Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease.
Aparna NathanJessica I BeynorYuriy BaglaenkoSara A SulimanKazuyoshi IshigakiSamira AsgariChuan-Chin HuangYang LuoZibiao ZhangKattya LopezCecilia S Lindestam ArlehamnJoel D ErnstJudith JimenezRoger I CalderonLeonid LeccaIldiko Van RhijnD Branch MoodyMegan B MurraySoumya RaychaudhuriPublished in: Nature immunology (2021)
Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state >4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (TH17) cell-like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state-uniquely identifiable with multimodal analysis-from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.
Keyphrases
- single cell
- mycobacterium tuberculosis
- rna seq
- cell therapy
- high throughput
- healthcare
- electronic health record
- emergency department
- induced apoptosis
- dendritic cells
- mesenchymal stem cells
- working memory
- mental health
- gene expression
- machine learning
- big data
- signaling pathway
- artificial intelligence
- cell proliferation
- regulatory t cells
- oxidative stress
- endoplasmic reticulum stress
- deep learning
- amino acid
- human immunodeficiency virus
- antibiotic resistance genes
- pi k akt