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Bacterial Volatile Compounds: Functions in Communication, Cooperation, and Competition

2020· review· en· W3042303476 on OpenAlexaff
Tina Netzker, E Shepherdson, Matthew Zambri, Marie A. Elliot

Bibliographic record

VenueAnnual Review of Microbiology · 2020
Typereview
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiologyCompetition (biology)ProtistBacteriaComputational biologyBiochemical engineeringEcologyBiochemistry

Abstract

fetched live from OpenAlex

Bacteria produce a multitude of volatile compounds. While the biological functions of these deceptively simple molecules are unknown in many cases, for compounds that have been characterized, it is clear that they serve impressively diverse purposes. Here, we highlight recent studies that are uncovering the volatile repertoire of bacteria, and the functional relevance and impact of these molecules. We present work showing the ability of volatile compounds to modulate nutrient availability in the environment; alter the growth, development, and motility of bacteria and fungi; influence protist and arthropod behavior; and impact plant and animal health. We further discuss the benefits associated with using volatile compounds for communication and competition, alongside the challenges of studying these molecules and their functional roles. Finally, we address the opportunities these compounds present from commercial, clinical, and agricultural perspectives.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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 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

Citations109
Published2020
Admission routes1
Has abstractyes

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