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Record W4387138358 · doi:10.1101/2023.09.27.559745

Dairy practices select for thermostable endolysins in phages

2023· preprint· en· W4387138358 on OpenAlexafffund
Frank Oechslin, Xiaojun Zhu, Carlee Morency, Vincent Somerville, Rong Shi, Sylvain Moineau

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversité Laval
FundersArgonne National LaboratoryNatural Sciences and Engineering Research Council of CanadaEli Lilly and CompanySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungU.S. Department of EnergyOffice of ScienceNational Science Foundation
KeywordsLysinStreptococcus thermophilusLytic cycleBacteriophageBiologyBacteriaDairy industryThermophilePeptidoglycanMicrobiologyBiochemistryFood scienceGeneticsEscherichia coliLactic acidGeneVirus

Abstract

fetched live from OpenAlex

Abstract Endolysins are phage lytic enzymes that degrade the bacterial cell wall to release phage progeny. We found that the diversity of endolysins is unsuspectedly low and dominated by a single structural type in distinct phages that infect Streptococcus thermophilus . Through X-ray crystallography, we discovered that this type of endolysin contains a highly conserved calcium-binding motif in its cell wall binding domain. Inactivation of the motif in the purified endolysin or in the phage genome revealed its key role in stabilizing the enzyme under conditions that mimic the cheesemaking process, including at elevated temperatures. Fermented dairy products such as yogurt and cheeses are incubated or cooked at higher temperatures and require the addition of thermophilic lactic acid bacteria such as S. thermophilus to drive milk fermentation. It appears that dairy practices have influenced the genetic signatures of streptococcal phages by selecting for thermostable endolysins, which in turn have limited their diversity.

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)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.265
Teacher spread0.235 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

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