In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Q: Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) was originally identified in Saudi Arabia in 2012. It has caused MERS outbreaks with high mortality in the Middle East and Europe, raising a serious concern about its pandemic potential. Therefore, development of effective vaccines is crucial for preventing its further spread and future pandemic. Our previous study has shown that subcutaneous (s.c.) vaccination of a recombinant protein containing receptor-binding domain (RBD) of MERS-CoV S fused with Fc of human IgG (RBD-Fc) induced strong systemic neutralizing antibody responses in vaccinated mice. Here, we compared local and systemic immune responses induced by RBD-Fc via intranasal (i.n.) and s.c. immunization pathways. We found that i.n. vaccination of MERS-CoV RBD-Fc induced systemic humoral immune responses comparable to those induced by s.c. vaccination, including neutralizing antibodies, but more robust systemic cellular immune responses and significantly higher local mucosal immune responses in mouse lungs. This study suggests the potential of developing MERS-CoV RBD protein into an effective and safe mucosal candidate vaccine for prevention of respiratory tract infections caused by MERS-CoV.

A: Intranasal vaccination with recombinant receptor-binding domain of MERS-CoV spike protein induces much stronger local mucosal immune responses than subcutaneous immunization: Implication for designing novel mucosal MERS vaccines
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Q: Motivation: Deep sequencing of clinical samples is now an established tool for the detection of infectious pathogens, with direct medical applications. The large amount of data generated produces an opportunity to detect species even at very low levels, provided that computational tools can effectively profile the relevant metagenomic communities. Data interpretation is complicated by the fact that short sequencing reads can match multiple organisms and by the lack of completeness of existing databases, in particular for viral pathogens. Here we present metaMix, a Bayesian mixture model framework for resolving complex metagenomic mixtures. We show that the use of parallel Monte Carlo Markov chains for the exploration of the species space enables the identification of the set of species most likely to contribute to the mixture. Results: We demonstrate the greater accuracy of metaMix compared with relevant methods, particularly for profiling complex communities consisting of several related species. We designed metaMix specifically for the analysis of deep transcriptome sequencing datasets, with a focus on viral pathogen detection; however, the principles are generally applicable to all types of metagenomic mixtures. Availability and implementation: metaMix is implemented as a user friendly R package, freely available on CRAN: http://cran.r-project.org/web/packages/metaMix Contact: sofia.morfopoulou.10@ucl.ac.uk Supplementary information: Supplementary data are available at Bionformatics online.

A: Bayesian mixture analysis for metagenomic community profiling
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Q: Feline coronavirus infection is common among domestic and exotic felid species and usually associated with mild or asymptomatic enteritis; however, feline infectious peritonitis (FIP) is a fatal disease of cats that is caused by systemic infection with a feline infectious peritonitis virus (FIPV), a variant of feline enteric coronavirus (FECV). Currently, there is no specific treatment approved for FIP despite the importance of FIP as the leading infectious cause of death in young cats. During the replication process, coronavirus produces viral polyproteins that are processed into mature proteins by viral proteases, the main protease (3C-like [3CL] protease) and the papain-like protease. Since the cleavages of viral polyproteins are an essential step for virus replication, blockage of viral protease is an attractive target for therapeutic intervention. Previously, we reported the generation of broad-spectrum peptidyl inhibitors against viruses that possess a 3C or 3CL protease. In this study, we further evaluated the antiviral effects of the peptidyl inhibitors against feline coronaviruses, and investigated the interaction between our protease inhibitor and a cathepsin B inhibitor, an entry blocker, against a feline coronavirus in cell culture. Herein we report that our compounds behave as reversible, competitive inhibitors of 3CL protease, potently inhibited the replication of feline coronaviruses (EC 50 in a nanomolar range) and, furthermore, combination of cathepsin B and 3CL protease inhibitors led to a strong synergistic interaction against feline coronaviruses in a cell culture system.

A:
Potent inhibition of feline coronaviruses with peptidyl compounds targeting coronavirus 3C-like protease
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