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Record W4407096258 · doi:10.1038/s42003-025-07572-4

Deletion of ESX-3 and ESX-4 secretion systems in Mycobacterium abscessus results in highly impaired pathogenicity

2025· article· en· W4407096258 on OpenAlexafffund
Wassim Daher, Vincent Le Moigne, Yara Tasrini, Shweta Parmar, Danielle L. Sexton, John Jairo Aguilera-Correa, Valentin Berdal, Elitza I. Tocheva, Jean‐Louis Herrmann, Laurent Kremer

Bibliographic record

VenueCommunications Biology · 2025
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleAgence Nationale de la RechercheGovernment of Canada
KeywordsSecretionVirulenceComplementationMicrobiologyMutantBiologyMycobacterium abscessusIntracellularCell biologyMycobacteriumBacteriaGeneticsGeneBiochemistry

Abstract

fetched live from OpenAlex

Type VII secretion systems participate in protein export, virulence, conjugation, and metabolic regulation. Five subtypes (ESX-1 to ESX-5) exist, each with specific roles and well-characterized secretion profiles in various mycobacterial species. Mycobacterium abscessus, encodes only ESX-3 and ESX-4. Here, single and double M. abscessus mutants lacking the main ATPases EccC3 and EccC4 were used to define ESX-3 and ESX-4 contributions to substrate secretion and virulence. Our results demonstrate that EsxG/H secretion depends entirely on ESX-3, whereas both ESX-3 and ESX-4 secrete EsxU/T. Furthermore, two newly identified PE/PPE substrates (MAB_0046/MAB_0047) require ESX-3 for secretion. Functional complementation restored secretion and revealed subpolar localization of these systems. Macrophage infections showed that ESX-3 and ESX-4 contribute to bacterial internalization, phagosomal escape, and intracellular survival. In mice, infections with eccC3- and/or eccC4-deletion mutants resulted in complete survival and reduced bacterial loads in the lungs. These findings demonstrate that both ESX systems drive M. abscessus pathogenicity.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.148
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.031
GPT teacher head0.337
Teacher spread0.306 · 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 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

Citations10
Published2025
Admission routes2
Has abstractyes

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