Jennifer J. Knapp

This paper develops and implements wastewater-based surveillance methods to monitor Influenza A H3N2 and respiratory syncytial virus A in Ontario, Canada, enabling real-time tracking of viral lineages and informing public health decisions.

The paper uses a yeast two-hybrid screen to identify novel effector-effector interactions in L. pneumophila, doubling the known number of such interactions.

The paper evaluates nine computational tools for identifying SARS-CoV-2 lineages in wastewater sequencing data using simulated samples, finding most tools reliably detect lineages above 5% frequency.

The paper maps binary SARS-CoV-2 protein interactions with host proteins, identifying key processes like immune signaling and ubiquitination, and suggests therapeutic targets.

The paper constructs a high-quality yeast binary interactome map and compares inner- and outer-complexome organization, finding the outer-complexome contains more interactions and exhibits higher functional heterogeneity.

Proximity-dependent biotinylation of 27 SARS-CoV-2 proteins in A549 cells maps 7810 virus-host proximity interactions across 2242 host proteins, including membrane-associated partners missed by affinity purification.

Proximity-dependent biotinylation (BioID) of 28 SARS-CoV-2 proteins in human cells maps 5,415 proximal interactions with 2,128 host targets across basal and poly(I:C) conditions.

The paper presents HuRI, a comprehensive human protein-protein interaction map, and demonstrates its utility in understanding cellular function and disease mechanisms.

This paper develops a deep mutational scanning framework to map functional missense variants in human genes and applies it to four proteins, identifying pathogenic variants and showing scalability to disease genes.