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Record W4378349026 · doi:10.3389/fmicb.2023.1173609

Comparison of salivary gland and midgut microbiome in the soft ticks Ornithodoros erraticus and Ornithodoros moubata

2023· article· en· W4378349026 on OpenAlexaff
Elianne Piloto‐Sardiñas, Ana Laura Cano‐Argüelles, Apolline Maître, Alejandra Wu‐Chuang, Lourdes Mateos‐Hernández, Alexandra Corduneanu, Dasiel Obregón, Ana Oleaga, Ricardo Pérez–Sánchez, Alejandro Cabezas‐Cruz

Bibliographic record

VenueFrontiers in Microbiology · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Guelph
FundersEuropean Regional Development FundJunta de Castilla y LeónAgence Nationale de la RechercheEuropean Commission
KeywordsBiologyMicrobiomeTickMidgutOrnithodorosSalivary glandBorreliaMicrobiologyZoologyVirologyBorrelia burgdorferiImmunologyGeneticsEcology

Abstract

fetched live from OpenAlex

Introduction Ornithodoros erraticus and Ornithodoros moubata are the main vectors of African swine fever virus (ASFV) and the human relapsing fever spirochetes Borrelia hispanica and Borrelia crocidurae in the Mediterranean region and Borrelia duttoni in continental Africa. Manipulation of the tick microbiome has been shown to reduce vector fitness and competence in tick vectors, suggesting that the identification of key microbial players associated with tick tissues can inform interventions such as anti-microbiota vaccines to block pathogen development in the midgut and/or salivary glands. Methods In this study, we analyzed and compared the microbiome of the salivary glands and midgut of O. erraticus and O. moubata . For the taxonomic and functional characterization of the tissue-specific microbiome, we used 16S rRNA amplicon sequencing and prediction of metabolic profiles using PICRUSt2. Co-occurrence networks were built to characterize the community assembly and identify keystone taxa in each tick species. Results Our results revealed differences in the composition, diversity, and assembly of the bacterial microbiome of salivary glands and midgut within each tick species, but differences were more noticeable in O. moubata . Differences were also found in the microbiome of each tissue, salivary gland and midgut, between species. However, the ‘Core Association Networks (CAN)’ analysis revealed conserved patterns of interacting taxa in tissues within and between tick species. Different keystone taxa were identified in O. erraticus and O. moubata tissues, but Muribaculaceae and Alistipes were found as keystone taxa in the salivary glands of both tick species which justifies their use as anti-microbiota vaccine candidates to alter the microbiome and reduce tick fitness and/or block pathogen transmission. The high similarity of predicted metabolic pathways profiles between tissues of the two tick species suggests that taxonomic variability of the microbiome is not associated with significant changes in microbial functional profiles. Conclusion We conclude that the taxonomic structure of the microbiome in O. erraticus and O. moubata is tissue-specific, suggesting niche partitioning of bacterial communities associated to these soft ticks. However, shared keystone taxa and conserved patterns of interacting taxa between tissues and tick species suggest the presence of key microbial players that could be used as anti-microbiota vaccine candidates to affect tick physiology and/or pathogen colonization.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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 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

Citations19
Published2023
Admission routes1
Has abstractyes

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