6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Human microbiota drives hospital-associated antimicrobial resistance dissemination in the urban environment and mirrors patient case rates

      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

          Background

          The microbial community composition of urban environments is primarily determined by human activity. The use of metagenomics to explore how microbial communities are shaped in a city provides a novel input that can improve decisions on public health measures, architectural design, and urban resilience. Of note, the sewage system in a city acts as a complex reservoir of bacteria, pharmaceuticals, and antimicrobial resistant (AMR) genes that can be an important source of epidemiological information. Hospital effluents are rich in patient-derived bacteria and can thus readily become a birthplace and hotspot reservoir for antibiotic resistant pathogens which are eventually incorporated into the environment. Yet, the scope to which nosocomial outbreaks impact the urban environment is still poorly understood.

          Results

          In this work, we extensively show that different urban waters from creeks, beaches, sewage spillways and collector pipes enclose discrete microbial communities that are characterized by a differential degree of contamination and admixture with human-derived bacteria. The abundance of human bacteria correlates with the abundance of AMR genes in the environment, with beta-lactamases being the top-contributing class to distinguish low vs. highly-impacted urban environments. Indeed, the abundance of beta-lactamase resistance and carbapenem resistance determinants in the urban environment significantly increased in a 1-year period. This was in line with a pronounced increase of nosocomial carbapenem-resistant infections reported during the same period that was mainly driven by an outbreak-causing, carbapenemase-producing Klebsiella pneumoniae (KPC) ST-11 strain. Genome-resolved metagenomics of urban waters before and after this outbreak, coupled with high-resolution whole-genome sequencing, confirmed the dissemination of the ST-11 strain and a novel KPC megaplasmid from the hospital to the urban environment. City-wide analysis showed that geospatial dissemination of the KPC megaplasmid in the urban environment inversely depended on the sewage system infrastructure.

          Conclusions

          We show how urban metagenomics and outbreak genomic surveillance can be coupled to generate relevant information for infection control, antibiotic stewardship, and pathogen epidemiology. Our results highlight the need to better characterize and understand how human-derived bacteria and antimicrobial resistance disseminate in the urban environment to incorporate this information in the development of effluent treatment infrastructure and public health policies.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40168-022-01407-8.

          Related collections

          Most cited references45

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

          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

            Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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.
                Bookmark

                Author and article information

                Contributors
                giraola@pasteur.edu.uy
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                2 December 2022
                2 December 2022
                2022
                : 10
                : 208
                Affiliations
                [1 ]GRID grid.418532.9, ISNI 0000 0004 0403 6035, Microbial Genomics Laboratory, Institut Pasteur de Montevideo, ; 11400 Montevideo, Uruguay
                [2 ]GRID grid.482688.8, ISNI 0000 0001 2323 2857, Molecular Microbiology Laboratory, Instituto de Investigaciones Biológicas Clemente Estable (IIBCE), ; Montevideo, Uruguay
                [3 ]GRID grid.414794.b, Hospital Maciel, ; Montevideo, Uruguay
                [4 ]GRID grid.5386.8, ISNI 000000041936877X, Department of Physiology and Biophysics, Weill Cornell Medicine, ; New York, NY USA
                [5 ]GRID grid.5386.8, ISNI 000000041936877X, The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, ; New York, NY USA
                [6 ]GRID grid.5386.8, ISNI 000000041936877X, The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, ; New York, NY USA
                [7 ]Servicio de Evaluación de la Calidad y Control Ambiental, Intendencia de Montevideo, Montevideo, Uruguay
                [8 ]GRID grid.11630.35, ISNI 0000000121657640, Instituto de Higiene, Facultad de Medicina, Universidad de la República, ; Montevideo, Uruguay
                [9 ]GRID grid.10306.34, ISNI 0000 0004 0606 5382, Wellcome Sanger Institute, ; Hinxton, UK
                [10 ]GRID grid.412199.6, ISNI 0000 0004 0487 8785, Center for Integrative Biology, , Universidad Mayor, ; Santiago de Chile, Chile
                Article
                1407
                10.1186/s40168-022-01407-8
                9715416
                36457116
                fbe8ac88-ccbd-4c63-a56f-c178f182f4d9
                © The Author(s) 2022

                Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 13 July 2022
                : 21 October 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                antimicrobial resistance,urban metagenomics,nanopore sequencing,carbapenem resistance,nosocomial outbreak,kpc,urban wastewater

                Comments

                Comment on this article