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Biology subjects

Sasser, L. E.

Publications and source records attributed to Sasser, L. E..

2 recordsLinked to original sources

Wobble Vaccines: Cross-Strain Protection Through Epitope Hierarchy Manipulation

Vaccination remains the most successful preventative measure against viral infection, but methods to stably deter rapidly-evolving pathogens have remained elusive. Vaccines capable of incorporating and anticipating viral evolution could address current challenges in seasonal vaccination efforts against SARS-CoV-2 and influenza where economic and disease burdens remain high despite decades of combined study. Rare epitope suppression (RES) is an underutilized concept within vaccine design, where humoral epitope targeting can be molded using complex antigen pools. Based in mRNA vaccine technology, wobble vaccines represent the novel application of RES to human pathogens designed to anticipate and resist viral evolution. To establish this platform, public SARS-CoV-2 sequencing data was compiled from the first two years of the COVID-19 pandemic to identify high-diversity sites across the receptor binding domain (RBD) of the spike protein. Wobble RBD (WobbRBD) libraries reflecting that entropy were synthesized and incorporated into established self-amplifying (SA) vaccine constructs. Animals immunized with these complex antigen pools showed no obvious adverse effects. By three days-post vaccination, WobbRBD stimulated robust primary immune activation with distinctive characteristics compared to traditional single-strain vaccine modalities. By day 14, germinal centers, class switching, and antibody-secreting cells were induced, creating potent SARS-CoV-2 spike-binding IgG antibodies. Despite similar overall activation profiles, WobbRBD generated significantly increased breadth against SARS-CoV-2 variant spikes in comparison to single-strain controls - even against future-emerging strains. Taken together, wobble vaccines represent a novel method for anticipating and preventing viral escape with promising applications in SARS-CoV-2, influenza, HIV, and beyond.

immunology↗

CRISP enables comparisons of image-based spatial transcriptomicsegmentation quality across ten organs

Image-based spatial transcriptomics depends on cell segmentation to assign transcripts to individual cells, but how segmentation algorithms perform across tissues with distinct cellular architectures is poorly understood. This study presents the broadest independent benchmark to date of cell segmentation algorithms for spatial transcriptomics, comparing five approaches across ten mouse tissues using a 5,006-gene Xenium panel. To quantify segmentation errors, Co-expression Rejection in Segmentation Purity (CRISP) was developed, an open-source tool available in R and Python that measures cell purity through tissue-specific mutually exclusive marker co-expression without requiring ground truth annotations. This benchmark revealed that segmentation algorithms face a fundamental tradeoff between maximizing transcript capture and maintaining cell purity, and that the severity of this tradeoff is tissue-dependent. Proseg achieved the highest average performance across tissues, though the magnitude of its advantage varies with tissue architecture. Overall, CRISP provides per-tissue performance profiles as a practical resource for algorithm selection.

bioinformatics↗