Biology subjects

Guthmiller, J.

Publications and source records attributed to Guthmiller, J..

3 recordsLinked to original sources

bioRxiv2026

Convergent antigenic drift of the influenza hemagglutinin lateral patch across time and species

The lateral patch epitope of the H1 hemagglutinin (HA) was a dominant target of antibodies following exposure to the 2009 pandemic H1N1 virus. However, the conservation and potential for antigenic drift in the lateral patch remain unresolved. Here, we used lateral patch-specific monoclonal antibodies (mAbs) to understand the antigenicity of the lateral patch of human, avian, and swine H1Nx viruses spanning from 1918 to 2022. We identified discrete mutations that evaded lateral patch-targeting mAbs in pre- and post-2009 H1N1 viruses, leading to genetic differences in lateral patch-targeting antibodies in individuals across birth years. We observed that the lateral patch remains well conserved across zoonotic sources, suggesting existing lateral patch antibodies could protect against a future H1Nx pandemic. Together, these data support that lateral patch antigenic drift has shaped the human B cell repertoire against influenza viruses and that the lateral patch remains an attractive target for pandemic preparedness.

microbiology↗

bioRxiv2025

Surveillance on California dairy farms reveals multiple sources of H5N1 transmission

Transmission routes of highly pathogenic H5N1 between cows or to humans remain unclear due to limited data from affected dairy farms. We performed air, farm wastewater, and milk sampling on 14 H5N1 positive dairy farms across two different California regions. Infectious virus was detected in the air in milking parlors and in wastewater streams, while viral RNA was found in exhaled breath of cows. Sequence analysis of infectious H5N1 virus from air and wastewater samples on one farm revealed viral variants relevant for potential human susceptibility. Longitudinal analysis of milk from the individual quarters of cows revealed a high prevalence of subclinical H5N1 positive cows. Additionally, a heterogeneous distribution of infected quarters that maintained a consistent pattern over time was observed, inconsistent with shared milking equipment serving as the sole transmission mode. The presence of subclinically infected cows was further supported by detection of antibodies in the milk of animals that exhibited no clinical signs during the H5N1 outbreak on one farm. Our data highlight additional sources and potential modes of H5N1 transmission on dairy farms.

microbiology↗

bioRxiv2024

An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries

Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines multiple antigens and multiple antibodies and determines quantitative biophysical parameters using deep sequencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of ten different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.

biochemistry↗