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Cofactor binding interactions with reductive dehalogenase shape cobamide utilization in organohalide-respiring
Huijuan Jin1, Jingjing Wang1, Xiuying Li1
1Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China.
Communications Biology
|May 18, 2026
Summary
Organohalide-respiring bacteria (OHRB) show specific cobamide preferences due to variations in reductive dehalogenase (RDase) enzyme structures. This study links RDase architecture to cobamide binding, enabling computational prediction of enzyme-cofactor compatibility.
Area of Science:
- Biogeochemistry
- Microbial Metabolism
- Enzyme Catalysis
Background:
- Organohalide respiration is crucial for global halogen cycling and bioremediation.
- Organohalide-respiring bacteria (OHRB) exhibit selective utilization of cobamides (vitamin B12 cofactors).
- Structural variations in cobamides, especially the lower base, can inhibit reductive dehalogenase (RDase) activity.
Purpose of the Study:
- To elucidate the molecular basis for specific cobamide utilization in OHRB.
- To correlate RDase cofactor-binding capabilities with OHRB cobamide selectivity.
- To develop computational methods for predicting cobamide-enzyme compatibility.
Main Methods:
- Competition-based in vivo assays to assess cobamide selectivity.
- Structural modeling and molecular docking to identify active-site features.
- In silico analysis of RDase homologs and their predicted cofactor-binding sites.
Main Results:
- RDase homologs display distinct cofactor-binding affinities that mirror the cobamide preferences of their host OHRB.
- Candidate active-site residues and features contributing to cobamide binding and stability were identified.
- A strong correlation between RDase architecture and cobamide-utilizing ability in OHRB was established.
Conclusions:
- Cobamide selectivity in OHRB is intrinsically linked to the architecture of their RDases.
- Computational prediction of cobamide-enzyme compatibility offers a novel approach for understanding and manipulating microbial communities.
- This approach can guide targeted interventions in environmental and host-associated microbiomes, including methanogenic communities.
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