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Record W6929438789 · doi:10.5061/dryad.98sf7m0ms

A highly divergent Wolbachia with a tiny genome in an insect-parasitic tylenchid nematode

2022· dataset· en· W6929438789 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsUniversity of Victoria
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsNucleofectionProteogenomicsHyporeflexiaGestational periodTSG101Fusible alloy

Abstract

fetched live from OpenAlex

Wolbachia symbionts are the most successful host-associated microbes on the planet, infecting arthropods and nematodes. Their role in nematodes is particularly enigmatic, with filarial nematode species either 100% infected and dependent on symbionts for reproduction and development, or not at all infected. We have discovered a highly divergent strain of Wolbachia in an insect-parasitic tylenchid nematode, Howardula sp., in a nematode clade that has not previously been known to harbour Wolbachia. While this nematode is 100% infected with Wolbachia, we did not detect it in related species. We sequenced the Howardula symbiont (wHow) genome and found that it is highly reduced, comprising only 550 kilobase pairs of DNA, ~35% smaller than the smallest Wolbachia nematode symbiont genomes. The wHow genome is a subset of all other Wolbachia genomes and has not acquired any new genetic information. While it has lost many genes, including genes involved in cell wall synthesis and cell division, it has retained the entire heme biosynthesis pathway, suggesting that heme supplementation is critical. wHow provides key insights into our understanding of what are the lower limits of Wolbachia cells, as well as the role of Wolbachia symbionts in the biology and convergent evolution of diverse parasitic nematodes.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.010

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 head0.021
GPT teacher head0.281
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations2
Published2022
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicPhotosynthetic Processes and MechanismsFrench-language works237,207