Single-cell transcriptomics of blood reveals a natural killer cell subset depletion in tuberculosis

EBioMedicine. 2020 Mar:53:102686. doi: 10.1016/j.ebiom.2020.102686. Epub 2020 Feb 27.

Abstract

Background: Tuberculosis (TB) continues to be a critical global health problem, which killed millions of lives each year. Certain circulating cell subsets are thought to differentially modulate the host immune response towards Mycobacterium tuberculosis (Mtb) infection, but the nature and function of these subsets is unclear.

Methods: Peripheral blood mononuclear cells (PBMC) were isolated from healthy controls (HC), latent tuberculosis infection (LTBI) and active tuberculosis (TB) and then subjected to single-cell RNA sequencing (scRNA-seq) using 10 × Genomics platform. Unsupervised clustering of the cells based on the gene expression profiles using the Seurat package and passed to tSNE for clustering visualization. Flow cytometry was used to validate the subsets identified by scRNA-Seq.

Findings: Cluster analysis based on differential gene expression revealed both known and novel markers for all main PBMC cell types and delineated 29 cell subsets. By comparing the scRNA-seq datasets from HC, LTBI and TB, we found that infection changes the frequency of immune-cell subsets in TB. Specifically, we observed gradual depletion of a natural killer (NK) cell subset (CD3-CD7+GZMB+) from HC, to LTBI and TB. We further verified that the depletion of CD3-CD7+GZMB+ subset in TB and found an increase in this subset frequency after anti-TB treatment. Finally, we confirmed that changes in this subset frequency can distinguish patients with TB from LTBI and HC.

Interpretation: We propose that the frequency of CD3-CD7+GZMB+ in peripheral blood could be used as a novel biomarker for distinguishing TB from LTBI and HC. FUND: The study was supported by Natural Science Foundation of China (81770013, 81525016, 81772145, 81871255 and 91942315), National Science and Technology Major Project (2017ZX10201301), Science and Technology Project of Shenzhen (JCYJ20170412101048337) and Guangdong Provincial Key Laboratory of Regional Immunity and Diseases (2019B030301009). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Keywords: CD3-CD7+GZMB+; NK cells; Single-cell RNA sequencing; Tuberculosis.

MeSH terms

  • Adolescent
  • Adult
  • Biomarkers / blood
  • Female
  • Humans
  • Killer Cells, Natural / immunology*
  • Latent Tuberculosis / blood*
  • Latent Tuberculosis / diagnosis
  • Latent Tuberculosis / immunology
  • Lymphocyte Count
  • Male
  • Middle Aged
  • Single-Cell Analysis
  • Transcriptome*
  • Tuberculosis, Pulmonary / blood*
  • Tuberculosis, Pulmonary / diagnosis
  • Tuberculosis, Pulmonary / immunology

Substances

  • Biomarkers