Experiment Overview
| Repository ID: | FR-FCM-Z4XN | Experiment name: | COVID-19 PBMC mass cytometry IFReC/CiDER | MIFlowCyt score: | 33.96% |
| Primary researcher: | James Wing | PI/manager: | James Wing | Uploaded by: | James Wing |
| Experiment dates: | 2020-09-05 - 2021-07-05 | Dataset uploaded: | Nov 2021 | Last updated: | Jan 2023 |
| Keywords: | [mass cytometry] [plasma cells] [Tregs] [COVID-19] [Tph cells] | Manuscripts: | [36669118] | ||
| Organizations: |
Osaka University, Center for infectious disease education and research (CiDER), Suita, (Japan)
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| Purpose: | COVID-19 is characterized by severe dysregulation of the immune system, in this study we find that regulatory T-cells are and that a sex biased imbalance between T-follicular regulatory cells, T-follicular helper cells and plasma cells may underlie recent reports of dysregulated antibody production in COVID-19 patients. | ||||
| Conclusion: | Sex-biased humoral immune responses to COVID-19 patients have been observed, but the cellular basis for this is not understood. Using single-cell proteomics by mass cytometry, we find disrupted regulation of humoral immunity in COVID-19 patients, with a sex-biased loss of circulating follicular regulatory T cells (cTfr) at a significantly greater rate in male patients. In addition, a male sex-associated cellular network of T-peripheral helper, plasma blasts, proliferating and extrafollicular/atypical CD11c+ memory B cells was strongly positively correlated with neutralizing antibody concentrations and negatively correlated with cTfr frequency. These results suggest that sex-specific differences to the balance of cTfr and a network of extrafollicular antibody production-associated cell types may be a key factor in the altered humoral immune responses between male and female COVID-19 patients. | ||||
| Comments: | Dataset was published in 10.1073/pnas.2217902120 Proc Natl Acad Sci U S A . 2023 Jan 24;120(4):e2217902120. doi: 10.1073/pnas.2217902120. Epub 2023 Jan 20. A sex-biased imbalance between Tfr, Tph, and atypical B cells determines antibody responses in COVID-19 patients. Jonas Nørskov Søndergaard, Janyerkye Tulyeu, Ryuya Edahiro, Yuya Shirai, Yuta Yamaguchi, Teruaki Murakami, Takayoshi Morita, Yasuhiro Kato, Haruhiko Hirata, Yoshito Takeda, Daisuke Okuzaki, Shimon Sakaguchi, Atsushi Kumanogoh, Yukinori Okada, James Badger Wing | ||||
| Funding: | This work was conducted as part of “The Nippon Foundation—Osaka University Project for Infectious Disease Prevention.” Funding: This work was funded by the Japan Society for the Promotion of Science, Kakenhi 19H01021, 20K21834 (Y.O.); Japan Agency for Medical Research and Development: JP21km0405211, JP21ek0109413, JP21ek0410075, JP21gm4010006, and JP21km0405217 (Y.O.); JST Moonshot R&D: JPMJMS2021, JPMJMS2024 (Y.O.); Takeda Science Foundation: (Y.O.); Bioinformatics Initiative of Osaka University Graduate School of Medicine, Osaka University: (Y.O.); IFReC grant program for next-generation principal investigators (J.B.W.); Nippon Foundation (J.B.W.); Japan Society for the Promotion of Science 16H06295 (S.S.); Japan Agency for Medical Research and Development JP19gm0010005 (S.S.); and Leading Advanced Projects for Medical Innovation (S.S.). | ||||
| Quality control: | Data was normalised by EQ beads via the flusigm normaliser. Cells were initially gated as live, DNA+, and CD45+ singlets with normal ion cloud Gaussian parameters. Nine Batch control samples (using two lots of healthy PBMCs) were examined for signs of batch effect and then excluded from further analysis The uploaded samples have already been gated as live, DNA positive, CD45 positive debarcoded singlets in Cytobank. | ||||
Experiment variables
| Conditions | |
|---|---|
| · Severe | SG_CO_OK_00009.fcs · SG_CO_OK_00010.fcs · SG_CO_OK_00012.fcs · SG_CO_OK_00013.fcs · SG_CO_OK_00014.fcs · SG_CO_OK_00015.fcs · SG_CO_OK_00016.fcs · SG_CO_OK_00018.fcs · SG_CO_OK_00019.fcs · SG_CO_OK_00021.fcs · SG_CO_OK_00023.fcs · SG_CO_OK_00025.fcs · SG_CO_OK_00026.fcs · SG_CO_OK_00027.fcs · SG_CO_OK_00029.fcs · SG_CO_OK_00030.fcs · SG_CO_OK_00031.fcs · SG_CO_OK_00032.fcs · SG_CO_OK_00033.fcs · SG_CO_OK_00034.fcs · SG_CO_OK_00036.fcs · SG_CO_OK_00038.fcs · SG_CO_OK_00039.fcs · SG_CO_OK_00040.fcs · SG_CO_OK_00041.fcs · SG_CO_OK_00043.fcs · SG_CO_OK_00046.fcs · SG_CO_OK_00047.fcs · SG_CO_OK_00048.fcs · SG_CO_OK_00050.fcs · SG_CO_OK_00052.fcs · SG_CO_OK_00053.fcs · SG_CO_OK_00054.fcs · SG_CO_OK_00055.fcs · SG_CO_OK_00068.fcs · SG_CO_OK_00070.fcs · SG_CO_OK_00071.fcs · SG_CO_OK_00072.fcs · SG_CO_OK_00076.fcs · SG_CO_OK_00077.fcs · SG_CO_OK_00079.fcs · SG_CO_OK_00080.fcs |
| · Critical | SG_CO_OK_00008.fcs · SG_CO_OK_00017.fcs · SG_CO_OK_00035.fcs · SG_CO_OK_00042.fcs · SG_CO_OK_00056.fcs · SG_CO_OK_00067.fcs · SG_CO_OK_00075.fcs |
| · Followup | SG_CO_OK_00015_2.fcs · SG_CO_OK_00017_2.fcs · SG_CO_OK_00021_2.fcs · SG_CO_OK_00023_2.fcs · SG_CO_OK_0004_2.fcs |
| · Moderate | SG_CO_OK_00022.fcs · SG_CO_OK_00028.fcs · SG_CO_OK_00037.fcs · SG_CO_OK_00057.fcs · SG_CO_OK_00060.fcs |
| · HC <50 | SC_HC_OS_00174.fcs · SC_HC_OS_00190.fcs · SC_HC_OS_00234.fcs · SC_HC_OS_0235.fcs · SG_HC_OS_00007.fcs · SG_HC_OS_0005.fcs · SG_HC_OS_00097.fcs · SG_HC_OS_00163.fcs · SG_HC_OS_00175.fcs · SG_HC_OS_00180.fcs · SG_HC_OS_00181.fcs · SG_HC_OS_00183.fcs · SG_HC_OS_00184.fcs · SG_HC_OS_00188.fcs · SG_HC_OS_00193.fcs · SG_HC_OS_00204.fcs · SG_HC_OS_00244.fcs · SG_HC_OS_00293.fcs · SG_HC_OS_0170.fcs · SG_HC_OS_0203.fcs · SG_HC_OS_0222.fcs · SG_HC_OS_0238.fcs |
| · HC 50+ | SC_HC_OS_00265.fcs · SG_HC_OS_00057.fcs · SG_HC_OS_00236.fcs · SG_HC_OS_00240.fcs · SG_HC_OS_00241.fcs · SG_HC_OS_00247.fcs · SG_HC_OS_00248.fcs · SG_HC_OS_00249.fcs · SG_HC_OS_00251.fcs · SG_HC_OS_00270.fcs · SG_HC_OS_00278.fcs · SG_HC_OS_00280.fcs · SG_HC_OS_00284.fcs · SG_HC_OS_00294.fcs · SG_HC_OS_00295.fcs |
| Sample Type | |
|---|---|
| · PBMC | SC_HC_OS_00174.fcs · SC_HC_OS_00190.fcs · SC_HC_OS_00234.fcs · SC_HC_OS_00265.fcs · SC_HC_OS_0235.fcs · SG_CO_OK_00008.fcs · SG_CO_OK_00009.fcs · SG_CO_OK_00010.fcs · SG_CO_OK_00012.fcs · SG_CO_OK_00013.fcs · SG_CO_OK_00014.fcs · SG_CO_OK_00015.fcs · SG_CO_OK_00015_2.fcs · SG_CO_OK_00016.fcs · SG_CO_OK_00017.fcs · SG_CO_OK_00017_2.fcs · SG_CO_OK_00018.fcs · SG_CO_OK_00019.fcs · SG_CO_OK_00021.fcs · SG_CO_OK_00021_2.fcs · SG_CO_OK_00022.fcs · SG_CO_OK_00023.fcs · SG_CO_OK_00023_2.fcs · SG_CO_OK_00025.fcs · SG_CO_OK_00026.fcs · SG_CO_OK_00027.fcs · SG_CO_OK_00028.fcs · SG_CO_OK_00029.fcs · SG_CO_OK_00030.fcs · SG_CO_OK_00031.fcs · SG_CO_OK_00032.fcs · SG_CO_OK_00033.fcs · SG_CO_OK_00034.fcs · SG_CO_OK_00035.fcs · SG_CO_OK_00036.fcs · SG_CO_OK_00037.fcs · SG_CO_OK_00038.fcs · SG_CO_OK_00039.fcs · SG_CO_OK_00040.fcs · SG_CO_OK_00041.fcs · SG_CO_OK_00042.fcs · SG_CO_OK_00043.fcs · SG_CO_OK_00046.fcs · SG_CO_OK_00047.fcs · SG_CO_OK_00048.fcs · SG_CO_OK_0004_2.fcs · SG_CO_OK_00050.fcs · SG_CO_OK_00052.fcs · SG_CO_OK_00053.fcs · SG_CO_OK_00054.fcs · SG_CO_OK_00055.fcs · SG_CO_OK_00056.fcs · SG_CO_OK_00057.fcs · SG_CO_OK_00060.fcs · SG_CO_OK_00067.fcs · SG_CO_OK_00068.fcs · SG_CO_OK_00070.fcs · SG_CO_OK_00071.fcs · SG_CO_OK_00072.fcs · SG_CO_OK_00075.fcs · SG_CO_OK_00076.fcs · SG_CO_OK_00077.fcs · SG_CO_OK_00079.fcs · SG_CO_OK_00080.fcs · SG_HC_OS_00007.fcs · SG_HC_OS_0005.fcs · SG_HC_OS_00057.fcs · SG_HC_OS_00097.fcs · SG_HC_OS_00163.fcs · SG_HC_OS_00175.fcs · SG_HC_OS_00180.fcs · SG_HC_OS_00181.fcs · SG_HC_OS_00183.fcs · SG_HC_OS_00184.fcs · SG_HC_OS_00188.fcs · SG_HC_OS_00193.fcs · SG_HC_OS_00204.fcs · SG_HC_OS_00236.fcs · SG_HC_OS_00240.fcs · SG_HC_OS_00241.fcs · SG_HC_OS_00244.fcs · SG_HC_OS_00247.fcs · SG_HC_OS_00248.fcs · SG_HC_OS_00249.fcs · SG_HC_OS_00251.fcs · SG_HC_OS_00270.fcs · SG_HC_OS_00278.fcs · SG_HC_OS_00280.fcs · SG_HC_OS_00284.fcs · SG_HC_OS_00293.fcs · SG_HC_OS_00294.fcs · SG_HC_OS_00295.fcs · SG_HC_OS_0170.fcs · SG_HC_OS_0203.fcs · SG_HC_OS_0222.fcs · SG_HC_OS_0238.fcs |
