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      Exploring antimicrobial resistance to beta-lactams, aminoglycosides and fluoroquinolones in E. coli and K. pneumoniae using proteogenomics

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          Abstract

          Antimicrobial resistance is mostly studied by means of phenotypic growth inhibition determinations, in combination with PCR confirmations or further characterization by means of whole genome sequencing (WGS). However, the actual proteins that cause resistance such as enzymes and a lack of porins cannot be detected by these methods. Improvements in liquid chromatography (LC) and mass spectrometry (MS) enabled easier and more comprehensive proteome analysis. In the current study, susceptibility testing, WGS and MS are combined into a multi-omics approach to analyze resistance against frequently used antibiotics within the beta-lactam, aminoglycoside and fluoroquinolone group in E. coli and K. pneumoniae. Our aim was to study which currently known mechanisms of resistance can be detected at the protein level using liquid chromatography–mass spectrometry (LC–MS/MS) and to assess whether these could explain beta-lactam, aminoglycoside, and fluoroquinolone resistance in the studied isolates. Furthermore, we aimed to identify significant protein to resistance correlations which have not yet been described before and to correlate the abundance of different porins in relation to resistance to different classes of antibiotics. Whole genome sequencing, high-resolution LC–MS/MS and antimicrobial susceptibility testing by broth microdilution were performed for 187 clinical E. coli and K. pneumoniae isolates. Resistance genes and proteins were identified using the Comprehensive Antibiotic Resistance Database (CARD). All proteins were annotated using the NCBI RefSeq database and Prokka. Proteins of small spectrum beta-lactamases, extended spectrum beta-lactamases, AmpC beta-lactamases, carbapenemases, and proteins of 16S ribosomal RNA methyltransferases and aminoglycoside acetyltransferases can be detected in E. coli and K. pneumoniae by LC–MS/MS. The detected mechanisms matched with the phenotype in the majority of isolates. Differences in the abundance and the primary structure of other proteins such as porins also correlated with resistance. LC–MS/MS is a different and complementary method which can be used to characterize antimicrobial resistance in detail as not only the primary resistance causing mechanisms are detected, but also secondary enhancing resistance mechanisms.

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          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.
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            The PRIDE database and related tools and resources in 2019: improving support for quantification data

            Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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              Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads

              The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce complete genome assemblies, but the sequencing is more expensive and error-prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate “hybrid” assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler uses a novel semi-global aligner to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long-read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.
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                Author and article information

                Contributors
                d.foudraine@erasmusmc.nl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                14 June 2021
                14 June 2021
                2021
                : 11
                : 12472
                Affiliations
                [1 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Medical Microbiology and Infectious Diseases, , Erasmus University Medical Center Rotterdam, ; Dr. Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
                [2 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Neurology, Neuro-Oncology Laboratory/Clinical and Cancer Proteomics, , Erasmus University Medical Center Rotterdam, ; Rotterdam, The Netherlands
                Article
                91905
                10.1038/s41598-021-91905-w
                8203672
                34127720
                bf05c78c-a62a-424b-b005-e98d56ed5dd4
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 March 2021
                : 2 June 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100013297, Eurostars;
                Award ID: 11873
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                © The Author(s) 2021

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                antimicrobial resistance,proteomics
                Uncategorized
                antimicrobial resistance, proteomics

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