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Tolerance of Pseudomonas pseudoalcaligenes KF707 to metals, polychlorobiphenyls and chlorobenzoates: effects on chemotaxis-, biofilm- and planktonic-grown cells

2010· article· en· W1858420640 on OpenAlexafffund
Valentina Tremaroli, Caterina Vacchi Suzzi, Stefano Fedi, Howard Ceri, Davide Zannoni, Raymond J. Turner

Bibliographic record

VenueFEMS Microbiology Ecology · 2010
Typearticle
Languageen
FieldEngineering
TopicEnvironmental remediation with nanomaterials
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsBiofilmChemotaxisBiologyPseudomonasBiphenylBacteriaMicrobiologyMetalloidMetalEnvironmental chemistryBioremediationMicroorganismBiodegradationMetal toxicityBiochemistryHeavy metalsChemistryEcologyOrganic chemistryReceptor

Abstract

fetched live from OpenAlex

Pseudomonas pseudoalcaligenes KF707 is a polychlorinated biphenyls (PCBs) degrader, also tolerant to several toxic metals and metalloids. The work presented here examines for the first time the chemotactic response of P. pseudoalcaligenes KF707 to biphenyl and intermediates of the PCB biodegradation pathway in the presence and absence of metals. Chemotaxis analyses showed that biphenyl, benzoic acid and chlorobenzoic acids acted as chemoattractants for KF707 cells and that metal cations such as Ni(2+) and Cu(2+) strongly affected the chemotactic response. Toxicity profiles of various metals on KF707 cells grown on succinate or biphenyl as planktonic and biofilm were determined both in the presence and in the absence of PCBs. Notably, KF707 cells from both biofilms and planktonic cultures were tolerant to high amounts (up to 0.5 g L(-1)) of Aroclor 1242, a commercial mixture of PCBs. Together, the data show that KF707 cells are chemotactic and can form a biofilm in the presence of Aroclor 1242 and specific metals. These findings provide new perspectives on the effectiveness of using PCB-degrading bacterial strains in bioremediation strategies of metal-co-contaminated sites.

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 categoriesMeta-epidemiology (narrow)
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 score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.004
GPT teacher head0.189
Teacher spread0.185 · 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.

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

Citations45
Published2010
Admission routes2
Has abstractyes

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