MétaCan
Menu
Back to cohort
Record W2604589627 · doi:10.3389/fmicb.2017.00526

Mosquito Microbiome Dynamics, a Background for Prevalence and Seasonality of West Nile Virus

2017· article· en· W2604589627 on OpenAlexaffabout
Eva Nováková, Douglas C. Woodhams, Sonia M. Rodríguez‐Ruano, Robert M. Brucker, Jonathan W. Leff, Amin Maharaj, Amnon Amir, Rob Knight, James A. Scott

Bibliographic record

VenueFrontiers in Microbiology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect symbiosis and bacterial influences
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersUniversity of Massachusetts Boston
KeywordsBiologyWolbachiaCulex pipiensMicrobiomeHost (biology)Abundance (ecology)EcologyRelative species abundanceZoology

Abstract

fetched live from OpenAlex

Symbiotic microbial communities augment host phenotype, including defense against pathogen carriage and infection. We sampled the microbial communities in eleven adult mosquito host species from six regions in southern Ontario, Canada over three years. Of the factors examined, we found that mosquito species was the largest driver of the microbiota, with remarkable phylosymbiosis between host and microbiota. Seasonal shifts of the microbiome were consistently repeated over the three-year period, while region had little impact. Both host species and seasonal shifts in microbiota were associated with patterns of West Nile virus (WNV) in these mosquitoes. The highest prevalence of WNV, with a seasonal spike each year in August, was in the Culex pipiens/restuans complex, and high WNV prevalence followed a decrease in relative abundance of Wolbachia in this species. Indeed, mean temperature, but not precipitation, was significantly correlated with Wolbachia abundance. This suggests that at higher temperatures Wolbachia abundance is reduced leading to greater susceptibility to WNV in the subsequent generation of C. pipiens/restuans hosts. Different mosquito genera harbored significantly different bacterial communities, and presence or abundance of Wolbachia was primarily associated with these differences. We identified several operational taxonomic units (OTUs) of Wolbachia that drive overall microbial community differentiation among mosquito taxa, locations and timepoints. Distinct Wolbachia OTUs were consistently found to dominate microbiomes of Cx. pipiens/restuans, and of Coquilletidia perturbans. Seasonal fluctuations of several other microbial taxa included Bacillus cereus, Enterococcus, Methylobacterium, Asaia, Pantoea, Acinetobacter johnsonii, Pseudomonas, and Mycoplasma. This suggests that microbiota may explain some of the variation in vector competence previously attributed to local environmental processes, especially because Wolbachia is known to affect carriage of viral pathogens.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.748

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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

Citations133
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in MicrobiologySame topicInsect symbiosis and bacterial influencesFrench-language works237,207