Human memory B cells show plasticity and adopt multiple fates upon recall response to SARS-CoV-2

The B cell response to different pathogens uses tailored effector mechanisms and results in functionally specialized memory B (Bm) cell subsets, including CD21+ resting, CD21–CD27+ activated and CD21–CD27– Bm cells. The interrelatedness between these Bm cell subsets remains unknown. Here we showed that single severe acute respiratory syndrome coronavirus 2-specific Bm cell clones showed plasticity upon antigen rechallenge in previously exposed individuals. CD21– Bm cells were the predominant subsets during acute infection and early after severe acute respiratory syndrome coronavirus 2-specific immunization. At months 6 and 12 post-infection, CD21+ resting Bm cells were the major Bm cell subset in the circulation and were also detected in peripheral lymphoid organs, where they carried tissue residency markers. Tracking of individual B cell clones by B cell receptor sequencing revealed that previously fated Bm cell clones could redifferentiate upon antigen rechallenge into other Bm cell subsets, including CD21–CD27– Bm cells, demonstrating that single Bm cell clones can adopt functionally different trajectories.

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Software and code
Policy information about availability of computer code Data collection Flow cytometry data was generated using Cytek SpectroFlo (Version 3.0.3) and for sorting using BD FACSDiva (Version 8.0.1).

Data analysis
For data analysis Graph-Pad Prism (Version 9.4.1, GraphPad Software, La Jolla California USA) and R (Version 4.1.0) were used. Flow cytometry data were analysed using FlowJo (version 10.8.0), and unsupervised analysis was performed using the CATALYST package (version 1.18.1) and Rphenograph package (version 0.99.1). For the scRNA-seq analysis the following packages were used: Cell Ranger's 'cellranger multi' pipeline (10x Genomics) (Version 6.1.2), Seurat (Version 4.1.1), ComplexHeatmap package (Version 2.13.1), pheatmap package (Version 1.0.12), package fgsea (Version 1.2), package msigdbr (Version 7.5.1), gsva (Version 1.42.0), limma (Version 3.50.3), Monocle3 (Version 1.2.9), Batchelor (Version 1.10.0), changeo-10x pipeline from the immcantation_suite-4.3.0, package scRepertoire (Version 1.3.5), Alakazam (Version 1.2.0), edgeR (Version 3.36). The code generated during the current study is available at https://github.com/Moors-Code/MBC_Plasticity_Moor_Boyman_Collaboration. For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Portfolio guidelines for submitting code & software for further information.
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March 2021
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our policy The sequencing data has been deposited at zenodo.org and is available under 10.5281/zenodo.7064118. Gene sets were obtained from the Molecular Signatures Database (v7.5.1, collections H and C5). The source data are provided with the article. The flow cytometry dataset is available upon request from the corresponding authors.

Human research participants
Policy information about studies involving human research participants and Sex and Gender in Research.

Reporting on sex and gender
The SARS-CoV-2 infection cohort for the flow cytometry analysis consisted of 33 female and 32 male patients, the tonsil cohort of 9 female and 7 male patients and the vaccination cohort of 5 female and 6 male individuals. Sex was collected from the electronic medical records, gender data was not collected.

Population characteristics
The cohort characterstics for the different (sub-)cohorts are shown in supplementary tables 1-4.

Recruitment
Patients at four hospitals in the Canton of Zurich, Switzerland, that had a reverse-transcriptase polymerase chain reaction confirmed SARS-CoV-2 infection and were symptomatic, were approached whether they would be interested in participating in the study. Patients had to be over 18 years old and had to be competent at the time of consent. Following written informed consent the COVID-19 patients donated blood and serum samples. Subsequently, patients visited again at month 6 and 12 post-infection and donated blood and serum samples at the respective time points. The patients were included in the study during their acute disease between April 2020 and September 2020 and for the 12 months follow-up between April 2021 and September 2021. As the patients had to be competent when providing the informed consent this might have skewed the disease severity distribution of the cohort. Additionally, patients that underwent a tonsillectomy at University Hospital Zurich between November 2021 and April 2022 were approached whether they wold be interested in participating in the study. All patients signed a written informed consent before sample collection. Subsequently paired tonsil and peripheral blood samples, as well as serum samples, were collected. Patients underwent their tonsillectomy for recurrent and chronic tonsillitis or obstructive sleep apnea. We recruited 11 healthy controls that had no history of SARS-CoV-2 infection. After providing a written informed consent the individuals donated blood before the vaccination, 8-13 days after the second vaccine shot, six months after the vaccination as well as 11-14 days after the third vaccine dose. All donors were seronegative for SARS-CoV-2 spike S1 antibodies. As the participants were recruited from hospital workers they tended to be younger than the patients in the SARS-CoV-2 infection cohort.

Ethics oversight
The study was approved by the Cantonal Ethical Committee of Zurich (BASEC #2016-01440) and all participants signed a written informed consent before inclusion into the study.
Note that full information on the approval of the study protocol must also be provided in the manuscript.

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Life sciences study design
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Sample size
The sample size for the SARS-CoV-2 Infection Cohort (n=65) was determined based on pre-experiments. For the SARS-CoV-2 Tonsil and Vaccination Cohorts the sample size was determined by sample availability.
Randomization Not applicable as this is an observational study.

Blinding
As the patients were included based on the SARS-CoV-2 infection history, blinding could not performed.

Reporting for specific materials, systems and methods
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March 2021
Flow Cytometry Plots Confirm that: The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.

Methodology
Sample preparation Blood was collected from patients and subsequently PBMCs were isolated using a Ficoll density gradient centrifugation, before being washed, counted and frozen in fetal bovine serum (FBS) with 10% dimethyl sulfoxide (DMSO) and stored in liquid nitrogen until use. Tonsils were mechanically cut into smaller pieces, grinded through a 70 micrometer cell strainer, washed in phosphate buffered saline, before a density gradient centrifugation was performed. Subsequently, the mononuclear cells were washed, counted, frozen in FBS with 10% DMSO and stored in liquid nitrogen until use. For subsequent analysis the frozen cells were thawed in pre-warmed R10 medium and subsequently processed for flow cytometry as described in the methods section.

Instrument
Samples were acquired on a Cytek Aurora and sorting was performed on an BD Aria III 4L.

Software
Flow cytometry data was generated using Cytek SpectroFlo (Version 3.0.3) and for sorting using BD FACSDiva (Version 8.0.1). The flow cytometry data were analysed using FlowJo (version 10.8.0).

Cell population abundance
As the cell numbers were low after sorting, all of the cells were loaded and processed for scRNA-sequencing using the 10x system. The cell identities were subsequently confirmed by single cell sequencing including feature barcoding.

Gating strategy
The full gating and sorting strategies are shown in the Extended Data Figures 2, 5 and 6.
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