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Induction of trap formation in nematode-trapping fungi by a bacterium

2011· article· en· W1917854025 on OpenAlexfundno aff
Lei Li, Mingchuan Ma, Yongjun Liu, Jingwei Zhou, Qing Qu, Kai-Ping Lu, Denggao Fu, Ke‐Qin Zhang

Bibliographic record

VenueFEMS Microbiology Letters · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsnot available
FundersNatural Science Foundation of Yunnan ProvinceNational Natural Science Foundation of ChinaMcMaster University
KeywordsBacteriaHyphaBiologyMicrobiologyNematodeMyceliumConidiumMicrobiological cultureBacterial cell structureBotanyEcology

Abstract

fetched live from OpenAlex

Three soil bacterial strains were identified as Chryseobacterium sp. TFB on the basis of their 16S rRNA gene sequences. Conidia of Arthrobotrys oligospora produced a few mycelial traps (MT) and conidial traps (CT) when cultured with bacterial cells that they did not produce when cultured with a bacterial cell-free culture filtrate. However, co-culture of A. oligospora with bacterial cells and bacteria-free filtrate simultaneously induced MT and CT in large amounts. With the increased concentration of bacteria-free filtrate, the number of typical CT increased, but conidial germination was progressively inhibited. Scanning electron microscopy of A. oligospora co-cultured with bacteria revealed that bacterial attachment to hyphae was a prerequisite to trap formation and that bacteria-free filtrate facilitated bacterial attachments to hyphae. The results that the addition of nutrients in co-culture medium decreased the number of traps suggest that this type of trap formation may be favoured at a low nutrient status. Eight fungi tested were able to form MT and CT when co-cultured with bacterial cells and bacteria-free culture filtrate, but the abilities varied among species. This study provides novel evidence that under laboratory conditions, soil bacteria attaching to hyphae could induce traps in nematode-trapping fungi.

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 score0.366
Threshold uncertainty score0.181

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)0.0000.000

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 head0.026
GPT teacher head0.188
Teacher spread0.162 · 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

Citations29
Published2011
Admission routes1
Has abstractyes

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