HLA Class I Supertype Classification Based on Structural Similarity.

HLA class I proteins, a critical component in adaptive immunity, bind and present intracellular Ags to CD8+ T cells. The extreme polymorphism of HLA genes and associated peptide binding specificities leads to challenges in various endeavors, including neoantigen vaccine development, disease association studies, and HLA typing. Supertype classification, defined by clustering functionally similar HLA alleles, has proven helpful in reducing the complexity of distinguishing alleles. However, determining supertypes via experiments is impractical, and current in silico classification methods exhibit limitations in stability and functional relevance. In this study, by incorporating three-dimensional structures we present a method for classifying HLA class I molecules with improved breadth, accuracy, stability, and flexibility. Critical for these advances is our finding that structural similarity highly correlates with peptide binding specificity. The new classification should be broadly useful in peptide-based vaccine development and HLA-disease association studies.

Predicted structural proteome of Sphagnum divinum and proteome-scale annotation.

MOTIVATION: Sphagnum-dominated peatlands store a substantial amount of terrestrial carbon. The genus is undersampled and under-studied. No experimental crystal structure from any Sphagnum species exists in the Protein Data Bank and fewer than 200 Sphagnum-related genes have structural models available in the AlphaFold Protein Structure Database. Tools and resources are needed to help bridge these gaps, and to enable the analysis of other structural proteomes now made possible by accurate structure prediction. RESULTS: We present the predicted structural proteome (25 134 primary transcripts) of Sphagnum divinum computed using AlphaFold, structural alignment results of all high-confidence models against an annotated nonredundant crystallographic database of over 90,000 structures, a structure-based classification of putative Enzyme Commission (EC) numbers across this proteome, and the computational method to perform this proteome-scale structure-based annotation. AVAILABILITY AND IMPLEMENTATION: All data and code are available in public repositories, detailed at https://github.com/BSDExabio/SAFA. The structural models of the S. divinum proteome have been deposited in the ModelArchive repository at https://modelarchive.org/doi/10.5452/ma-ornl-sphdiv.

HLA-Clus: HLA class I clustering based on 3D structure.

BACKGROUND: In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria. RESULTS: The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved. CONCLUSIONS: The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository ( https://github.com/yshen25/HLA-Clus ).

OpenMDlr: parallel, open-source tools for general protein structure modeling and refinement from pairwise distances.

SUMMARY: Easy-to-use, open-source, general-purpose programs for modeling a protein structure from inter-atomic distances are needed for modeling from experimental data and refinement of predicted protein structures. OpenMDlr is an open-source Python package for modeling protein structures from pairwise distances between any atoms, and optionally, dihedral angles. We provide a user-friendly input format for harnessing modern biomolecular force fields in an easy-to-install package that can efficiently make use of multiple compute cores. AVAILABILITY AND IMPLEMENTATION: OpenMDlr is available at https://github.com/BSDExabio/OpenMDlr-amber. The package is written in Python (versions 3.x). All dependencies are open-source and can be installed with the Conda package management system. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptional Control of hgcAB by an ArsR-Like Regulator in Pseudodesulfovibrio mercurii ND132.

The hgcAB gene pair encodes mercury (Hg) methylation capability in a diverse group of microorganisms, but its evolution and transcriptional regulation remain unknown. Working from the possibility that the evolutionary function of HgcAB may not be Hg methylation, we test a possible link to arsenic resistance. Using model Hg methylator Pseudodesulfovibrio mercurii ND132, we evaluated transcriptional control of hgcAB by a putative ArsR encoded upstream and cotranscribed with hgcAB. This regulator shares homology with ArsR repressors of arsenic resistance and S-adenosylhomocysteine (SAH)-responsive regulators of methionine biosynthesis but is distinct from other ArsR/SahR proteins in P. mercurii. Using quantitative PCR (qPCR) and RNA sequencing (RNA-seq) transcriptome analyses, we confirmed this ArsR regulates hgcAB transcription and is responsive to arsenic and SAH. Additionally, RNA-seq indicated a possible link between hgcAB activity and arsenic transformations, with significant upregulation of other ArsR-regulated arsenic resistance operons alongside hgcAB. Interestingly, wild-type ND132 was less sensitive to As(V) (but not As(III)) than an hgcAB knockout strain, supporting the idea that hgcAB may be linked to arsenic resistance. Arsenic significantly impacted rates of Hg methylation by ND132; however, responses varied with culture conditions. Differences in growth and metabolic activity did not account for arsenic impacts on methylation. While arsenic significantly increased hgcAB expression, hgcAB gene and transcript abundance was not a good predictor of Hg methylation rates. Taken together, these results support the idea that Hg and As cycling are linked in P. mercurii ND132. Our results may hold clues to the evolution of hgcAB and the controls on Hg methylation in nature. IMPORTANCE This work reveals a link between microbial mercury methylation and arsenic resistance and may hold clues to the evolution of mercury methylation genes (hgcAB). Microbes with hgcAB produce methylmercury, a strong neurotoxin that readily accumulates in the food web. This study addresses a critical gap in our understanding about the environmental factors that control hgcAB expression. We show that hgcAB expression is controlled by an ArsR-like regulator responsive to both arsenic and S-adenosylhomocysteine in our model organism, Pseudodesulfovibrio mercurii ND132. Exposure to arsenic also significantly impacted Pseudodesulfovibrio mercurii ND132 mercury methylation rates. However, expression of hgcAB was not always a good predictor of Hg methylation rates, highlighting the roles of Hg bioavailability and other biochemical mechanisms in methylmercury production. This study improves our understanding of the controls on hgcAB expression, which is needed to better predict environmental methylmercury production.

Multidrug Efflux Pumps and the Two-Faced Janus of Substrates and Inhibitors.

Antibiotics are miracle drugs that can cure infectious bacterial diseases. However, their utility is challenged by antibiotic-resistant bacteria emerging in clinics and straining modern medicine and our ways of life. Certain bacteria such as Gram-negative (Gram(-)) and Mycobacteriales species are intrinsically resistant to most clinical antibiotics and can further gain multidrug resistance through mutations and plasmid acquisition. These species stand out by the presence of an additional external lipidic membrane, the outer membrane (OM), that is composed of unique glycolipids. Although formidable, the OM is a passive permeability barrier that can reduce penetration of antibiotics but cannot affect intracellular steady-state concentrations of drugs. The two-membrane envelopes are further reinforced by active efflux transporters that expel antibiotics from cells against their concentration gradients. The major mechanism of antibiotic resistance in Gram(-) pathogens is the active efflux of drugs, which acts synergistically with the low permeability barrier of the OM and other mutational and plasmid-borne mechanisms of antibiotic resistance.The synergy between active efflux and slow uptake offers Gram(-) bacteria an impressive degree of protection from potentially harmful chemicals, but it is also their Achilles heel. Kinetic studies have revealed that even small changes in the efficiency of either of the two factors can have dramatic effects on drug penetration into the cell. In line with these expectations, two major approaches to overcome this antibiotic resistance mechanism are currently being explored: (1) facilitation of antibiotic penetration across the outer membranes and (2) avoidance and inhibition of clinically relevant multidrug efflux pumps. Herein we summarize the progress in the latter approach with a focus on efflux pumps from the resistance-nodulation-division (RND) superfamily. The ability to export various substrates across the OM at the expense of the proton-motive force acting on the inner membrane and the engagement of accessory proteins for their functions are the major mechanistic advantages of these pumps. Both the RND transporters and their accessory proteins are being targeted in the discovery of efflux pump inhibitors, which in combination with antibiotics can potentiate antibacterial activities. We discuss intriguing relationships between substrates and inhibitors of efflux pumps, as these two types of ligands face similar barriers and binding sites in the transporters and accessory proteins and both types of activities often occur with the same chemical scaffold. Several distinct chemical classes of efflux inhibitors have been discovered that are as structurally diverse as the substrates of efflux pumps. Recent mechanistic insights, both empirical and computational, have led to the identification of features that distinguish OM permeators and efflux pump avoiders as well as efflux inhibitors from substrates. These findings suggest a path forward for optimizing the OM permeation and efflux-inhibitory activities in antibiotics and other chemically diverse compounds.

Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide-MHC Binding Predictions.

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell-based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2Db are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., K d < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell-based vaccines.

Lpp positions peptidoglycan at the AcrA-TolC interface in the AcrAB-TolC multidrug efflux pump.

The multidrug efflux pumps of Gram-negative bacteria are a class of complexes that span the periplasm, coupling both the inner and outer membranes to expel toxic molecules. The best-characterized example of these tripartite pumps is the AcrAB-TolC complex of Escherichia coli. However, how the complex interacts with the peptidoglycan (PG) cell wall, which is anchored to the outer membrane (OM) by Braun's lipoprotein (Lpp), is still largely unknown. In this work, we present molecular dynamics simulations of a complete, atomistic model of the AcrAB-TolC complex with the inner membrane, OM, and PG layers all present. We find that the PG localizes to the junction of AcrA and TolC, in agreement with recent cryo-tomography data. Free-energy calculations reveal that the positioning of PG is determined by the length and conformation of multiple Lpp copies anchoring it to the OM. The distance between the PG and OM measured in cryo-electron microscopy images of wild-type E. coli also agrees with the simulation-derived spacing. Sequence analysis of AcrA suggests a conserved role for interactions with PG in the assembly and stabilization of efflux pumps, one that may extend to other trans-envelope complexes as well.

Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases.

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. This approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking.

Mechanistic Investigation of Dimethylmercury Formation Mediated by a Sulfide Mineral Surface.

Mercury (Hg) pollution is a global environmental problem. The abiotic formation of dimethylmercury (DMeHg) from monomethylmercury (MMeHg) may account for a large portion of DMeHg in oceans. Previous experimental work has shown that abiotic formation of DMeHg from MMeHg can be facilitated by reduced sulfur groups on sulfide mineral surfaces. In that work, a mechanism was proposed in which neighboring MMeHg moieties bound to sulfide sites on a mineral surface react through an SN2-type mechanism to form DMeHg and incorporate the remaining Hg atoms into the mineral surface. Here, we perform density functional theory calculations to explore the mechanisms of DMeHg formation on the 110 surface of a CdS(s) (hawleyite) nanoparticle. We show that coordination of MMeHg substituents to adjacent reduced sulfur groups protruding from the surface indeed facilitates DMeHg formation and that the reaction proceeds through direct transmethylation from one MMeHg substituent to another. Coordination of Hg by multiple S atoms provides a transition-state stabilization and activates a C-Hg bond for methyl transfer. In addition, solvation effects play an important role in the surface reconstruction of the nanoparticle and in decreasing the energetic barrier for DMeHg formation relative to the corresponding reaction in vacuo.

Insight into the Catalytic Mechanism of GH11 Xylanase: Computational Analysis of Substrate Distortion Based on a Neutron Structure.

The reaction mechanism of biomass decomposition by xylanases remains the subject of debate. To clarify the mechanism we investigated the glycosylation step of GH11 xylanase, an enzyme that catalyzes the hydrolysis of lignocellulosic hemicellulose (xylan). Making use of a recent neutron crystal structure, which revealed the protonation states of relevant residues, we used ab initio quantum mechanics/molecular mechanics (QM/MM) calculations to determine the detailed reaction mechanism of the glycosylation step. In particular, our focus is on the controversial question of whether or not an oxocarbenium ion intermediate is formed on the reaction pathway. The calculations support the validity of a basic retaining mechanism within a double-displacement scheme. The estimated free energy barrier of this reaction is ∼18 kcal/mol with QM/MM-CCSD(T)/6-31(+)G**//MP2/6-31+G**/AMBER calculations, and the rate-determining step of the glycosylation is scission of the glycosidic bond after proton transfer from the acidic Glu177. The estimated lifetime of the oxocarbenium ion intermediate (on the order of tens of ps) and the secondary kinetic isotope effect suggest that there is no accumulation of this intermediate on the reaction path, although the intermediate can be transiently formed. In the enzyme-substrate (ES) complex, the carbohydrate structure of the xylose residue at the -1 subsite has a rather distorted (skewed) geometry, and this xylose unit at the active site has an apparent half-chair conformation when the oxocarbenium ion intermediate is formed. The major catalytic role of the protein environment is to orient residues that take part in the initial proton transfer. Because of a fine alignment of catalytic residues, the enzyme can accelerate the glycosylation reaction without paying a reorganization energy penalty.

Horizontal transfer of a pathway for coumarate catabolism unexpectedly inhibits purine nucleotide biosynthesis.

A microbe's ecological niche and biotechnological utility are determined by its specific set of co-evolved metabolic pathways. The acquisition of new pathways, through horizontal gene transfer or genetic engineering, can have unpredictable consequences. Here we show that two different pathways for coumarate catabolism failed to function when initially transferred into Escherichia coli. Using laboratory evolution, we elucidated the factors limiting activity of the newly acquired pathways and the modifications required to overcome these limitations. Both pathways required host mutations to enable effective growth with coumarate, but the necessary mutations differed. In one case, a pathway intermediate inhibited purine nucleotide biosynthesis, and this inhibition was relieved by single amino acid replacements in IMP dehydrogenase. A strain that natively contains this coumarate catabolism pathway, Acinetobacter baumannii, is resistant to inhibition by the relevant intermediate, suggesting that natural pathway transfers have faced and overcome similar challenges. Molecular dynamics simulation of the wild type and a representative single-residue mutant provide insight into the structural and dynamic changes that relieve inhibition. These results demonstrate how deleterious interactions can limit pathway transfer, that these interactions can be traced to specific molecular interactions between host and pathway, and how evolution or engineering can alleviate these limitations.

A Minimal Membrane Metal Transport System: Dynamics and Energetics of mer Proteins.

The mer operon in bacteria encodes a set of proteins and enzymes that impart resistance to environmental mercury toxicity by importing Hg2+ and reducing it to volatile Hg(0). Because the reduction occurs in the cytoplasm, mercuric ions must first be transported across the cytoplasmic membrane by one of a few known transporters. MerF is the smallest of these, containing only two transmembrane helices and two pairs of vicinal cysteines that coordinate mercuric ions. In this work, we use molecular dynamics simulations to characterize the dynamics of MerF in its apo and Hg2+ -bound states. We find that the apo state positions one of the cysteine pairs closer to the periplasmic side of the membrane, while in the bound state the same pair approaches the cytoplasmic side. This finding is consistent with the functional requirement of accepting Hg2+ from the periplasmic space, sequestering it on acceptance, and transferring it to the cytoplasm. Conformational changes in the TM helices facilitate the functional interaction of the two cysteine pairs. Free-energy calculations provide a barrier of 16 kcal/mol for the association of the periplasmic Hg2+ -bound protein MerP with MerF and 7 kcal/mol for the subsequent association of MerF's two cysteine pairs. Despite the significant conformational changes required to move the binding site across the membrane, coarse-grained simulations of multiple copies of MerF support the expectation that it functions as a monomer. Our results demonstrate how conformational changes and binding thermodynamics could lead to such a small membrane protein acting as an ion transporter. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.

The AQUA-MER databases and aqueous speciation server: A web resource for multiscale modeling of mercury speciation.

To assess the chemical reactivity, toxicity, and mobility of pollutants in the environment, knowledge of their species distributions is critical. Because their direct measurement is often infeasible, speciation modeling is widely adopted. Mercury (Hg) is a representative pollutant for which study of its speciation benefits from modeling. However, Hg speciation modeling is often hindered by a lack of reliable thermodynamic constants. Although computational chemistry (e.g., density functional theory [DFT]) can generate these constants, methods for directly coupling DFT and speciation modeling are not available. Here, we combine computational chemistry and continuum-scale modeling with curated online databases to ameliorate the problem of unreliable inputs to Hg speciation modeling. Our AQUA-MER databases and web server (https://aquamer.ornl.gov) provides direct speciation results by combining web-based interfaces to a speciation calculator, databases of thermodynamic constants, and a computational chemistry toolkit to estimate missing constants. Although Hg is presented as a concrete use case, AQUA-MER can also be readily applied to other elements. © 2019 Wiley Periodicals, Inc.

Environmental Mercury Chemistry - In Silico.

Mercury (Hg) is a global environmental contaminant. Major anthropogenic sources of Hg emission include gold mining and the burning of fossil fuels. Once deposited in aquatic environments, Hg can undergo redox reactions, form complexes with ligands, and adsorb onto particles. It can also be methylated by microorganisms. Mercury, especially its methylated form methylmercury, can be taken up by organisms, where it bioaccumulates and biomagnifies in the food chain, leading to detrimental effects on ecosystem and human health. In support of the recently enforced Minamata Convention on Mercury, a legally binding international convention aimed at reducing the anthropogenic emission of-and human exposure to-Hg, its global biogeochemical cycle must be understood. Thus, a detailed understanding of the molecular-level interactions of Hg is crucial. The ongoing rapid development of hardware and methods has brought computational chemistry to a point that it can usefully inform environmental science. This is particularly true for Hg, which is difficult to handle experimentally due to its ultratrace concentrations in the environment and its toxicity. The current account provides a synopsis of the application of computational chemistry to filling several major knowledge gaps in environmental Hg chemistry that have not been adequately addressed experimentally. Environmental Hg chemistry requires defining the factors that determine the relative affinities of different ligands for Hg species, as they are critical for understanding its speciation, transformation and bioaccumulation in the environment. Formation constants and the nature of bonding have been determined computationally for environmentally relevant Hg(II) complexes such as chlorides, hydroxides, sulfides and selenides, in various physical phases. Quantum chemistry has been used to determine the driving forces behind the speciation of Hg with hydrochalcogenide and halide ligands. Of particular importance is the detailed characterization of solvation effects. Indeed, the aqueous phase reverses trends in affinities found computationally in the gas phase. Computation has also been used to investigate complexes of methylmercury with (seleno)amino acids, providing a molecular-level understanding of the toxicological antagonism between Hg and selenium (Se). Furthermore, evidence is emerging that ice surfaces play an important role in Hg transport and transformation in polar and alpine regions. Therefore, the diffusion of Hg and its ions through an idealized ice surface has been characterized. Microorganisms are major players in environmental mercury cycling. Some methylate inorganic Hg species, whereas others demethylate methylmercury. Quantum chemistry has been used to investigate catalytic mechanisms of enzymatic Hg methylation and demethylation. The complex interplay between the myriad chemical reactions and transport properties both in and outside microbial cells determines net biogeochemical cycling. Prospects for scaling up molecular work to obtain a mechanistic understanding of Hg cycling with comprehensive multiscale biogeochemical modeling are also discussed.

Molecular Dynamics Simulation of the Structures, Dynamics, and Aggregation of Dissolved Organic Matter.

Dissolved organic matter (DOM) plays a significant role in the transport and transformation of pollutants in the aquatic environment. However, the experimental characterization of DOM has been limited mainly to bulk properties, and the molecular-level interactions among various components of DOM remain to be fully characterized. Here, we use molecular dynamics (MD) simulations to probe the structural properties of model DOM systems at atomic detail. The 200 ns simulations, validated by available experimental data, reveal processes and mechanisms by which chemical species (cations, peptides, lipids, lignin, carbohydrates, and some low-molecular-weight aliphatic and aromatic compounds) aggregate to form complex DOM. The DOM aggregates are dynamic, consisting of a hydrophobic core and amphiphilic exterior. The lipid tails and other hydrophobic fragments form the core, with hydrophilic and amphiphilic groups exposed to water, making DOM accessible to both polar and nonpolar species. Thus, the lipid component acts as a nucleator, whereas cations (especially Ca2+) connect the molecular fragments on the surface by coordinating with the O-containing functional groups of DOM. The structural details revealed here provide new insights including surface accessible atoms, overall assemblage, and interactions among the molecules of DOM for understanding the kinetics and mechanisms through which DOM interacts with metal and other contaminants.

Identification of Binding Sites for Efflux Pump Inhibitors of the AcrAB-TolC Component AcrA.

The overexpression of multidrug efflux pumps is an important mechanism of clinical resistance in Gram-negative bacteria. Recently, four small molecules were discovered that inhibit efflux in Escherichia coli and interact with the AcrAB-TolC efflux pump component AcrA. However, the binding site(s) for these molecules was not determined. Here, we combine ensemble docking and molecular dynamics simulations with tryptophan fluorescence spectroscopy, site-directed mutagenesis, and antibiotic susceptibility assays to probe binding sites and effects of binding of these molecules. We conclude that clorobiocin and SLU-258 likely bind at a site located between the lipoyl and ß-barrel domains of AcrA.

Mycolyltransferase from Mycobacterium tuberculosis in covalent complex with tetrahydrolipstatin provides insights into antigen 85 catalysis.

Mycobacterium tuberculosis antigen 85 (Ag85) enzymes catalyze the transfer of mycolic acid (MA) from trehalose monomycolate to produce the mycolyl arabinogalactan (mAG) or trehalose dimycolate (TDM). These lipids define the protective mycomembrane of mycobacteria. The current model of substrate binding within the active sites of Ag85s for the production of TDM is not sterically and geometrically feasible; additionally, this model does not account for the production of mAG. Furthermore, this model does not address how Ag85s limit the hydrolysis of the acyl-enzyme intermediate while catalyzing acyl transfer. To inform an updated model, we obtained an Ag85 acyl-enzyme intermediate structure that resembles the mycolated form. Here, we present a 1.45-Å X-ray crystal structure of M. tuberculosis Ag85C covalently modified by tetrahydrolipstatin (THL), an esterase inhibitor that suppresses M. tuberculosis growth and mimics structural attributes of MAs. The mode of covalent inhibition differs from that observed in the reversible inhibition of the human fatty-acid synthase by THL. Similarities between the Ag85-THL structure and previously determined Ag85C structures suggest that the enzyme undergoes structural changes upon acylation, and positioning of the peptidyl arm of THL limits hydrolysis of the acyl-enzyme adduct. Molecular dynamics simulations of the modeled mycolated-enzyme form corroborate the structural analysis. From these findings, we propose an alternative arrangement of substrates that rectifies issues with the previous model and suggest a direct role for the ß-hydroxy of MA in the second half-reaction of Ag85 catalysis. This information affords the visualization of a complete mycolyltransferase catalytic cycle.

Kinetics of Enzymatic Mercury Methylation at Nanomolar Concentrations Catalyzed by HgcAB.

Methylmercury (MeHg) is a potent bioaccumulative neurotoxin that is produced by certain anaerobic bacteria and archaea. Mercury (Hg) methylation has been linked to the gene pair hgcAB, which encodes a membrane-associated corrinoid protein and a ferredoxin. Although microbial Hg methylation has been characterized in vivo, the cellular biochemistry and the specific roles of the gene products HgcA and HgcB in Hg methylation are not well understood. Here, we report the kinetics of Hg methylation in cell lysates of Desulfovibrio desulfuricans ND132 at nanomolar Hg concentrations. The enzymatic Hg methylation mediated by HgcAB is highly oxygen sensitive, irreversible, and follows Michaelis-Menten kinetics, with an apparent Km of 3.2 nM and Vmax of 19.7 fmol · min-1 · mg-1 total protein for the substrate Hg(II). Although the abundance of HgcAB in the cell lysates is extremely low, Hg(II) was quantitatively converted to MeHg at subnanomolar substrate concentrations. Interestingly, increasing thiol/Hg(II) ratios did not impact Hg methylation rates, which suggests that HgcAB-mediated Hg methylation effectively competes with cellular thiols for Hg(II), consistent with the low apparent Km Supplementation of 5-methyltetrahydrofolate or pyruvate did not enhance MeHg production, while both ATP and a nonhydrolyzable ATP analog decreased Hg methylation rates in cell lysates under the experimental conditions. These studies provide insights into the biomolecular processes associated with Hg methylation in anaerobic bacteria.IMPORTANCE The concentration of Hg in the biosphere has increased dramatically over the last century as a result of industrial activities. The microbial conversion of inorganic Hg to MeHg is a global public health concern due to bioaccumulation and biomagnification of MeHg in food webs. Exposure to neurotoxic MeHg through the consumption of fish represents a significant risk to human health and can result in neuropathies and developmental disorders. Anaerobic microbial communities in sediments and periphyton biofilms have been identified as sources of MeHg in aquatic systems, but the associated biomolecular mechanisms are not fully understood. In the present study, we investigate the biochemical mechanisms and kinetics of MeHg formation by HgcAB in sulfate-reducing bacteria. These findings advance our understanding of microbial MeHg production and may help inform strategies to limit the formation of MeHg in the environment.

Mercury Uptake by Desulfovibrio desulfuricans ND132: Passive or Active?

Recent studies have identified HgcAB proteins as being responsible for mercury [Hg(II)] methylation by certain anaerobic microorganisms. However, it remains controversial whether microbes take up Hg(II) passively or actively. Here, we examine the dynamics of concurrent Hg(II) adsorption, uptake, and methylation by both viable and inactivated cells (heat-killed or starved) or spheroplasts of the sulfate-reducing bacterium Desulfovibrio desulfuricans ND132 in laboratory incubations. We show that, without addition of thiols, >60% of the added Hg(II) (25 nM) was taken up passively in 48 h by live and inactivated cells and also by cells treated with the proton gradient uncoupler, carbonylcyanide-3-chlorophenylhydrazone (CCCP). Inactivation abolished Hg(II) methylation, but the cells continued taking up Hg(II), likely through competitive binding or ligand exchange of Hg(II) by intracellular proteins or thiol-containing cellular components. Similarly, treatment with CCCP impaired the ability of spheroplasts to methylate Hg(II) but did not stop Hg(II) uptake. Spheroplasts showed a greater capacity to adsorb Hg(II) than whole cells, and the level of cytoplasmic membrane-bound Hg(II) correlated well with MeHg production, as Hg(II) methylation is associated with cytoplasmic HgcAB. Our results indicate that active metabolism is not required for cellular Hg(II) uptake, thereby providing an improved understanding of Hg(II) bioavailability for methylation.