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Record W3128470920 · doi:10.1101/2021.02.02.429488

<i>In vivo</i> antigen expression regulates CD4 T cell differentiation and vaccine efficacy against <i>Mycobacterium tuberculosis</i> infection

2021· preprint· en· W3128470920 on OpenAlexafffund
Helena Strand Clemmensen, Jean-Yves Dubé, Fiona McIntosh, Ida Rosenkrands, Gregers Jungersen, Claus Aagaard, Peter Andersen, Marcel A. Behr, Rasmus Mortensen

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institute of Allergy and Infectious DiseasesStatens Serum InstitutLundbeckfondenH. Lundbeck A/SNational Institutes of HealthMcGill University Health CentreMcGill University
KeywordsBiologyAntigenMycobacterium tuberculosisESAT-6ImmunologyT cellVaccinationImmune systemVirologyMicrobiologyTuberculosisMedicine

Abstract

fetched live from OpenAlex

Abstract New vaccines are urgently needed against Mycobacterium tuberculosis (Mtb), which kills more than 1.4 million people each year. CD4 T cell differentiation is a key determinant of protective immunity against Mtb, but it is not fully understood how host-pathogen interactions shape individual antigen-specific T cell populations and their protective capacity. Here, we investigated the immunodominant Mtb antigen, MPT70, which is upregulated in response to IFN-γ or nutrient/oxygen deprivation of in vitro infected macrophages. Using a murine aerosol infection model, we compared the in vivo expression kinetics of MPT70 to a constitutively expressed antigen, ESAT-6, and analysed their corresponding CD4 T cell phenotype and vaccine-protection. For wild-type Mtb, we found that in vivo expression of MPT70 was delayed compared to ESAT-6. This delayed expression was associated with induction of less differentiated MPT70-specific CD4 T cells but, compared to ESAT-6, also reduced protection after vaccination. In contrast, infection with an MPT70-overexpressing Mtb strain promoted highly differentiated KLRG1 + CX3CR1 + CD4 T cells with limited lung-homing capacity. Importantly, this differentiated phenotype could be prevented by vaccination and, against the overexpressing strain, vaccination with MPT70 conferred similar protection as ESAT-6. Together our data indicate that high in vivo antigen expression drives T cells towards terminal differentiation and that targeted vaccination with adjuvanted protein can counteract this phenomenon by maintaining T cells in a protective less-differentiated state. These observations shed new light on host-pathogen interactions and provide guidance on how future Mtb vaccines can be designed to tip the immune-balance in favor of the host. Importance Tuberculosis, caused by Mtb, constitutes a global health crisis of massive proportions and the impact of the current COVID-19 pandemic is expected to cause a rise in tuberculosis-related deaths. Improved vaccines are therefore needed more than ever, but a lack of knowledge on protective immunity hampers their development. The present study shows that constitutively expressed antigens with high availability drive highly differentiated CD4 T cells with diminished protective capacity, which could be a survival strategy by Mtb to evade T cell immunity against key antigens. We demonstrate that immunisation with such antigens can counteract this phenomenon by maintaining antigen-specific T cells in a state of low differentiation. Future vaccine strategies should therefore explore combinations of multiple highly expressed antigens and we suggest that T cell differentiation could be used as a readily measurable parameter to identify these in both preclinical and clinical studies.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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 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

Citations2
Published2021
Admission routes2
Has abstractyes

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