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Record W4414014444 · doi:10.1099/mic.0.001604

Microbial Primer: Biosurfactants – the ABCs of microbial surface-active metabolites

2025· review· en· W4414014444 on OpenAlexafffund
Maxence Roy, Éric Déziel

Bibliographic record

VenueMicrobiology · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrobial ecologyBiologyBacteriaAmphiphileMicroorganismSupramolecular chemistryArchaeaChemistryComputational biologyBiochemistryMicrobiologyOrganic chemistryGeneticsMolecule

Abstract

fetched live from OpenAlex

Microbial surfactants (biosurfactants) are low-molecular-weight amphiphilic secondary metabolites synthesized by a wide range of micro-organisms, including bacteria, yeasts and fungi. These compounds reduce surface and interfacial tension, promote emulsification and self-assemble into supramolecular structures such as micelles. Their remarkable structural diversity reflects the metabolic complexity of their microbial producers. In this primer, we outline shared features across biosurfactant-producing organisms, focusing on biosynthetic pathways, biological functions and regulatory mechanisms. The study of biosurfactants lies at the intersection of ecological, biotechnological and medical research, offering valuable insights into microbial ecology and promising avenues for sustainable innovation.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.018
GPT teacher head0.271
Teacher spread0.253 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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