Factors associated with resistance to SARS-CoV-2 infection discovered using large-scale medical record data and machine learning.

There have been over 621 million cases of COVID-19 worldwide with over 6.5 million deaths. Despite the high secondary attack rate of COVID-19 in shared households, some exposed individuals do not contract the virus.

Tandem phage-display for the identification of non-overlapping binding pairs of recombinant affinity reagents.

The 'sandwich' binding format, which uses two reagents that can bind simultaneously to a given analyte, is the gold standard in diagnostics and many biochemical techniques. One of the bottlenecks in creating a sandwich assay is identifying pairs of reagents that bind non-competitively to the target. To bridge this gap, we invented Megaprimer Shuffling for Tandem Affinity Reagents (MegaSTAR) to identify non-competitive binding pairs of recombinant affinity reagents through phage-display.

Streamlining the Pipeline for Generation of Recombinant Affinity Reagents by Integrating the Affinity Maturation Step.

Often when generating recombinant affinity reagents to a target, one singles out an individual binder, constructs a secondary library of variants, and affinity selects a tighter or more specific binder. To enhance the throughput of this general approach, we have developed a more integrated strategy where the "affinity maturation" step is part of the phage-display pipeline, rather than a follow-on process. In our new schema, we perform two rounds of affinity selection, followed by error-prone PCR on the pools of recovered clones, generation of secondary libraries, and three additional rounds of affinity selection, under conditions of off-rate competition.