Altering the mRNA-1273 dosing interval impacts the kinetics, quality, and magnitude of immune responses in mice.

For a vaccine to achieve durable immunity and optimal efficacy, many require a multi-dose primary vaccination schedule that acts to first "prime" naive immune systems and then "boost" initial immune responses by repeated immunizations (ie, prime-boost regimens). In the context of the global coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2-dose primary vaccination regimens were often selected with short intervals between doses to provide rapid protection while still inducing robust immunity. However, emerging post-authorization evidence has suggested that longer intervals between doses 1 and 2 for SARS-CoV-2 vaccines may positively impact robustness and durability of immune responses. Here, the dosing interval for mRNA-1273, a messenger RNA based SARS-CoV-2 vaccine administered on a 2-dose primary schedule with 4 weeks between doses, was evaluated in mice by varying the dose interval between 1 and 8 weeks and examining immune responses through 24 weeks after dose 2. A dosing interval of 6 to 8 weeks generated the highest level of antigen-specific serum immunoglobulin G binding antibody titers. Differences in binding antibody titers between mRNA-1273 1 µg and 10 µg decreased over time for dosing intervals of ≥4 weeks, suggesting a potential dose-sparing effect. Longer intervals (≥4 weeks) also increased antibody-dependent cellular cytotoxicity activity and numbers of antibody-secreting cells (including long-lived plasma cells) after the second dose. An interval of 6 to 8 weeks elicited the strongest CD8+ T-cell responses, while an interval of 3 weeks elicited the strongest CD4+ T-cell response. Overall, these results suggest that in a non-pandemic setting, a longer interval (≥6 weeks) between the doses of the primary series for mRNA-1273 may induce more durable immune responses.

Improved integration of single-cell transcriptome and surface protein expression by LinQ-View

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). Graphical Highlights • LinQ-View integrates mRNA and protein expression data to reveal cell heterogeneity• LinQ-View prevents single dominant ADT features from affecting clustering• LinQ-View presents a quantitative purity metric for CITE-seq data• LinQ-View is specialized in handling CITE-seq data with fewer ADT features 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. Li et al. present LinQ-View, a computational workflow that provides an effective solution for integrating multiple modalities of CITE-seq data and quantitative assessment of cluster purity. LinQ-View could be helpful for multimodal analysis and purity assessment of CITE-seq datasets that target specific cell populations.

Variant SARS-CoV-2 mRNA vaccines confer broad neutralization as primary or booster series in mice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of a global pandemic. Safe and effective COVID-19 vaccines are now available, including mRNA-1273, which has shown 94% efficacy in prevention of symptomatic COVID-19 disease. However, the emergence of SARS-CoV-2 variants has led to concerns of viral escape from vaccine-induced immunity. Several variants have shown decreased susceptibility to neutralization by vaccine-induced immunity, most notably B.1.351 (Beta), although the overall impact on vaccine efficacy remains to be determined. Here, we present the initial evaluation in mice of 2 updated mRNA vaccines designed to target SARS-CoV-2 variants: (1) monovalent mRNA-1273.351 encodes for the spike protein found in B.1.351 and (2) mRNA-1273.211 comprising a 1:1 mix of mRNA-1273 and mRNA-1273.351. Both vaccines were evaluated as a 2-dose primary series in mice; mRNA-1273.351 was also evaluated as a booster dose in animals previously vaccinated with mRNA-1273. The results demonstrated that a primary vaccination series of mRNA-1273.351 was effective at increasing neutralizing antibody titers against B.1.351, while mRNA-1273.211 was effective at providing broad cross-variant neutralization. A third (booster) dose of mRNA-1273.351 significantly increased both wild-type and B.1.351-specific neutralization titers. Both mRNA-1273.351 and mRNA-1273.211 are being evaluated in pre-clinical challenge and clinical studies.

Attenuated activation of pulmonary immune cells in mRNA-1273-vaccinated hamsters after SARS-CoV-2 infection.

The mRNA-1273 vaccine is effective against SARS-CoV-2 and was granted emergency use authorization by the FDA. Clinical studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Hamsters are the only model that reliably exhibits severe SARS-CoV-2 disease similar to that in hospitalized patients, making them pertinent for vaccine evaluation. We demonstrate that prime or prime-boost administration of mRNA-1273 in hamsters elicited robust neutralizing antibodies, ameliorated weight loss, suppressed SARS-CoV-2 replication in the airways, and better protected against disease at the highest prime-boost dose. Unlike in mice and nonhuman primates, low-level virus replication in mRNA-1273-vaccinated hamsters coincided with an anamnestic response. Single-cell RNA sequencing of lung tissue permitted high-resolution analysis that is not possible in vaccinated humans. mRNA-1273 prevented inflammatory cell infiltration and the reduction of lymphocyte proportions, but enabled antiviral responses conducive to lung homeostasis. Surprisingly, infection triggered transcriptome programs in some types of immune cells from vaccinated hamsters that were shared, albeit attenuated, with mock-vaccinated hamsters. Our results support the use of mRNA-1273 in a 2-dose schedule and provide insight into the potential responses within the lungs of vaccinated humans who are exposed to SARS-CoV-2.

Improved integration of single-cell transcriptome and surface protein expression by LinQ-View.

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).

SARS-CoV-2 mRNA vaccine design enabled by prototype pathogen preparedness.

A vaccine for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is needed to control the coronavirus disease 2019 (COVID-19) global pandemic. Structural studies have led to the development of mutations that stabilize Betacoronavirus spike proteins in the prefusion state, improving their expression and increasing immunogenicity1. This principle has been applied to design mRNA-1273, an mRNA vaccine that encodes a SARS-CoV-2 spike protein that is stabilized in the prefusion conformation. Here we show that mRNA-1273 induces potent neutralizing antibody responses to both wild-type (D614) and D614G mutant2 SARS-CoV-2 as well as CD8+ T cell responses, and protects against SARS-CoV-2 infection in the lungs and noses of mice without evidence of immunopathology. mRNA-1273 is currently in a phase III trial to evaluate its efficacy.