Arsenic | EPFL Graph Search

L'arsenic est l'élément chimique de numéro atomique 33, noté par le symbole As. Son corps simple se présente sous la forme d'un solide cristallin argenté. L'arsenic appartient au groupe des pnictogènes () avec l'azote (N), le phosphore (P), l'antimoine (Sb), le bismuth (Bi) et le moscovium (Mc). Il a des propriétés intermédiaires entre celles des métaux et des non-métaux, comme l'antimoine dont il est proche. Il est généralement considéré comme un métalloïde. C'est un élément hautement toxique et un polluant réglementé depuis 2005 en Europe par une directive. Le groupe des pnictogènes montre une tendance croissante à former des sulfures stables plutôt que des oxydes. De même, les ions à base d'As, Sb et Bi sont précipités par le sulfure d'hydrogène en solution. L’arsenic est chimiquement très semblable au phosphore, élément non-métal qui le précède dans le même groupe. On dit qu'il est son « analogue chimique ». Il présente aussi une grande analogie avec l'antimoine semi-métalliqu

Methylation of arsenic by single-species and soil-derived microbial cultures

Karen Elda Viacava Romo

Arsenic (As) is simultaneously a ubiquitous and a toxic element. Arsenic is subject to bio-transformations catalyzed by microorganisms constituting the As biogeochemical cycle. The primordial Earth was devoid of oxygen, exposing life to the highly mobile and toxic arsenite. This early contact with As is imprinted in the tree of life as arsenic resistance genes, e.g. arsenite efflux by transmembrane transporters. Arsenic bio-transformations includes As methylation catalyzed by the ArsM enzyme. ArsM attaches methyl groups to inorganic As, generating organic As in the trivalent (highly toxic species) and pentavalent (relatively innocuous species) forms. Worldwide concern about exposure to As has been raised due to the high As levels in groundwater in South-East Asia used for consumption and rice cultivation. Rice plants are grown under flooded conditions which are conducive to arsenite mobilization and uptake by roots, resulting in the presence of inorganic and methylated As in grains. Compared to inorganic As, methylarsenicals are more easily accumulated in rice grains and are implicated in rice plant disorders resulting in sterility. Methylated species are not synthesized by the plant but by soil microorganisms. To date, mainly aerobic microbial species able to methylate As as an apparent detoxification strategy, have been isolated from paddies. Thus, despite the fact that methylarsenical synthesis appears to be enhanced during anoxic conditions, the drivers and the physiological role of As methylation remain unknown in the absence of oxygen. The thesis focuses on the identification of active As-methylating microorganisms as single species and as members of anaerobic microbiomes from rice paddy soils. In the first part, five bacterial strains and two methanogenic archaea, belonging to genera identified in paddy soils, were evaluated for active arsenite methylation. While aerobic bacterial strains were sensitive to increasing As concentrations, they efficiently methylated As. Conversely, anaerobic bacterial strains were resistant to increasing As concentrations but methylated poorly. Suspecting that As detoxification was occurring through As efflux and outcompeting methylation under anaerobic conditions, we proceeded with the deletion of the arsenite transmembrane transporter in the anaerobic strain Clostridium pasteurianum. The As efflux was disrupted in the mutant leading to higher intracellular concentrations, higher arsM transcription, and increase in the methylation efficiency. Based on the results, we hypothesize that under anoxic conditions, the efficient arsenite efflux systems from anaerobic microorganisms preclude efficient As methylation. In the second part, meta-omic approaches (metagenomics, metatranscriptomics and metaproteomics) were used to identify active As methylators in two soil-derived microbiomes shown to methylate arsenite. The metagenomic data was used to reconstruct the microbial genomes present as metagenome-assembled genomes (MAG). The metabolic capacity for each MAG was identified by the functional annotation of genes while active metabolisms were deciphered from mRNA transcripts (metatranscriptome) and protein expression (metaproteome). Annotation and expression of arsenic resistance genes pointed to fermenting microorganisms as the main drivers of As methylation in both microbiomes. This work is a contribution to the understanding of the linkages between microbial diversity and arsenic bio-transformation.

EPFL2020

Adsorptive Removal of Pb(II) and As(V) from Aqueous Solution by PVDF/HMO Ultrafiltration Mixed Matrix Membrane

Younes Lucas Seghrouchni

Lead and arsenic are among the designated chemicals of major concern by the World Health Organization, they affect millions of people worldwide with both acute and chronic effects on human health. In the current study, mixed matrix membranes (MMMs) were fabricated using polyvinylidene fluoride (PVDF) for the matrix and hydrous manganese dioxide nanoparticles to remove lead, Pb(II), and arsenic, As(V), form water. The objectives of the study were to fabricate membrane with HMO:PVDF ratios from 0 to 1 and to characterize their adsorption properties on the two metals and their filtration performances. The HMO nanoparticles were synthesized using manganese sulfate monohydrate and potassium permanganate. The membranes were fabricated using phase inversion, a dope solution was prepared with HMO:PVDF ratios between 0 and 1, NMP as a solvent at an NMP:PVDF ratio of 5.57 and PVP at a PVP:PVDF ratio of 0.1 to increase the permeance of the membranes. The dope solution was casted and then soaked in a water coagulation bath for phase inversion. The structure of the nanoparticles was observed using TEM, and the structure of the membranes was described using SEM. The adsorption tests assessed the adsorption capacity, the adsorption kinetic and the effect of the pH on the adsorption capacity for the two metals. The concentration in the samples was measured with ICP-OES. A FTIR analysis was performed as a proof of adsorption. The tests that were run to assess the filtration performance of the membranes were the following ones: pure water permeance test, hydrophilicity test, surface analysis using XPS, pore size with AFM and finally filtration capacity on lead and arsenic. The HMO particles that were produced had sizes in the nanometer range and were elongated, which provided them a large surface-to-volume ratio. The membranes had asymmetric structures and the membrane with large HMO ratios had the surface of their pores covered uniformly with HMO particles. The adsorption capacities of pure HMO particles were 36 [mg/g] for arsenic and 283 [mg/g] for lead. The adsorption capacity of the membranes with an HMO:PVDF ratio of 1 was 11 [mg/g] for arsenic and 146 [mg/g] for lead. The Freundlich isotherm was used to describe the adsorption capacity of the membranes for both lead and arsenic. The adsorption kinetic was described by a pseudo-second order kinetic model for arsenic and the results were not significant enough the assess the adsorption kinetic model for lead. The equilibrium was almost reached in 30 minutes for the adsorption of the two metals on pure HMO. The adsorption capacity was enhanced with increasing pH for lead adsorption and it was the opposite for arsenic adsorption. The sensitivity to the pH was higher for lead compared to arsenic and this sensitivity to the pH could be used to regenerate the membrane in case of lead adsorption. The average permeance of the membranes was around 1500 [L/m2h bar], the pore sizes were in the ultrafiltration range, between 41 [nm] and 70 [nm] and the membranes were in the hydrophilic range, with an average contact angle of 69 [°]. The HMO ratio in the membranes had a limited impact on these three parameters. The filtration capacity on arsenic was too low to remove arsenic at ppb concentrations and the results of this test on lead were not significant enough to be interpreted.

2018

Modeling and analysis of parts and devices of genetic regulation

Yves Berset

DNA encrypts the composition of the cellular material that is synthesized through transcription and translation. Never-theless, gene regulation mechanisms determine the final amount of transcribed and translated material. Transcription factors (TF) are a class of proteins that bind to DNA motifs and can either facilitate or prevent the RNA polymerase to transcribe a strand of DNA into an mRNA. These mechanisms allow the cell to sense the environment and adapt to different environmental conditions, e.g. presence of toxic compounds, oxidative stress or absence of nutrients. TF interactions with DNA are depicted by networks of molecular interactions. Some TFs bind to very specific DNA sites, and others have a broad range of binding sites. Moreover, TFs often interact each other, e.g. through heterodimerization prior to bind to DNA, leading to changes in their binding specificities. However, these effects remain poorly understood. By combining detailed mathematical modeling and high-throughput experimental techniques for quantification of molecular interactions, we built a heterodimer-DNA specificity model with higher predictive power than a one-site model. Bioreporters are living cells that emit a signal in the presence of a chemical compound. In arsenic bioreporters, a TF triggers the detoxification response in presence of arsenic. To better understand the key mechanisms involved in the response, we built a detailed mechanistic model of the gene regulatory circuits of different bioreporters. In this study, we used mathematical modeling (ODE, SSA) to create, calibrate and analyze detailed networks of molecular interactions involved in gene regulations. We quantified the cooperative binding of transcription factors forming heterodimers on a DNA library, and optimized bioreporters for the detection of arsenic by modeling feedback, uncoupled and toggle switched-based gene regulatory circuits.

EPFL2018