Single-Cell Transcriptomic Analysis of the Immune Response to COVID-19 and Tuberculosis Coinfection

Yi Wang , Maike Zheng , Yun Zhang , Yu Xue , Sibo Long , Chaohong Wang , Qing Sun , Jun Yan , Yiheng Shi , Bin Yang , Shang Ma , Tiantian Zhang , Lei Cao , Yan Chen , Wenfu Ju , Jing Zhang , Yan Zhao , Mengqiu Gao , Laurence Don Wai Luu , Xinting Yang , Guirong Wang

Exploration ›› 2025, Vol. 5 ›› Issue (5) : 20240022

PDF
Exploration ›› 2025, Vol. 5 ›› Issue (5) :20240022 DOI: 10.1002/EXP.20240022
RESEARCH ARTICLE
Single-Cell Transcriptomic Analysis of the Immune Response to COVID-19 and Tuberculosis Coinfection
Author information +
History +
PDF

Abstract

The immune characteristics and pathological mechanisms of COVID-19 and tuberculosis coinfection are not well understood. Single-cell RNA sequencing has emerged as a powerful tool for dissecting complex immune responses and cellular interactions in infectious diseases. Here, we employed scRNA-seq, combined with laboratory examinations and clinical observations, to elucidate potential mechanisms of immunopathology and protective immunity in coinfected patients. Substantial alterations in immune cell populations in patients with severe coinfection were observed, characterized by severe lymphopenia and massive expansion of myeloid cells. Lymphocytopenia may have resulted from lymphocyte apoptosis and migration. Systemic upregulation of S100 family proteins, mainly released by classical monocytes, might contribute to inflammatory cytokine storm via S100-TLR4-MyD88 signaling pathway in severely coinfected patients. Myeloid cells may contribute to immune paralysis in severe cases through expansion of myeloid-derived suppressor cells and dysregulated dendritic cell function. The immune landscape of T cells in severe patients were featured by dysregulated Th1 response, widespread exhaustion and increased cytotoxic, apoptosis, migration and inflammatory states. We observed increased plasma cells and overexpression of B-cell-activation-related pathways in severe patients. Together, we provide a comprehensive atlas illustrating the immune response to coinfected patients at the single-cell resolution and highlight mechanisms of pathogenesis in severe patients.

Keywords

Coinfection / COVID-19 / Dysregulated immune response / scRNA-seq / Tuberculosis

Cite this article

Download citation ▾
Yi Wang, Maike Zheng, Yun Zhang, Yu Xue, Sibo Long, Chaohong Wang, Qing Sun, Jun Yan, Yiheng Shi, Bin Yang, Shang Ma, Tiantian Zhang, Lei Cao, Yan Chen, Wenfu Ju, Jing Zhang, Yan Zhao, Mengqiu Gao, Laurence Don Wai Luu, Xinting Yang, Guirong Wang. Single-Cell Transcriptomic Analysis of the Immune Response to COVID-19 and Tuberculosis Coinfection. Exploration, 2025, 5(5): 20240022 DOI:10.1002/EXP.20240022

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Y. Wang, Q. Sun, Y. Zhang, et al., “Systemic Immune Dysregulation in Severe Tuberculosis Patients Revealed by a Single-Cell Transcriptome Atlas,” Journal of Infection86, no. 5 (2023): 421-438.

[2]

Y. Cai, Y. Wang, C. Shi, et al., “Single-Cell Immune Profiling Reveals Functional Diversity of T Cells in Tuberculous Pleural Effusion,”Journal of Experimental Medicine219, no. 3 (2022): e20211777.

[3]

Y. Wang, Y. Chen, L. Gu, L. Lou, J. Zhang, and K. Zhang, “The Clinical Characteristics and Risk Factors for Severe COVID-19 in Patients With COVID-19 and Tuberculosis Coinfection,” Frontiers in Microbiology13 (2022): 1061879.

[4]

Q. Wang, Y. Cao, X. Liu, et al., “Systematic Review and Meta-Analysis of Tuberculosis and COVID-19 Co-Infection: Prevalence, Fatality, and Treatment Considerations,” PLoS Neglected Tropical Diseases18 (2024): e0012136.

[5]

G. Chen, D. Wu, W. Guo, et al., “Clinical and Immunological Features of Severe and Moderate Coronavirus Disease 2019,” Journal of Clinical Investigation130 (2020): 2620-2629. (a) C. Yao, S. A. Bora, T. Parimon, et al., “Cell-Type-Specific Immune Dysregulation in Severely Ill COVID-19 Patients,” Cell Reports34 (2021): 108943. (b) W. Liu, J. Jia, Y. Dai, et al., “Delineating COVID-19 Immunological Features Using Single-Cell RNA Sequencing,” The Innovation3 (2022): 100289.

[6]

E. Nagy, V. Cseh, I. Barcs, and E. Ludwig, “The Impact of Comorbidities and Obesity on the Severity and Outcome of COVID-19 in Hospitalized Patients—A Retrospective Study in a Hungarian Hospital,” International Journal of Environmental Research and Public Health20 (2023): 1372.

[7]

B. J. Langford, M. So, S. Raybardhan, et al., “Bacterial Co-Infection and Secondary Infection in Patients With COVID-19: A Living Rapid Review and Meta-Analysis,” Clinical Microbiology and Infection26 (2020): 1622-1629.

[8]

E. du Bruyn, C. Stek, R. Daroowala, et al., “Effects of Tuberculosis and/or HIV-1 Infection on COVID-19 Presentation and Immune Response in Africa,” Nature Communications14 (2023): 188. (a) S. Sarkar, P. Khanna, and A. K. Singh, “Impact of COVID-19 in Patients With Concurrent Co-Infections: A Systematic Review and Meta-Analyses,” Journal of Medical Virology93 (2021): 2385-2395.

[9]

X. Yang, J. Yan, Y. Xue, et al., “Single-Cell Profiling Reveals Distinct Immune Response Landscapes in Tuberculous Pleural Effusion and Non-TPE,” Frontiers in Immunology14: 1191357.

[10]

J. Schulte-Schrepping, N. Reusch, D. Paclik, et al., “Severe COVID-19 is Marked by a Dysregulated Myeloid Cell Compartment,” Cell182 (2020): 1419-1440.

[11]

L. Petrone, E. Petruccioli, V. Vanini, et al., “Coinfection of Tuberculosis and COVID-19 Limits the Ability to In Vitro Respond to SARS-CoV-2,” International Journal of Infectious Diseases113 (2021): S82-S87.

[12]

C. Riou, E. du Bruyn, C. Stek, et al., “Relationship of SARS-CoV-2-Specific CD4 Response to COVID-19 Severity and Impact of HIV-1 and Tuberculosis Coinfection,” Journal of Clinical Investigation131 (2021): e149125.

[13]

S. Najafi-Fard, A. Aiello, A. Navarra, et al., “Characterization of the Immune Impairment of Patients With Tuberculosis and COVID-19 Coinfection,” International Journal of Infectious Diseases130 (2023): S34-S42.

[14]

D. Su, Z. Jiao, S. Li, et al., “Spatiotemporal Single-Cell Transcriptomic Profiling Reveals Inflammatory Cell States in a Mouse Model of Diffuse Alveolar Damage,” Exploration3 (2023): 20220171.

[15]

Y. Wang, L. D. W. Luu, S. Liu, et al., “Single-Cell Transcriptomic Analysis Reveals a Systemic Immune Dysregulation in COVID-19-Associated Pediatric Encephalopathy,” Signal Transduction and Targeted Therapy8 (2023): 398.

[16]

K. Xiao, Y. Cao, Z. Han, et al., “A Pan-Immune Panorama of Bacterial Pneumonia Revealed by a Large-Scale Single-Cell Transcriptome Atlas,” Signal Transduction and Targeted Therapy10 (2025): 5.

[17]

A. C. Villani, R. Satija, G. Reynolds, et al., “Single-Cell RNA-Seq Reveals New Types of Human Blood Dendritic Cells, Monocytes, and Progenitors,” Science356 (2017): eaah4573.

[18]

F. Veglia, M. Perego, and D. Gabrilovich, “Myeloid-Derived Suppressor Cells Coming of Age,” Nature Immunology19 (2018): 108-119.

[19]

A. E. Mengos, D. A. Gastineau, and M. P. Gustafson, “The CD14+HLA-DRlo/Neg Monocyte: An Immunosuppressive Phenotype That Restrains Responses to Cancer Immunotherapy,” Frontiers in Immunology10 (2019): 1147.

[20]

D. I. Gabrilovich and S. Nagaraj, “Myeloid-Derived Suppressor Cells as Regulators of the Immune System,” Nature Reviews Immunology9 (2009): 162-174.

[21]

S. Wang, R. Song, Z. Wang, Z. Jing, S. Wang, and J. Ma, “S100A8/A9 in Inflammation,” Frontiers in Immunology9 (2018): 1298.

[22]

E. Bell, “TLR4 Signalling,” Nature Reviews Immunology8 (2008): 241.

[23]

N. Tong, Z. He, Y. Ma, et al., “Tumor Associated Macrophages, as the Dominant Immune Cells, Are an Indispensable Target for Immunologically Cold Tumor—Glioma Therapy?,” Frontiers in Cell and Developmental Biology9 (2021): 706286.

[24]

D. Foell, H. Wittkowski, C. Kessel, et al., “Proinflammatory S100A12 Can Activate Human Monocytes via Toll-Like Receptor 4,” American Journal of Respiratory and Critical Care Medicine187 (2013): 1324-1334.

[25]

S. Elmore, “Apoptosis: A Review of Programmed Cell Death,” Toxicologic Pathology35 (2007): 495-516.

[26]

Y. Su, D. Chen, D. Yuan, et al., “Multi-Omics Resolves a Sharp Disease-State Shift Between Mild and Moderate COVID-19,” Cell183 (2020): 1479-1495.

[27]

Y. Wang, X. Wang, X. Jia, et al., “Influenza Vaccination Features Revealed by a Single-Cell Transcriptome Atlas,” Journal of Medical Virology95 (2023): e28174.

[28]

Y. Wang, X. Wang, L. D. W. Luu, et al., “Single-Cell Transcriptomic Atlas Reveals Distinct Immunological Responses Between COVID-19 Vaccine and Natural SARS-CoV-2 Infection,” Journal of Medical Virology94 (2022): 5304-5324.

[29]

Z. Chen and E. J. Wherry, “T Cell Responses in Patients With COVID-19,” Nature Reviews Immunology20 (2020): 529-536.

[30]

B. Diao, C. Wang, Y. Tan, et al., “Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19),” Frontiers in Immunology11 (2020): 827. (a) Y. Liu, X. Du, J. Chen, et al., “Neutrophil-To-Lymphocyte Ratio as an Independent Risk Factor for Mortality in Hospitalized Patients With COVID-19,” Journal of Infection81 (2020): e6-e12. (b) J. Rivas, Y. Liu, S. Alhakeem, et al., “Interleukin-10 Suppression Enhances T-Cell Antitumor Immunity and Responses to Checkpoint Blockade in Chronic Lymphocytic Leukemia,” Leukemia35 (2021): 3188-3200.

[31]

A. Silvin, N. Chapuis, G. Dunsmore, et al., “Elevated Calprotectin and Abnormal Myeloid Cell Subsets Discriminate Severe From Mild COVID-19,” Cell182 (2020): 1401-1418.

[32]

L. Ruhl, I. Pink, J. F. Kühne, et al., “Endothelial Dysfunction Contributes to Severe COVID-19 in Combination With Dysregulated Lymphocyte Responses and Cytokine Networks,” Signal Transduction and Targeted Therapy6 (2021): 418.

[33]

I. Korsunsky, N. Millard, J. Fan, et al., “Fast, Sensitive and Accurate Integration of Single-Cell Data With Harmony,” Nature Methods16 (2019): 1289-1296.

[34]

V. A. Traag, L. Waltman, and N. J. van Eck, “From Louvain to Leiden: Guaranteeing Well-Connected Communities,” Scientific Reports9 (2019): 5233. (a) J. H. Levine, E. F. Simonds, S. C. Bendall, et al., “Data-Driven Phenotypic Dissection of AML Reveals Progenitor-Like Cells That Correlate With Prognosis,” Cell162 (2015): 184-197.

[35]

Y. Wang, S. Yang, B. Han, et al., “Single-Cell Landscape Revealed Immune Characteristics Associated With Disease Phases in Brucellosis Patients,” iMeta3 (2024): e226.

[36]

F. A. Wolf, F. K. Hamey, M. Plass, et al., “PAGA: Graph Abstraction Reconciles Clustering With Trajectory Inference Through a Topology Preserving Map of Single Cells,” Genome Biology20 (2019): 59.

RIGHTS & PERMISSIONS

2025 The Author(s). Exploration published by Henan University and John Wiley & Sons Australia, Ltd.

PDF

7

Accesses

0

Citation

Detail

Sections
Recommended

/