Sen, N. | Search bioRxiv

bioRxiv2019

Temperature-Dependent Regulation of Upstream Open Reading Frame Translation in S. Cerevisiae

BackgroundTranslation of an mRNA in eukaryotes starts at AUG in most cases. Near-cognate codons (NCCs) such as UUG, ACG and AUU are also used as start sites at low levels in S. cerevisiae. Initiation from NCCs or AUGs in the 5-untranslated regions (UTRs) of mRNAs can lead to translation of upstream open reading frames (uORFs) that might regulate expression of the main ORF (mORF). Although there is some circumstantial evidence that the translation of uORFs can be affected by environmental conditions, little is known about how it is affected by changes in growth temperature.\n\nResultsUsing reporter assays, we found that changes in growth temperature can affect translation from NCC start sites in yeast cells, suggesting the possibility that gene expression could be regulated by temperature by altering use of different uORF start codons. Using ribosome profiling, we provide evidence that growth temperature regulates the efficiency of translation of nearly 200 uORFs in S. cerevisiae. Of these uORFs, most that start with an AUG codon have increased translational efficiency at 37 {degrees}C relative to 30 {degrees}C and decreased efficiency at 20 {degrees}C. For translationally regulated uORFs starting with NCCs, we did not observe a general trend for the direction of regulation as a function of temperature, suggesting mRNA-specific features can determine the mode of temperature-dependent regulation. Consistent with this conclusion, the position of the uORFs in the 5-leader relative to the 5-cap and the start codon of the main ORF correlates with the direction of temperature-dependent regulation of uORF translation. We have identified several novel cases in which changes in uORF translation are inversely correlated with changes in the translational efficiency of the downstream main ORF. Our data suggest that translation of these mRNAs is subject to temperature-dependent, uORF-mediated regulation.\n\nConclusionsOverall, our data suggest that alterations in the translation of specific uORFs by temperature can regulate gene expression in S. cerevisiae.

genomics↗

bioRxiv2019

Predicting and Designing therapeutics against the Nipah virus

Though every outbreak of the Nipah Virus has resulted in high mortality rates (>70% in Southeast Asia), there are no licensed drugs against it. In this study we have considered all 9 Nipah proteins as potential therapeutic targets and computationally identified putative peptides (against G, F, and M proteins) and small molecules inhibitors (against F, G, M, N, and P proteins). The computations include extensive homology/ab initio modelling, peptide design and small molecule docking. An important contribution of this study is the increased structural characterization of Nipah proteins by approximately 90% of what is deposited in the PDB. In addition, we have carried out molecular dynamics simulations on all the designed protein-peptide complexes to check for stability and to estimate binding strengths. Details, including atomic coordinates of all the proteins and their ligand bound complexes, can be accessed at http://cospi.iiserpune.ac.in/Nipah. Our strategy was to tackle the development of therapeutics on a proteome wide scale and the lead compounds identified could be attractive starting points for drug development. To this end, we have designed 4 peptide inhibitors and predicted 70 small molecules (13 with high confidence) against 3 and 5 Nipah proteins respectively. To counter the threat of drug resistance, we have analyzed the sequences of the viral strains from different outbreaks, to check whether they would be sensitive to the binding of the proposed inhibitors.\n\nAuthor SummaryNipah virus infections have killed 72-86% of the infected individuals in Bangladesh and India. The infections are spread via bodily secretions of bats, pigs and other infected individuals. Even though, the disease was first detected in the human population in 1998, there are no approved drugs/vaccines against it. In this study, we have tried to model the 3D structures of the Nipah virus proteins. We have then used these models to design/predict small inhibitory molecules that would bind them and prevent their function. We have also analyzed the different strains of the virus to identify conservation patterns of amino acids in the proteins, which in turn informs us of the efficacy of the drugs. The designed/docked compounds as well as the protein models are freely accessible for experimental validation and hypothesis testing.

bioinformatics↗