Nonsense-containing mRNAs that accumulate in the absence of a functional nonsense-mediated mRNA decay pathway are destabilized rapidly upon its restitution.

Nonsense-mediated mRNA decay (NMD) is a conserved proofreading mechanism that protects eukaryotic cells from the potentially deleterious effects of truncated proteins. Studies of Saccharomyces cerevisiae imply that NMD is a predominantly cytoplasmic decay pathway, while studies of mammalian systems suggest that decay of most substrate mRNAs may occur while they are still associated with the nucleus, possibly during a round of translation that occurs during their export to the cytoplasm. Complete entry of the latter mRNAs into the cytoplasm appears to render them immune to further NMD; i.e., they escape further susceptibility to this decay pathway. To determine if yeast cytoplasmic nonsense-containing mRNAs that evade decay are subsequently immune to NMD, we examined the consequences of placing each of the three UPF/NMD genes under the control of a galactose-inducible promoter. The decay kinetics of ADE2 and PGK1 nonsense-containing mRNAs were then analyzed when expression of UPF1, NMD2, or UPF3 was either repressed or subsequently induced. Results from these experiments demonstrated that activation of NMD caused rapid and immediate degradation of both substrate transcripts, with half-lives of both stable mRNA populations shortened to approximately 7 min. These findings make it unlikely that yeast nonsense-containing mRNAs can escape degradation by NMD and indicate that such mRNAs are available to this decay pathway at each round of translation.

Database-Centric Method for Automated High-Throughput Deconvolution and Analysis of Kinetic Antibody Screening Data.

The state-of-the-art industrial drug discovery approach is the empirical interrogation of a library of drug candidates against a target molecule. The advantage of high-throughput kinetic measurements over equilibrium assessments is the ability to measure each of the kinetic components of binding affinity. Although high-throughput capabilities have improved with advances in instrument hardware, three bottlenecks in data processing remain: (1) intrinsic molecular properties that lead to poor biophysical quality in vitro are not accounted for in commercially available analysis models, (2) processing data through a user interface is time-consuming and not amenable to parallelized data collection, and (3) a commercial solution that includes historical kinetic data in the analysis of kinetic competition data does not exist. Herein, we describe a generally applicable method for the automated analysis, storage, and retrieval of kinetic binding data. This analysis can deconvolve poor quality data on-the-fly and store and organize historical data in a queryable format for use in future analyses. Such database-centric strategies afford greater insight into the molecular mechanisms of kinetic competition, allowing for the rapid identification of allosteric effectors and the presentation of kinetic competition data in absolute terms of percent bound to antigen on the biosensor.