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Quantifies arsenic-binding affinities in ArsR proteins, suggesting implications for environmental bioremediation.
ArsR, an As(III)-binding transcriptional repressor protein, plays a critical role in arsenic (As) detoxification by selectively binding As(III) and regulating cellular responses. Recent studies have revealed that ArsRs exhibit broad diversity in their arsenic recognition and binding sites. Multiple ArsRs are often found in highly As-resistant microbes, allowing for coping with complicated arsenical stresses. However, quantitative assessments of ArsR binding affinities and their contributions to arsenic resistance remain limited due to methodological challenges. In this study, we developed a novel biomimetic self-assembly approach, applied in a protein purification-free manner after initial validation, to quantify the arsenic binding affinity of ArsR-As interaction. ArsR was immobilized on the surface of biosilica spheres (S) via the covalently cross-link self-assembly of ArsR-SpyTag and ELP-SpyCatcher@SiO 2 , created a novel solid-phase arsenic adsorbent (S-ArsR) for precise binding affinity measurements. Using this technological platform, we characterized nine diverse ArsR homologs (RpArsR) from the highly arsenic-resistant bacterium Rhodopseudomonas palustris CGA009. RpArsR1 and RpArsR2 exhibited the highest affinity constants ( K A > 10 7 M) for As(III), with binding affinity influenced by both cysteine content and structural context. Phylogenetic analysis clustered nine RpArsRs into three distinct subgroups (I, III, and IV), with binding affinities ranked as III > I > IV. These results reveal functional diversity in As(III)-binding behavior among ArsR homologs and provide a quantitative framework for comparing their binding properties. Notably, RpArsR2 significantly lowered As(III) accumulation in plants, highlighting its bioremediation potential. Our work enables a purification-free application strategy after initial validation and offers broad applicability for analyzing various protein-ligand interactions. It also provides a new strategy for developing highly selective arsenic adsorbents for environmental bioremediation.
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Cui et al. (2026) studied this question.
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