Mathematical modeling of the effects of glutathione on arsenic methylation

Epicatechin ameliorates glucose intolerance and hepatotoxicity in sodium arsenite-treated mice

Arsenic is a metalloid found in the environment that causes toxic effects in different organs, mainly the liver. This study aimed to investigate the protective effects of epicatechin (EC), a natural flavonol, on glucose intolerance (GI) and liver toxicity caused by sodium arsenite (SA) in mice. Our findings showed that SA exposure led to the development of GI. Liver tissue damage and decreased pancreatic Langerhans islet size were also observed in this study. Mice exposed to SA exhibited hepatic oxidative damage, indicated by reduced antioxidant markers (such as superoxide dismutase, catalase, glutathione peroxidase, and glutathione), along with elevated levels of thiobarbituric acid reactive substances. SA administration elevated the serum activities of liver enzymes alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase. Furthermore, notable increases in the levels of inflammatory and apoptotic markers (Toll-like receptor 4, nuclear factor-kappa B, tumor necrosis factor-α, nitric oxide, B-cell lymphoma-2, and cysteine aspartate-specific protease-3) were observed in the liver. Treatment of SA-exposed mice with EC considerably reversed these biochemical and histological changes. This study demonstrated the beneficial effects of EC in ameliorating SA-induced hyperglycemia and hepatotoxicity due to its ability to enhance the antioxidant system by modulating inflammation and apoptosis.

Assessing the Impact of PM2.5-Bound Arsenic on Cardiovascular Risk among Workers in a Non-ferrous Metal Smelting Area: Insights from Chemical Speciation and Bioavailability

Inhalation of fine particulate matter PM2.5-bound arsenic (PM2.5-As) may cause significant cardiovascular damage, due to its high concentration, long transmission range, and good absorption efficiency in organisms. However, both the contribution and the effect of the arsenic exposure pathway, with PM2.5 as the medium, on cardiovascular system damage in nonferrous smelting sites remain to be studied. In this work, a one-year site sample collection and analysis work showed that the annual concentration of PM2.5-As reached 0.74 μg/m3, which was 120 times the national standard. The predominant species in the PM2.5 samples were As (V) and As (III). A panel study among workers revealed that PM2.5-As exposure dominantly contributed to human absorption of As. After exposure of mice to PM2.5-As for 8 weeks, the accumulation of As in the high exposure group reached equilibrium, and its bioavailability was 24.5%. A series of animal experiments revealed that PM2.5-As exposure induced cardiac injury and dysfunction at the environmental relevant concentration and speciation. By integrating environmental and animal exposure assessments, more accurate health risk assessment models exposed to PM2.5-As were established for metal smelting areas. Therefore, our research provides an important scientific basis for relevant departments to formulate industry supervision, prevention and control policies.

Mathematical model for glutathione dynamics in the retina

The retina is highly susceptible to the generation of toxic reactive oxygen species (ROS) that disrupt the normal operations of retinal cells. The glutathione (GSH) antioxidant system plays an important role in mitigating ROS. To perform its protective functions, GSH depends on nicotinamide adenine dinucleotide phosphate (NADPH) produced through the pentose phosphate pathway. This work develops the first mathematical model for the GSH antioxidant system in the outer retina, capturing the most essential components for formation of ROS, GSH production, its oxidation in detoxifying ROS, and subsequent reduction by NADPH. We calibrate and validate the model using experimental measurements, at different postnatal days up to PN28, from control mice and from the rd1 mouse model for the disease retinitis pigmentosa (RP). Global sensitivity analysis is then applied to examine the model behavior and identify the pathways with the greatest impact in control compared to RP conditions. The findings underscore the importance of GSH and NADPH production in dealing with oxidative stress during retinal development, especially after peak rod degeneration occurs in RP, leading to increased oxygen tension. This suggests that stimulation of GSH and NADPH synthesis could be a potential intervention strategy in degenerative mouse retinas with RP.

Protection against Mitochondrial Oxidative-Stress by Flesh-Extract of Edible Freshwater Snail Bellamya bengalensis Prevents Arsenic Induced DNA and Tissue Damage

AIMS

Arsenic has carcinogenic properties because of the formation of Reactive Oxygen Species (ROS). ROS damages different macromolecules, tissues and organs, and severely exhausts cellular antioxidants.

BACKGROUND

Cytosolic and mitochondrial contribution of ROS production by arsenic are not well reported. In regard to the issues of therapy against arsenic or any other toxicity, natural product has gained its popularity due to its less side-effects and non-invasive nature.

OBJECTIVES

Here, as an ethnomedicine, the flesh-extract (BBE; 100mg/100g bw) of Bellamya bengalensis (an aquatic mollusk) was applied in arsenic intoxicated (0.6 ppm/100g bw/for 28 days alone or in combination with BBE) experimental rats. Our objective was to study the anti-oxidative and anti-apoptotic role of BBE in hepato-gastrointestinal tissue damage by arsenic.

METHODS

DNA fragmentation assay, catalase activity (gel-zymogram assay) suggests that BBE has a strong protective role against arsenic toxicity, which is decisively demonstrated in hepatic histoarchitecture study by HE (hematoxylin and eosin) staining and by intestinal PAS (Periodic Acid Schiff) staining.

RESULTS

Measurement of mitochondrial-membrane-potential by fluorescent microcopy clearly demonstrated less membrane damage and lower release of the redox-active inner-membrane product (cytochrome-C, ubiquinone, etc.) in BBE supplemented group compared to that of the only arsenic fed group. The present study clearly suggests that mitochondrial disintegrity is one of the major causes of ROS mediated tissue damage by arsenic.

CONCLUSION

This study also offers an option for prevention/treatment against arsenic toxicity and its carcinogenicity by widely available low-cost, non-invasive Bellamya extract by protecting cytoskeleton, DNA and mitochondria in the cell.

Omic methodologies for assessing metal(-loid)s-host-microbiota interplay: A review

Omic methodologies have become key analytical tools in a wide number of research topics such as systems biology, environmental analysis, biomedicine or food analysis. They are especially useful when they are combined providing a new perspective and a holistic view of the analytical problem. Methodologies for microbiota analysis have been mostly focused on genome sequencing. However, information provided by these metagenomic studies is limited to the identification of the presence of genes, taxa and their inferred functionality. To achieve a deeper knowledge of microbial functionality in health and disease, especially in dysbiosis conditions related to metal and metalloid exposure, the introduction of additional meta-omic approaches including metabolomics, metallomics, metatranscriptomics and metaproteomics results essential. The possible impact of metals and metalloids on the gut microbiota and their effects on gut-brain axis (GBA) only begin to be figured out. To this end new analytical workflows combining powerful tools are claimed such as high resolution mass spectrometry and heteroatom-tagged proteomics for the absolute quantification of metal-containing biomolecules using the metal as a "tag" in a sensitive and selective detector (e.g. ICP-MS). This review focus on current analytical methodologies related with the analytical techniques and procedures available for metallomics and microbiota analysis with a special attention on their advantages and drawbacks.

Arsenic toxicokinetic modeling and risk analysis: Progress, needs and applications

Arsenic (As) poses unique challenges in PBTK model development and risk analysis applications. Arsenic metabolism is complex, adequate information to attribute specific metabolites to particular adverse effects in humans is sparse, and measurement of relevant metabolites in biological media can be difficult. Multiple As PBTK models have been published and used or adapted for use in various exposure and risk analysis applications. These applications illustrate the broad utility of PBTK models for exposure and dose-response analysis, particularly for arsenic where multi-pathway, multi-route exposures and multiple toxic effects are of concern. Arsenic PBTK models have been used together with exposure reconstruction and dose-response functions to estimate risk of specific adverse health effects due to drinking water exposure and consumption of specific foodstuffs (e.g. rice, seafood), as well as to derive safe exposure levels and develop consumption advisories. Future refinements to arsenic PBTK models can enhance the confidence in such analyses. Improved estimates for methylation biotransformation parameters based on in vitro to in vivo extrapolation (IVIVE) methods and estimation of interindividual variability in key model parameters for specific toxicologically relevant metabolites are two important areas for consideration.

Distribution of arsenic and its biotransformation genes in sediments from the East China Sea

Microbial transformation of arsenic (As) plays a key role in As biogeochemical cycling and affects the mobility, bioavailability, and toxicity of As. This study aims to investigate the accumulation of As in marine sediments at different water depths in the East China Sea and reveal the abundance and diversity of the aioA, arrA, arsC, and arsM genes through quantitative real-time polymerase chain reaction (qPCR) and high-throughput sequencing. Results showed that the As content in sediments ranged from 5.53 mg kg^-1 to 17.70 mg kg^-1, which decreased with water depth. Abundant As biotransformation genes with low diversity were identified in these sediments, of which arsM and arrA were the most abundant. Significant positive correlation exists between the arsM and arrA gene abundance and between arsC and aioA, indicating the co-occurrence of the As biotransformation genes in microbes in marine sediments. Metagenomics analysis revealed that arsM gene was mainly distributed in Alphaproteobacteria, Solibacteres, Deltaproteobacteria, Clostridia, and Bacilli in these sediments. Among the sediment properties, total N, total S, C/N, and TOC were important factors that shaped the abundance profile of the genes involved in As transformation. This study provides a picture of As biotransformation genes in marine sediments from the East China Sea, which may affect As transformation and the ultimate fate of As in a marine environment.

Targeted metabolomics to understand the association between arsenic metabolism and diabetes-related outcomes: Preliminary evidence from the Strong Heart Family Study

BACKGROUND

Inorganic arsenic exposure is ubiquitous and both exposure and inter-individual differences in its metabolism have been associated with cardiometabolic risk. A more efficient arsenic metabolism profile (lower MMA%, higher DMA%) has been associated with reduced risk for arsenic-related health outcomes. This profile, however, has also been associated with increased risk for diabetes-related outcomes.

OBJECTIVES

The mechanism behind these conflicting associations is unclear; we hypothesized the one-carbon metabolism (OCM) pathway may play a role.

METHODS

We evaluated the influence of OCM on the relationship between arsenic metabolism and diabetes-related outcomes (HOMA2-IR, waist circumference, fasting plasma glucose) using metabolomic data from an OCM-specific and P180 metabolite panel measured in plasma, arsenic metabolism measured in urine, and HOMA2-IR and FPG measured in fasting plasma. Samples were drawn from baseline visits (2001-2003) in 59 participants from the Strong Heart Family Study, a family-based cohort study of American Indians aged ≥14 years from Arizona, Oklahoma, and North/South Dakota.

RESULTS

In unadjusted analyses, a 5% increase in DMA% was associated with higher HOMA2-IR (geometric mean ratio (GMR)= 1.13 (95% CI: 1.03, 1.25)) and waist circumference (mean difference=3.66 (0.95, 6.38). MMA% was significantly associated with lower HOMA2-IR and waist circumference. After adjustment for OCM-related metabolites (SAM, SAH, cysteine, glutamate, lysophosphatidylcholine 18.2, and three phosphatidlycholines), associations were attenuated and no longer significant.

CONCLUSIONS

These preliminary results indicate that the association of lower MMA% and higher DMA% with diabetes-related outcomes may be influenced by OCM status, either through confounding, reverse causality, or mediation.

Arsenic-induced oxidative stress, cholinesterase activity in the brain of Swiss albino mice, and its amelioration by antioxidants Vitamin E and Coenzyme Q10

Arsenic toxicity becomes one of the major public health issues in several countries. Chronic and acute exposure to arsenic has been reported to be toxic to various systems of the human body and also observed in controlled experimental studies. The study was conducted to evaluate the neurotoxic effect of arsenic in Swiss albino mice and its amelioration by Vitamin E, Coenzyme Q10 and their combination. Swiss albino mice were treated with arsenic of 136 ppm for 15 days. The daily dose is 1/3 of LD 50 (acute) reported dose of arsenic. Thereafter, the animals were maintained either on drinking water or treated with Vitamin E (50 mg/kg bwt), Coenzyme Q10 (10 mg/kg bwt), and their combination by i.p.daily for 15 days. After the treatment, animals were sacrificed. The weight of the brain was marginally lower (ns), in arsenic-treated group as compared to control and antioxidant-protected groups. The LPO (lipid peroxidation) level was higher in arsenic-treated group, and this elevation was checked to some extent by the selected antioxidants which were statistically significant in combination of antioxidant-protected group. A significant reduction was found in GSH (reduced glutathione) level in the brain of arsenic-treated mice whereas GSH level was considerably higher in antioxidant-protected groups. Further, total thiol and total protein level were lower in arsenic-treated group. However, total thiol was significantly higher in antioxidant-protected groups. CAT (catalase) activity was significantly lower while SOD (superoxide dismutase) activity was marginally lowered in arsenic-treated group, and it was slightly higher in antioxidant-protected groups. Further, reduction in AChE (acetylcholinesterase) and BChE (butyrylcholinesterase) and motor coordination activity were also observed in arsenic-treated groups. Whereas, a higher AChE, BChE, and motor coordination activity was observed in antioxidant-protected group. These data indicate a positive role of selected antioxidant against the toxicity of arsenic in the brain of mice.

Nutritional Influences on One-Carbon Metabolism: Effects on Arsenic Methylation and Toxicity

Exposure to inorganic arsenic (InAs) via drinking water and/or food is a considerable worldwide problem. Methylation of InAs generates monomethyl (MMAs^III+V)- and dimethyl (DMAs^III+V)-arsenical species in a process that facilitates urinary As elimination; however, MMAs is considerably more toxic than either InAs or DMAs. Emerging evidence suggests that incomplete methylation of As to DMAs, resulting in increased MMAs, is associated with increased risk for a host of As-related health outcomes. The biochemical pathway that provides methyl groups for As methylation, one-carbon metabolism (OCM), is influenced by folate and other micronutrients, including choline and betaine. Individuals and species differ widely in their ability to methylate As. A growing body of research, including cell-culture, animal-model, and epidemiological studies, has demonstrated the role of OCM-related micronutrients in As methylation. This review examines the evidence that nutritional status and nutritional interventions can influence the metabolism and toxicity of As, with a primary focus on folate.

Including Rebinding Reactions in Well-Mixed Models of Distributive Biochemical Reactions

The behavior of biochemical reactions requiring repeated enzymatic substrate modification depends critically on whether the enzymes act processively or distributively. Whereas processive enzymes bind only once to a substrate before carrying out a sequence of modifications, distributive enzymes release the substrate after each modification and thus require repeated bindings. Recent experimental and computational studies have revealed that distributive enzymes can act processively due to rapid rebindings (so-called quasi-processivity). In this study, we derive an analytical estimate of the probability of rapid rebinding and show that well-mixed ordinary differential equation models can use this probability to quantitatively replicate the behavior of spatial models. Importantly, rebinding requires that connections be added to the well-mixed reaction network; merely modifying rate constants is insufficient. We then use these well-mixed models to suggest experiments to 1) detect quasi-processivity and 2) test the theory. Finally, we show that rapid rebindings drastically alter the reaction's Michaelis-Menten rate equations.

Mathematical Models for Immunology: Current State of the Art and Future Research Directions

The advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years.

Arsenic and Environmental Health: State of the Science and Future Research Opportunities

BACKGROUND

Exposure to inorganic and organic arsenic compounds is a major public health problem that affects hundreds of millions of people worldwide. Exposure to arsenic is associated with cancer and noncancer effects in nearly every organ in the body, and evidence is mounting for health effects at lower levels of arsenic exposure than previously thought. Building from a tremendous knowledge base with > 1,000 scientific papers published annually with "arsenic" in the title, the question becomes, what questions would best drive future research directions?

OBJECTIVES

The objective is to discuss emerging issues in arsenic research and identify data gaps across disciplines.

METHODS

The National Institutes of Health's National Institute of Environmental Health Sciences Superfund Research Program convened a workshop to identify emerging issues and research needs to address the multi-faceted challenges related to arsenic and environmental health. This review summarizes information captured during the workshop.

DISCUSSION

More information about aggregate exposure to arsenic is needed, including the amount and forms of arsenic found in foods. New strategies for mitigating arsenic exposures and related health effects range from engineered filtering systems to phytogenetics and nutritional interventions. Furthermore, integration of omics data with mechanistic and epidemiological data is a key step toward the goal of linking biomarkers of exposure and susceptibility to disease mechanisms and outcomes.

CONCLUSIONS

Promising research strategies and technologies for arsenic exposure and adverse health effect mitigation are being pursued, and future research is moving toward deeper collaborations and integration of information across disciplines to address data gaps.

CITATION

Carlin DJ, Naujokas MF, Bradham KD, Cowden J, Heacock M, Henry HF, Lee JS, Thomas DJ, Thompson C, Tokar EJ, Waalkes MP, Birnbaum LS, Suk WA. 2016. Arsenic and environmental health: state of the science and future research opportunities. Environ Health Perspect 124:890-899; http://dx.doi.org/10.1289/ehp.1510209.

Mathematical analysis of the regulation of competing methyltransferases

BACKGROUND

Methyltransferase (MT) reactions, in which methyl groups are attached to substrates, are fundamental to many aspects of cell biology and human physiology. The universal methyl donor for these reactions is S-adenosylmethionine (SAM) and this presents the cell with an important regulatory problem. If the flux along one pathway is changed then the SAM concentration will change affecting all the other MT pathways, so it is difficult for the cell to regulate the pathways independently.

METHODS

We created a mathematical model, based on the known biochemistry of the folate and methionine cycles, to study the regulatory mechanisms that enable the cell to overcome this difficulty. Some of the primary mechanisms are long-range allosteric interactions by which substrates in one part of the biochemical network affect the activity of enzymes at distant locations in the network (not distant in the cell). Because of these long-range allosteric interactions, the dynamic behavior of the network is very complicated, and so mathematical modeling is a useful tool for investigating the effects of the regulatory mechanisms and understanding the complicated underlying biochemistry and cell biology.

RESULTS

We study the allosteric binding of 5-methyltetrahydrofolate (5 mTHF) to glycine-N-methyltransferase (GNMT) and explain why data in the literature implies that when one molecule binds, GNMT retains half its activity. Using the model, we quantify the effects of different regulatory mechanisms and show how cell processes would be different if the regulatory mechanisms were eliminated. In addition, we use the model to interpret and understand data from studies in the literature. Finally, we explain why a full understanding of how competing MTs are regulated is important for designing intervention strategies to improve human health.

CONCLUSIONS

We give strong computational evidence that once bound GNMT retains half its activity. The long-range allosteric interactions enable the cell to regulate the MT reactions somewhat independently. The low K m values of many MTs also play a role because the reactions then run near saturation and changes in SAM have little effect. Finally, the inhibition of the MTs by the product S-adenosylhomocysteine also stabilizes reaction rates against changes in SAM.

Using mathematical models to understand metabolism, genes, and disease

Mathematical models are a useful tool for investigating a large number of questions in metabolism, genetics, and gene–environment interactions. A model based on the underlying biology and biochemistry is a platform for in silico biological experimentation that can reveal the causal chain of events that connect variation in one quantity to variation in another. We discuss how we construct such models, how we have used them to investigate homeostatic mechanisms, gene–environment interactions, and genotype–phenotype mapping, and how they can be used in precision and personalized medicine.