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Record W2990075611 · doi:10.1111/mmi.14435

Surface resistance to SSVs and SIRVs in pilin deletions of <i>Sulfolobus islandicus</i>

2019· article· en· W2990075611 on OpenAlexaff
Elizabeth F. Rowland, María A. Bautista, Changyi Zhang, Rachel J. Whitaker

Bibliographic record

VenueMolecular Microbiology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Calgary
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsSulfolobusBiologyPilinGeneticsPilusSulfolobus solfataricusVirologyGeneMicrobiologyArchaeaVirulence

Abstract

fetched live from OpenAlex

Characterizing the molecular interactions of viruses in natural microbial populations offers insights into virus-host dynamics in complex ecosystems. We identify the resistance of Sulfolobus islandicus to Sulfolobus spindle-shaped virus (SSV9) conferred by chromosomal deletions of pilin genes, pilA1 and pilA2 that are individually able to complement resistance. Mutants with deletions of both pilA1 and pilA2 or the prepilin peptidase, PibD, show the reduction in the number of pilins observed in TEM and reduced surface adherence but still adsorb SSV9. The proteinaceous outer S-layer proteins, SlaA and SlaB, are not required for adsorption nor infection demonstrating that the S-layer is not the primary receptor for SSV9 surface binding. Strains lacking both pilins are resistant to a broad panel of SSVs as well as a panel of unrelated S. islandicus rod-shaped viruses (SIRVs). Unlike SSV9, we show that pilA1 or pilA2 is required for SIRV8 adsorption. In sequenced Sulfolobus strains from around the globe, one copy of each pilA1 and pilA2 is maintained and show codon-level diversification, demonstrating their importance in nature. By characterizing the molecular interactions at the initiation of infection between S. islandicus and two different types of viruses we hope to increase the understanding of virus-host interactions in the archaeal domain.

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 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 score0.257
Threshold uncertainty score0.720

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)0.0010.000

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 head0.003
GPT teacher head0.198
Teacher spread0.195 · 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

Citations31
Published2019
Admission routes1
Has abstractyes

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