A dual-domain chitinase mechanism enables marine bacteria tosense and localize sparse crystalline chitin in the ocean
Tanimoto, H.; Tsudome, M.; Tachioka, M.; Baba, A.; Miyazaki, M.; Uchihashi, T.; Iino, R.; Deguchi, S.; Nakamura, A.
Show abstract
Chitin is one of the most abundant biopolymers in the ocean, and its remineralisation underpins major pathways of marine carbon cycling. A central challenge for chitinolytic bacteria is to locate and remain associated with sparsely distributed crystalline chitin particles. Here, we show that the GH18 chitinase VpChi1 from Vibrio parahaemolyticus possesses a dual-domain architecture that enhances particle encounter and retention. Full-length VpChi1 displayed much higher catalytic efficiency than a CBD-truncated mutant at low chitin concentrations, whereas substrate inhibition occurred at higher concentrations. Single-molecule fluorescence imaging demonstrated that the additional C-terminal chitin-binding domain (CBD) enables selective binding to the hydrophobic surface of crystalline chitin and substantially prolongs enzyme residence time. Kinetic simulations using experimentally determined dissociation rates showed that this extended residence arises from CBD-assisted rebinding of the catalytic domain. High-speed atomic force microscopy confirmed that the CBD does not alter stepping velocity or travel distance along individual crystals, indicating that substrate inhibition likely results from CBD engagement with neighbouring particles rather than impaired motility. Screening of seawater and marine sediments across multiple depths identified Vibrio and Pseudoalteromonas species as dominant chitin degraders, many encoding GH18 chitinases with dual CBDs, whereas terrestrial bacteria generally lacked this architecture. We propose that this two-domain configuration confers an ecological advantage by increasing enzyme retention on particulate chitin and enabling sustained production of chitobiose, a potent chemotactic signal for marine bacteria. These findings reveal a mechanistic basis for how bacteria sense and exploit particulate chitin and highlight an adaptive strategy for resource acquisition in the ocean.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- The fish pathogen Aliivibrio salmonicida LFI1238 can degrade and metabolize chitin despite major gene loss in the chitinolytic pathway 95%
- Thermophilic carboxylesterases from hydrothermal vents of the volcanic island of Ischia active on synthetic and biobased polymers and mycotoxins 94%
- Loosenin-like proteins from Phanerochaete carnosa impact both cellulose and chitin fiber networks 93%
Similar papers in this journal
- Identification of the Clostridial cellulose synthase and characterization of the cognate glycosyl hydrolase, CcsZ 94%
- Crystal structure of β-L-arabinobiosidase belonging to glycoside hydrolase family 121 92%
- Biophysical and biochemical evidence for the role of acetate kinases (AckAs) in an acetogenic pathway in pathogenic spirochetes 92%
Similar papers in this journal
- Diversity, structure-function relationships and evolution of cell wall-binding domains of staphylococcal phage endolysins 94%
- Vibrio campbellii chitoporin: thermostability study and implications for the development of therapeutic agents against Vibrio infections 92%
- Structural framework for the understanding spectroscopic and functional signatures of the cyanobacterial Orange Carotenoid Protein families 92%
Similar papers in this journal
- Characterization of TelE, an LXG effector exhibiting a conserved C-terminal glycine zipper motif required for toxicity 94%
- Lysis cassette-mediated exoprotein release in Yersinia entomophaga is controlled by a PhoB-like regulator 93%
- Comparative phylogenomic analysis reveals evolutionary genomic changes and novel toxin families in endophytic Liberibacter pathogens 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.