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Record W4403553297 · doi:10.1101/2024.10.16.618703

Identification and characterization of a wet adhesive protein extracted from <i>Dreissena bugensis</i> , the freshwater quagga mussel

2024· preprint· en· W4403553297 on OpenAlexaff
Angelico Obille, Judith Ng, Karina M. M. Carneiro, Eli D. Sone

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldEngineering
TopicMarine Biology and Environmental Chemistry
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDreissenaMusselIdentification (biology)Freshwater bivalveFisheryAquatic animalBiologyEcologyZoologyMolluscaBivalviaFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract Mechanisms of wet adhesion have been developed by several aquatic organisms over millions of years of evolutionary processes. Yet, the repertoire of synthetic biocompatible wet adhesive materials is still limited. In most marine bioadhesive proteins, 3,4-dihydroxyphenylalanine (DOPA) plays a significant role in strong interfacial interactions. The bioadhesive proteins in freshwater organisms are less well understood. The quagga mussel ( Dreissena bugensis ) is a notorious freshwater invasive species in the Great Lakes that attaches to a plethora of surfaces via a byssus. To determine the adhesive proteins in the quagga mussel byssus, we utilized quantitative proteomics to identify the proteins enriched at the byssus-substrate interface. Among the identified proteins was the Dbfp7 protein family. Dbfp7 is a small, polymorphic, and mostly disordered protein that lacks significant amounts of DOPA. Atomic force microscopy measurements of Dbfp7 confirm that this protein has similar adhesion energy to marine mussel adhesive proteins in aqueous conditions despite lacking DOPA. These results suggest that freshwater mussels may employ different mechanisms of adhesion compared to marine byssates. The inclusion of Dbfp7 to the library of known wet bioadhesive proteins – the first functionally characterized freshwater bioadhesive protein to our knowledge – will allow for a better understanding of the fundamental properties required to achieve biocompatible wet adhesion, a crucial step for the development of bio-inspired wet adhesive materials, such as improved medical adhesives. Significance Statement While many aquatic organisms evolved strategies to adhere to surfaces underwater, current synthetic biocompatible adhesives lack reliable adhesive strength in varying aqueous conditions. Investigating freshwater mussel adhesive proteins expands the current understanding of aquatic bioadhesion and offers potential advancements in wet adhesive technology. The discovery of a DOPA-deficient wet adhesive protein derived from the invasive quagga mussels presents a paradigm shift to the currently known mechanisms of byssal bioadhesion, thereby expanding the repertoire of wet adhesive strategies. Further, understanding the mechanism of adhesion employed by this biofouling species can help with the design of anti-fouling strategies to mitigate the impacts of these animals on the infrastructure and ecosystems in the Great Lakes and connected freshwater systems in North America.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.168
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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