Kockmartinsen8209

Interestingly, most type I-E CRISPR-Cas systems identified carried spacers matching the backbone regions of IncF plasmids. CONCLUSIONS Our results suggest that the absence of type I-E CRISPR-Cas systems in K. pneumoniae CC258 is strongly associated with the dissemination of IncF epidemic plasmids, contributing to the global success of the international high-risk linkage CC258-IncF. Our findings provide new information regarding the dissemination and evolution of the high-risk linkage of K. pneumoniae CC258-IncF and pave the way for new strategies to address the problem of antibiotic resistance. © The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email journals.permissions@oup.com.MOTIVATION Hi-C is currently the method of choice to investigate the global 3D organisation of the genome. A major limitation of Hi-C is the sequencing depth required to robustly detect loops in the data. A popular approach used to mitigate this issue, even in single-cell Hi-C data, is genome-wide averaging (piling-up) of peaks, or other features, annotated in high-resolution datasets, to measure their prominence in less deeply sequenced data. However current tools do not provide a computationally efficient and versatile implementation of this approach. RESULTS Here we describe coolpup.py - a versatile tool to perform pile-up analysis on Hi-C data. We demonstrate its utility by replicating previously published findings regarding the role of cohesin and CTCF in 3D genome organization, as well as discovering novel details of Polycomb-driven interactions. We also present a novel variation of the pile-up approach that can aid the in statistical analysis of looping interactions. We anticipate that coolpup.py will aid in Hi-C data analysis by allowing easy to use, versatile and efficient generation of pileups. Selleckchem MF-438 AVAILABILITY Coolpup.py is cross-platform, open-source and free (MIT licensed) software. Source code is available from https//github.com/Phlya/coolpuppy and it can be installed from the Python Packaging Index. © The Author(s) 2020. Published by Oxford University Press.Moonlighting proteins provide more options for cells to execute multiple functions without increasing the genome and transcriptome complexity. Although there have long been calls for computational methods for the prediction of moonlighting proteins, no method has been designed for determining moonlighting long noncoding ribonucleicacidz (RNAs) (mlncRNAs). Previously, we developed an algorithm MoonFinder for the identification of mlncRNAs at the genome level based on the functional annotation and interactome data of lncRNAs and proteins. Here, we update MoonFinder to MoonFinder v2.0 by providing an extensive framework for the detection of protein modules and the establishment of RNA-module associations in human. A novel measure, moonlighting coefficient, was also proposed to assess the confidence of an ncRNA acting in a moonlighting manner. Moreover, we explored the expression characteristics of mlncRNAs in sepsis, in which we found that mlncRNAs tend to be upregulated and differentially expressed. Interestingly, the mlncRNAs are mutually exclusive in terms of coexpression when compared to the other lncRNAs. Overall, MoonFinder v2.0 is dedicated to the prediction of human mlncRNAs and thus bears great promise to serve as a valuable R package for worldwide research communities (https//cran.r-project.org/web/packages/MoonFinder/index.html). Also, our analyses provide the first attempt to characterize mlncRNA expression and coexpression properties in adult sepsis patients, which will facilitate the understanding of the interaction and expression patterns of mlncRNAs. © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email journals.permissions@oup.com.OBJECTIVES To review the utilization of prostate-specific antigen (PSA) testing in Winnipeg, a major Canadian city, and to compare PSA testing rates between Winnipeg and Calgary, another major Canadian city of comparable size. METHODS PSA testing results were reviewed by year and age group. We focused our studies in years 2011 and 2016, for which census demographic data are available. RESULTS In Winnipeg, the PSA testing rates (patients with one or two PSA tests divided by the male population) showed a declining trend over years from 2008 to 2017. For almost all age groups, PSA testing rates in 2016 decreased in comparison to those in 2011. For age older than 40 years, the relative percentage decreases were 14% to 20%.In 2011, Winnipeg PSA testing rates were consistently higher than those in Calgary for all age groups. For age older than 40 years, the relative percentage differences were 36% to 50%.In addition, 41% and 40% of patients in Winnipeg who underwent PSA testing were younger than 50 years or older than 69 years in 2011 and 2016, respectively. CONCLUSIONS PSA testing utilization may be falling short of optimal rates. There is a need to reinforce the optimal use of clinical recommendations. © American Society for Clinical Pathology, 2020. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.MOTIVATION To facilitate accurate estimation of statistical significance of sequence similarity in profile-profile searches, queries should ideally correspond to protein domains. For multidomain proteins, using domains as queries depends on delineation of domain borders, which may be unknown. Thus, proteins are commonly used as queries that complicates establishing homology for similarities close to cut-off levels of statistical significance. RESULTS In this report we describe an iterative approach, called LAMPA, LArge Multidomain Protein Annotator, that resolves the above conundrum by gradual expansion of hit coverage of multidomain proteins through re-evaluating statistical significance of hit similarity using ever smaller queries defined at each iteration. LAMPA employs TMHMM and HHsearch for recognition of transmembrane regions and homology, respectively. We used Pfam database for annotating 2985 multidomain proteins (polyproteins) composed of more than 1000 amino acid residues, which dominate proteomes of RNA viruses.