Quantifying arsenic-binding affinities of ArsR proteins via biomimetic self-assembly.

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Autori principali: Cui, Liang, Zhang, Xiaobo, Sun, Xiaohui, Yang, Yi, Zhu, Bitong, Wang, Shasha, Lin, RuoXin, Zhao, Chungui, Zhang, Guangya, Chen, Jian, Yang, Suping
Natura: Artículo científico
Lingua:en
Pubblicazione: Frontiers in microbiology 2026
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author Cui, Liang
Zhang, Xiaobo
Sun, Xiaohui
Yang, Yi
Zhu, Bitong
Wang, Shasha
Lin, RuoXin
Zhao, Chungui
Zhang, Guangya
Chen, Jian
Yang, Suping
author_facet Cui, Liang
Zhang, Xiaobo
Sun, Xiaohui
Yang, Yi
Zhu, Bitong
Wang, Shasha
Lin, RuoXin
Zhao, Chungui
Zhang, Guangya
Chen, Jian
Yang, Suping
Cui, Liang
Zhang, Xiaobo
Sun, Xiaohui
Yang, Yi
Zhu, Bitong
Wang, Shasha
Lin, RuoXin
Zhao, Chungui
Zhang, Guangya
Chen, Jian
Yang, Suping
collection PubMed - marine biology
contents Quantifying arsenic-binding affinities of ArsR proteins via biomimetic self-assembly. Cui, Liang Zhang, Xiaobo Sun, Xiaohui Yang, Yi Zhu, Bitong Wang, Shasha Lin, RuoXin Zhao, Chungui Zhang, Guangya Chen, Jian Yang, Suping 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, 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 CGA009. RpArsR1 and RpArsR2 exhibited the highest affinity constants ( > 10 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.
format Artículo científico
id pubmed_42254499
institution PubMed
language en
publishDate 2026
publisher Frontiers in microbiology
record_format pubmed
spellingShingle Quantifying arsenic-binding affinities of ArsR proteins via biomimetic self-assembly.
Cui, Liang
Zhang, Xiaobo
Sun, Xiaohui
Yang, Yi
Zhu, Bitong
Wang, Shasha
Lin, RuoXin
Zhao, Chungui
Zhang, Guangya
Chen, Jian
Yang, Suping
Quantifying arsenic-binding affinities of ArsR proteins via biomimetic self-assembly. Cui, Liang Zhang, Xiaobo Sun, Xiaohui Yang, Yi Zhu, Bitong Wang, Shasha Lin, RuoXin Zhao, Chungui Zhang, Guangya Chen, Jian Yang, Suping 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, 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 CGA009. RpArsR1 and RpArsR2 exhibited the highest affinity constants ( > 10 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.
title Quantifying arsenic-binding affinities of ArsR proteins via biomimetic self-assembly.
url https://pubmed.ncbi.nlm.nih.gov/42254499/