Dataset Information

Shifting the Specificity of E. coli Biosensor from Inorganic Arsenic to Phenylarsine Oxide through Genetic Engineering.

ABSTRACT: It has recently been discovered that organic and inorganic arsenics could be detrimental to human health. Although organic arsenic is less toxic than inorganic arsenic, it could form inorganic arsenic through chemical and biological processes in environmental systems. In this regard, the availability of tools for detecting organic arsenic species would be beneficial. Because As-sensing biosensors employing arsenic responsive genetic systems are regulated by ArsR which detects arsenics, the target selectivity of biosensors could be obtained by modulating the selectivity of ArsR. In this study, we demonstrated a shift in the specificity of E. coli cell-based biosensors from the detection of inorganic arsenic to that of organic arsenic, specifically phenylarsine oxide (PAO), through the genetic engineering of ArsR. By modulating the number and location of cysteines forming coordinate covalent bonds with arsenic species, an E. coli cell-based biosensor that was specific to PAO was obtained. Despite its restriction to PAO at the moment, it offers invaluable evidence of the potential to generate new biosensors for sensing organic arsenic species through the genetic engineering of ArsR.

SUBMITTER: Kim H

PROVIDER: S-EPMC7309064 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Shifting the Specificity of <i>E. coli</i> Biosensor from Inorganic Arsenic to Phenylarsine Oxide through Genetic Engineering.

Kim Hyojin H Jeon Yangwon Y Lee Woonwoo W Jang Geupil G Yoon Youngdae Y

Sensors (Basel, Switzerland) 20200530 11

It has recently been discovered that organic and inorganic arsenics could be detrimental to human health. Although organic arsenic is less toxic than inorganic arsenic, it could form inorganic arsenic through chemical and biological processes in environmental systems. In this regard, the availability of tools for detecting organic arsenic species would be beneficial. Because As-sensing biosensors employing arsenic responsive genetic systems are regulated by ArsR which detects arsenics, the targe ...[more]

PMID: 32486164

Similar Datasets

Project description:Arsenic occurs naturally in the environment, and exists predominantly as inorganic arsenite (As (III) and arsenate As (V)). Arsenic contamination of drinking water has long been recognized as a major global health concern. Arsenic exposure causes changes in skin color and lesions, and more severe health conditions such as black foot disease as well as various cancers originating in the lungs, skin, and bladder. In order to efficiently metabolize and excrete arsenic, it is methylated to monomethylarsonic and dimethylarsinic acid. One single enzyme, arsenic methyltransferase (AS3MT) is responsible for generating both metabolites. AS3MT has been purified from several mammalian and nonmammalian species, and its mRNA sequences were determined from amino acid sequences. With the advent of genome technology, mRNA sequences of AS3MT have been predicted from many species throughout the animal kingdom. Horizontal gene transfer had been postulated for this gene through phylogenetic studies, which suggests the importance of this gene in appropriately handling arsenic exposures in various organisms. An altered ability to methylate arsenic is dependent on specific single nucleotide polymorphisms (SNPs) in AS3MT. Reduced AS3MT activity resulting in poor metabolism of iAs has been shown to reduce expression of the tumor suppressor gene, p16, which is a potential pathway in arsenic carcinogenesis. Arsenic is also known to induce oxidative stress in cells. However, the presence of antioxidant response elements (AREs) in the promoter sequences of AS3MT in several species does not correlate with the ability to methylate arsenic. ARE elements are known to bind NRF2 and induce antioxidant enzymes to combat oxidative stress. NRF2 may be partly responsible for the biotransformation of iAs and the generation of methylated arsenic species via AS3MT. In this article, arsenic metabolism, excretion, and toxicity, a discussion of the AS3MT gene and its evolutionary history, and DNA methylation resulting from arsenic exposure have been reviewed.

Project description:Arsenic (As) accumulation in rice grain is a significant public health concern. Inorganic As (iAs) is of particular concern because it has increased toxicity as compared to organic As. Irrigation management practices, such as alternate wetting and drying (AWD), as well as genotypic differences between cultivars, have been shown to influence As accumulation in rice grain. A 2 year field study using a Lemont × TeQing backcross introgression line (TIL) mapping population examined the impact of genotype and AWD severity on iAs grain concentrations. The "Safe"-AWD [35-40% soil volumetric water content (VWC)] treatment did not reduce grain iAs levels, whereas the more severe AWD30 (25-30% VWC) consistently reduced iAs concentrations across all genotypes. The TILs displayed a range of iAs concentrations by genotype, from less than 10 to up to 46 μg kg-1 under AWD30 and from 28 to 104 μg kg-1 under Safe-AWD. TIL grain iAs concentrations for flood treatments across both years ranged from 26 to 127 μg kg-1. Additionally, seven quantitative trait loci (QTLs) were identified in the mapping population associated with grain iAs. A subset of eight TILs and their parents were grown to confirm field-identified grain iAs QTLs in a controlled greenhouse environment. Greenhouse results confirmed the genotypic grain iAs patterns observed in the field; however, iAs concentrations were higher under greenhouse conditions as compared to the field. In the greenhouse, the number of days under AWD was negatively correlated with grain iAs concentrations. Thus, longer drying periods to meet the same soil VWC resulted in lower grain iAs levels. Both the number and combinations of iAs-affecting QTLs significantly impacted grain iAs concentrations. Therefore, identifying more grain iAs-affecting QTLs could be important to inform future breeding efforts for low iAs rice varieties. Our study suggests that coupling AWD practices targeting a soil VWC of less than or equal to 30% coupled with the use of cultivars developed to possess multiple QTLs that negatively regulate grain iAs concentrations will be helpful in mitigating exposure of iAs from rice consumption.

Project description:Following an official request to EFSA from the European Commission, EFSA assessed the chronic dietary exposure to inorganic arsenic (iAs) in the European population. A total of 13,608 analytical results on iAs were considered in the current assessment (7,623 corresponding to drinking water and 5,985 to different types of food). Samples were collected across Europe between 2013 and 2018. The highest mean dietary exposure estimates at the lower bound (LB) were in toddlers (0.30 ?g/kg body weight (bw) per day), and in both infants and toddlers (0.61 ?g/kg bw per day) at the upper bound (UB). At the 95th percentile, the highest exposure estimates (LB-UB) were 0.58 and 1.20 ?g/kg bw per day in toddlers and infants, respectively. In general, UB estimates were two to three times higher than LB estimates. The mean dietary exposure estimates (LB) were overall below the range of benchmark dose lower confidence limit (BMDL 01) values of 0.3-8 ?g/kg bw per day established by the EFSA Panel on Contaminants in the Food Chain in 2009. However, for the 95th percentile dietary exposure (LB), the maximum estimates for infants, toddlers and other children were within this range of BMDL 01 values. Across the different age classes, the main contributors to the dietary exposure to iAs (LB) were 'Rice', 'Rice-based products', 'Grains and grain-based products (no rice)' and 'Drinking water'. Different ad hoc exposure scenarios (e.g. consumption of rice-based formulae) showed dietary exposure estimates in average and for high consumers close to or within the range of BMDL 01 values. The main uncertainties associated with the dietary exposure estimations refer to the impact of using the substitution method to treat the left-censored data (LB-UB differences), to the lack of information (consumption and occurrence) on some iAs-containing ingredients in specific food groups, and to the effect of food preparation on the iAs levels. Recommendations were addressed to improve future dietary exposure assessments to iAs.

Dataset Information

Shifting the Specificity of E. coli Biosensor from Inorganic Arsenic to Phenylarsine Oxide through Genetic Engineering.

Publications

Shifting the Specificity of <i>E. coli</i> Biosensor from Inorganic Arsenic to Phenylarsine Oxide through Genetic Engineering.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets