Arsenic (As) poisoning in aquifers is a serious problem worldwide, especially in the middle-Gangetic Plain (MGP) of India. Microbially-mediated As speciation in such aquifers is governed by the arsenate-reductase enzyme, ArsC, encoded by the arsC gene of As-metabolizing bacteria. In this study, ArsC1 (119 aa) and ArsC2 (141 aa) of a highly resistant strain to arsenic, Citrobacter youngae IITK SM2 (CyIITKSM2), isolated from a mixed-oxic MGP groundwater were biochemically characterized. Coupled-arsenate-reductase assay and IC-ICP-MS analysis confirmed that ArsC2 showed higher As(V) reduction than ArsC1 in the dissolved phase, which was consistent with the prominent structural changes in ArsC2 as identified through circular dichroism spectroscopy. Furthermore, the two ArsCs were able to mobilize arsenic from solid-bound arsenate [As(V)-loaded goethite, AsG] predominantly as As(III). However, the total arsenic released in the presence of ArsC2 was ∼38 % and ∼88 % higher, respectively, as compared to the ArsC1-containing and ArsC-free conditions. A process-based model that considered ArsC-mediated As(V) reduction to As(III) in the dissolved phase, and surface complexation of As(V) and As(III) on goethite, suggested that the extent of arsenate binding with ArsC was not affected by whether As(V) was dissolved or was sorbed. However, the catalytic reduction rate was at least an order of magnitude lower in sorbed As(V) than in dissolved As(V). Mutants of ArsC2 exhibited variable but reduced efficiencies compared to the wild-type ArsC2. This reduction may be attributed to the C-terminal loop observed in the AlphaFold predicted structure of ArsC2, which was absent in ArsC1. This comprehensive biochemical and biophysical analysis of the arsenate reductases in Citrobacter youngae could enhance our understanding of the role these microbes play in arsenic mobilization within MGP aquifers.
Keywords: Arsenate-loaded goethite; Arsenate-reductase proteins (ArsC); Arsenic; Citrobacter youngae IITK SM2 (CyIITKSM2); Goethite; Process-based modeling; Reduction efficiency.
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