often organized into operons. However, the composition and architecture of operons are highly variable and frequently differ even among closely related genomes. Therefore, to efficiently extract reliable functional predictions for uncharacterized genes from comparative analyses of the rapidly growing genomic databases, dedicated computational approaches are required. We developed a protocol to systematically and automatically identify genes that are likely to be functionally associated with a 'bait' gene or locus by using relevance metrics. Given a set of bait loci and a genomic database defined by the user, this protocol compares the genomic neighborhoods of the baits to identify genes that are likely to be functionally linked to the baits by calculating the abundance of a given gene within and outside the bait neighborhoods and the distance to the bait. We exemplify the performance of the protocol with three test cases, namely, genes linked to CRISPR-Cas systems using the 'CRISPRicity' metric, genes associated with archaeal proviruses and genes linked to Argonaute genes in halobacteria. The protocol can be run by users with basic computational skills. The computational cost depends on the sizes of the genomic dataset and the list of reference loci and can vary from one CPU-hour to hundreds of hours on a supercomputer.

MtpB, a member of the MttB superfamily from the human intestinal acetogen Eubacterium limosum, catalyzes proline betaine demethylation

The trimethylamine methyltransferase MttB is the founding member of a widely distributed superfamily of microbial proteins. Genes encoding most members of the MttB superfamily lack the codon for pyrrolysine that distinguishes previously characterized trimethylamine methyltransferases, leaving the function(s) of most of the enzymes in this superfamily unknown. Here, investigating the MttB family member MtpB from the human intestinal isolate Eubacterium limosum ATCC 8486, an acetogen that excretes N-methyl proline during growth on proline betaine, we demonstrate that MtpB catalyzes anoxic demethylation of proline betaine. MtpB along with MtqC (a corrinoid protein) and MtqA (a methylcorrinoid:tetrahydrofolate methyltransferase) was much more abundant in E. limosum cells grown on proline betaine than on lactate. We observed that recombinant MtpB methylates Co(I)-MtqC in the presence of proline betaine and that other quaternary amines are much less preferred substrates. MtpB, MtqC, and MtqA catalyze tetrahydrofolate methylation with proline betaine, thereby forming a key intermediate in the Wood-Ljungdahl acetogenesis pathway. To our knowledge, MtpB methylation of Co(I)-MtqC for the subsequent methylation of tetrahydrofolate represents the first described anoxic mechanism of proline betaine demethylation. The activities of MtpB and associated proteins in acetogens or other anaerobes provide a possible mechanism for the production of N-methyl proline by the gut microbiome. MtpB's activity characterized here strengthens the hypothesis that much of the MttB superfamily comprises quaternary amine-dependent methyltransferases.

Analysis of RNA Methylation by Phylogenetically Diverse Cfr Radical S-Adenosylmethionine Enzymes Reveals an Iron-Binding Accessory Domain in a Clostridial Enzyme

Cfr is a radical S-adenosylmethionine (SAM) RNA methylase linked to multidrug antibiotic resistance in bacterial pathogens. It catalyzes a chemically challenging C-C bond-forming reaction to methylate C8 of A2503 (Escherichia coli numbering) of 23S rRNA during ribosome assembly. The cfr gene has been identified as a mobile genetic element in diverse bacteria and in the genome of select Bacillales and Clostridiales species. Despite the importance of Cfr, few representatives have been purified and characterized in vitro. Here we show that Cfr homologues from Bacillus amyloliquefaciens, Enterococcus faecalis, Paenibacillus lautus, and Clostridioides difficile act as C8 adenine RNA methylases in biochemical assays. C. difficile Cfr contains an additional Cys-rich C-terminal domain that binds a mononuclear Fe²⁺ ion in a rubredoxin-type Cys₄ motif. The C-terminal domain can be truncated with minimal impact on C. difficile Cfr activity, but the rate of turnover is decreased upon disruption of the Fe²⁺-binding site by Zn²⁺ substitution or ligand mutation. These findings indicate an important purpose for the observed C-terminal iron in the native fusion protein. Bioinformatic analysis of the C. difficile Cfr Cys-rich domain shows that it is widespread (∼1400 homologues) as a stand-alone gene in pathogenic or commensal Bacilli and Clostridia, with >10% encoded adjacent to a predicted radical SAM RNA methylase. Although the domain is not essential for in vitro C. difficile Cfr activity, the genomic co-occurrence and high abundance in the human microbiome suggest a possible functional role for a specialized rubredoxin in certain radical SAM RNA methylases that are relevant to human health.

Structure-guided function discovery of an NRPS-like glycine betaine reductase for choline biosynthesis in fungi

Nonribosomal peptide synthetases (NRPSs) and NRPS-like enzymes have diverse functions in primary and secondary metabolisms. By using a structure-guided approach, we uncovered the function of a NRPS-like enzyme with unusual domain architecture, catalyzing two sequential two-electron reductions of glycine betaine to choline. Structural analysis based on the homology model suggests cation-π interactions as the major substrate specificity determinant, which was verified using substrate analogs and inhibitors. Bioinformatic analysis indicates this NRPS-like glycine betaine reductase is highly conserved and widespread in kingdom fungi. Genetic knockout experiments confirmed its role in choline biosynthesis and maintaining glycine betaine homeostasis in fungi. Our findings demonstrate that the oxidative choline-glycine betaine degradation pathway can operate in a fully reversible fashion and provide insight in understanding fungal choline metabolism. The use of an NRPS-like enzyme for reductive choline formation is energetically efficient compared with known pathways. Our discovery also underscores the capabilities of the structure-guided approach in assigning functions of uncharacterized multidomain proteins, which can potentially aid functional discovery of new enzymes by genome mining.

Exploring the sequence, function, and evolutionary space of protein superfamilies using sequence similarity networks and phylogenetic reconstructions

Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions by enabling the observation and investigation of complex sequence-structure-function and evolutionary relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) and phylogenetic reconstructions to map the functional divergence and evolutionary history of protein superfamilies. We exemplify this approach using the nitroreductase (NTR) flavoenzyme superfamily, demonstrating that SSN investigations can provide a rapid and effective means to classify groups of proteins, expose sequence similarity relationships across the global scale of a protein superfamily, and efficiently support detailed phylogenetic analyses. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes, their evolution, and their associated physiological roles.

Functional annotation of orthologs in metagenomes: a case study of genes for the transformation of oceanic dimethylsulfoniopropionate

Dimethylsulfoniopropionate (DMSP) is produced mainly by phytoplankton and bacteria. It is relatively abundant and ubiquitous in the marine environment, where bacterioplankton make use of it readily as both carbon and sulfur sources. In one transformation pathway, part of the molecule becomes dimethylsulfide (DMS), which escapes into the atmosphere and plays an important role in the sulfur exchange between oceans and atmosphere. Through its other dominant catabolic pathway, bacteria are able to use it as sulfur source. During the past few years, a number of genes involved in its transformation have been characterized. Identifying genes in taxonomic groups not amenable to conventional methods of cultivation is challenging. Indeed, functional annotation of genes in environmental studies is not straightforward, considering that particular taxa are not well represented in the available sequence databases. Furthermore, many genes belong to families of paralogs with similar sequences but perhaps different functions. In this study, we develop in silico approaches to infer protein function of an environmentally important gene (dmdA) that carries out the first step in the sulfur assimilation from DMSP. The method combines a set of tools to annotate a targeted gene in genome databases and metagenome assemblies. The method will be useful to identify genes that carry out key biochemical processes in the environment.

The GbsR Family of Transcriptional Regulators: Functional Characterization of the OpuAR Repressor

Accumulation of compatible solutes is a common stress response of microorganisms challenged by high osmolarity; it can be achieved either through synthesis or import. These processes have been intensively studied in Bacillus subtilis, where systems for the production of the compatible solutes proline and glycine betaine have been identified, and in which five transporters for osmostress protectants (Opu) have been characterized. Glycine betaine synthesis relies on the import of choline via the substrate-restricted OpuB system and the promiscuous OpuC transporter and its subsequent oxidation by the GbsAB enzymes. Transcription of the opuB and gbsAB operons is under control of the MarR-type regulator GbsR, which acts as an intracellular choline-responsive repressor. Modeling studies using the X-ray structure of the Mj223 protein from Methanocaldococcus jannaschii as the template suggest that GbsR is a homo-dimer with an N-terminal DNA-reading head and C-terminal dimerization domain; a flexible linker connects these two domains. In the vicinity of the linker region, an aromatic cage is predicted as the inducer-binding site, whose envisioned architecture resembles that present in choline and glycine betaine substrate-binding proteins of ABC transporters. We used bioinformatics to assess the phylogenomics of GbsR-type proteins and found that they are widely distributed among Bacteria and Archaea. Alignments of GbsR proteins and analysis of the genetic context of the corresponding structural genes allowed their assignment into four sub-groups. In one of these sub-groups of GbsR-type proteins, gbsR-type genes are associated either with OpuA-, OpuB-, or OpuC-type osmostress protectants uptake systems. We focus here on GbsR-type proteins, named OpuAR by us, that control the expression of opuA-type gene clusters. Using such a system from the marine bacterium Bacillus infantis, we show that OpuAR acts as a repressor of opuA transcription, where several compatible solutes (e.g., choline, glycine betaine, proline betaine) serve as its inducers. Site-directed mutagenesis studies allowed a rational improvement of the putative inducer-binding site in OpuAR with respect to the affinity of choline and glycine betaine binding. Collectively, our data characterize GbsR-/OpuAR-type proteins as an extended sub-group within the MarR-superfamily of transcriptional regulators and identify a novel type of substrate-inducible import system for osmostress protectants.

Gene Gangs of the Chloroviruses: Conserved Clusters of Collinear Monocistronic Genes

Chloroviruses (family Phycodnaviridae) are dsDNA viruses found throughout the world's inland waters. The open reading frames in the genomes of 41 sequenced chloroviruses (330 ± 40 kbp each) representing three virus types were analyzed for evidence of evolutionarily conserved local genomic "contexts", the organization of biological information into units of a scale larger than a gene. Despite a general loss of synteny between virus types, we informatically detected a highly conserved genomic context defined by groups of three or more genes that we have termed "gene gangs". Unlike previously described local genomic contexts, the definition of gene gangs requires only that member genes be consistently co-localized and are not constrained by strand, regulatory sites, or intervening sequences (and therefore represent a new type of conserved structural genomic element). An analysis of functional annotations and transcriptomic data suggests that some of the gene gangs may organize genes involved in specific biochemical processes, but that this organization does not involve their coordinated expression.

Advances in enzyme substrate analysis with capillary electrophoresis

Capillary electrophoresis provides a rapid, cost-effective platform for enzyme and substrate characterization. The high resolution achievable by capillary electrophoresis enables the analysis of substrates and products that are indistinguishable by spectroscopic techniques alone, while the small volume requirement enables analysis of enzymes or substrates in limited supply. Furthermore, the compatibility of capillary electrophoresis with various detectors makes it suitable for KM determinations ranging from nanomolar to millimolar concentrations. Capillary electrophoresis fundamentals are discussed with an emphasis on the separation mechanisms relevant to evaluate sets of substrate and product that are charged, neutral, and even chiral. The basic principles of Michaelis-Menten determinations are reviewed and the process of translating capillary electrophoresis electropherograms into a Michaelis-Menten curve is outlined. The conditions that must be optimized in order to couple off-line and on-line enzyme reactions with capillary electrophoresis separations, such as incubation time, buffer pH and ionic strength, and temperature, are examined to provide insight into how the techniques can be best utilized. The application of capillary electrophoresis to quantify enzyme inhibition, in the form of KI or IC50 is detailed. The concept and implementation of the immobilized enzyme reactor is described as a means to increase enzyme stability and reusability, as well as a powerful tool for screening enzyme substrates and inhibitors. Emerging techniques focused on applying capillary electrophoresis as a rapid assay to obtain structural identification or sequence information about a substrate and in-line digestions of peptides and proteins coupled to mass spectrometry analyses are highlighted.

Revealing Unexplored Sequence-Function Space Using Sequence Similarity Networks

The rapidly expanding number of protein sequences found in public databases can improve our understanding of how protein functions evolve. However, our current knowledge of protein function likely represents a small fraction of the diverse repertoire that exists in nature. Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions through the observation and investigation of the complex sequence-structure-function relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) to identify previously unexplored sequence and function space. We exemplify this approach using the nitroreductase (NTR) superfamily. We demonstrate that SSN investigations can provide a rapid and effective means to classify groups of proteins, therefore exposing experimentally unexplored sequences that may exhibit novel functionality. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes and their associated physiological roles.

Atlas of the Radical SAM Superfamily: Divergent Evolution of Function Using a "Plug and Play" Domain

The radical SAM superfamily contains over 100,000 homologous enzymes that catalyze a remarkably broad range of reactions required for life, including metabolism, nucleic acid modification, and biogenesis of cofactors. While the highly conserved SAM-binding motif responsible for formation of the key 5'-deoxyadenosyl radical intermediate is a key structural feature that simplifies identification of superfamily members, our understanding of their structure-function relationships is complicated by the modular nature of their structures, which exhibit varied and complex domain architectures. To gain new insight about these relationships, we classified the entire set of sequences into similarity-based subgroups that could be visualized using sequence similarity networks. This superfamily-wide analysis reveals important features that had not previously been appreciated from studies focused on one or a few members. Functional information mapped to the networks indicates which members have been experimentally or structurally characterized, their known reaction types, and their phylogenetic distribution. Despite the biological importance of radical SAM chemistry, the vast majority of superfamily members have never been experimentally characterized in any way, suggesting that many new reactions remain to be discovered. In addition to 20 subgroups with at least one known function, we identified additional subgroups made up entirely of sequences of unknown function. Importantly, our results indicate that even general reaction types fail to track well with our sequence similarity-based subgroupings, raising major challenges for function prediction for currently identified and new members that continue to be discovered. Interactive similarity networks and other data from this analysis are available from the Structure-Function Linkage Database.

Functional assignment of multiple catabolic pathways for D-apiose

Colocation of the genes encoding ABC, TRAP, and TCT transport systems and catabolic pathways for the transported ligand provides a strategy for discovering novel microbial enzymes and pathways. We screened solute-binding proteins (SBPs) for ABC transport systems and identified three that bind D-apiose, a branched pentose in the cell walls of higher plants. Guided by sequence similarity networks (SSNs) and genome neighborhood networks (GNNs), the identities of the SBPs enabled the discovery of four catabolic pathways for D-apiose with eleven previously unknown reactions. The new enzymes include D-apionate oxidoisomerase, which catalyzes hydroxymethyl group migration, as well as 3-oxo-isoapionate-4-phosphate decarboxylase and 3-oxo-isoapionate-4-phosphate transcarboxylase/hydrolase, which are RuBisCO-like proteins (RLPs). The web tools for generating SSNs and GNNs are publicly accessible ( http://efi.igb.illinois.edu/efi-est/ ), so similar 'genomic enzymology' strategies for discovering novel pathways can be used by the community.

Crius: A novel fragment-based algorithm of de novo substrate prediction for enzymes

The study of enzyme substrate specificity is vital for developing potential applications of enzymes. However, the routine experimental procedures require lot of resources in the discovery of novel substrates. This article reports an in silico structure-based algorithm called Crius, which predicts substrates for enzyme. The results of this fragment-based algorithm show good agreements between the simulated and experimental substrate specificities, using a lipase from Candida antarctica (CALB), a nitrilase from Cyanobacterium syechocystis sp. PCC6803 (Nit6803), and an aldo-keto reductase from Gluconobacter oxydans (Gox0644). This opens new prospects of developing computer algorithms that can effectively predict substrates for an enzyme.

Stress-responsively modulated ymdAB-clsC operon plays a role in biofilm formation and apramycin susceptibility in Escherichia coli

The YmdB protein, an inhibitor of biofilm formation and an inducer of apramycin susceptibility in Escherichia coli (E. coli), is part of a putative operon. However, transcription of this operon and its subsequent effects on biological pathways has not been fully studied. Here, we characterized the operon in terms of promoter activity, transcription and function. Promoter activity assays identified two new growth- and cold-shock-responsive upstream (PymdA) and inner (PclsC) promoters, respectively. Moreover, investigation of the operon-derived transcripts identified different polycistronic transcripts harboring multiple heterogeneous 3΄ ends. Overexpression of YmdA or ClsC proteins inhibited biofilm formation and affected apramycin susceptibility, a process dependent on the sucA gene, suggesting that the operon genes or their encoded proteins are functionally linked. Additional investigation of the effects of polycistronic transcripts on the response of E. coli cells to apramycin revealed that transcripts containing ymdA (-213 to +27) are required for apramycin susceptibility. Thus, ymdAB-clsC is a new stress-responsive operon that plays a role in inhibiting undesired biofilm forming and antibiotic-resistant bacterial populations.

Pelagibaca bermudensis promotes biofuel competence of Tetraselmis striata in a broad range of abiotic stressors: dynamics of quorum-sensing precursors and strategic improvement in lipid productivity

BACKGROUND

Amelioration of biofuel feedstock of microalgae using sustainable means through synthetic ecology is a promising strategy. The co-cultivation model (Tetraselmis striata and Pelagibaca bermudensis) was evaluated for the robust biofuel production under varying stressors as well as with the selected two-stage cultivation modes. In addition, the role of metabolic exudates including the quorum-sensing precursors was assessed.

RESULTS

The co-cultivation model innovated in this study supported the biomass production of T. striata in a saline/marine medium at a broad range of pH, salinity, and temperature/light conditions, as well as nutrient limitation with a growth promotion of 1.2-3.6-fold. Hence, this developed model could contribute to abiotic stress mitigation of T. striata. The quorum-sensing precursor dynamics of the growth promoting bacteria P. bermudensis exhibited unique pattern under varying stressors as revealed through targeted metabolomics (using liquid chromatography-mass spectrometry, LC-MS). P. bermudensis and its metabolic exudates mutually promoted the growth of T. striata, which elevated the lipid productivity. Interestingly, hydroxy alkyl quinolones independently showed growth inhibition of T. striata on elevated concentration. Among two-stage cultivation modes (low pH, elevated salinity, and nitrate limitation), specifically, nitrate limitation induced a 1.5 times higher lipid content (30-31%) than control in both axenic and co-cultivated conditions.

CONCLUSION

Pelagibaca bermudensis is established as a potential growth promoting native phycospheric bacteria for robust biomass generation of T. striata in varying environment, and two-stage cultivation using nitrate limitation strategically maximized the biofuel precursors for both axenic and co-cultivation conditions (T and T-PB, respectively). Optimum metabolic exudate of P. bermudensis which act as a growth substrate to T. striata surpasses the antagonistic effect of excessive hydroxy alkyl quinolones [HHQ, 4-hydroxy-2-alkylquinolines and PQS (pseudomonas quorum signal), 2-heptyl-3-hydroxy-4(1H)-quinolone].