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Record W3202440228 · doi:10.1371/journal.pntd.0009828

Mining nematode protein secretomes to explain lifestyle and host specificity

2021· article· en· W3202440228 on OpenAlexafffund
Lucienne Tritten, Cristina Ballesteros, Robin N. Beech, Timothy G. Geary, Yovany Moreno

Bibliographic record

VenuePLoS neglected tropical diseases · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicStudies on Chitinases and Chitosanases
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsBiologyNematodeHost (biology)Caenorhabditis elegansComputational biologyGeneEvolutionary biologyGeneticsEcology

Abstract

fetched live from OpenAlex

Parasitic nematodes are highly successful pathogens, inflicting disease on humans, animals and plants. Despite great differences in their life cycles, host preference and transmission modes, these parasites share a common capacity to manipulate their host's immune system. This is at least partly achieved through the release of excretory/secretory proteins, the most well-characterized component of nematode secretomes, that are comprised of functionally diverse molecules. In this work, we analyzed published protein secretomes of parasitic nematodes to identify common patterns as well as species-specific traits. The 20 selected organisms span 4 nematode clades, including plant pathogens, animal parasites, and the free-living species Caenorhabditis elegans. Transthyretin-like proteins were the only component common to all adult secretomes; many other protein classes overlapped across multiple datasets. The glycolytic enzymes aldolase and enolase were present in all parasitic species, but missing from C. elegans. Secretomes from larval stages showed less overlap between species. Although comparison of secretome composition across species and life-cycle stages is challenged by the use of different methods and depths of sequencing among studies, our workflow enabled the identification of conserved protein families and pinpointed elements that may have evolved as to enable parasitism. This strategy, extended to more secretomes, may be exploited to prioritize therapeutic targets in the future.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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 teacher head, 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

Citations27
Published2021
Admission routes2
Has abstractyes

Explore more

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