Cofactory: sequence-based prediction of cofactor specificity of Rossmann folds

In silico comparative structural and functional analysis of arsenite methyltransferase from bacteria, fungi, fishes, birds, and mammals

BACKGROUND

Arsenic, a ubiquitous toxic metalloid, is a threat to the survival of all living organisms. Bioaccumulation of arsenic interferes with the normal physiological pathway. To overcome arsenic toxicity, organisms have developed arsenite methyltransferase enzyme, which methylates inorganic arsenite to organic arsenic MMA (III) in the presence of S-adenosylmethionine (SAM). Bacteria-derived arsM might be horizontally transported to different domains of life as arsM or as3mt (animal ortholog). A systematic study on the functional diversity of arsenite methyltransferase from various sources will be used in arsenic bioremediation.

RESULTS

Several arsenite methyltransferase protein sequences of bacteria, fungi, fishes, birds, and mammals were retrieved from the UniProt database. In silico physicochemical studies confirmed the acidic, hydrophilic, and thermostable nature of these enzymes. Interkingdom relationships were revealed by performing phylogenetic analysis. Homology modeling was performed by SWISS-MODEL, and that was validated through SAVES-v.6.0. QMEAN values ranged from - 0.93 to - 1.30, ERRAT score (83-96), PROCHECK (88-92%), and other parameters suggested models are statistically significant. MOTIF and PrankWeb discovered several functional motifs and active pockets within the proteins respectively. The STRING database showed protein-protein interaction networks.

CONCLUSION

All of our in silico studies confirmed the fact that arsenite methyltransferase is a cytosolic stable enzyme with conserved sequences over a wide range of organisms. Thus, because of its stable and ubiquitous nature, arsenite methyltransferase could be employed in arsenic bioremediation.

Relative Activities of the β-ketoacyl-CoA and Acyl-CoA Reductases Influence Product Profile and Flux in a Reversed β-Oxidation Pathway

The β-Oxidation pathway, normally involved in the catabolism of fatty acids, can be functionally made to act as a fermentative, iterative, elongation pathway when driven by the activity of a trans-enoyl-CoA reductase. The terminal acyl-CoA reduction to alcohol can occur on substrates with varied chain lengths, leading to a broad distribution of fermentation products in vivo. Tight control of the average chain length and product profile is desirable as chain length greatly influences molecular properties and commercial value. Lacking a termination enzyme with a narrow chain length preference, we sought alternative factors that could influence the product profile and pathway flux in the iterative pathway. In this study, we reconstituted the reversed β-oxidation (R-βox) pathway in vitro with a purified tri-functional complex (FadBA) responsible for the thiolase, enoyl-CoA hydratase and hydroxyacyl-CoA dehydrogenase activities, a trans-enoyl-CoA reductase (TER), and an acyl-CoA reductase (ACR). Using this system, we determined the rate limiting step of the elongation cycle and demonstrated that by controlling the ratio of these three enzymes and the ratio of NADH and NADPH, we can influence the average chain length of the alcohol product profile.

A comparative analysis of mitochondrial ORFs provides new insights on expansion of mitochondrial genome size in Arcidae

BACKGROUND

Arcidae, comprising about 260 species of ark shells, is an ecologically and economically important lineage of bivalve mollusks. Interestingly, mitochondrial genomes of several Arcidae species are 2-3 times larger than those of most bilaterians, and are among the largest bilaterian mitochondrial genomes reported to date. The large mitochondrial genome size is mainly due to expansion of unassigned regions (regions that are functionally unassigned). Previous work on unassigned regions of Arcidae mtDNA genomes has focused on nucleotide-level analyses to observe sequence characteristics, however the origin of expansion remains unclear.

RESULTS

We assembled six new mitogenomes and sequenced six transcriptomes of Scapharca broughtonii to identify conserved functional ORFs that are transcribed in unassigned regions. Sixteen lineage-specific ORFs with different copy numbers were identified from seven Arcidae species, and 11 of 16 ORFs were expressed and likely biologically active. Unassigned regions of 32 Arcidae mitogenomes were compared to verify the presence of these novel mitochondrial ORFs and their distribution. Strikingly, multiple structural analyses and functional prediction suggested that these additional mtDNA-encoded proteins have potential functional significance. In addition, our results also revealed that the ORFs have a strong connection to the expansion of Arcidae mitochondrial genomes and their large-scale duplication play an important role in multiple expansion events. We discussed the possible origin of ORFs and hypothesized that these ORFs may originate from duplication of mitochondrial genes.

CONCLUSIONS

The presence of lineage-specific mitochondrial ORFs with transcriptional activity and potential functional significance supports novel features for Arcidae mitochondrial genomes. Given our observation and analyses, these ORFs may be products of mitochondrial gene duplication. These findings shed light on the origin and function of novel mitochondrial genes in bivalves and provide new insights into evolution of mitochondrial genome size in metazoans.

De novo transcriptome assembly of Conium maculatum L. to identify candidate genes for coniine biosynthesis

Poison hemlock (Conium maculatum L.) is a notorious weed containing the potent alkaloid coniine. Only some of the enzymes in the coniine biosynthesis have so far been characterized. Here, we utilize the next-generation RNA sequencing approach to report the first-ever transcriptome sequencing of five organs of poison hemlock: developing fruit, flower, root, leaf, and stem. Using a de novo assembly approach, we derived a transcriptome assembly containing 123,240 transcripts. The assembly is deemed high quality, representing over 88% of the near-universal ortholog genes of the Eudicots clade. Nearly 80% of the transcripts were functionally annotated using a combination of three approaches. The current study focuses on describing the coniine pathway by identifying in silico transcript candidates for polyketide reductase, L-alanine:5-keto-octanal aminotransferase, γ-coniceine reductase, and S-adenosyl-L-methionine:coniine methyltransferase. In vitro testing will be needed to confirm the assigned functions of the selected candidates.

Protein cost minimization promotes the emergence of coenzyme redundancy

Metabolism relies on a small class of molecules (coenzymes) that serve as universal donors and acceptors of key chemical groups and electrons. Although metabolic networks crucially depend on structurally redundant coenzymes [e.g., NAD(H) and NADP(H)] associated with different enzymes, the criteria that led to the emergence of this redundancy remain poorly understood. Our combination of modeling and structural and sequence analysis indicates that coenzyme redundancy may not be essential for metabolism but could rather constitute an evolved strategy promoting efficient usage of enzymes when biochemical reactions are near equilibrium. Our work suggests that early metabolism may have operated with fewer coenzymes and that adaptation for metabolic efficiency may have driven the rise of coenzyme diversity in living systems.

Coenzymes distribute a variety of chemical moieties throughout cellular metabolism, participating in group (e.g., phosphate and acyl) and electron transfer. For a variety of reactions requiring acceptors or donors of specific resources, there often exist degenerate sets of molecules [e.g., NAD(H) and NADP(H)] that carry out similar functions. Although the physiological roles of various coenzyme systems are well established, it is unclear what selective pressures may have driven the emergence of coenzyme redundancy. Here, we use genome-wide metabolic modeling approaches to decompose the selective pressures driving enzymatic specificity for either NAD(H) or NADP(H) in the metabolic network of Escherichia coli. We found that few enzymes are thermodynamically constrained to using a single coenzyme, and in principle a metabolic network relying on only NAD(H) is feasible. However, structural and sequence analyses revealed widespread conservation of residues that retain selectivity for either NAD(H) or NADP(H), suggesting that additional forces may shape specificity. Using a model accounting for the cost of oxidoreductase enzyme expression, we found that coenzyme redundancy universally reduces the minimal amount of protein required to catalyze coenzyme-coupled reactions, inducing individual reactions to strongly prefer one coenzyme over another when reactions are near thermodynamic equilibrium. We propose that protein minimization generically promotes coenzyme redundancy and that coenzymes typically thought to exist in a single pool (e.g., coenzyme A [CoA]) may exist in more than one form (e.g., dephospho-CoA).

Rossmann-toolbox: a deep learning-based protocol for the prediction and design of cofactor specificity in Rossmann fold proteins

The Rossmann fold enzymes are involved in essential biochemical pathways such as nucleotide and amino acid metabolism. Their functioning relies on interaction with cofactors, small nucleoside-based compounds specifically recognized by a conserved βαβ motif shared by all Rossmann fold proteins. While Rossmann methyltransferases recognize only a single cofactor type, the S-adenosylmethionine, the oxidoreductases, depending on the family, bind nicotinamide (nicotinamide adenine dinucleotide, nicotinamide adenine dinucleotide phosphate) or flavin-based (flavin adenine dinucleotide) cofactors. In this study, we showed that despite its short length, the βαβ motif unambiguously defines the specificity towards the cofactor. Following this observation, we trained two complementary deep learning models for the prediction of the cofactor specificity based on the sequence and structural features of the βαβ motif. A benchmark on two independent test sets, one containing βαβ motifs bearing no resemblance to those of the training set, and the other comprising 38 experimentally confirmed cases of rational design of the cofactor specificity, revealed the nearly perfect performance of the two methods. The Rossmann-toolbox protocols can be accessed via the webserver at https://lbs.cent.uw.edu.pl/rossmann-toolbox and are available as a Python package at https://github.com/labstructbioinf/rossmann-toolbox.

Transcriptor: a comprehensive platform for annotation of the enzymatic functions of transcripts

MOTIVATION

Rapid advances in sequencing technology have resulted huge increases in the accessibility of sequencing data. Moreover, researchers are focusing more on organisms that lack a reference genome. However, few easy-to-use web servers focusing on annotations of enzymatic functions are available. Accordingly, in this study, we describe Transcriptor, a novel platform for annotating transcripts encoding enzymes.

RESULTS

The transcripts were evaluated using more than 300 000 in-house enzymatic reactions through bridges of Enzyme Commission numbers. Transcriptor also enabled ontology term identification and along with associated enzymes, visualization and prediction of domains and annotation of regulatory structure, such as long noncoding RNAs, which could facilitate the discovery of new functions in model or nonmodel species. Transcriptor may have applications in elucidation of the roles of organs transcriptomes and secondary metabolite biosynthesis in organisms lacking a reference genome.

AVAILABILITY AND IMPLEMENTATION

Transcriptor is available at http://design.rxnfinder.org/transcriptor/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In silico analysis of phylogeny, structure, and function of arsenite oxidase from unculturable microbiome of arsenic contaminated soil

Background

Arsenite oxidase (EC 1.20.2.1) is a metalloenzyme that catalyzes the oxidation of arsenite into lesser toxic arsenate. In this study, 78 amino acid sequences of arsenite oxidase from unculturable bacteria available in metagenomic data of arsenic-contaminated soil have been characterized by using standard bioinformatics tools to investigate its phylogenetic relationships, three-dimensional structure and functional parameters.

Results

The phylogenetic relationship of all arsenite oxidase from unculturable microorganisms was revealed their closeness to bacterial order Rhizobiales. The higher aliphatic content showed that these enzymes are thermostable and could be used for in situ bioremediation. A representative protein from each phylogenetic cluster was analysed for secondary structure arrangements which indicated the presence of α-helices (~63%), β-sheets (57–60%) and turns (13–15%). The validated 3D models suggested that these proteins are hetero-dimeric with two chains whereas alpha chain is the main catalytic subunit which binds with arsenic oxides. Three representative protein models were deposited in Protein Model Database. The query enzymes were predicted with two conserved motifs, one is Rieske 3Fe-4S and the other is molybdopterin protein.

Conclusions

Computational analysis of protein interactome revealed the protein partners might be involved in the whole process of arsenic detoxification by Rhizobiales. The overall report is unique to the best of our knowledge, and the importance of this study is to understand the theoretical aspects of the structure and functions of arsenite oxidase in unculturable bacteria residing in arsenic-contaminated sites.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-021-00146-x.

Functional effects of protein variants

Genetic and other variations frequently affect protein functions. Scientific articles can contain confusing descriptions about which function or property is affected, and in many cases the statements are pure speculation without any experimental evidence. To clarify functional effects of protein variations of genetic or non-genetic origin, a systematic conceptualisation and framework are introduced. This framework describes protein functional effects on abundance, activity, specificity and affinity, along with countermeasures, which allow cells, tissues and organisms to tolerate, avoid, repair, attenuate or resist (TARAR) the effects. Effects on abundance discussed include gene dosage, restricted expression, mis-localisation and degradation. Enzymopathies, effects on kinetics, allostery and regulation of protein activity are subtopics for the effects of variants on activity. Variation outcomes on specificity and affinity comprise promiscuity, specificity, affinity and moonlighting. TARAR mechanisms redress variations with active and passive processes including chaperones, redundancy, robustness, canalisation and metabolic and signalling rewiring. A framework for pragmatic protein function analysis and presentation is introduced. All of the mechanisms and effects are described along with representative examples, most often in relation to diseases. In addition, protein function is discussed from evolutionary point of view. Application of the presented framework facilitates unambiguous, detailed and specific description of functional effects and their systematic study.

Computational-based insights into the phylogeny, structure, and function of Rhodococcus alkane-1-monooxygenase

Alkane-1-monooxygenase of alkanotrophic Rhodococcus species has been characterized using standard bioinformatics tools to investigate phylogenetic relationships, and three-dimensional structure and functions. Results revealed that activity of the Rhodococcus alkane-1-monooxygenase would be optimum in alkaline pH as their isoelectric points were in the range of 7.5 to 9. Higher aliphatic index (87 to 95) indicated that these enzymes are thermostable. Extinction coefficient of the enzyme varied from 68,793 to 1,25,820 M^-1 cm^-1 and average molecular weight was 45 kDa. Secondary structures predicted maximum alpha-helical content rather than the other conformations such as sheets or turns. The instability index (II) of most stable query protein was 39.7% which was lowest among all 76 proteins analysed in this study. Predicted 3D structure of query protein revealed that it contains homodimer polypeptides. The suitable template for query protein was Flavin-dependent luciferase-type alkane monooxygenase. The presence of 98.3% amino acid residues in Ramachandran plot was determined in 3-D protein model which confirmed the model feasibility. The predicted model contains 12% more α-helix than template protein which indicated towards membrane localization of the protein. The protein interactome partners of predicted model were determined as FMN-dependent oxidoreductase, molybdopterin, nuclear transport factor, and peroxiredoxin. The predicted tertiary model of R. rhodochrous alkane-1-monooxygenase (OOL33526.1) was deposited in Protein Model Database (Accession No.: PM0083166). The overall report is unique to best of our knowledge, and the importance of this study is to understand the theoretical aspects of structure and functions of alkane-1-monooxygenase of hydrocarbonoclastic strains of Rhodococcus.

Characterization and Application of a Robust Glucose Dehydrogenase from Paenibacillus pini for Cofactor Regeneration in Biocatalysis

Glucose dehydrogenases are important auxiliary enzymes in biocatalysis, employed in the regeneration of reduced nicotinamide cofactors for oxidoreductase catalysed reactions. Here we report the identification and characterization of a novel glucose-1-dehydrogenase (GDH) from Paenibacillus pini that prefers NAD⁺ as cofactor over NADP⁺. The purified recombinant P. pini GDH displayed a specific activity of 247.5 U/mg. The enzyme was stable in the pH range 4-8.5 and exhibited excellent thermostability till 50 °C for 24 h, even in the absence of NaCl or glycerol. Paenibacillus pini GDH was also tolerant to organic solvents, demonstrating its potential for recycling cofactors for biotransformation. The potential application of the enzyme was evaluated by coupling with a NAD⁺-dependent alcohol dehydrogenase for the reduction of acetophenone and ethyl-4-chloro-3-oxo-butanoate. Conversions higher than 95% were achieved within 2 h with low enzyme loading using lyophilized cell lysate, suggesting that P. pini GDH could be highly effective for recycling NADH in redox biocatalysis.

Identification of coenzyme-binding proteins with machine learning algorithms

The coenzyme-binding proteins play a vital role in the cellular metabolism processes, such as fatty acid biosynthesis, enzyme and gene regulation, lipid synthesis, particular vesicular traffic, and β-oxidation donation of acyl-CoA esters. Based on the theory of Star Graph Topological Indices (SGTIs) of protein primary sequences, we proposed a method to develop a first classification model for predicting protein with coenzyme-binding properties. To simulate the properties of coenzyme-binding proteins, we created a dataset containing 2897 proteins, among 456 proteins functioned as coenzyme-binding activity. The SGTIs of peptide sequence were calculated with Sequence to Star Network (S2SNet) application. We used the SGTIs as inputs to several classification techniques with a machine learning software - Weka. A Random Forest classifier based on 3 features of the embedded and non-embedded graphs was identified as the best predictive model for coenzyme-binding proteins. This model developed was with the true positive (TP) rate of 91.7%, false positive (FP) rate of 7.6%, and Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.971. The prediction of new coenzyme-binding activity proteins using this model could be useful for further drug development or enzyme metabolism researches.

Advances in Protein Super-Secondary Structure Prediction and Application to Protein Structure Prediction

Due to the advancement in various sequencing technologies, the gap between the number of protein sequences and the number of experimental protein structures is ever increasing. Community-wide initiatives like CASP have resulted in considerable efforts in the development of computational methods to accurately model protein structures from sequences. Sequence-based prediction of super-secondary structure has direct application in protein structure prediction, and there have been significant efforts in the prediction of super-secondary structure in the last decade. In this chapter, we first introduce the protein structure prediction problem and highlight some of the important progress in the field of protein structure prediction. Next, we discuss recent methods for the prediction of super-secondary structures. Finally, we discuss applications of super-secondary structure prediction in structure prediction/analysis of proteins. We also discuss prediction of protein structures that are composed of simple super-secondary structure repeats and protein structures that are composed of complex super-secondary structure repeats. Finally, we also discuss the recent trends in the field.

Origins and structure of chloroplastic and mitochondrial plant protoporphyrinogen oxidases: implications for the evolution of herbicide resistance

Protoporphyrinogen IX oxidase (PPO)-inhibiting herbicides are effective tools to control a broad spectrum of weeds, including those that have evolved resistance to glyphosate. Their utility is being threatened by the appearance of biotypes that are resistant to PPO inhibitors. While the chloroplastic PPO1 isoform is thought to be the primary target of PPO herbicides, evolved resistance mechanisms elucidated to date are associated with changes to the mitochondrial PPO2 isoform, suggesting that the importance of PPO2 has been underestimated. Our investigation of the evolutionary and structural biology of plant PPOs provides some insight into the potential reasons why PPO2 is the preferred target for evolution of resistance. The most common target-site mutation imparting resistance involved the deletion of a key glycine codon. The genetic environment that facilitates this deletion is apparently only present in the gene encoding PPO2 in a few species. Additionally, both species with this mutation (Amaranthus tuberculatus and Amaranthus palmeri) have dual targeting of PPO2 to both the chloroplast and the mitochondria, which might be a prerequisite to impart herbicide resistance. The most recent target-site mutations have substituted a key arginine residue involved in stabilizing the substrate in the catalytic domain of PPO2. This arginine is highly conserved across all plant PPOs, suggesting that its substitution could be equally likely on PPO1 and PPO2, yet it has only occurred on PPO2, underscoring the importance of this isoform for the evolution of herbicide resistance. © 2017 Society of Chemical Industry.

Fast automated reconstruction of genome-scale metabolic models for microbial species and communities

Genome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism, for model-guided re-engineering, and unraveling cross-feeding in microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual curation required to obtain good quality models. Here, we present an automated tool, CarveMe, for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We show that CarveMe models perform closely to manually curated models in reproducing experimental phenotypes (substrate utilization and gene essentiality). Additionally, we build a collection of 74 models for human gut bacteria and test their ability to reproduce growth on a set of experimentally defined media. Finally, we create a database of 5587 bacterial models and demonstrate its potential for fast generation of microbial community models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.

Protein engineering of oxidoreductases utilizing nicotinamide-based coenzymes, with applications in synthetic biology

Two natural nicotinamide-based coenzymes (NAD and NADP) are indispensably required by the vast majority of oxidoreductases for catabolism and anabolism, respectively. Most NAD(P)-dependent oxidoreductases prefer one coenzyme as an electron acceptor or donor to the other depending on their different metabolic roles. This coenzyme preference associated with coenzyme imbalance presents some challenges for the construction of high-efficiency in vivo and in vitro synthetic biology pathways. Changing the coenzyme preference of NAD(P)-dependent oxidoreductases is an important area of protein engineering, which is closely related to product-oriented synthetic biology projects. This review focuses on the methodology of nicotinamide-based coenzyme engineering, with its application in improving product yields and decreasing production costs. Biomimetic nicotinamide-containing coenzymes have been proposed to replace natural coenzymes because they are more stable and less costly than natural coenzymes. Recent advances in the switching of coenzyme preference from natural to biomimetic coenzymes are also covered in this review. Engineering coenzyme preferences from natural to biomimetic coenzymes has become an important direction for coenzyme engineering, especially for in vitro synthetic pathways and in vivo bioorthogonal redox pathways.

A protein complex bearing an oxidase with napthalene dihydrodiol dehydrogenase activity is induced in Mucor circinelloides strain YR-1 during growth on polycyclic aromatic compounds

Fungi are organisms capable of growing in a myriad of conditions and respond to counteract environmental cues. Several locations in the world are polluted with oil and its derivatives, and some microorganisms tolerant to these compounds have been isolated. Some fungi can grow in the presence of molecules such as polycyclic aromatic hydrocarbons as sole carbon sources. In this report, we further characterized the induced enzymes with phenanthrene from Mucor circinelloides YR-1 strain, isolated from a polluted field near a petrochemical facility in México. We identified a putative oxidase that is induced when growth with phenanthrene as sole carbon source at a pH of 8.5 and is NADP⁺ dependent. We show that this enzyme bears naphthalene dihydrodiol dehydrogenase activity with substrate preference for the cis-naphthalene over the trans-naphthalene, with an optimal pH in the range of 8-10. Mass spectrometry analysis revealed that the induced enzyme belongs to the NADP⁺ oxidase family enzymes with the typical Rossmann-fold for NADP⁺ binding. This enzyme seems to form a high molecular weight structure (~ 541 kDa) and with a monomer of 57 kDa, suggesting that the multimer is constituted of 10 subunits. Our findings contribute to understanding of the roles that dihydrodiol dehydrogenases have in organisms exposed to toxic compounds in the environment and can regulate their expression.

Identification of new channels by systematic analysis of the mitochondrial outer membrane

Channels in the mitochondrial outer membrane exchange metabolites, ions, and proteins with the rest of the cell. Kruger et al. identify several new types of channel and suggest that the outer mitochondrial membrane is a more selective molecular sieve with a greater variety of channel-forming proteins than previously appreciated.

The mitochondrial outer membrane is essential for communication between mitochondria and the rest of the cell and facilitates the transport of metabolites, ions, and proteins. All mitochondrial outer membrane channels known to date are β-barrel membrane proteins, including the abundant voltage-dependent anion channel and the cation-preferring protein-conducting channels Tom40, Sam50, and Mdm10. We analyzed outer membrane fractions of yeast mitochondria and identified four new channel activities: two anion-preferring channels and two cation-preferring channels. We characterized the cation-preferring channels at the molecular level. The mitochondrial import component Mim1 forms a channel that is predicted to have an α-helical structure for protein import. The short-chain dehydrogenase-related protein Ayr1 forms an NADPH-regulated channel. We conclude that the mitochondrial outer membrane contains a considerably larger variety of channel-forming proteins than assumed thus far. These findings challenge the traditional view of the outer membrane as an unspecific molecular sieve and indicate a higher degree of selectivity and regulation of metabolite fluxes at the mitochondrial boundary.

Coupled reactions by coupled enzymes: alcohol to lactone cascade with alcohol dehydrogenase-cyclohexanone monooxygenase fusions

The combination of redox enzymes for redox-neutral cascade reactions has received increasing appreciation. An example is the combination of an alcohol dehydrogenase (ADH) with a cyclohexanone monooxygenase (CHMO). The ADH can use NADP⁺ to oxidize cyclohexanol to form cyclohexanone and NADPH. Both products are then used by CHMO to produce ε-caprolactone. In this study, these two redox-complementary enzymes were fused, to create a self-sufficient bifunctional enzyme that can convert alcohols to esters or lactones. Three different ADH genes were fused to a gene coding for a thermostable CHMO, in both orientations (ADH-CHMO and CHMO-ADH). All six fusion enzymes could be produced and purified. For two of the three ADHs, we found a clear difference between the two orientations: one that showed the expected ADH activity, and one that showed low to no activity. The ADH activity of each fusion enzyme correlated with its oligomerization state. All fusions retained CHMO activity, and stability was hardly affected. The TbADH-TmCHMO fusion was selected to perform a cascade reaction, producing ε-caprolactone from cyclohexanol. By circumventing substrate and product inhibition, a > 99% conversion of 200 mM cyclohexanol could be achieved in 24 h, with > 13,000 turnovers per fusion enzyme molecule.

Exploring complex cellular phenotypes and model-guided strain design with a novel genome-scale metabolic model of Clostridium thermocellum DSM 1313 implementing an adjustable cellulosome

BACKGROUND

Clostridium thermocellum is a gram-positive thermophile that can directly convert lignocellulosic material into biofuels. The metabolism of C. thermocellum contains many branches and redundancies which limit biofuel production, and typical genetic techniques are time-consuming. Further, the genome sequence of a genetically tractable strain C. thermocellum DSM 1313 has been recently sequenced and annotated. Therefore, developing a comprehensive, predictive, genome-scale metabolic model of DSM 1313 is desired for elucidating its complex phenotypes and facilitating model-guided metabolic engineering.

RESULTS

We constructed a genome-scale metabolic model iAT601 for DSM 1313 using the KEGG database as a scaffold and an extensive literature review and bioinformatic analysis for model refinement. Next, we used several sets of experimental data to train the model, e.g., estimation of the ATP requirement for growth-associated maintenance (13.5 mmol ATP/g DCW/h) and cellulosome synthesis (57 mmol ATP/g cellulosome/h). Using our tuned model, we investigated the effect of cellodextrin lengths on cell yields, and could predict in silico experimentally observed differences in cell yield based on which cellodextrin species is assimilated. We further employed our tuned model to analyze the experimentally observed differences in fermentation profiles (i.e., the ethanol to acetate ratio) between cellobiose- and cellulose-grown cultures and infer regulatory mechanisms to explain the phenotypic differences. Finally, we used the model to design over 250 genetic modification strategies with the potential to optimize ethanol production, 6155 for hydrogen production, and 28 for isobutanol production.

CONCLUSIONS

Our developed genome-scale model iAT601 is capable of accurately predicting complex cellular phenotypes under a variety of conditions and serves as a high-quality platform for model-guided strain design and metabolic engineering to produce industrial biofuels and chemicals of interest.

A sacrificial millipede altruistically protects its swarm using a drone blood enzyme, mandelonitrile oxidase

Soldiers of some eusocial insects exhibit an altruistic self-destructive defense behavior in emergency situations when attacked by large enemies. The swarm-forming invasive millipede, Chamberlinius hualienensis, which is not classified as eusocial animal, exudes irritant chemicals such as benzoyl cyanide as a defensive secretion. Although it has been thought that this defensive chemical was converted from mandelonitrile, identification of the biocatalyst has remained unidentified for 40 years. Here, we identify the novel blood enzyme, mandelonitrile oxidase (ChuaMOX), which stoichiometrically catalyzes oxygen consumption and synthesis of benzoyl cyanide and hydrogen peroxide from mandelonitrile. Interestingly the enzymatic activity is suppressed at a blood pH of 7, and the enzyme is segregated by membranes of defensive sacs from mandelonitrile which has a pH of 4.6, the optimum pH for ChuaMOX activity. In addition, strong body muscle contractions are necessary for de novo synthesis of benzoyl cyanide. We propose that, to protect its swarm, the sacrificial millipede also applies a self-destructive defense strategy—the endogenous rupturing of the defensive sacs to mix ChuaMOX and mandelonitrile at an optimum pH. Further study of defensive systems in primitive arthropods will pave the way to elucidate the evolution of altruistic defenses in the animal kingdom.

Transcription factor Rex in regulation of pathophysiology in oral pathogens

The NAD(+) and NADH-sensing transcriptional regulator Rex is widely conserved across gram-positive bacteria. Rex monitors cellular redox poise and controls the expression of genes/operons involved in diverse pathways including alternative fermentation, oxidative stress responses, and biofilm formation. The oral cavity undergoes frequent and drastic fluctuations in nutrient availability, pH, temperature, oxygen tension, saliva, and shear forces. The oral streptococci are major colonizers of oral mucosa and tooth surfaces and include commensals as well as opportunistic pathogens, including the primary etiological agent of dental caries, Streptococcus mutans. Current understanding of the Rex regulon in oral bacteria is mostly based on studies in S. mutans and endodontic pathogen Enterococcus faecalis. Indeed, other oral bacteria encode homologs of the Rex protein and much is to be gleaned from more in-depth studies. Our current understanding has Rex positioned at the interface of oxygen and energy metabolism. In biofilms, heterogeneous oxygen tension influences the ratio of intracellular NADH and NAD(+) , which is finely tuned through glycolysis and fermentation. In S. mutans, Rex regulates the expression of glycolytic enzyme NAD(+) -dependent glyceraldehyde 3-phosphate dehydrogenase, and NADH-dependent fermentation enzymes/complexes lactate dehydrogenase, pyruvate dehydrogenase, alcohol-acetaldehyde dehydrogenase, and fumarate reductase. In addition, Rex controls the expression of NADH oxidase, a major enzyme used to eliminate oxidative stress and regenerate NAD(+) . Here, we summarize recent studies carried out on the Rex regulators in S. mutans and E. faecalis. This research has important implications for understanding how Rex monitors redox balance and optimizes fermentation pathways for survival and subsequent pathogenicity.

Substitutions at the cofactor phosphate-binding site of a clostridial alcohol dehydrogenase lead to unexpected changes in substrate specificity

Changing the cofactor specificity of an enzyme from nicotinamide adenine dinucleotide 2′-phosphate (NADPH) to the more abundant NADH is a common strategy for increasing overall enzyme efficiency in microbial metabolic engineering. The aim of this study was to switch the cofactor specificity of the primary–secondary alcohol dehydrogenase from Clostridium autoethanogenum, a bacterium with considerable promise for the bio-manufacturing of fuels and other petrochemicals, from strictly NADPH-dependent to NADH-dependent. We used insights from a homology model to build a site-saturation library focussed on residue S199, the position deemed most likely to disrupt binding of the 2′-phosphate of NADPH. Although the CaADH(S199X) library did not yield any NADH-dependent enzymes, it did reveal that substitutions at the cofactor phosphate-binding site can cause unanticipated changes in the substrate specificity of the enzyme. Using consensus-guided site-directed mutagenesis, we were able to create an enzyme that was stringently NADH-dependent, albeit with a concomitant reduction in activity. This study highlights the role that distal residues play in substrate specificity and the complexity of enzyme–cofactor interactions.

Using a Label Free Quantitative Proteomics Approach to Identify Changes in Protein Abundance in Multidrug-Resistant Mycobacterium tuberculosis

Reports in recent years indicate that the increasing emergence of resistance to drugs be using to TB treatment. The resistance to them severely affects to options for effective treatment. The emergence of multidrug-resistant tuberculosis has increased interest in understanding the mechanism of drug resistance in M. tuberculosis and the development of new therapeutics, diagnostics and vaccines. In this study, a label-free quantitative proteomics approach has been used to analyze proteome of multidrug-resistant and susceptible clinical isolates of M. tuberculosis and identify differences in protein abundance between the two groups. With this approach, we were able to identify a total of 1,583 proteins. The majority of identified proteins have predicted roles in lipid metabolism, intermediary metabolism, cell wall and cell processes. Comparative analysis revealed that 68 proteins identified by at least two peptides showed significant differences of at least twofolds in relative abundance between two groups. In all protein differences, the increase of some considering proteins such as NADH dehydrogenase, probable aldehyde dehydrogenase, cyclopropane mycolic acid synthase 3, probable arabinosyltransferase A, putative lipoprotein, uncharacterized oxidoreductase and six membrane proteins in resistant isolates might be involved in the drug resistance and to be potential diagnostic protein targets. The decrease in abundance of proteins related to secretion system and immunogenicity (ESAT-6-like proteins, ESX-1 secretion system associated proteins, O-antigen export system and MPT63) in the multidrug-resistant strains can be a defensive mechanism undertaken by the resistant cell.

Retinol dehydrogenases: membrane-bound enzymes for the visual function

Retinoid metabolism is important for many physiological functions, such as differenciation, growth, and vision. In the visual context, after the absorption of light in rod photoreceptors by the visual pigment rhodopsin, 11-cis retinal is isomerized to all-trans retinal. This retinoid subsequently undergoes a series of modifications during the visual cycle through a cascade of reactions occurring in photoreceptors and in the retinal pigment epithelium. Retinol dehydrogenases (RDHs) are enzymes responsible for crucial steps of this visual cycle. They belong to a large family of proteins designated as short-chain dehydrogenases/reductases. The structure of these RDHs has been predicted using modern bioinformatics tools, which allowed to propose models with similar structures including a common Rossman fold. These enzymes undergo oxidoreduction reactions, whose direction is dictated by the preference and concentration of their individual cofactor (NAD(H)/NADP(H)). This review presents the current state of knowledge on functional and structural features of RDHs involved in the visual cycle as well as knockout models. RDHs are described as integral or peripheral enzymes. A topology model of the membrane binding of these RDHs via their N- and (or) C-terminal domain has been proposed on the basis of their individual properties. Membrane binding is a crucial issue for these enzymes because of the high hydrophobicity of their retinoid substrates.

Uncovering rare NADH-preferring ketol-acid reductoisomerases

All members of the ketol-acid reductoisomerase (KARI) enzyme family characterized to date have been shown to prefer the nicotinamide adenine dinucleotide phosphate hydride (NADPH) cofactor to nicotinamide adenine dinucleotide hydride (NADH). However, KARIs with the reversed cofactor preference are desirable for industrial applications, including anaerobic fermentation to produce branched-chain amino acids. By applying insights gained from structural and engineering studies of this enzyme family to a comprehensive multiple sequence alignment of KARIs, we identified putative NADH-utilizing KARIs and characterized eight whose catalytic efficiencies using NADH were equal to or greater than NADPH. These are the first naturally NADH-preferring KARIs reported and demonstrate that this property has evolved independently multiple times, using strategies unlike those used previously in the laboratory to engineer a KARI cofactor switch.