Distinct and overlapping immunological responses to SARS-CoV-2 and Mycobacterium tuberculosis identified by single-cell RNA-seq of co-infected whole blood

Introduction: COVID-19 and tuberculosis (TB) exhibit similar symptomatic presentation and clinical parameters. Common underlying immunological mechanisms also highlight potential routes of immunopathogenic interaction between these diseases during co-infection. To explore immunological similarities, differences and interactions, single-cell RNA-seq (scRNA-seq) was performed on whole blood infected with Mycobacterium tuberculosis (Mtb), SARS-CoV-2, or both pathogens. Methods: Whole blood from four healthy adults, were subjected to ex vivo infection with Mtb and/or SARS-CoV-2 ancestral strain, or were maintained in an uninfected state, for 24 or 96 hours. At each timepoint, for each condition, the four biological replicates were captured, fixed and cryopreserved to be processed for scRNA-seq as a single batch. Following quality control filtering, genotype-based demultiplexing was performed to obtain data from each biological replicate for pseudobulk differential expression analysis. Results: Thirteen distinct clusters of cells were identified based on marker gene expression. Profound differences in the proportions of monocytes, T cells and neutrophils were observed between infection conditions and timepoints. The greatest divergence between pathogen responses occurred within myeloid cells at early timepoints of infection. Co-infection had the greatest synergistic effect 24 hours post-infection with 238 immunological pathways uniquely enriched, including IFN-γ and TNF production, whilst by 96 hours post-infection there was a large overlap of 182 shared pathways between Mtb, SARS-CoV-2 and co-infection. SARS-CoV-2-only infection resulted in widespread cell death by 96 hours post-infection, while Mtb-only and co-infected samples remained enriched for monocyte, T cell and NK cell signatures, sharing negative regulation of extrinsic apoptotic signalling. Distinct from Mtb, SARS-Co-V-2 had unique regulating of αβ T cell activation and differentiation at both time points. Conclusion: These data provide a high-resolution characterisation of distinct and overlapping immunological responses generated by SARS-CoV-2 and Mtb when a single infection or co-infection occurs. This sheds light on the potential effects of novel or existing host-directed therapies that target these pathways, which is particularly crucial for settings where dual presentation is common. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The COVID Profile study was supported by WHO Unity funds and WEHI Philanthropic funds. The funders had no role in study design, data collection and analysis. D.S. is supported by WEHI and NHMRC (2020750). A.K.C. is funded by WEHI, philanthropic donors, NHMRC (2020750) and the Australian Respiratory Council ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Acquisition of human blood samples and immunological investigations were approved by the Human Research Ethics Committee at the Walter and Eliza Hall Institute (WEHI HREC #18_09LR and #20/08) and Melbourne Health (RMH69108) as part of the COVID PROFILE study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The raw fastq files and processed transcript count matrices for this study can be found in the gene expression omnibus database under the accession number GSE232705. The scripts used to analyse these data have been uploaded to GitHub - https://github.com/sheerind-wehi/Mtb\_SARS\_co-infection [https://github.com/sheerind-wehi/Mtb\_SARS\_co-infection][1] [1]: https://github.com/sheerind-wehi/Mtb_SARS_co-infection