Characterization of the Impaired Glucose Homeostasis Produced in C57BL/6 Mice by Chronic Exposure to Arsenic and High-Fat Diet

Background: Type 2 diabetes is characterized by glucose intolerance and insulin resistance. Obesity is the leading cause of type 2 diabetes. Growing evidence suggests that chronic exposure to inorganic arsenic (iAs) also produces symptoms consistent with diabetes. Thus, iAs exposure may further increase the risk of diabetes in obese individuals

Characterization of the Impaired Glucose Homeostasis Produced in C57BL/6 Mice by Chronic Exposure to Arsenic and High-Fat Diet

Background: Type 2 diabetes is characterized by glucose intolerance and insulin resistance. Obesity is the leading cause of type 2 diabetes. Growing evidence suggests that chronic exposure to inorganic arsenic (iAs) also produces symptoms consistent with diabetes. Thus, iAs exposure may further increase the risk of diabetes in obese individuals

Methylation of arsenic by recombinant human wild-type arsenic (+3 oxidation state) methyltransferase and its methionine 287 threonine (M287T) polymorph: Role of glutathione

Arsenic (+3 oxidation state) methyltransferase (AS3MT) is the key enzyme in the pathway for methylation of arsenicals. A common polymorphism in the AS3MT gene that replaces a threonyl residue in position 287 with a methionyl residue (AS3MT/M287T) occurs at a frequency of about 10% among populations worldwide. Here, we compared catalytic properties of recombinant human wild-type (wt) AS3MT and AS3MT/M287T in reaction mixtures containing S-adenosylmethionine, arsenite (iAsIII) or methylarsonous acid (MAsIII) as substrates and endogenous or synthetic reductants, including glutathione (GSH), a thioredoxin reductase (TR)/thioredoxin (Trx)/NADPH reducing system, or tris (2-carboxyethyl) phosphine hydrochloride (TCEP). With either TR/Trx/NADPH or TCEP, wtAS3MT or AS3MT/M287T catalyzed conversion of iAsIII to MAsIII, methylarsonic acid (MAsV), dimethylarsinous acid (DMAsIII), and dimethylarsinic acid (DMAsV); MAsIII was converted to DMAsIII and DMAsV. Although neither enzyme required GSH to support methylation of iAsIII or MAsIII, addition of 1 mM GSH decreased Km and increased Vmax estimates for either substrate in reaction mixtures containing TR/Trx/NADPH. Without GSH, Vmax and Km values were significantly lower for AS3MT/M287T than for wtAS3MT. In the presence of 1 mM GSH, significantly more DMAsIII was produced from iAsIII in reactions catalyzed by the M287T variant than in wtAS3MT-catalyzed reactions. Thus, 1 mM GSH modulates AS3MT activity, increasing both methylation rates and yield of DMAsIII. AS3MT genotype exemplified by differences in regulation of wtAS3MT and AS3MT/M287T-catalyzed reactions by GSH may contribute to differences in the phenotype for arsenic methylation and, ultimately, to differences in the disease susceptibility in individuals chronically exposed to inorganic arsenic

Metabolomic profiles of arsenic (+3 oxidation state) methyltransferase knockout mice: effect of sex and arsenic exposure

Arsenic (+3 oxidation state) methyltransferase (As3mt) is the key enzyme in the pathway for methylation of inorganic arsenic (iAs). Altered As3mt expression and AS3MT polymorphism have been linked to changes in iAs metabolism and in susceptibility to iAs toxicity in laboratory models and in humans. As3mt-knockout mice have been used to study the association between iAs metabolism and adverse effects of iAs exposure. However, little is known about systemic changes in metabolism of these mice and how these changes lead to their increased susceptibility to iAs toxicity. Here, we compared plasma and urinary metabolomes of male and female wild-type (WT) and As3mt-KO (KO) C57BL6 mice and examined metabolomic shifts associated with iAs exposure in drinking water. Surprisingly, exposure to 1 ppm As elicited only small changes in the metabolite profiles of either WT or KO mice. In contrast, comparisons of KO mice with WT mice revealed significant differences in plasma and urinary metabolites associated with lipid (phosphatidylcholines, cytidine, acyl-carnitine), amino acid (hippuric acid, acetylglycine, urea), and carbohydrate (L-sorbose, galactonic acid, gluconic acid) metabolism. Notably, most of these differences were sex-specific. Sex-specific differences were also found between WT and KO mice in plasma triglyceride and lipoprotein cholesterol levels. Some of the differentially changed metabolites (phosphatidylcholines, carnosine, and sarcosine) are substrates or products of reactions catalyzed by other methyltransferases. These results suggest that As3mt KO alters major metabolic pathways in a sex-specific manner, independent of iAs treatment, and that As3mt may be involved in other cellular processes beyond iAs methylation

Comparative oxidation state specific analysis of arsenic species by high-performance liquid chromatography-inductively coupled plasma-mass spectrometry and hydride generation-cryotrapping-atomic absorption spectrometry

The formation of methylarsonous acid (MAsIII) and dimethylarsinous acid (DMAsIII) in the course of inorganic arsenic (iAs) metabolism plays an important role in the adverse effects of chronic exposure to iAs. High-performance liquid chromatography-inductively coupled plasma-mass spectrometry (HPLC-ICP-MS) and hydride generation-cryotrapping-atomic absorption spectrometry (HG-CT-AAS) have been frequently used for the analysis of MAsIII and DMAsIII in biological samples. While HG-CT-AAS has consistently detected MAsIII and DMAsIII, HPLC-ICP-MS analyses have provided inconsistent and contradictory results. This study compares the capacities of both methods to detect and quantify MAsIII and DMAsIII in an in vitro methylation system consisting of recombinant human arsenic (+3 oxidation state) methyltransferase (AS3MT), S-adenosylmethionine as a methyl donor, a non-thiol reductant tris(2-carboxyethyl)phosphine, and arsenite (iAsIII) or MAsIII as substrate. The results show that reversed-phase HPLC-ICP-MS can identify and quantify MAsIII and DMAsIII in aqueous mixtures of biologically relevant arsenical standards. However, HPLC separation of the in vitro methylation mixture resulted in significant losses of MAsIII, and particularly DMAsIII with total arsenic recoveries below 25%. Further analyses showed that MAsIII and DMAsIII bind to AS3MT or interact with other components of the methylation mixture, forming complexes that do not elute from the column. Oxidation of the mixture with H2O2 which converted trivalent arsenicals to their pentavalent analogs prior to HPLC separation increased total arsenic recoveries to ~95%. In contrast, HG-CT-AAS analysis found large quantities of methylated trivalent arsenicals in mixtures incubated with either iAsIII or MAsIII and provided high (>72%) arsenic recoveries. These data suggest that an HPLC-based analysis of biological samples can underestimate MAsIII and DMAsIII concentrations and that controlling for arsenic species recovery is essential to avoid artifacts

Selective hydride generation-cryotrapping-ICP-MS for arsenic speciation analysis at picogram levels: analysis of river and sea water reference materials and human bladder epithelial cells

An ultra sensitive method for arsenic (As) speciation analysis based on selective hydride generation (HG) with preconcentration by cryotrapping (CT) and inductively coupled plasma- mass spectrometry (ICP-MS) detection is presented. Determination of valence of the As species is performed by selective HG without prereduction (trivalent species only) or with L-cysteine prereduction (sum of tri- and pentavalent species). Methylated species are resolved on the basis of thermal desorption of formed methyl substituted arsines after collection at −196°C. Limits of detection of 3.4, 0.04, 0.14 and 0.10 pg mL−1 (ppt) were achieved for inorganic As, mono-, di- and trimethylated species, respectively, from a 500 μL sample

Chronic Exposure to Arsenic and Markers of Cardiometabolic Risk: A Cross-Sectional Study in Chihuahua, Mexico

BackgroundExposure to arsenic (As) concentrations in drinking water > 150 μg/L has been associated with risk of diabetes and cardiovascular disease, but little is known about the effects of lower exposures.ObjectiveThis study aimed to examine whether moderate As exposure, or indicators of individual As metabolism at these levels of exposure, are associated with cardiometabolic risk.MethodsWe analyzed cross-sectional associations between arsenic exposure and multiple markers of cardiometabolic risk using drinking-water As measurements and urinary As species data obtained from 1,160 adults in Chihuahua, Mexico, who were recruited in 2008–2013. Fasting blood glucose and lipid levels, the results of an oral glucose tolerance test, and blood pressure were used to characterize cardiometabolic risk. Multivariable logistic, multinomial, and linear regression were used to assess associations between cardiometabolic outcomes and water As or the sum of inorganic and methylated As species in urine.ResultsAfter multivariable adjustment, concentrations in the second quartile of water As (25.5 to < 47.9 μg/L) and concentrations of total speciated urinary As (< 55.8 μg/L) below the median were significantly associated with elevated triglycerides, high total cholesterol, and diabetes. However, moderate water and urinary As levels were also positively associated with HDL cholesterol. Associations between arsenic exposure and both dysglycemia and triglyceridemia were higher among individuals with higher proportions of dimethylarsenic in urine.ConclusionsModerate exposure to As may increase cardiometabolic risk, particularly in individuals with high proportions of urinary dimethylarsenic. In this cohort, As exposure was associated with several markers of increased cardiometabolic risk (diabetes, triglyceridemia, and cholesterolemia), but exposure was also associated with higher rather than lower HDL cholesterol.CitationMendez MA, González-Horta C, Sánchez-Ramírez B, Ballinas-Casarrubias L, Hernández Cerón R, Viniegra Morales D, Baeza Terrazas FA, Ishida MC, Gutiérrez-Torres DS, Saunders RJ, Drobná Z, Fry RC, Buse JB, Loomis D, García-Vargas GG, Del Razo LM, Stýblo M. 2016. Chronic exposure to arsenic and markers of cardiometabolic risk: a cross-sectional study in Chihuahua, Mexico. Environ Health Perspect 124:104–111; http://dx.doi.org/10.1289/ehp.140874

Association Between Variants in Arsenic (+3 Oxidation State) Methyltranserase ( AS3MT ) and Urinary Metabolites of Inorganic Arsenic: Role of Exposure Level

Variants in AS3MT, the gene encoding arsenic (+3 oxidation state) methyltranserase, have been shown to influence patterns of inorganic arsenic (iAs) metabolism. Several studies have suggested that capacity to metabolize iAs may vary depending on levels of iAs exposure. However, it is not known whether the influence of variants in AS3MT on iAs metabolism also vary by level of exposure. We investigated, in a population of Mexican adults exposed to drinking water As, whether associations between 7 candidate variants in AS3MT and urinary iAs metabolites were consistent with prior studies, and whether these associations varied depending on the level of exposure. Overall, associations between urinary iAs metabolites and AS3MT variants were consistent with the literature. Referent genotypes, defined as the genotype previously associated with a higher percentage of urinary dimethylated As (DMAs%), were associated with significant increases in the DMAs% and ratio of DMAs to monomethylated As (MAs), and significant reductions in MAs% and iAs%. For 3 variants, associations between genotypes and iAs metabolism were significantly stronger among subjects exposed to water As >50 versus ≤50 ppb (water As X genotype interaction P < .05). In contrast, for 1 variant (rs17881215), associations were significantly stronger at exposures ≤50 ppb. Results suggest that iAs exposure may influence the extent to which several AS3MT variants affect iAs metabolism. The variants most strongly associated with iAs metabolism—and perhaps with susceptibility to iAs-associated disease—may vary in settings with exposure level

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species–season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds