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Record W2978080790 · doi:10.29173/aar75

Learning the Science Behind Bacteriocins Through Lacticin 3147; a Promising Lantibiotic

2019· article· en· W2978080790 on OpenAlexaffvenue
Allison Wan, Cherry Ibarra-Romero, John C. Vederas, Sorina Chiorean

Bibliographic record

VenueAlberta Academic Review · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLantibioticsBacteriocinNisinAntimicrobialBacteriaBiologyAntimicrobial peptidesChromatographyLactococcus lactisFood scienceMicrobiologyChemistry

Abstract

fetched live from OpenAlex

As microorganisms continue to develop resistance and survive against many different forms of antimicrobial solutions, such as antibiotics, the threat that antimicrobial resistance poses grows considerably. One solution to this persistent issue could be bacteriocins: ribosomally synthesized antimicrobial peptides that are synthesized by bacteria. In this study, the specific lantibiotic—a subclass of bacteriocin—used was lacticin 3147, which is comprised of two components: A1 and A2. Lacticin 3147 was first purified and isolated in order to properly analyze its antimicrobial effects, which show potential use in antibiotics or food preservation. The procedure started with growing the producer bacteria strain, Lactococcus lactis DPC 3147 in a broth which was later used to inoculate a large volume of media. This media was then separated through centrifugation into two components: the supernatant and cell pellet, both of which were each individually concentrated and purified through a series of columns. Approximately one milliliter of each component was run through a High Performance Liquid Chromatography (HPLC) machine, and the resulting chromatograms interpreted to evaluate and compare the concentrations of lacticin 3147 produced in the liquid media portion (supernatant) and the cell components (cell pellet). Subsequently, fractions were collected from all runs from the HPLC and further subjected to Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI TOF) mass spectrometry. This allows to test the molecular weights of the compounds in the samples to check if they aligned with the known molecular weights of both the A1 and A2 components of lacticin 3147. The final step was to prepare a spot on lawn assay using the indicator species: Lactococcus lactis subsp. cremoris HP. The spot on lawn assay prepared for lacticin 3147 was a visual indicator of the strong antimicrobial effects of the bacteriocin. Ultimately, this highly effective bacteriocin, lacticin 3147, could be utilized in smaller concentrations than current antibiotics, and thus shows great promise in the field of antibiotics. Further studies are being conducted to understand the interactions between the A1 and A2 components of lacticin 3147, including their synergistic effects.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.270
Teacher spread0.248 · 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 designNot applicable
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

Citations0
Published2019
Admission routes2
Has abstractyes

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