4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Comparative Genomic Analyses and CRISPR-Cas Characterization of Cutibacterium acnes Provide Insights Into Genetic Diversity and Typing Applications

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Cutibacterium acnes is an important member of the human skin microbiome and plays a critical role in skin health and disease. C. acnes encompasses different phylotypes that have been found to be associated with different skin phenotypes, suggesting a genetic basis for their impact on skin health. Here, we present a comprehensive comparative analysis of 255 C. acnes genomes to provide insights into the species genetic diversity and identify unique features that define various phylotypes. Results revealed a relatively small and open pan genome (6,240 genes) with a large core genome (1,194 genes), and three distinct phylogenetic clades, with multiple robust sub-clades. Furthermore, we identified several unique gene families driving differences between distinct C. acnes clades. Carbohydrate transporters, stress response mechanisms and potential virulence factors, potentially involved in competitive growth and host colonization, were detected in type I strains, which are presumably responsible for acne. Diverse type I-E CRISPR-Cas systems and prophage sequences were detected in select clades, providing insights into strain divergence and adaptive differentiation. Collectively, these results enable to elucidate the fundamental differences among C. acnes phylotypes, characterize genetic elements that potentially contribute to type I-associated dominance and disease, and other key factors that drive the differentiation among clades and sub-clades. These results enable the use of comparative genomics analyses as a robust method to differentiate among the C. acnes genotypes present in the skin microbiome, opening new avenues for the development of biotherapeutics to manipulate the skin microbiota.

          Related collections

          Most cited references90

          • Record: found
          • Abstract: found
          • Article: not found

          Prokka: rapid prokaryotic genome annotation.

          T Seemann (2014)
          The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            BLAST+: architecture and applications

            Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Prodigal: prokaryotic gene recognition and translation initiation site identification

              Background The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals. Results With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives. Conclusion We built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                03 November 2021
                2021
                : 12
                : 758749
                Affiliations
                [1] 1Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University , Raleigh, NC, United States
                [2] 2BASF Corporation , Tarrytown, NY, United States
                Author notes

                Edited by: Guangcai Duan, Zhengzhou University, China

                Reviewed by: Pedro H. Oliveira, Commissariat à l’Energie Atomique et aux Energies Alternatives (CEA), France; Yingjun Li, Huazhong Agricultural University, China

                *Correspondence: Claudio Hidalgo-Cantabrana, chidalg@ 123456ncsu.edu
                Rodolphe Barrangou, rbarran@ 123456ncsu.edu

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.758749
                8595920
                34803983
                cc9a7eed-91f0-442e-8909-6b80afc2ef7b
                Copyright © 2021 Cobian, Garlet, Hidalgo-Cantabrana and Barrangou.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 August 2021
                : 15 October 2021
                Page count
                Figures: 5, Tables: 0, Equations: 0, References: 90, Pages: 15, Words: 7854
                Funding
                Funded by: North Carolina State University, doi 10.13039/100007703;
                Funded by: BASF Corporation, doi 10.13039/100007487;
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                crispr,genomics,cas,genotyping,phylogeny
                Microbiology & Virology
                crispr, genomics, cas, genotyping, phylogeny

                Comments

                Comment on this article