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.

Ex Input:
Ubiquitination, a post-translational modification, mediates diverse cellular functions including endocytic transport of molecules. Kaposi's sarcoma-associated herpesvirus (KSHV), an enveloped herpesvirus, enters endothelial cells primarily through clathrin-mediated endocytosis. Whether ubiquitination and proteasome activity regulates KSHV entry and endocytosis remains unknown. We showed that inhibition of proteasome activity reduced KSHV entry into endothelial cells and intracellular trafficking to nuclei, thus preventing KSHV infection of the cells. Three-dimensional (3-D) analyses revealed accumulation of KSHV particles in a cytoplasmic compartment identified as EEA1+ endosomal vesicles upon proteasome inhibition. KSHV particles are colocalized with ubiquitin-binding proteins epsin and eps15. Furthermore, ubiquitination mediates internalization of both KSHV and one of its receptors integrin b1. KSHV particles are colocalized with activated forms of the E3 ligase c-Cbl. Knock-down of c-Cbl or inhibition of its phosphorylation reduced viral entry and intracellular trafficking, resulting in decreased KSHV infectivity. These results demonstrate that ubiquitination mediates internalization of both KSHV and one of its cognate receptors integrin b1, and identify c-Cbl as a potential E3 ligase that facilitates this process.

Ex Output:
Associated Herpesvirus in Endothelial Cells


Ex Input:
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.

Ex Output:
Bayesian mixture analysis for metagenomic community profiling


Ex Input:
The surveillance and prevention of pathogenic microbiological contamination are the most important tasks of biosafety management in the lab. There is an urgent need to establish an effective and unbiased method to evaluate and monitor such contamination. This study aims to investigate the utility of next generation sequencing (NGS) method to detect possible contamination in the microbiology laboratory. Environmental samples were taken at multiple sites at the lab including the inner site of centrifuge rotor, the bench used for molecular biological tests, the benches of biosafety cabinets used for viral culture, clinical sample pre-treatment and nucleic acids extraction, by scrubbing the sites using sterile flocked swabs. The extracted total nucleic acids were used to construct the libraries for deep sequencing according to the protocol of Ion Torrent platform. At least 1G raw data was obtained for each sample. The reads of viruses and bacteria accounted for 0.01 ± 0.02%, and 77.76 ± 12.53% of total reads respectively. The viral sequences were likely to be derived from gene amplification products, the nucleic acids contaminated in fetal bovine serum. Reads from environmental microorganisms were also identified. Our results suggested that NGS method was capable of monitoring the nucleic acids contaminations from different sources in the lab, demonstrating its promising utility in monitoring and assessing the risk of potential laboratory contamination. The risk of contamination from reagents, remnant DNA and environment should be considered in data analysis and results interpretation.

Ex Output:

Application of next generation sequencing technology on contamination monitoring in microbiology laboratory