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Summary: Multimodal advances in single-cell sequencing have enabled the simultaneous quantification of cell surface protein expression alongside unbiased transcriptional profiling. Here, we present LinQ-View, a toolkit designed for multimodal single-cell data visualization and analysis. LinQ-View integrates transcriptional and cell surface protein expression profiling data to reveal more accurate cell heterogeneity and proposes a quantitative metric for cluster purity assessment. Through comparison with existing multimodal methods on multiple public CITE-seq datasets, we demonstrate that LinQ-View efficiently generates accurate cell clusters, especially in CITE-seq data with routine numbers of surface protein features, by preventing variations in a single surface protein feature from affecting results. Finally, we utilized this method to integrate single-cell transcriptional and protein expression data from SARS-CoV-2-infected patients, revealing antigen-specific B cell subsets after infection. Our results suggest LinQ-View could be helpful for multimodal analysis and purity assessment of CITE-seq datasets that target specific cell populations (e.g., B cells). Motivation: Multimodal single-cell sequencing enables multiple aspects for characterizing the dynamics of cell states and developmental processes. Properly integrating information from multiple modalities is a crucial step for interpreting cell heterogeneity. Here, we present LinQ-View, a computational workflow that provides an effective solution for integrating multiple modalities of CITE-seq data for downstream interpretation. LinQ-View balances information from multiple modalities to achieve accurate clustering results and is specialized in handling CITE-seq data with routine numbers of surface protein features.

Dissecting the evolution of memory B cells (MBCs) against SARS-CoV-2 is critical for understanding antibody recall upon secondary exposure. Here, we utilized single-cell sequencing to profile SARS-CoV-2-reactive B cells in 38 COVID-19 patients. Using oligo-tagged antigen baits, we isolated B cells specific to the SARS-CoV-2 spike, nucleoprotein (NP), open reading frame 8 (ORF8), and endemic coronavirus (HCoV) spike proteins. SARS-CoV-2 spike-specific cells were enriched in the memory compartment of acutely infected and convalescent patients several months post-symptom onset. With severe acute infection, substantial populations of endemic HCoV-reactive antibody-secreting cells were identified and possessed highly mutated variable genes, signifying preexisting immunity. Finally, MBCs exhibited pronounced maturation to NP and ORF8 over time, especially in older patients. Monoclonal antibodies against these targets were non-neutralizing and non-protective in vivo. These findings reveal antibody adaptation to non-neutralizing intracellular antigens during infection, emphasizing the importance of vaccination for inducing neutralizing spike-specific MBCs., Graphical Abstract, Dugan et al. utilize a multi-antigen bait sorting and single cell sequencing approach to profile B cell immunodominance upon SARS-CoV-2 infection, revealing a dynamic response that evolves toward internal virus proteins over time. Antibodies to internal proteins were non-protective in vivo, suggesting vaccination may generate superior anti-spike immunological memory.

With the ongoing pandemic, it is critical to understand how natural immunity against SARS-CoV-2 and COVID-19 develops. We have identified that subjects with more severe COVID-19 disease mount a more robust and neutralizing antibody response against SARS-CoV-2 spike protein., Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a global pandemic. The antigen specificity of the antibody response mounted against this novel virus is not understood in detail. Here, we report that subjects with a more severe SARS-CoV-2 infection exhibit a larger antibody response against the spike and nucleocapsid protein and epitope spreading to subdominant viral antigens, such as open reading frame 8 and nonstructural proteins. Subjects with a greater antibody response mounted a larger memory B cell response against the spike, but not the nucleocapsid protein. Additionally, we revealed that antibodies against the spike are still capable of binding the D614G spike mutant and cross-react with the SARS-CoV-1 receptor binding domain. Together, this study reveals that subjects with a more severe SARS-CoV-2 infection exhibit a greater overall antibody response to the spike and nucleocapsid protein and a larger memory B cell response against the spike.

Background Convalescent plasma therapy for COVID‐19 relies on transfer of anti‐viral antibody from donors to recipients via plasma transfusion. The relationship between clinical characteristics and antibody response to COVID‐19 is not well defined. We investigated predictors of convalescent antibody production and quantified recipient antibody response in a convalescent plasma therapy clinical trial. Methods Multivariable analysis of clinical and serological parameters in 103 confirmed COVID‐19 convalescent plasma donors 28 days or more following symptom resolution was performed. Mixed‐effects regression models with piecewise linear trends were used to characterize serial antibody responses in 10 convalescent plasma recipients with severe COVID‐19. Results Donor antibody titres ranged from 0 to 1 : 3892 (anti‐receptor binding domain (RBD)) and 0 to 1 : 3289 (anti‐spike). Higher anti‐RBD and anti‐spike titres were associated with increased age, hospitalization for COVID‐19, fever and absence of myalgia (all P

Clinical trials emerged in rapid succession as the COVID-19 pandemic created an unprecedented need for life-saving therapies. Fair and equitable subject selection in clinical trials offering investigational therapies ought to be an urgent moral concern. Subject selection determines the distribution of risks and benefits, and impacts the applicability of the study results for the larger population. While Research Ethics Committees monitor fair subject selection within each trial, no standard oversight exists for subject selection across multiple trials for the same disease. Drawing on the experience of multiple clinical trials at a single academic medical centre in the USA, we posit that concurrent COVID-19 trials are liable to unfair and inequitable subject selection on account of scientific uncertainty, lack of transparency, scarcity and, lastly, structural barriers to equity compounded by implicit bias. To address the critical gap in the current literature and international regulation, we propose new ethical guidelines for research design and conduct that bolsters fair and equitable subject selection. Although the proposed guidelines are tailored to the research design and protocol of concurrent trials in the COVID-19 pandemic, they may have broader relevance to single COVID-19 trials.