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Record W2750277627 · doi:10.1073/pnas.1708097114

Host-derived viral transporter protein for nitrogen uptake in infected marine phytoplankton

2017· article· en· W2750277627 on OpenAlexaff
Adam Monier, Aurélie Chambouvet, David S. Milner, Victoria Attah, Ramón Terrado, Connie Lovejoy, Hervé Moreau, Alyson E. Santoro, Évelyne Derelle, Thomas A. Richards

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsDalhousie UniversityUniversité Laval
FundersLeibniz-GemeinschaftUniversity of ExeterRoyal SocietyLeverhulme TrustWellcome TrustGordon and Betty Moore FoundationNational Science Foundation
KeywordsNutrientBiologyHost (biology)TransporterGeneVirusPhytoplanktonEcologyVirologyGenetics

Abstract

fetched live from OpenAlex

, a host-derived ammonium transporter. This gene is transcribed during infection and when expressed in yeast mutants the viral protein is located to the plasma membrane and rescues growth when cultured with ammonium as the sole nitrogen source. We also show that viral infection alters the nature of nitrogen compound uptake of host cells, by both increasing substrate affinity and allowing the host to access diverse nitrogen sources. This is important because the availability of nitrogen often limits phytoplankton growth. Collectively, these data show that a virus can acquire genes encoding nutrient transporters from a host genome and that expression of the viral gene can alter the nutrient uptake behavior of host cells. These results have implications for understanding how viruses manipulate the physiology and ecology of phytoplankton, influence marine nutrient cycles, and act as vectors for horizontal gene transfer.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.026
GPT teacher head0.284
Teacher spread0.258 · 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 designObservational
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

Citations115
Published2017
Admission routes1
Has abstractyes

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