The relevance of arsenic speciation analysis in health & medicine

Environmental fate of monosodium methanearsonate (MSMA)-Part 1: Conceptual model

Monosodium methanearsonate (MSMA), the sodium salt of monomethylarsonic acid (MMA), is used as a selective, broad-spectrum contact herbicide to control weeds in cotton and a variety of turf. In water, MSMA dissociates into ions of sodium (Na+) and of MMA-, which is the herbicide's active component. Certain soil microorganisms can methylate MMA to dimethylarsinic acid (DMA) other microorganisms can demethylate MMA to inorganic arsenic (iAs). To predict the groundwater concentration of iAs that may result from MSMA application, the processes affecting the environmental behavior of MSMA must be quantified and modeled. There is an extensive body of literature regarding the environmental behavior of MSMA. There is a consensus among scientists that the fate of MMA in soil is controlled by microbial activity and sorption to solid surfaces and that iAs sorption is even more extensive than that of MMA. The sorption and transformation of MMA and its metabolites are affected by several factors including aeration condition, temperature, pH, and the availability of nutrients. The precise nature and extent of each of these processes vary depending on site-specific conditions; however, such variability is constrained in typical MSMA use areas that are highly managed. Monomethylarsonic acid is strongly sorbed on mineral surfaces and becomes sequestered into the soil matrix. Over time, a greater portion of MMA and iAs becomes immobile and unavailable to soil microorganisms and to leaching. This review synthesizes the results of studies that are relevant for the behavior of MSMA used as a herbicide to reliably predict the fate of MSMA in its use conditions. Integr Environ Assess Manag 2024;20:1859-1875. © 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Data mining of arsenic-based small molecules geometrics present in Cambridge structural database

Arsenic, ubiquitous in various industrial processes and consumer products, presents both essential functions and considerable toxicity risks, driving extensive research into safer applications. Our investigation, drawing from 7182 arsenic-containing molecules in the Cambridge Structural Database (CSD), outlines their diverse bonding patterns. Notably, 51% of these molecules exhibit cyclic connections, while 49% display acyclic ones. Arsenic forms eight distinct bonding types with other elements, with significant interactions observed, particularly with phenyl rings, O3 and F6 moieties. Top interactions involve carbon, nitrogen, oxygen, fluorine, sulfur, and arsenic itself. We meticulously evaluated average bond lengths under three conditions: without an R-factor cut-off, with R-factor ≤0.075, and with R-factor ≤0.05, supporting the credibility of our results. Comparative analysis with existing literature data enriches our understanding of arsenic's bonding behaviour. Our findings illuminate the structural attributes, molecular coordination, geometry, and bond lengths of arsenic with 68 diverse atoms, enriching our comprehension of arsenic chemistry. These revelations not only offer a pathway for crafting innovative and safer arsenic-based compounds but also foster the evolution of arsenic detoxification mechanisms, tackling pivotal health and environmental challenges linked to arsenic exposure across different contexts.

Urine Self-Sampling Kit Combined with an Automated Preparation-Sampler Device for Convenient and Reliable Analysis of Arsenic Metabolites by HPLC-ICPMS

Speciation analysis of arsenic in urine is essential for the studies of arsenic metabolism and biological effects, but the unstable arsenic species represented by MMAIII and DMAIII pose a huge challenge to analytical accuracy. Herein, a novel urine self-sampling (USS) kit combined with an automated preparation-sampler (APS) device is rationally designed and used for convenient analysis of arsenic metabolites by high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICPMS). The subject can collect urine into a sampling vial at home and use a homemade syringe to pump argon to displace oxygen in the vial, thereby inhibiting the oxidation of MMAIII and DMAIII. After USS and transportation, the sampling vial is loaded directly onto the APS device, where the urine sample can be automatically mixed with diluent, filtered, and loaded into HPLC-ICPMS for arsenic speciation analysis under anaerobic conditions. For a single sample, the sampling time and the analysis time are <8 and <18 min, respectively. The recoveries of MMAIII and DMAIII in urine over 24 h at 4 °C are 86 and 67%, surpassing the conventional sampling method by 28 and 67%, respectively. When the APS is coupled to HPLC-ICPMS, the detection limits of AsC, iAsIII, MMAIII, DMAV, MMAV, DMAIII, and iAsV are 0.03-0.10 μg L-1 with precisions of <10%. The present method provides a convenient and reliable tool for the storage and analysis of unstable arsenic species in urine and lays the foundation for studying the metabolic and biological effects of methylated trivalent arsenicals.

Urinary arsenic metabolism, genetic susceptibility, and their interaction on type 2 diabetes

Growing studies investigated the association of arsenic metabolism with type 2 diabetes (T2D), however, the epidemiological evidence is inconsistent. In addition, the interaction of arsenic metabolism-related genetic risk score (GRS)-arsenic on T2D risk was unclear. The present study aimed to evaluate the association of arsenic metabolism efficiency [inorganic arsenic (iAs)%, monomethylarsonic acid (MMA)%, and dimethylarsinic acid (DMA%)] with T2D risk. Moreover, the relationship of GRS and arsenic metabolism efficiency and the interaction of GRS-arsenic on T2D were investigated. Age- and sex-matched new-onset diabetes case-control study derived from the Dongfeng-Tongji cohort was conducted and 996 pairs participants were included in this study. The leave-one-out approach was used to evaluate the association of arsenic metabolism efficiency with T2D risk. The GRS and weight GRS (wGRS) were calculated based on 79 candidate SNPs. We estimated the relationship of GRS with arsenic metabolism efficiency by linear regression model. The interaction of GRS-arsenic on T2D was assessed by adding a multiplicative interaction term (GRS × arsenic) in the logistic regression models. Urinary iAs% was positively associated with T2D risk, and the OR (95% CI) was 1.06 (1.01, 1.12). MMA% and PMI were negatively associated with T2D risk, and the ORs (95% CI) were 0.87 (0.78, 0.97) and 0.64 (0.47, 0.86), respectively. Urinary DMA, As3+, and As5+ were positively associated with T2D risk. Similar relationships were found between arsenic metabolites and levels of FPG and HbA1c. Moreover, arsenic metabolism-related GRS/wGRS was positively associated with MMA% but negatively associated with DMA%. Genetic predisposition to arsenic metabolism modified the association of inorganic arsenic with T2D risk (Pinteraction = 0.033). Taken together, lower arsenic primary metabolism efficiency (higher iAs% and lower MMA%) may increase T2D risk. Genetic predisposition to arsenic metabolism was associated with arsenic metabolism efficiency, and might modify the association of inorganic arsenic with T2D risk.

Arsenic binding to human metallothionein-3

Arsenic poisoning is of great concern with respect to its neurological toxicity, which is especially significant for young children. Human exposure to arsenic occurs worldwide from contaminated drinking water. In human physiology, one response to toxic metals is through coordination with the metallochaperone metallothionein (MT). Central nervous system expression of MT isoform 3 (MT3) is thought to be neuroprotective. We report for the first time on the metalation pathways of As3+ binding to apo-MT3 under physiological conditions, yielding the absolute binding constants (log Kn, n = 1-6) for each sequential As3+ binding event: 10.20, 10.02, 9.79, 9.48, 9.06, and 8.31 M-1. We report on the rate of the reaction of As3+ with apo-MT3 at pH 3.5 with rate constants (kn, n = 1-6) determined for each sequential As3+ binding event: 116.9, 101.2, 85.6, 64.0, 43.9, and 21.0 M-1 s-1. We further characterize the As3+ binding pathway to fully metalated Zn7MT3 and partially metalated Zn-MT3. As3+ binds rapidly with high binding constants under physiological conditions in a noncooperative manner, but is unable to replace the Zn2+ in fully-metalated Zn-MT3. As3+ binding to partially metalated Zn-MT3 takes place with a rearrangement of the Zn-binding profile. Our work shows that As 3+ rapidly and efficiently binds to both apo-MT3 and partially metalated Zn-MT3 at physiological pH.