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Record W4402312328 · doi:10.1128/spectrum.01509-24

<i>Acinetobacter calcoaceticus-baumannii</i> complex prevalence, spatial-temporal distribution, and contamination sources in Canadian aquatic environments

2024· article· en· W4402312328 on OpenAlexafffundabout
Thomas Benoit, Dania Sajjad, Michel Cloutier, David R. Lapen, Emilia Craiovan, Ellen M. E. Sykes, Ayush Kumar, Izhar U. H. Khan

Bibliographic record

VenueMicrobiology Spectrum · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of ManitobaUniversity of OttawaAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsAcinetobacter baumanniiAcinetobacter calcoaceticusEffluentContaminationBiologyVeterinary medicineAcinetobacterSurface waterEnvironmental scienceMicrobiologyToxicologyEcologyMedicineEnvironmental engineeringBacteriaAntibioticsPseudomonas aeruginosa

Abstract

fetched live from OpenAlex

ABSTRACT Acinetobacter calcoaceticus-baumannii (ACB) complex has been identified as a group of emerging opportunistic pathogens that cause nosocomial infections. The current study investigates the prevalence, distribution, and diversity of pathogenic ACB complex in various aquatic systems with different uses. Of the total 157 agricultural, raw drinking water intake, recreational beach, and wastewater treatment plant (WWTP) effluent samples, acinetobacters were isolated, quantified, and confirmed by genus- and ACB complex-specific PCR assays. Of all agricultural surface water samples, A. calcoaceticus (65%) was more frequently detected than A. pittii (14%), A. nosocomialis (9%), and A. baumannii (3%). In WWTP effluent samples, A. baumannii was more prevalent in de-chlorinated (60%) samples compared to both A. pittii and A. nosocomialis (40%). Interestingly , A. nosocomialis (43%), A. calcoaceticus (29%), and A. baumannii (14%) were detected in raw drinking water intake samples, whereas A. pittii (50%) and A. nosocomialis (25%) were detected in beach samples. Although no sampling location-specific differences were recorded, significant ( P < 0.05) seasonal differences were observed when agricultural surface water samples collected in spring were compared with the summer and fall. Whereas effluent chlorination significantly impacted the degree of prevalence of Acinetobacter in WWTP effluent samples, overall, the prevalence of ACB complex in all sampling locations and seasons indicates that these water sources, containing human-associated ACB complex, may pose potential health risks as community-acquired opportunistic infections. IMPORTANCE Acinetobacter calcoaceticus-baumannii (ACB) complex is a group of organisms known to cause problematic nosocomial opportunistic infections. A member of the species complex, A. baumannii , is becoming a global threat to infection treatment as strains are increasingly develop resistance to antibiotics. The prevalence and distribution of potentially pathogenic Acinetobacter calcoaceticus-baumannii complex species remain poorly understood, and there is a need to better understand the occurrence of A. baumannii in non-nosocomial environments. Our research details the spatial-temporal distribution of ACB complex species in a regional watershed and highlights the presence of ACB complex in wastewater effluent that is discharged into a river. These findings deepen our understanding of this group of species in non-nosocomial environments and encourage the development of monitoring programs for these species in regional waters.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.216
Teacher spread0.210 · 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 designObservational
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

Citations4
Published2024
Admission routes3
Has abstractyes

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