Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas
bioRxiv. 2025. DOI 10.1101/2025.03.10.642376. PMID 40161687. PMCID PMC11952478.
How to cite
AMA
Jain N, Ogbonna EC, Maliga Z, Jacobson C, Zhang L, Shih A, et al. Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas. bioRxiv. 2025. doi:10.1101/2025.03.10.642376APA
Jain, N., Ogbonna, E. C., Maliga, Z., Jacobson, C., Zhang, L., Shih, A., et al. (2025). Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas. bioRxiv. https://doi.org/10.1101/2025.03.10.642376BibTeX
@article{jain2025multiomic,
title = {Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas},
author = {Jain, Neharika and Ogbonna, Emmanuel C. and Maliga, Zoltan and Jacobson, Connor and Zhang, Liang and Shih, Angela and others},
journal = {bioRxiv},
year = {2025},
doi = {10.1101/2025.03.10.642376},
pmid = {40161687}
}Tuberculosis is still one of the world's deadliest infections, and drug-resistant strains make it harder to treat. One proposed add-on therapy targets immune-suppressing cells called MDSCs, which are well studied in cancer. Whether they even gather inside human TB granulomas — the walled-off lung lesions where the bacteria hide — was unknown.
The team profiled eighty-four granulomas from three people with active TB, pairing region-level gene readouts with single-cell protein imaging of intact lung tissue. Immune suppression turned out to come not from classical MDSCs but mainly from a kind of dendritic cell that makes the enzyme IDO1. These cells gathered in the more cellular granulomas and sat close to activated regulatory T cells.
That points to IDO1-positive dendritic cells, rather than MDSCs, as the suppressive population worth targeting in tuberculosis.
Key findings
- In TB granulomas, immune suppression traced to IDO1+ dendritic cells, not the classical MDSCs known from cancer. Across 84 granulomas from three individuals with active TB, IDO1+ dendritic cells were the most abundant suppressive myeloid population at 2.5% of all cells, while classical monocytic MDSCs made up just 0.2%.
- Whole-slide cyclic immunofluorescence phenotyped more than 1.9 million single cells in intact lung tissue. Imaging on the CyteFinder resolved lineage and functional markers — including IDO1, PD-L1, FOXP3 and ICOS — across all 84 granulomas while every cell kept its position on the slide.
- Seven recurrent granuloma microenvironments emerged, and the suppressive one placed IDO1+ dendritic cells beside activated regulatory T cells. A nearest-neighbor analysis defined seven microenvironments (GME1–GME7); in the immunosuppressive one, IDO1+ dendritic cells were the most prevalent cell type at 28%, and activated (ICOS+) regulatory T cells sat closer to them than their resting counterparts.
CyteFinder in the methods
“Images were acquired on a CyteFinder slide scanning fluorescence microscope (RareCyte Inc.), using a 20x/0.75 NA objective – with a 2×2 binning.”
— Jain et al., bioRxiv (2025), Methods, “t-CyCIF Protocol and Image Acquisition”
Why it matters for CyteFinder users
If you are weighing the CyteFinder for a tissue study, look at the specific job it did here. This was a multiomic study: a region-level transcriptomics arm read which genes were active across granuloma zones, but that measurement cannot say which individual cells carry a protein or where they sit. That is the question the CyteFinder answered. The authors ran cyclic immunofluorescence on intact FFPE lung sections, staining lineage and functional markers — among them CD11b, FOXP3, IDO1, PD-L1 and ICOS — across successive rounds, then scanned each cycle on the instrument and registered them into one whole-slide image. From that image they assigned phenotypes to more than 1.9 million cells across 84 granulomas, singled out IDO1+ dendritic cells as the dominant suppressive population, and measured how closely those cells sat to activated regulatory T cells. For your own work the point is concrete: when a question turns on which cells express a marker and who their neighbors are in tissue you cannot dissociate, whole-slide cyclic imaging is the measurement that answers it, at single-cell resolution across a million-plus cells.
