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Anti-influenza T cells in bronchoalveolar microenvironment of critically severe COVID-19 patients

Until December 13, 2021, there have been 269,468,311 confirmed infection cases and 5,304,248 deaths attributed to COVID-19 caused by SARS-COV-2 virus ( Recently, the global COVID-19 pandemic is merging with the influenza season, leading to an increased risk of COVID-19 and influenza co-infection. The rates of COVID-19 and influenza co-infection were reported to range from 0.2 to 45.7% in different COVID-19 cohorts [1]. Moreover, both SARS-CoV-2 and influenza viruses preferentially infect alveolar type 2 (AT2) cells [2]. The co-infection with influenza A virus causes more severe and prolonged pneumonia in SARS-CoV-2-infected hamsters [3]. However, there is still a lack of evidence to support the co-infection of SARS-CoV-2 with influenza virus in the bronchoalveolar microenvironment of human lungs, and T cell response under this circumstance remains unknown.

The specificity of T cell response is presented by the antigen-specific T cell clonotypes defined by their unique T cell receptors (TCRs) [4]. TCR directly recognizes and interacts with the antigenic epitope, which determines the specificity of T cell response [4]. Thus, the antigenic T cell response can be directly analyzed by epitope-specific TCR sequence [4]. Recently, T-Detect™ COVID (Adaptive Biotechnologies)—the first assay of detecting TCR-β chain—has been approved by the US Food and Drug Administration (FDA) to determine SARS-CoV-2 infection status based on SARS-CoV-2 specific TCR-β sequence [5].

Here, we constructed the analysis framework of digitalized sorting of epitope-specific T cells (DSET; Fig. 1A) according to the amino acid sequence of complementarity determining region 3 (CDR3) in TCR-β, as reported in our previous study [4]. The marker of influenza infection—TCR-β CDR3 sequences of influenza A-specific T cell clonotypes—was collected from previous studies (Fig. 1A). Next, through applying DSET analysis on the single-cell T cell receptor sequencing (scTCR-seq) data of bronchoalveolar lavage fluid (BALF) in a COVID-19 cohort [6], we directly investigated the anti-influenza T cells in bronchoalveolar microenvironment of COVID-19 patients.

Fig. 1
figure 1

Influenza A-specific T cell clonotypes in the bronchoalveolar lavage fluid T cells from COVID-19 patients. A The analysis framework of the digitalized sorting of epitope-specific T cells. Epitope-specific T cells were sorted according to their antigenic-specific TCR-β sequence. In this study, influenza A-specific T cell clonotypes were defined by T cell clonotypes with influenza A-specific TCR-β sequence using single-cell RNA sequencing. B The donut plot shows the percentage of COVID-19 patients defined by the categories of influenza A-specific T cells and COVID-19 disease severity. The colors represent the COVID-19 patients with or without influenza A-specific T cells in bronchoalveolar lavage fluid T cells. C The percentage (%) of influenza A-specific T cells in bronchoalveolar T cells in COVID-19 patients with mild (n = 3), severe (n = 1), and critical (n = 5) disease severity, with color coding according to the specificity of T cells to different epitopes from different genes of influenza A virus. The “*” shows the epitopes that could be found to elicit T cell response

We found that 33.3% of COVID-19 patients had positive anti-influenza T cells in BALF (red group; Fig. 1B). Notably, all patients with positive anti-influenza T cells were patients with critical severity. Comparatively, critical infection was observed in only 33.2% patients with negative anti-influenza T cells (blue group; Fig. 1B). Next, we analyzed the abundance of anti-influenza T cells in BALF from COVID-19 patients and its relationship with disease severity defined by mild, severe, and critical COVID-19 infections. The anti-influenza T cells were defined by different specificities to different epitopes from different genes of the influenza A virus. As shown in Fig. 1C, no anti-influenza T cells could be found in COVID-19 patients with mild and severe infections. Comparatively, patients with critical infection had positive anti-influenza T cells with an average percentage of 1.23% (Fig. 1C). Moreover, it is worth noting that two of eight influenza A-epitopes, GILGFVFTL and SSLENFRAYV, could elicit T cell response in critically severe COVID-19 patients.

The co-infection of COVID-19 with influenza might complicate the diagnosis, treatment, and prognosis of COVID-19, posing potential challenges to public health. In this study, we provide the first evidence in human bronchoalveolar microenvironment that anti-influenza T cells exist in critically severe COVID-19 patients, but not patients with moderate disease severity. The existence of anti-influenza T cells specifically indicates the immunological status for influenza infection. This finding reveals that the co-infection of SARS-CoV-2 with influenza might cause more severe illness, suggesting that the prevention of influenza infection during the current SARS-CoV-2 pandemic might be important for reducing casualties caused by COVID-19. Considering the upcoming flu season will inevitably merge with the current COVID-19 pandemic, influenza vaccination might be beneficial in high‐risk populations of COVID‐19 infection. Additionally, the surveillance of influenza infection should be considered in COVID-19 patients.

Availability of data and materials

The data that support the findings of this study will be available from the corresponding author upon reasonable request.


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We thank Dr. Zhang and his colleagues for the data of single-cell T cell receptor sequencing from their previously published study that were deposited in Gene Expression Omnibus ( under the accession number GSE145926.


This project was supported by the National Natural Science Foundation of China (32100739) to Dr. Ming Zheng.

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M.Z. conceived the project, developed the method, conducted data analysis, and wrote the manuscript. The author read and approved the final manuscript.

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Correspondence to Ming Zheng.

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No human subjects were directly involved in this study. All the data used in this study were derived from existing de-identified biological samples from prior studies. Thus, ethical and patient consent was not required in this study.

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This study was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Zheng, M. Anti-influenza T cells in bronchoalveolar microenvironment of critically severe COVID-19 patients. Crit Care 25, 444 (2021).

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