MétaCan
Menu
Back to cohort
Record W2035334195 · doi:10.1371/journal.pone.0081285

Helical Antifreeze Proteins Have Independently Evolved in Fishes on Four Occasions

2013· article· en· W2035334195 on OpenAlexafffund
Laurie A. Graham, Rod S. Hobbs, Garth L. Fletcher, Peter L. Davies

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMemorial University of NewfoundlandQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsAntifreeze proteinBiologyEvolutionary biologyConvergent evolutionMolecular evolutionSequence alignmentPeptide sequenceGeneticsPhylogeneticsGene

Abstract

fetched live from OpenAlex

Alanine-rich α-helical (type I) antifreeze proteins (AFPs) are produced by a variety of fish species from three different orders to protect against freezing in icy seawater. Interspersed amongst and within these orders are fishes making AFPs that are completely different in both sequence and structure. The origin of this variety of types I, II, III and antifreeze glycoproteins (AFGPs) has been attributed to adaptation following sea-level glaciations that occurred after the divergence of most of the extant families of fish. The presence of similar types of AFPs in distantly related fishes has been ascribed to lateral gene transfer in the case of the structurally complex globular type II lectin-like AFPs and to convergent evolution for the AFGPs, which consist of a well-conserved tripeptide repeat. In this paper, we examine the genesis of the type I AFPs, which are intermediate in complexity. These predominantly α-helical peptides share many features, such as putative capping structures, Ala-richness and amphipathic character. We have added to the type I repertoire by cloning additional sequences from sculpin and have found that the similarities between the type I AFPs of the four distinct groups of fishes are not borne out at the nucleotide level. Both the non-coding sequences and the codon usage patterns are strikingly different. We propose that these AFPs arose via convergence from different progenitor helices with a weak affinity for ice and that their similarity is dictated by the propensity of specific amino acids to form helices and to align water on one side of the helix into an ice-like pattern.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.068
GPT teacher head0.212
Teacher spread0.144 · 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; both teacher heads agree on what is shown here.

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

Citations61
Published2013
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicPhysiological and biochemical adaptationsFrench-language works237,207