Experiment Overview
| Repository ID: | FR-FCM-Z4KY | Experiment name: | A regulatory T cell signature distinguishes the immune landscape of COVID-19 patients from those with other respiratory infections - T cell panel | MIFlowCyt score: | 56.50% |
| Primary researcher: | Marie FRUTOSO | PI/manager: | Marie FRUTOSO | Uploaded by: | Marie FRUTOSO |
| Experiment dates: | 2020-09-29 - 2021-04-01 | Dataset uploaded: | Sep 2021 | Last updated: | Sep 2021 |
| Keywords: | None | Manuscripts: | |||
| Organizations: | None | ||||
| Purpose: | We analyzed PBMCs from a unique cohort of age- and sex- matched patients hospitalized with respiratory infections including Flu, RSV, or SARS-CoV-2 compared to PBMCs from healthy donors. The patients infected with the different viruses are classified from moderate to critical diseases. To extensively characterize the cellular immunotypes present in the peripheral blood of patients hospitalized with Flu, RSV, or SARS-CoV-2 infection compared to healthy donors, we combined several high-parameter flow cytometry panels to profile myeloid cells, T cells, NK cells, or regulatory T cells (Treg). | ||||
| Conclusion: | Our in-depth profiling indicates that the immune landscape in SARS-CoV-2 patients is largely similar to patients hospitalized with Flu or RSV. Unique to patients infected with SARS-CoV-2 who had the most critical clinical disease were changes in the regulatory T cell (Treg) compartment. A Treg signature including increased frequency, activation status, and migration markers was correlated with the severity of COVID-19. These findings are particularly relevant as Tregs are considered for therapy to combat the severe inflammation seen in COVID-19 patients. Likewise, having defined the overlapping immune landscapes in SARS-CoV-2, existing knowledge of Flu and RSV infections could be leveraged to identify common treatment strategies. | ||||
| Comments: | Our dataset contains 4 different panels (T cell panel, NK cell panel, Treg panel and APC panel) Each of the panels contains 70 samples (from healthy donors, Flu, RSV or SARS-CoV-2 infected patients) The 50 first samples were assessed on Day 1 and are linked to their own compensation matrix (ie: Treg panel comp1) The second 20 samples were assessed on Day 2 and are linked to their own compensation matrix (ie: Treg panel comp2) For each panel, a FlowJo workspace contains the 70 compensated samples as well as the gating strategy All FlowJo workspaces contain 3 additional keywords with the Match ID, (age and sex-mateched patients), the condition (healthy, Flu, RSV, SARS-CoV-2) as well as he severity of the disease (moderate, critical, severe). This folder contains the data from the T cell panel. | ||||
| Funding: | This work was supported by NIH grant R01 AI121129 and R01 AI141435. | ||||
| Quality control: | BD CST and Spherotec Ultra Rainbow beads for instrument QC prior to each experiment, Fluorescence Minus One (FMO) controls used to assess resolution of dimly expressed markers, assessment of spillover spreading error issues using spill over spreading matrix and visual inspection using NxN plots, Signal-over-time for acquisition. | ||||
