Origins of specificity and promiscuity in metabolic networks

Minimal catalytic dissipative assemblies via cooperation of an amino acid, a nucleobase precursor and a cofactor

Functions arising from cooperation between protobiopolymers have fueled the chemical emergence of living matter, which requires a continuous supply of energy to exist in a far-from-equilibrium state. Non-equilibrium conditions imparted by available energy sources have played critical roles in the appearance of complex co-assembled architectures, which exploit the properties of different classes of biopolymers. Such co-assemblies formed from mixtures of nitrogenous heterocycles as protonucleobases and peptide precursors might have acted as early versions of catalytic machinery, capable of sustaining chemical reaction networks. Herein, we show the generation of catalytic non-equilibrium networks from a mixture of a nitrogenous heterocycle, an amino acid and a cofactor driven by an aromatic substrate. The cooperation, a result of supramolecular interactions between different components, rendered the assemblies capable of activating the cofactor towards oxidative degradation of the substrate, which resulted in autonomous disassembly (negative feedback). Furthermore, utilising promiscuous hydrolytic capability, the transient co-assemblies could metabolise a precursor to generate additional amounts of the substrate, enhancing the lifetime (positive feedback) of the assemblies.

Pathway-Dependent Catalytic Activity of Short-Peptide-Based Metallozyme: From Promiscuous Activity to Cascade Reaction

Many natural enzymes contain metal ions as cofactors in the active site for biological activity. However, the pathway of the introduction of metal ions in the earliest protein folds for the emergence of higher catalytic activity remains an intriguing open question. Herein, we demonstrate that pathway-dependent self-assembly of short-peptide-based metallozymes results in differences in catalytic activity. Short-peptide-based amyloids with solvent exposed arrays of colocalized catalytic units are able to bind highly soluble Cu2+ ions to demonstrate oxidase-like and RNase-like activity (promiscuity). Further, the metallozyme was able to exhibit higher hydrolase-oxidase cascade activity compared to the mixture of natural enzymes, esterase, and laccase. The collaboration between short-peptide-based amyloid microphases and metal ions suggests that metallozymes might have played a pivotal role in early metabolic processes and biopolymer evolution on the prebiotic earth.

Oomycete Metabolism Is Highly Dynamic and Reflects Lifestyle Adaptations

The selective pressure of pathogen-host symbiosis drives adaptations. How these interactions shape the metabolism of pathogens is largely unknown. Here, we use comparative genomics to systematically analyze the metabolic networks of oomycetes, a diverse group of eukaryotes that includes saprotrophs as well as animal and plant pathogens, with the latter causing devastating diseases with significant economic and/or ecological impacts. In our analyses of 44 oomycete species, we uncover considerable variation in metabolism that can be linked to lifestyle differences. Comparisons of metabolic gene content reveal that plant pathogenic oomycetes have a bipartite metabolism consisting of a conserved core and an accessory set. The accessory set can be associated with the degradation of defense compounds produced by plants when challenged by pathogens. Obligate biotrophic oomycetes have smaller metabolic networks, and taxonomically distantly related biotrophic lineages display convergent evolution by repeated gene losses in both the conserved as well as the accessory set of metabolisms. When investigating to what extent the metabolic networks in obligate biotrophs differ from those in hemibiotrophic plant pathogens, we observe that the losses of metabolic enzymes in obligate biotrophs are not random and that gene losses predominantly influence the terminal branches of the metabolic networks. Our analyses represent the first metabolism-focused comparison of oomycetes at this scale and will contribute to a better understanding of the evolution of oomycete metabolism in relation to lifestyle adaptation. Numerous oomycete species are devastating plant pathogens that cause major damage in crops and natural ecosystems. Their interactions with hosts are shaped by strong selection, but how selection affects adaptation of the primary metabolism to a pathogenic lifestyle is not yet well established. By pan-genome and metabolic network analyses of distantly related oomycete pathogens and their nonpathogenic relatives, we reveal considerable lifestyle- and lineage-specific adaptations. This study contributes to a better understanding of metabolic adaptations in pathogenic oomycetes in relation to lifestyle, host, and environment, and the findings will help in pinpointing potential targets for disease control. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Temporal (Dis)Assembly of Peptide Nanostructures Dictated by Native Multistep Catalytic Transformations

Emergence of complex catalytic machinery via simple building blocks under non-equilibrium conditions can contribute toward the system level understanding of the extant biocatalytic reaction network that fuels metabolism. Herein, we report temporal (dis)assembly of peptide nanostructures in presence of a cofactor dictated by native multistep cascade transformations. The short peptide can form a dynamic covalent bond with the thermodynamically activated substrate and recruit cofactor hemin to access non-equilibrium catalytic nanostructures (positive feedback). The neighboring imidazole and hemin moieties in the assembled state rapidly converted the substrate to product(s) via a two-step cascade reaction (hydrolase-peroxidase like) that subsequently triggered the disassembly of the catalytic nanostructures (negative feedback). The feedback coupled reaction cycle involving intrinsic catalytic prowess of short peptides to realize the advanced trait of two-stage cascade degradation of a thermodynamically activated substrate foreshadows the complex non-equilibrium protometabolic networks that might have preceded the chemical emergence of life.

Expanded Substrate Specificity in D-Amino Acid Transaminases: A Case Study of Transaminase from Blastococcus saxobsidens

Enzymes with expanded substrate specificity are good starting points for the design of biocatalysts for target reactions. However, the structural basis of the expanded substrate specificity is still elusive, especially in the superfamily of pyridoxal-5'-phosphate-dependent transaminases, which are characterized by a conserved organization of both the active site and functional dimer. Here, we analyze the structure-function relationships in a non-canonical D-amino acid transaminase from Blastococcus saxobsidens, which is active towards D-amino acids and primary (R)-amines. A detailed study of the enzyme includes a kinetic analysis of its substrate scope and a structural analysis of the holoenzyme and its complex with phenylhydrazine-a reversible inhibitor and analogue of (R)-1-phenylethylamine-a benchmark substrate of (R)-selective amine transaminases. We suggest that the features of the active site of transaminase from B. saxobsidens, such as the flexibility of the R34 and R96 residues, the lack of bulky residues in the β-turn at the entrance to the active site, and the short O-pocket loop, facilitate the binding of substrates with and without α-carboxylate groups. The proposed structural determinants of the expanded substrate specificity can be used for the design of transaminases for the stereoselective amination of keto compounds.

Aqueous microdroplets promote C-C bond formation and sequences in the reverse tricarboxylic acid cycle

The reverse tricarboxylic acid cycle (rTCA) is a central anabolic network that uses carbon dioxide (CO2) and may have provided complex carbon substrates for life before the advent of RNA or enzymes. However, non-enzymatic promotion of the rTCA cycle, in particular carbon fixation, remains challenging, even with primordial metal catalysis. Here, we report that the fixation of CO2 by reductive carboxylation of succinate and α-ketoglutarate was achieved in aqueous microdroplets under ambient conditions without the use of catalysts. Under identical conditions, the aqueous microdroplets also facilitated the sequences in the rTCA cycle, including reduction, hydration, dehydration and retro-aldol cleavage and linked with the glyoxylate cycle. These reactions of the rTCA cycle were compatible with the aqueous microdroplets, as demonstrated with two-reaction and four-reaction sequences. A higher selectivity giving higher product yields was also observed. Our results suggest that the microdroplets provide an energetically favourable microenvironment and facilitate a non-enzymatic version of the rTCA cycle in prebiotic carbon anabolism.

Emergence of Photomodulated Protometabolism by Short Peptide-Based Assemblies

In the early Earth, rudimentary enzymes must have utilized the available light energy source to modulate protometabolic processes. Herein, we report the light-responsive C-C bond manipulation via short peptide-based assemblies bound to the photosensitive molecular cofactor (azo-based photoswitch) where the energy of the light source regulated the binding sites which subsequently modulated the retro-aldolase activity. In the presence of a continual source of high-energy photons, temporal realization of a catalytically more proficient state could be achieved under nonequilibrium conditions. Further, the hydrophobic surface of peptide assemblies facilitated the binding of an orthogonal molecular catalyst that showed augmented activity (promiscuous hydrolytic activity) upon binding. This latent activity was utilized for the in situ generation of light-sensitive cofactor that subsequently modulated the retro-aldolase activity, thus creating a reaction network.

The evolution of strictly monofunctional naphthoquinol C-methyltransferases is vital in cyanobacteria and plastids

Prenylated quinones are membrane-associated metabolites that serve as vital electron carriers for respiration and photosynthesis. The UbiE (EC 2.1.1.201)/MenG (EC 2.1.1.163) C-methyltransferases catalyze pivotal ring methylations in the biosynthetic pathways of many of these quinones. In a puzzling evolutionary pattern, prokaryotic and eukaryotic UbiE/MenG homologs segregate into 2 clades. Clade 1 members occur universally in prokaryotes and eukaryotes, excluding cyanobacteria, and include mitochondrial COQ5 enzymes required for ubiquinone biosynthesis; Clade 2 members are specific to cyanobacteria and plastids. Functional complementation of an Escherichia coli ubiE/menG mutant indicated that Clade 1 members display activity with both demethylbenzoquinols and demethylnaphthoquinols, independently of the quinone profile of their original taxa, while Clade 2 members have evolved strict substrate specificity for demethylnaphthoquinols. Expression of the gene-encoding bifunctional Arabidopsis (Arabidopsis thaliana) COQ5 in the cyanobacterium Synechocystis or its retargeting to Arabidopsis plastids resulted in synthesis of a methylated variant of plastoquinone-9 that does not occur in nature. Accumulation of methylplastoquinone-9 was acutely cytotoxic, leading to the emergence of suppressor mutations in Synechocystis and seedling lethality in Arabidopsis. These data demonstrate that in cyanobacteria and plastids, co-occurrence of phylloquinone and plastoquinone-9 has driven the evolution of monofunctional demethylnaphthoquinol methyltransferases and explains why plants cannot capture the intrinsic bifunctionality of UbiE/MenG to simultaneously synthesize their respiratory and photosynthetic quinones.

Supramolecular enzyme-mimicking catalysts self-assembled from peptides

Natural enzymes catalyze biochemical transformations in superior catalytic efficiency and remarkable substrate specificity. The excellent catalytic repertoire of enzymes is attributed to the sophisticated chemical structures of their active sites, as a result of billions-of-years natural evolution. However, large-scale practical applications of natural enzymes are restricted due to their poor stability, difficulty in modification, and high costs of production. One viable solution is to fabricate supramolecular catalysts with enzyme-mimetic active sites. In this review, we introduce the principles and strategies of designing peptide-based artificial enzymes which display catalytic activities similar to those of natural enzymes, such as aldolases, laccases, peroxidases, and hydrolases (mainly the esterases and phosphatases). We also discuss some multifunctional enzyme-mimicking systems which are capable of catalyzing orthogonal or cascade reactions. We highlight the relationship between structures of enzyme-like active sites and the catalytic properties, as well as the significance of these studies from an evolutionary point of view.

Systems chemistry of peptide-assemblies for biochemical transformations

During the billions of years of the evolutionary journey, primitive polymers, involved in proto metabolic pathways with low catalytic activity, played critical roles in the emergence of modern enzymes with remarkable substrate specificity. The precise positioning of amino acid residues and the complex orchestrated interplay in the binding pockets of evolved enzymes promote covalent and non-covalent interactions to foster a diverse set of complex catalytic transformations. Recent efforts to emulate the structural and functional information of extant enzymes by minimal peptide based assemblies have attempted to provide a holistic approach that could help in discerning the prebiotic origins of catalytically active binding pockets of advanced proteins. In addition to the impressive sets of advanced biochemical transformations, catalytic promiscuity and cascade catalysis by such small molecule based dynamic systems can foreshadow the ancestral catalytic processes required for the onset of protometabolism. Looking beyond minimal systems that work close to equilibrium, catalytic systems and compartments under non-equilibrium conditions utilizing simple prebiotically relevant precursors have attempted to shed light on how bioenergetics played an essential role in chemical emergence of complex behaviour. Herein, we map out these recent works and progress where diverse sets of complex enzymatic transformations were demonstrated by utilizing minimal peptide based self-assembled systems. Further, we have attempted to cover the examples of peptide assemblies that could feature promiscuous activity and promote complex multistep cascade reaction networks. The review also covers a few recent examples of minimal transient catalytic assemblies under non-equilibrium conditions. This review attempts to provide a broad perspective for potentially programming functionality via rational selection of amino acid sequences leading towards minimal catalytic systems that resemble the traits of contemporary enzymes.

Emergence of a Promiscuous Peroxidase Under Non-Equilibrium Conditions

Herein, we report the substrate induced generation of a transient catalytic microenvironment from a single amino acid functionalized fatty acid in presence of a cofactor hemin. The catalytic state accessed under non-equilibrium conditions showed acceleration of peroxidase activity resulting in degradation of the substrate and subsequently led to disassembly. Equilibrated systems could not access the three-dimensional microphases and showed substantially lower catalytic activity. Further, the assembled state showed latent catalytic function (promiscuity) to hydrolyze a precursor to yield the same substrate. Consequently, the assembly demonstrated protometabolism by exploiting the peroxidase-hydrolase cascade to augment the lifetime and the mechanical properties of the catalytic state.

Application of free and immobilized novel bifunctional biocatalyst in biotransformation of recalcitrant lignocellulosic biomass

Herein, an innovative, green, and practical biocatalyst was developed using conjugation of a novel bifunctional mannanase/xylanase biocatalyst (PersiManXyn1) to the modified cellulose nanocrystals (CNCs). Firstly, PersiManXyn1 was multi-stage in-silico screened from rumen macrobiota, and then cloned, expressed, and purified. Next, CNCs were synthesized from sugar beet pulp using enzymatic and acid hydrolysis processes, and then Fe₃O₄ NPs were anchored on their surface to produce magnetic CNCs (MCNCs). This hybrid was modified by dopamine providing DA/MCNCs nano-carrier. The bifunctional PersiManXyn1 demonstrated the superior hydrolysis activity on corn cob compared with the monofunctional xylanase enzyme (PersiXyn2). Moreover, the immobilization of PersiManXyn1 on the nano-carrier resulted in an improvement of the thermal stability, kinetic parameters (K_cat), and storage stability of the enzyme. Incorporation of the Fe₃O₄ NPs on the CNCs made magnetic nano-carrier with high magnetization value (25.8 emu/g) which exhibited rapid response toward the external magnetic fields. Hence, the immobilized biocatalyst could be easily separated from the products by a magnet, and reused up to 8 cycles with maintaining more than 50% of its original activity. The immobilized PersiManXyn1 generated 22.2%, 38.7%, and 35.1% more reducing sugars after 168 h hydrolysis of the sugar beet pulp, coffee waste, and rice straw, respectively, compared to the free enzyme. Based on the results, immobilization of the bifunctional PersiManXyn1 exhibited the superb performance of the enzyme to improve the conversion of the lignocellulosic wastes into high value products and develop the cost-competition biomass operations.

Moonlighting Biochemistry of Cysteine Synthase: A Species-specific Global Regulator

Cysteine Synthase (CS), the enzyme that synthesizes cysteine, performs non-canonical regulatory roles by binding and modulating functions of disparate proteins. Beyond its role in catalysis and regulation in the cysteine biosynthesis pathway, it exerts its moonlighting effect by binding to few other proteins which possess a C-terminal "CS-binding motif", ending with a terminal ILE. Therefore, we hypothesized that CS might regulate many other disparate proteins with the "CS-binding motif". In this study, we developed an iterative sequence matching method for mapping moonlighting biochemistry of CS and validated our prediction by analytical and structural approaches. Using a minimal protein-peptide interaction system, we show that five previously unknown CS-binder proteins that participate in diverse metabolic processes interact with CS in a species-specific manner. Furthermore, results show that signatures of protein-protein interactions, including thermodynamic, competitive-inhibition, and structural features, highly match the known CS-Binder, serine acetyltransferase (SAT). Together, the results presented in this study allow us to map the extreme multifunctional space (EMS) of CS and reveal the biochemistry of moonlighting space, a subset of EMS. We believe that the integrated computational and experimental workflow developed here could be further modified and extended to study protein-specific moonlighting properties of multifunctional proteins.

Multifunctional alkalophilic α-amylase with diverse raw seaweed degrading activities

Uncultured microbes are an important resource for the discovery of novel enzymes. In this study, an amylase gene (amy2587) that codes a protein with 587 amino acids (Amy2587) was obtained from the metagenomic library of macroalgae-associated bacteria. Recombinant Amy2587 was expressed in Escherichia coli BL21 (DE3) and was found to simultaneously possess α-amylase, agarase, carrageenase, cellulase, and alginate lyase activities. Moreover, recombinant Amy2587 showed high thermostability and alkali resistance which are important characteristics for industrial application. To investigate the multifunctional mechanism of Amy2587, three motifs (functional domains) in the Amy2587 sequence were deleted to generate three truncated Amy2587 variants. The results showed that, even though these functional domains affected the multiple substrates degrading activity of Amy2587, they did not wholly explain its multifunctional characteristics. To apply the multifunctional activity of Amy2587, three seaweed substrates (Grateloupia filicina, Chondrus ocellatus, and Scagassum) were digested using Amy2587. After 2 h, 6 h, and 24 h of digestion, 121.2 ± 4 µg/ml, 134.8 ± 6 µg/ml, and 70.3 ± 3.5 µg/ml of reducing sugars were released, respectively. These results show that Amy2587 directly and effectively degraded three kinds of raw seaweeds. This finding provides a theoretical basis for one-step enzymatic digestion of raw seaweeds to obtain seaweed oligosaccharides.

The Transporter-Mediated Cellular Uptake and Efflux of Pharmaceutical Drugs and Biotechnology Products: How and Why Phospholipid Bilayer Transport Is Negligible in Real Biomembranes

Over the years, my colleagues and I have come to realise that the likelihood of pharmaceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient aqueous channels, the high concentrations of proteins serve to stop such activity, (iii) natural evolution long ago selected against transport methods that just let any undesirable products enter a cell, (iv) transporters have now been identified for all kinds of molecules (even water) that were once thought not to require them, (v) many experiments show a massive variation in the uptake of drugs between different cells, tissues, and organisms, that cannot be explained if lipid bilayer transport is significant or if efflux were the only differentiator, and (vi) many experiments that manipulate the expression level of individual transporters as an independent variable demonstrate their role in drug and nutrient uptake (including in cytotoxicity or adverse drug reactions). This makes such transporters valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and also as drug targets. The same considerations apply to the exploitation of substrate uptake and product efflux transporters in biotechnology. We are also beginning to recognise that transporters are more promiscuous, and antiporter activity is much more widespread, than had been realised, and that such processes are adaptive (i.e., were selected by natural evolution). The purpose of the present review is to summarise the above, and to rehearse and update readers on recent developments. These developments lead us to retain and indeed to strengthen our contention that for transmembrane pharmaceutical drug transport "phospholipid bilayer transport is negligible".

Enzyme Promiscuity Prediction Using Hierarchy-Informed Multi-Label Classification

MOTIVATION

As experimental efforts are costly and time consuming, computational characterization of enzyme capabilities is an attractive alternative. We present and evaluate several machine-learning models to predict which of 983 distinct enzymes, as defined via the Enzyme Commission (EC) numbers, are likely to interact with a given query molecule. Our data consists of enzyme-substrate interactions from the BRENDA database. Some interactions are attributed to natural selection and involve the enzyme's natural substrates. The majority of the interactions however involve non-natural substrates, thus reflecting promiscuous enzymatic activities.

RESULTS

We frame this "enzyme promiscuity prediction" problem as a multi-label classification task. We maximally utilize inhibitor and unlabelled data to train prediction models that can take advantage of known hierarchical relationships between enzyme classes. We report that a hierarchical multi-label neural network, EPP-HMCNF, is the best model for solving this problem, outperforming k-nearest neighbours similarity-based and other machine learning models. We show that inhibitor information during training consistently improves predictive power, particularly for EPP-HMCNF. We also show that all promiscuity prediction models perform worse under a realistic data split when compared to a random data split, and when evaluating performance on non-natural substrates compared to natural substrates.

AVAILABILITY AND IMPLEMENTATION

We provide Python code for EPP-HMCNF and other models in a repository termed EPP (Enzyme Promiscuity Prediction) at https://github.com/hassounlab/EPP.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Nonenzymatic Metabolic Reactions and Life's Origins

Prebiotic chemistry aims to explain how the biochemistry of life as we know it came to be. Most efforts in this area have focused on provisioning compounds of importance to life by multistep synthetic routes that do not resemble biochemistry. However, gaining insight into why core metabolism uses the molecules, reactions, pathways, and overall organization that it does requires us to consider molecules not only as synthetic end goals. Equally important are the dynamic processes that build them up and break them down. This perspective has led many researchers to the hypothesis that the first stage of the origin of life began with the onset of a primitive nonenzymatic version of metabolism, initially catalyzed by naturally occurring minerals and metal ions. This view of life's origins has come to be known as "metabolism first". Continuity with modern metabolism would require a primitive version of metabolism to build and break down ketoacids, sugars, amino acids, and ribonucleotides in much the same way as the pathways that do it today. This review discusses metabolic pathways of relevance to the origin of life in a manner accessible to chemists, and summarizes experiments suggesting several pathways might have their roots in prebiotic chemistry. Finally, key remaining milestones for the protometabolic hypothesis are highlighted.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

Larger active site in an ancestral hydroxynitrile lyase increases catalytically promiscuous esterase activity

Hydroxynitrile lyases (HNL's) belonging to the α/β-hydrolase-fold superfamily evolved from esterases approximately 100 million years ago. Reconstruction of an ancestral hydroxynitrile lyase in the α/β-hydrolase fold superfamily yielded a catalytically active hydroxynitrile lyase, HNL1. Several properties of HNL1 differ from the modern HNL from rubber tree (HbHNL). HNL1 favors larger substrates as compared to HbHNL, is two-fold more catalytically promiscuous for ester hydrolysis (p-nitrophenyl acetate) as compared to mandelonitrile cleavage, and resists irreversible heat inactivation to 35 °C higher than for HbHNL. We hypothesized that the x-ray crystal structure of HNL1 may reveal the molecular basis for the differences in these properties. The x-ray crystal structure solved to 1.96-Å resolution shows the expected α/β-hydrolase fold, but a 60% larger active site as compared to HbHNL. This larger active site echoes its evolution from esterases since related esterase SABP2 from tobacco also has a 38% larger active site than HbHNL. The larger active site in HNL1 likely accounts for its ability to accept larger hydroxynitrile substrates. Site-directed mutagenesis of HbHNL to expand the active site increased its promiscuous esterase activity 50-fold, consistent with the larger active site in HNL1 being the primary cause of its promiscuous esterase activity. Urea-induced unfolding of HNL1 indicates that it unfolds less completely than HbHNL (m-value = 0.63 for HNL1 vs 0.93 kcal/mol·M for HbHNL), which may account for the ability of HNL1 to better resist irreversible inactivation upon heating. The structure of HNL1 shows changes in hydrogen bond networks that may stabilize regions of the folded structure.

Bacterial symbionts support larval sap feeding and adult folivory in (semi-)aquatic reed beetles

Symbiotic microbes can enable their host to access untapped nutritional resources but may also constrain niche space by promoting specialization. Here, we reconstruct functional changes in the evolutionary history of the symbiosis between a group of (semi-)aquatic herbivorous insects and mutualistic bacteria. Sequencing the symbiont genomes across 26 species of reed beetles (Chrysomelidae, Donaciinae) spanning four genera indicates that the genome-eroded mutualists provide life stage-specific benefits to larvae and adults, respectively. In the plant sap-feeding larvae, the symbionts are inferred to synthesize most of the essential amino acids as well as the B vitamin riboflavin. The adult reed beetles’ folivory is likely supported by symbiont-encoded pectinases that complement the host-encoded set of cellulases, as revealed by transcriptome sequencing. However, mapping the occurrence of the symbionts’ pectinase genes and the hosts’ food plant preferences onto the beetles’ phylogeny reveals multiple independent losses of pectinase genes in lineages that switched to feeding on pectin-poor plants, presumably constraining their hosts’ subsequent adaptive potential.

Symbiotic microbes in insects can enable their hosts to access untapped nutritional resources. Here, the authors show that symbiotic bacteria in reed beetles can provide essential amino acids to sap-feeding larvae and help leaf-feeding adults to degrade pectin, respectively.

Protein promiscuity in drug discovery, drug-repurposing and antibiotic resistance

Proteins are supposed to bind to their substrates/ligands in a specific manner via their pre-formed binding sites, according to classical biochemistry. In recent years, several types of deviations from this norm have been observed and called promiscuous behavior. Enzymatic promiscuities allow several biochemical functions to be carried out by the same enzyme. The promiscuous activity can also be the origin of "new proteins" via gene duplication. In more recent years, proteins from prokaryotes, eukaryotes and viruses have been found to have intrinsic disorder and lack a preformed binding site. Intrinsic disorder is exploited in regulatory proteins such as those that are involved in transcription and signal transduction. Such proteins function by folding locally while binding to their ligands or interacting with other proteins. These phenomena have also been classified as examples of protein promiscuity and encompass diverse kinds of ligands that can bind to a protein. Given the significant extent of structural homology in many protein families, it is not surprising that ligands also have been found to display promiscuity. Promiscuous behavior of proteins offers both challenges and opportunities to the drug discovery programs such as drug repurposing. Pathogens when exposed to antibiotics exploit protein promiscuity in several ways to develop resistance to the drug. There is increasing evidence now to support that the disorder in proteins is a major tool used by pathogens for virulence and evade drug action by exploiting protein promiscuity. This review provides a holistic view of this multi-faceted phenomenon called protein promiscuity.

Larger active site in an ancestral hydroxynitrile lyase increases catalytically promiscuous esterase activity.. [DOI: 10.1101/2020.04.06.027797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Hydroxynitrile lyases (HNL’s) belonging to the α/β-hydrolase-fold superfamily evolved from esterases approximately 100 million years ago. Reconstruction of an ancestral hydroxynitrile lyase in the α/β-hydrolase fold superfamily yielded a catalytically active hydroxynitrile lyase, HNL1. Several properties of HNL1 differ from the modern HNL from rubber tree (HbHNL). HNL1 favors larger substrates as compared to HbHNL, is two-fold more catalytically promiscuous for ester hydrolysis (p-nitrophenyl acetate) as compared to mandelonitrile cleavage, and resists irreversible heat inactivation to 35 °C higher than for HbHNL. We hypothesized that the x-ray crystal structure of HNL1 may reveal the molecular basis for the differences in these properties. The x-ray crystal structure solved to 1.96-Å resolution shows the expected α/β-hydrolase fold, but a 60% larger active site as compared to HbHNL. This larger active site echoes its evolution from esterases since related esterase SABP2 from tobacco also has a 38% larger active site than HbHNL. The larger active site in HNL1 likely accounts for its ability to accept larger hydroxynitrile substrates. Site-directed mutagenesis of HbHNL to expand the active site increased its promiscuous esterase activity 50-fold, consistent with the larger active site in HNL1 being the primary cause of its promiscuous esterase activity. Urea-induced unfolding of HNL1 indicates that it unfolds less completely than HbHNL (m-value = 0.63 for HNL1 vs 0.93 kcal/ mol·M for HbHNL), which may account for the ability of HNL1 to better resist irreversible inactivation upon heating. The structure of HNL1 shows changes in hydrogen bond networks that may stabilize regions of the folded structure.

Molecular evolution of gland cell types and chemical interactions in animals

Across the Metazoa, the emergence of new ecological interactions has been enabled by the repeated evolution of exocrine glands. Specialized glands have arisen recurrently and with great frequency, even in single genera or species, transforming how animals interact with their environment through trophic resource exploitation, pheromonal communication, chemical defense and parental care. The widespread convergent evolution of animal glands implies that exocrine secretory cells are a hotspot of metazoan cell type innovation. Each evolutionary origin of a novel gland involves a process of 'gland cell type assembly': the stitching together of unique biosynthesis pathways; coordinated changes in secretory systems to enable efficient chemical release; and transcriptional deployment of these machineries into cells constituting the gland. This molecular evolutionary process influences what types of compound a given species is capable of secreting, and, consequently, the kinds of ecological interactions that species can display. Here, we discuss what is known about the evolutionary assembly of gland cell types and propose a framework for how it may happen. We posit the existence of 'terminal selector' transcription factors that program gland function via regulatory recruitment of biosynthetic enzymes and secretory proteins. We suggest ancestral enzymes are initially co-opted into the novel gland, fostering pleiotropic conflict that drives enzyme duplication. This process has yielded the observed pattern of modular, gland-specific biosynthesis pathways optimized for manufacturing specific secretions. We anticipate that single-cell technologies and gene editing methods applicable in diverse species will transform the study of animal chemical interactions, revealing how gland cell types are assembled and functionally configured at a molecular level.

Polyesters as a Model System for Building Primitive Biologies from Non-Biological Prebiotic Chemistry

A variety of organic chemicals were likely available on prebiotic Earth. These derived from diverse processes including atmospheric and geochemical synthesis and extraterrestrial input, and were delivered to environments including oceans, lakes, and subaerial hot springs. Prebiotic chemistry generates both molecules used by modern organisms, such as proteinaceous amino acids, as well as many molecule types not used in biochemistry. As prebiotic chemical diversity was likely high, and the core of biochemistry uses a rather small set of common building blocks, the majority of prebiotically available organic compounds may not have been those used in modern biochemistry. Chemical evolution was unlikely to have been able to discriminate which molecules would eventually be used in biology, and instead, interactions among compounds were governed simply by abundance and chemical reactivity. Previous work has shown that likely prebiotically available α-hydroxy acids can combinatorially polymerize into polyesters that self-assemble to create new phases which are able to compartmentalize other molecule types. The unexpectedly rich complexity of hydroxy acid chemistry and the likely enormous structural diversity of prebiotic organic chemistry suggests chemical evolution could have been heavily influenced by molecules not used in contemporary biochemistry, and that there is a considerable amount of prebiotic chemistry which remains unexplored.

Emulating evolutionary processes to morph aureothin-type modular polyketide synthases and associated oxygenases

Polyketides produced by modular type I polyketide synthases (PKSs) play eminent roles in the development of medicines. Yet, the production of structural analogs by genetic engineering poses a major challenge. We report an evolution-guided morphing of modular PKSs inspired by recombination processes that lead to structural diversity in nature. By deletion and insertion of PKS modules we interconvert the assembly lines for related antibiotic and antifungal agents, aureothin (aur) and neoaureothin (nor) (aka spectinabilin), in both directions. Mutational and functional analyses of the polyketide-tailoring cytochrome P450 monooxygenases, and PKS phylogenies give contradictory clues on potential evolutionary scenarios (generalist-to-specialist enzyme evolution vs. most parsimonious ancestor). The KS-AT linker proves to be well suited as fusion site for both excision and insertion of modules, which supports a model for alternative module boundaries in some PKS systems. This study teaches important lessons on the evolution of PKSs, which may guide future engineering approaches.

The wealth of complex polyketides is an essential source for drug discovery. Here, the authors report an evolution-guided rational morphing of modular polyketide synthases (PKSs) for aurothin and neoaurothin biosynthesis, and reveal engineering site suitable for diversifying PKS systems.

Systems Metabolic Engineering Meets Machine Learning: A New Era for Data-Driven Metabolic Engineering

The recent increase in high-throughput capacity of 'omics datasets combined with advances and interest in machine learning (ML) have created great opportunities for systems metabolic engineering. In this regard, data-driven modeling methods have become increasingly valuable to metabolic strain design. In this review, the nature of 'omics is discussed and a broad introduction to the ML algorithms combining these datasets into predictive models of metabolism and metabolic rewiring is provided. Next, this review highlights recent work in the literature that utilizes such data-driven methods to inform various metabolic engineering efforts for different classes of application including product maximization, understanding and profiling phenotypes, de novo metabolic pathway design, and creation of robust system-scale models for biotechnology. Overall, this review aims to highlight the potential and promise of using ML algorithms with metabolic engineering and systems biology related datasets.

Exploiting enzyme promiscuity to shape plant specialized metabolism

The amazing variability of plant metabolism and its rapid divergence during evolution pose fundamental questions as to the driving forces, mechanisms, and players in metabolic differentiation. This review examines concepts that help us understand adaptive pathway evolution, with a particular emphasis on plant specialized metabolism, previously often termed secondary metabolism. Following a general introduction to pathway and metabolite evolution, the focus is directed to enzyme promiscuity and its classification. Promiscuous enzymes (or substrates), 'silent' elements of the metabolome, and the 'underground metabolism' may be used and combined to evolve 'new' metabolic pathways. It appears that new pathways rarely appear from scratch, but instead emerge from 'floppy' enzymes and elements of a 'messy' metabolism, and in this way a range of metabolites is generated, some of which may provide benefits to the plant.

A study on multi-omic oscillations in Escherichia coli metabolic networks

BACKGROUND

Two important challenges in the analysis of molecular biology information are data (multi-omic information) integration and the detection of patterns across large scale molecular networks and sequences. They are are actually coupled beause the integration of omic information may provide better means to detect multi-omic patterns that could reveal multi-scale or emerging properties at the phenotype levels.

RESULTS

Here we address the problem of integrating various types of molecular information (a large collection of gene expression and sequence data, codon usage and protein abundances) to analyse the E.coli metabolic response to treatments at the whole network level. Our algorithm, MORA (Multi-omic relations adjacency) is able to detect patterns which may represent metabolic network motifs at pathway and supra pathway levels which could hint at some functional role. We provide a description and insights on the algorithm by testing it on a large database of responses to antibiotics. Along with the algorithm MORA, a novel model for the analysis of oscillating multi-omics has been proposed. Interestingly, the resulting analysis suggests that some motifs reveal recurring oscillating or position variation patterns on multi-omics metabolic networks. Our framework, implemented in R, provides effective and friendly means to design intervention scenarios on real data. By analysing how multi-omics data build up multi-scale phenotypes, the software allows to compare and test metabolic models, design new pathways or redesign existing metabolic pathways and validate in silico metabolic models using nearby species.

CONCLUSIONS

The integration of multi-omic data reveals that E.coli multi-omic metabolic networks contain position dependent and recurring patterns which could provide clues of long range correlations in the bacterial genome.

SimCAL: a flexible tool to compute biochemical reaction similarity

Background

Computation of reaction similarity is a pre-requisite for several bioinformatics applications including enzyme identification for specific biochemical reactions, enzyme classification and mining for specific inhibitors. Reaction similarity is often assessed at either two levels: (i) comparison across all the constituent substrates and products of a reaction, reaction level similarity, (ii) comparison at the transformation center with various degrees of neighborhood, transformation level similarity. Existing reaction similarity computation tools are designed for specific applications and use different features and similarity measures. A single system integrating these diverse features enables comparison of the impact of different molecular properties on similarity score computation.

Results

To address these requirements, we present SimCAL, an integrated system to calculate reaction similarity with novel features and capability to perform comparative assessment. SimCAL provides reaction similarity computation at both whole reaction level and transformation level. Novel physicochemical features such as stereochemistry, mass, volume and charge are included in computing reaction fingerprint. Users can choose from four different fingerprint types and nine molecular similarity measures. Further, a comparative assessment of these features is also enabled. The performance of SimCAL is assessed on 3,688,122 reaction pairs with Enzyme Commission (EC) number from MetaCyc and achieved an area under the curve (AUC) of > 0.9. In addition, SimCAL results showed strong correlation with state-of-the-art EC-BLAST and molecular signature based reaction similarity methods.

Conclusions

SimCAL is developed in java and is available as a standalone tool, with intuitive, user-friendly graphical interface and also as a console application. With its customizable feature selection and similarity calculations, it is expected to cater a wide audience interested in studying and analyzing biochemical reactions and metabolic networks.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2248-5) contains supplementary material, which is available to authorized users.

Cryptic indole hydroxylation by a non-canonical terpenoid cyclase parallels bacterial xenobiotic detoxification

Terpenoid natural products comprise a wide range of molecular architectures that typically result from C–C bond formations catalysed by classical type I/II terpene cyclases. However, the molecular diversity of biologically active terpenoids is substantially increased by fully unrelated, non-canonical terpenoid cyclases. Their evolutionary origin has remained enigmatic. Here we report the in vitro reconstitution of an unusual flavin-dependent bacterial indoloterpenoid cyclase, XiaF, together with a designated flavoenzyme-reductase (XiaP) that mediates a key step in xiamycin biosynthesis. The crystal structure of XiaF with bound FADH₂ (at 2.4 Å resolution) and phylogenetic analyses reveal that XiaF is, surprisingly, most closely related to xenobiotic-degrading enzymes. Biotransformation assays show that XiaF is a designated indole hydroxylase that can be used for the production of indigo and indirubin. We unveil a cryptic hydroxylation step that sets the basis for terpenoid cyclization and suggest that the cyclase has evolved from xenobiotics detoxification enzymes.

The biosynthesis of xiamycin, an antimicrobial bacterial indolosesquiterpenoid, involves an unusual cyclization cascade. Here, the authors characterise the XiaF enzyme, which resembles xenobiont-degrading enzymes and is responsible for a hidden indole hydroxylation step that triggers the cyclization reaction.

Analysis of drug-endogenous human metabolite similarities in terms of their maximum common substructures

In previous work, we have assessed the structural similarities between marketed drugs (‘drugs’) and endogenous natural human metabolites (‘metabolites’ or ‘endogenites’), using ‘fingerprint’ methods in common use, and the Tanimoto and Tversky similarity metrics, finding that the fingerprint encoding used had a dramatic effect on the apparent similarities observed. By contrast, the maximal common substructure (MCS), when the means of determining it is fixed, is a means of determining similarities that is largely independent of the fingerprints, and also has a clear chemical meaning. We here explored the utility of the MCS and metrics derived therefrom. In many cases, a shared scaffold helps cluster drugs and endogenites, and gives insight into enzymes (in particular transporters) that they both share. Tanimoto and Tversky similarities based on the MCS tend to be smaller than those based on the MACCS fingerprint-type encoding, though the converse is also true for a significant fraction of the comparisons. While no single molecular descriptor can account for these differences, a machine learning-based analysis of the nature of the differences (MACCS_Tanimoto vs MCS_Tversky) shows that they are indeed deterministic, although the features that are used in the model to account for this vary greatly with each individual drug. The extent of its utility and interpretability vary with the drug of interest, implying that while MCS is neither ‘better’ nor ‘worse’ for every drug–endogenite comparison, it is sufficiently different to be of value. The overall conclusion is thus that the use of the MCS provides an additional and valuable strategy for understanding the structural basis for similarities between synthetic, marketed drugs and natural intermediary metabolites.

Origin of an ancient hormone/receptor couple revealed by resurrection of an ancestral estrogen

The origin of ancient ligand/receptor couples is often analyzed via reconstruction of ancient receptors and, when ligands are products of metabolic pathways, they are not supposed to evolve. However, because metabolic pathways are inherited by descent with modification, their structure can be compared using cladistic analysis. Using this approach, we studied the evolution of steroid hormones. We show that side-chain cleavage is common to most vertebrate steroids, whereas aromatization was co-opted for estrogen synthesis from a more ancient pathway. The ancestral products of aromatic activity were aromatized steroids with a side chain, which we named "paraestrols." We synthesized paraestrol A and show that it effectively binds and activates the ancestral steroid receptor. Our study opens the way to comparative studies of biologically active small molecules.

Amy63, a novel type of marine bacterial multifunctional enzyme possessing amylase, agarase and carrageenase activities

A multifunctional enzyme is one that performs multiple physiological functions, thus benefiting the organism. Characterization of multifunctional enzymes is important for researchers to understand how organisms adapt to different environmental challenges. In the present study, we report the discovery of a novel multifunctional enzyme Amy63 produced by marine bacterium Vibrio alginolyticus 63. Remarkably, Amy63 possesses amylase, agarase and carrageenase activities. Amy63 is a substrate promiscuous α-amylase, with the substrate priority order of starch, carrageenan and agar. Amy63 maintains considerable amylase, carrageenase and agarase activities and stabilities at wide temperature and pH ranges, and optimum activities are detected at temperature of 60 °C and pH of 6.0, respectively. Moreover, the heteroexpression of Amy63 dramatically enhances the ability of E. coli to degrade starch, carrageenan and agar. Motif searching shows three continuous glycosyl hydrolase 70 (GH70) family homologs existed in Amy63 encoding sequence. Combining serial deletions and phylogenetic analysis of Amy63, the GH70 homologs are proposed as the determinants of enzyme promiscuity. Notably, such enzymes exist in all kingdoms of life, thus providing an expanded perspective on studies of multifunctional enzymes. To our knowledge, this is the first report of an amylase having additional agarase and carrageenase activities.

Physicochemical characteristics of structurally determined metabolite-protein and drug-protein binding events with respect to binding specificity

To better understand and ultimately predict both the metabolic activities as well as the signaling functions of metabolites, a detailed understanding of the physical interactions of metabolites with proteins is highly desirable. Focusing in particular on protein binding specificity vs. promiscuity, we performed a comprehensive analysis of the physicochemical properties of compound-protein binding events as reported in the Protein Data Bank (PDB). We compared the molecular and structural characteristics obtained for metabolites to those of the well-studied interactions of drug compounds with proteins. Promiscuously binding metabolites and drugs are characterized by low molecular weight and high structural flexibility. Unlike reported for drug compounds, low rather than high hydrophobicity appears associated, albeit weakly, with promiscuous binding for the metabolite set investigated in this study. Across several physicochemical properties, drug compounds exhibit characteristic binding propensities that are distinguishable from those associated with metabolites. Prediction of target diversity and compound promiscuity using physicochemical properties was possible at modest accuracy levels only, but was consistently better for drugs than for metabolites. Compound properties capturing structural flexibility and hydrogen-bond formation descriptors proved most informative in PLS-based prediction models. With regard to diversity of enzymatic activities of the respective metabolite target enzymes, the metabolites benzylsuccinate, hypoxanthine, trimethylamine N-oxide, oleoylglycerol, and resorcinol showed very narrow process involvement, while glycine, imidazole, tryptophan, succinate, and glutathione were identified to possess broad enzymatic reaction scopes. Promiscuous metabolites were found to mainly serve as general energy currency compounds, but were identified to also be involved in signaling processes and to appear in diverse organismal systems (digestive and nervous system) suggesting specific molecular and physiological roles of promiscuous metabolites.

The Impact of Non-Enzymatic Reactions and Enzyme Promiscuity on Cellular Metabolism during (Oxidative) Stress Conditions

Cellular metabolism assembles in a structurally highly conserved, but functionally dynamic system, known as the metabolic network. This network involves highly active, enzyme-catalyzed metabolic pathways that provide the building blocks for cell growth. In parallel, however, chemical reactivity of metabolites and unspecific enzyme function give rise to a number of side products that are not part of canonical metabolic pathways. It is increasingly acknowledged that these molecules are important for the evolution of metabolism, affect metabolic efficiency, and that they play a potential role in human disease—age-related disorders and cancer in particular. In this review we discuss the impact of oxidative and other cellular stressors on the formation of metabolic side products, which originate as a consequence of: (i) chemical reactivity or modification of regular metabolites; (ii) through modifications in substrate specificity of damaged enzymes; and (iii) through altered metabolic flux that protects cells in stress conditions. In particular, oxidative and heat stress conditions are causative of metabolite and enzymatic damage and thus promote the non-canonical metabolic activity of the cells through an increased repertoire of side products. On the basis of selected examples, we discuss the consequences of non-canonical metabolic reactivity on evolution, function and repair of the metabolic network.

Biological messiness vs. biological genius: Mechanistic aspects and roles of protein promiscuity

In contrast to the traditional biological paradigms focused on 'specificity', recent research and theoretical efforts have focused on functional 'promiscuity' exhibited by proteins and enzymes in many biological settings, including enzymatic detoxication, steroid biochemistry, signal transduction and immune responses. In addition, divergent evolutionary processes are apparently facilitated by random mutations that yield promiscuous enzyme intermediates. The intermediates, in turn, provide opportunities for further evolution to optimize new functions from existing protein scaffolds. In some cases, promiscuity may simply represent the inherent plasticity of proteins resulting from their polymeric nature with distributed conformational ensembles. Enzymes or proteins that bind or metabolize noncognate substrates create 'messiness' or noise in the systems they contribute to. With our increasing awareness of the frequency of these promiscuous behaviors it becomes interesting and important to understand the molecular bases for promiscuous behavior and to distinguish between evolutionarily selected promiscuity and evolutionarily tolerated messiness. This review provides an overview of current understanding of these aspects of protein biochemistry and enzymology.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

A substrate ambiguous enzyme facilitates genome reduction in an intracellular symbiont

BACKGROUND

Genome evolution in intracellular microbial symbionts is characterized by gene loss, generating some of the smallest and most gene-poor genomes known. As a result of gene loss these genomes commonly contain metabolic pathways that are fragmented relative to their free-living relatives. The evolutionary retention of fragmented metabolic pathways in the gene-poor genomes of endosymbionts suggests that they are functional. However, it is not always clear how they maintain functionality. To date, the fragmented metabolic pathways of endosymbionts have been shown to maintain functionality through complementation by host genes, complementation by genes of another endosymbiont and complementation by genes in host genomes that have been horizontally acquired from a microbial source that is not the endosymbiont. Here, we demonstrate a fourth mechanism.

RESULTS

We investigate the evolutionary retention of a fragmented pathway for the essential nutrient pantothenate (vitamin B5) in the pea aphid, Acyrthosiphon pisum endosymbiosis with Buchnera aphidicola. Using quantitative analysis of gene expression we present evidence for complementation of the Buchnera pantothenate biosynthesis pathway by host genes. Further, using complementation assays in an Escherichia coli mutant we demonstrate functional replacement of a pantothenate biosynthesis enzyme, 2-dehydropantoate 2-reductase (E.C. 1.1.1.169), by an endosymbiont gene, ilvC, encoding a substrate ambiguous enzyme.

CONCLUSIONS

Earlier studies have speculated that missing enzyme steps in fragmented endosymbiont metabolic pathways are completed by adaptable endosymbiont enzymes from other pathways. Here, we experimentally demonstrate completion of a fragmented endosymbiont vitamin biosynthesis pathway by recruitment of a substrate ambiguous enzyme from another pathway. In addition, this work extends host/symbiont metabolic collaboration in the aphid/Buchnera symbiosis from amino acid metabolism to include vitamin biosynthesis.

Distinct substrate selectivity of a metabolic hydrolase from Mycobacterium tuberculosis

The transition between dormant and active Mycobacterium tuberculosis infection requires reorganization of its lipid metabolism and activation of a battery of serine hydrolase enzymes. Among these serine hydrolases, Rv0045c is a mycobacterial-specific serine hydrolase with limited sequence homology outside mycobacteria but structural homology to divergent bacterial hydrolase families. Herein, we determined the global substrate specificity of Rv0045c against a library of fluorogenic hydrolase substrates, constructed a combined experimental and computational model for its binding pocket, and performed comprehensive substitutional analysis to develop a structural map of its binding pocket. Rv0045c showed strong substrate selectivity toward short, straight chain alkyl esters with the highest activity toward four atom chains. This strong substrate preference was maintained through the combined action of residues in a flexible loop connecting the cap and α/β hydrolase domains and in residues close to the catalytic triad. Two residues bracketing the substrate-binding pocket (Gly90 and His187) were essential to maintaining the narrow substrate selectivity of Rv0045c toward various acyl ester substituents, as independent conversion of these residues significantly increased its catalytic activity and broadened its substrate specificity. Focused saturation mutagenesis of position 187 implicated this residue, as the differentiation point between the substrate specificity of Rv0045c and the structurally homologous ybfF hydrolase family. Insertion of the analogous tyrosine residue from ybfF hydrolases into Rv0045c increased the catalytic activity of Rv0045 by over 20-fold toward diverse ester substrates. The unique binding pocket structure and selectivity of Rv0045c provide molecular indications of its biological role and evidence for expanded substrate diversity in serine hydrolases from M. tuberculosis.

Lipid changes after leaf wounding in Arabidopsis thaliana: expanded lipidomic data form the basis for lipid co-occurrence analysis

A direct-infusion electrospray ionization triple-quadrupole mass spectrometry method with multiple reaction monitoring (MRM) was employed to measure 264 lipid analytes extracted from leaves of Arabidopsis thaliana subjected to mechanical wounding. The method provided precise measurements with an average coefficient of variation of 6.1%. Lipid classes analyzed comprised galactolipids and phospholipids (including monoacyl molecular species, molecular species with oxidized acyl chains, phosphatidic acids (PAs)), tri- and tetra-galactosyldiacylglycerols (TrGDGs and TeGDGs), head-group-acylated galactolipids, and head-group-acylated phosphatidylglycerol (acPG), sulfoquinovosyldiacylglycerols (SQDGs), sphingolipids, di- and tri-acylglycerols (DAGs and TAGs), and sterol derivatives. Of the 264 lipid analytes, 254 changed significantly in response to wounding. In general, levels of structural lipids decreased, whereas monoacyl molecular species, galactolipids and phosphatidylglycerols (PGs) with oxidized fatty acyl chains, PAs, TrGDGs, TeGDGs, TAGs, head-group-acylated galactolipids, acPG, and some sterol derivatives increased, many transiently. The observed changes are consistent with activation of lipid oxidizing, hydrolyzing, glycosylating, and acylating activities in the wounding response. Correlation analysis of the levels of lipid analytes across individual control and treated plants was used to construct a lipid dendrogram and to define clusters and sub-clusters of lipid analytes, each composed of a group of lipids which occurred in a coordinated manner. Current knowledge of metabolism supports the notion that observed sub-clusters comprise lipids generated by a common enzyme and/or metabolically downstream of a common enzyme. This work demonstrates that co-occurrence analysis, based on correlation of lipid levels among plants, is a powerful approach to defining lipids generated in vivo by a common enzymatic pathway.