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CITE-seq analysis of Mycobacterium tuberculosis infected wild-type and IL-1R KO mixed bone marrow chimera mouse lungs

GSE254983 Mus musculus Expression profiling by high throughput sequencing; Other 6 samples Submitted 2026/04/01 Platform GPL24247
Summary
Mycobacterium tuberculosis (Mtb) causes 1.6 million deaths a year. However, tuberculosis pathogenesis remains poorly understood and is not fully recapitulated in standard mouse models. Here we report that a comparison across three different susceptible mouse models identifies Mtb-induced gene signatures that predict active TB disease in humans significantly better than a signature from the standard C57BL/6 mouse model. Common to signatures from susceptible mice were myeloid cell response and immunosuppressive genes. In line with the signatures, an increase in lung myeloid cells, including neutrophils, was conserved across the susceptible mouse models, mimicking the neutrophilic inflammation observed in humans. Myeloid cells in the susceptible models and non-human primates exhibited high expression of immunosuppressive molecules including IL-1 receptor antagonist, which inhibits IL-1 signaling. Prior reports have suggested that excessive IL-1 signaling impairs Mtb control. By contrast, we found that enhancement of IL-1 signaling via deletion of IL-1 receptor antagonist promoted bacterial control in all three susceptible mouse models. IL-1 signaling enhanced cytokine production by lymphoid and stromal cells, suggesting a mechanism for IL-1 signaling in promoting Mtb control. Thus, we propose that myeloid cell expression of immunosuppressive molecules is a conserved mechanism exacerbating Mtb disease in mice, non-human primates, and humans.
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Direct links to NCBI, no account and no request form: the whole study as GSE254983_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1072739 and SRA study SRP487831. Searching any of these in the dataset finder brings you back here.

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