Tri-snRNP-associated proteins interact with subunits of the TRAMP and nuclear exosome complexes, linking RNA decay and pre-mRNA splicing

Nuclear RNA decay factors are involved in many different pathways including rRNA processing, snRNA and snoRNA biogenesis, pre-mRNA processing, and the rapid decay of cryptic intergenic transcripts. In contrast to its yeast counterpart, the mammalian nuclear decay machinery is largely uncharacterized. Here we report interactions of several putative components of the human nuclear RNA decay machinery, including the TRAMP complex protein Mtr4 and the nuclear exosome constituents PM/Scl-100 and PM/Scl-75, with components of the U4/U6.U5 tri-snRNP complex required for pre-mRNA splicing. The tri-snRNP component Prp31 interacts indirectly with Mtr4 and PM/Scl-100 in a manner that is dependent on the phosphorylation sites in the middle of the protein, while Prp3 and Prp4 interact with the nuclear decay complex independent of Prp31. Together our results suggest recruitment of the nuclear decay machinery to the spliceosome to ensure production of properly spliced mRNA

A Preliminary Investigation in the Molecular Basis of Host Shutoff Mechanism in SARS-CoV

Recent events leading to the worldwide pandemic of COVID-19 have demonstrated the effective use of genomic sequencing technologies to establish the genetic sequence of this virus. In contrast, the COVID-19 pandemic has demonstrated the absence of computational approaches to understand the molecular basis of this infection rapidly. Here we present an integrated approach to the study of the nsp1 protein in SARS-CoV-1, which plays an essential role in maintaining the expression of viral proteins and further disabling the host protein expression, also known as the host shutoff mechanism. We present three independent methods of evaluating two potential binding sites speculated to participate in host shutoff by nsp1. We have combined results from computed models of nsp1, with deep mining of all existing protein structures (using PDBMine), and binding site recognition (using msTALI) to examine the two sites consisting of residues 55-59 and 73-80. Based on our preliminary results, we conclude that the residues 73-80 appear as the regions that facilitate the critical initial steps in the function of nsp1. Given the 90% sequence identity between nsp1 from SARS-CoV-1 and SARS-CoV-2, we conjecture the same critical initiation step in the function of COVID-19 nsp1.Comment: Consists of 9 pages, 8 figures and 7 tables. 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics 202

A Major Determinant of Cyclophilin Dependence and Cyclosporine Susceptibility of Hepatitis C Virus Identified by a Genetic Approach

Since the advent of genome-wide small interfering RNA screening, large numbers of cellular cofactors important for viral infection have been discovered at a rapid pace, but the viral targets and the mechanism of action for many of these cofactors remain undefined. One such cofactor is cyclophilin A (CyPA), upon which hepatitis C virus (HCV) replication critically depends. Here we report a new genetic selection scheme that identified a major viral determinant of HCV's dependence on CyPA and susceptibility to cyclosporine A. We selected mutant viruses that were able to infect CyPA-knockdown cells which were refractory to infection by wild-type HCV produced in cell culture. Five independent selections revealed related mutations in a single dipeptide motif (D316 and Y317) located in a proline-rich region of NS5A domain II, which has been implicated in CyPA binding. Engineering the mutations into wild-type HCV fully recapitulated the CyPA-independent and CsA-resistant phenotype and four putative proline substrates of CyPA were mapped to the vicinity of the DY motif. Circular dichroism analysis of wild-type and mutant NS5A peptides indicated that the D316E/Y317N mutations (DEYN) induced a conformational change at a major CyPA-binding site. Furthermore, nuclear magnetic resonance experiments suggested that NS5A with DEYN mutations adopts a more extended, functional conformation in the putative CyPA substrate site in domain II. Finally, the importance of this major CsA-sensitivity determinant was confirmed in additional genotypes (GT) other than GT 2a. This study describes a new genetic approach to identifying viral targets of cellular cofactors and identifies a major regulator of HCV's susceptibility to CsA and its derivatives that are currently in clinical trials

Insights Gained from an Inquiry-Driven Biochemistry Laboratory during the COVID-19 Pandemic

The early stages of the COVID-19 pandemic required us to implement innovative ideas, especially in upper-level chemistry laboratory courses that train students to implement critical thinking and problem-solving skills. Due to the pandemic-enforced close down of the campus in the spring of 2020, many students lacked laboratory skills. At the same time our university, like many others, adopted the HyFlex model to accommodate multiple waves of COVID-19 and to provide flexibility for the students to learn materials from home. In accordance with these changes, the senior-level biochemistry laboratory course was restructured into a hybrid course focusing on the study of a SARS coronavirus protein. To establish inquiry-driven learning, this hybrid course included two modules: Module I included computer-based studies that allowed students to propose a hypothesis, and Module II included in-person laboratory sessions that allowed students to verify the hypothesis. The computer-based module was offered in synchronous hybrid (virtual and in-person) mode, while the hands-on activities were run in a synchronous in-person mode. This computer-based module could be adapted in any biochemistry lecture or laboratory course as a separate module or as a semester-long project to study the structure–function relationship of a protein of interest. In this communication, I present the activities and the key lessons learned from the inquiry-driven biochemistry laboratory course. Based on this experience, several adjustments are made for future courses to offer flexibility to students

A Tale of Two RNAs during Viral Infection: How Viruses Antagonize mRNAs and Small Non-Coding RNAs in The Host Cell

Viral infection initiates an array of changes in host gene expression. Many viruses dampen host protein expression and attempt to evade the host anti-viral defense machinery. Host gene expression is suppressed at several stages of host messenger RNA (mRNA) formation including selective degradation of translationally competent messenger RNAs. Besides mRNAs, host cells also express a variety of noncoding RNAs, including small RNAs, that may also be subject to inhibition upon viral infection. In this review we focused on different ways viruses antagonize coding and noncoding RNAs in the host cell to its advantage

Can a Calibration-Free Dynamic Rainfall‒Runoff Model Predict FDCs in Data-Scarce Regions? Comparing the IDW Model with the Dynamic Budyko Model in South India

Construction of flow duration curves (FDCs) is a challenge for hydrologists as most streams and rivers worldwide are ungauged. Regionalization methods are commonly followed to solve the problem of discharge data scarcity by transforming hydrological information from gauged basins to ungauged basins. As a consequence, regionalization-based FDC predictions are not very reliable where discharge data are scarce quantitatively and/or qualitatively. In such a scenario, it is perhaps more meaningful to use a calibration-free rainfall‒runoff model that can exploit easily available meteorological information to predict FDCs in ungauged basins. This hypothesis is tested in this study by comparing a well-known regionalization-based model, the inverse distance weighting (IDW) model, with the recently proposed calibration-free dynamic Budyko model (DB) in a region where discharge observations are not only insufficient quantitatively but also show apparent signs of observational errors. The DB model markedly outperformed the IDW model in the study region. Furthermore, the IDW model’s performance sharply declined when we randomly removed discharge gauging stations to test the model in a variety of data availability scenarios. The analysis here also throws some light on how errors in observational datasets and drainage area influence model performance and thus provides a better picture of the relative strengths of the two models. Overall, the results of this study support the notion that a calibration-free rainfall‒runoff model can be chosen to predict FDCs in discharge data-scarce regions. On a philosophical note, our study highlights the importance of process understanding for the development of meaningful hydrological models