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McKay, B.

Publications and source records attributed to McKay, B..

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Heavy metal sensitivities of gene deletion strains for ITT1 and RPS1A connect their activities to the expression of URE2, a key gene involved in metal detoxification in yeast

Heavy metal and metalloid contaminations are among the most concerning types of pollutant in the environment. Consequently, it is important to investigate the molecular mechanisms of cellular responses and detoxification pathways for these compounds in living organisms. To date, a number of genes have been linked to the detoxification process. The expression of these genes can be controlled at both transcriptional and translational levels. In bakers yeast, Saccharomyces cerevisiae, resistance to a wide range of toxic metals is regulated by glutathione S-transferases. Yeast URE2 encodes for a protein that has glutathione peroxidase activity and is homologous to mammalian glutathione S-transferases. The URE2 expression is critical to cell survival under heavy metal stress. Here, we report on the finding of two genes, ITT1, an inhibitor of translation termination, and RPS1A, a small ribosomal protein, that when deleted yeast cells exhibit similar metal sensitivity phenotypes to gene deletion strain for URE2. Neither of these genes were previously linked to metal toxicity. Our gene expression analysis illustrates that these two genes affect URE2 mRNA expression at the level of translation.\n\nSummary statementWe identified two yeast genes, ITT1 and RPS1A, that when deleted, results in yeast cells sensitivity to heavy metals and metalloids. Further investigation indicated that they influence the expression of URE2 gene, a key player in metal detoxification, by upregulating its translation. Our findings suggest that ITT1 and RPS1A play an indirect role in responding to toxic metal stress.

genomics

Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design

BackgroundVaccination is an effective method to protect against infectious diseases. An important consideration in any vaccine formulation is the inoculum dose, i.e., amount of antigen or live attenuated pathogen that is used. Higher levels generally lead to better stimulation of the immune response but might cause more severe side effects and allow for less population coverage in the presence of vaccine shortages. Determining the optimal amount of inoculum dose is an important component of rational vaccine design. A combination of mathematical models with experimental data can help determine the impact of the inoculum dose.\n\nMethodsWe designed mathematical models and fit them to data from influenza A virus (IAV) infection of mice and human parainfluenza virus (HPIV) of cotton rats at different inoculum doses. We used the model to predict the level of immune protection and morbidity for different inoculum doses and to explore what an optimal inoculum dose might be.\n\nResultsWe show how a framework that combines mathematical models with experimental data can be used to study the impact of inoculum dose on important outcomes such as immune protection and morbidity. We find that the impact of inoculum dose on immune protection and morbidity depends on the pathogen and both protection and morbidity do not always increase with increasing inoculum dose. An intermediate inoculum dose can provide the best balance between immune protection and morbidity, though this depends on the specific weighting of protection and morbidity.\n\nConclusionsOnce vaccine design goals are specified with required levels of protection and acceptable levels of morbidity, our proposed framework which combines data and models can help in the rational design of vaccines and determination of the optimal amount of inoculum.

systems biology