German, J. | bioRxiv Science

bioRxiv2026

Development and validation of two economical and flexible immunoassays for detecting antibodies against LCMV in mouse serum

Measurement of antibody responses to viral infection is essential for surveillance, diagnostics, epidemiological research, and natural history of infection studies. However, current methods to detect virus-specific antibodies are often resource-intensive and impractical for deployment in outbreak settings or in field-based studies. This manuscript presents two economical, high-throughput immunoassays--the cytoblot immunoassay (CBA) and strip immunoblot assay (SIA)--for detecting and quantifying anti-lymphocytic choriomeningitis mammarenavirus (LCMV) antibodies in mouse serum. To validate, we tested serum from acutely or persistently experimentally infected mice. Both assays detected LCMV-specific IgG and IgM antibodies with high sensitivity and specificity across multiple timepoints. By facilitating the study of immune responses in rodent reservoirs, these tools can enhance our understanding of zoonotic viral transmission, provide scalable platforms for outbreak preparedness, and serve as adaptable models for the development of rapid serological assays for other viral pathogens.

microbiology↗

bioRxiv2021

High confidence identification of intra-host single nucleotide variants for person-to-person influenza transmission tracking in congregate settings

Influenza within-host viral populations are the source of all global influenza diversity and play an important role in driving the evolution and escape of the influenza virus from human immune responses, antiviral treatment, and vaccines, and have been used in precision tracking of influenza transmission chains. Next Generation Sequencing (NGS) has greatly improved our ability to study these populations, however, major challenges remain, such as accurate identification of intra-host single nucleotide variants (iSNVs) that represent within-host viral diversity of influenza virus. In order to investigate the sources and the frequency of called iSNVs in influenza samples, we used a set of longitudinal influenza patient samples collected within a University of Maryland (UMD) cohort of college students in a living learning community. Our results indicate that technical replicates aid in removal of random RT-PCR, PCR, and platform sequencing errors, while the use of clonal plasmids for removal of systematic errors is more important in samples of low RNA abundance. We show that the choice of reference for read mapping affects the frequency of called iSNVs, with the sample self-reference resulting in the lowest amount of iSNV noise. The importance of variant caller choice is also highlighted in our study, as we observe differential sensitivity of variant callers to the mapping reference choice, as well as the poor overlap of their called iSNVs. Based on this, we develop an approach for identification of highly probable iSNVs by removal of sequencing and bioinformatics algorithm-associated errors, which we implement in phylogenetic analyses of the UMD samples for a greater resolution of transmission links. In addition to identifying closely related transmission connections supported by the presence of highly confident shared iSNVs between patients, our results also indicate that the rate of minor variant turnover within a host may be a limiting factor for utilization of iSNVs to determine patient epidemiological links.

genomics↗