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Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017
Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia...
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Published in: | PloS one 2021-01, Vol.16 (1), p.e0244413-e0244413 |
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description | Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics-ampicillin, cefotaxime, ciprofloxacin and gentamicin-for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany. |
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This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics-ampicillin, cefotaxime, ciprofloxacin and gentamicin-for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0244413</identifier><identifier>PMID: 33471826</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Animal populations ; Animals ; Anti-Bacterial Agents - pharmacology ; Antibiotic resistance ; Antibiotics ; Antimicrobial resistance ; Biology and Life Sciences ; Biosafety ; Cefotaxime - pharmacology ; Ciprofloxacin - pharmacology ; Cluster Analysis ; Computer programs ; Consumer protection ; Development and progression ; Drug resistance ; Drug resistance in microorganisms ; Drug Resistance, Bacterial - drug effects ; Drug therapy ; E coli ; Editing ; Epidemiology ; Escherichia coli ; Escherichia coli - drug effects ; Escherichia coli - isolation & purification ; Escherichia coli infections ; Escherichia coli Infections - microbiology ; Escherichia coli Infections - pathology ; Food ; Germany ; Health care ; Health risks ; Human populations ; Humans ; Infections ; Infectious diseases ; Laboratories ; Medicine and Health Sciences ; Methodology ; Microbial Sensitivity Tests ; Microbiological research ; Monitoring ; People and places ; Populations ; Poultry - microbiology ; Public health ; Reviews ; Risk assessment ; Safety ; Software ; Surveillance ; Swine - microbiology ; Telemedicine ; Testing ; Veterinary medicine ; Visualization ; Zoonoses</subject><ispartof>PloS one, 2021-01, Vol.16 (1), p.e0244413-e0244413</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Suwono et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics-ampicillin, cefotaxime, ciprofloxacin and gentamicin-for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. 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isolation & purification</subject><subject>Escherichia coli infections</subject><subject>Escherichia coli Infections - microbiology</subject><subject>Escherichia coli Infections - pathology</subject><subject>Food</subject><subject>Germany</subject><subject>Health care</subject><subject>Health risks</subject><subject>Human populations</subject><subject>Humans</subject><subject>Infections</subject><subject>Infectious diseases</subject><subject>Laboratories</subject><subject>Medicine and Health Sciences</subject><subject>Methodology</subject><subject>Microbial Sensitivity Tests</subject><subject>Microbiological research</subject><subject>Monitoring</subject><subject>People and places</subject><subject>Populations</subject><subject>Poultry - microbiology</subject><subject>Public health</subject><subject>Reviews</subject><subject>Risk assessment</subject><subject>Safety</subject><subject>Software</subject><subject>Surveillance</subject><subject>Swine - microbiology</subject><subject>Telemedicine</subject><subject>Testing</subject><subject>Veterinary medicine</subject><subject>Visualization</subject><subject>Zoonoses</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNk12P1CAUhhujcdfRf2C0iYnRixmhMFBuTDaTdZ1kk038uiWUHqZMaJmF1rh3_nSZne46NXthGgqB5305HDhZ9hKjBSYcf9j6IXTKLXa-gwUqKKWYPMpOsSDFnBWIPD4an2TPYtwitCQlY0-zE0Iox2XBTrPfKzfEHkKuktdNtDH3Jg-QBr3qNOTat5XtVG99F3Pb5edRNxCsbqxKa87mJvg2r60xEKDr82ZoVZfM6tRsq1y-87vB_dVfQEjATV4gTOfpx59nT4xyEV6M_Sz7_un82-rz_PLqYr06u5xrJop-LhjBxFQ1WlIMZSG4AIZIrUteKVItK44pAibIsiLIlLwwukBUFHSpGcaUGzLLXh98d85HOSYvyoJyQWkpEErE-kDUXm3lLqTww430ysrbCR82UoXeagdSaabKqjJaJHNFsSi1qisuWFULDKCT18dxt6FqodYpNUG5iel0pbON3PifkpeYp1iSwbvRIPjrAWIvWxs1OKc68MMhbo5KSvfom3_Qh083UhuVDmA749O-em8qzxgVmJMy5XiWLR6g0ldDa3V6acam-Yng_USQmB5-9Rs1xCjXX7_8P3v1Y8q-PWIbUK5vonfD7UOagvQA6uBjDGDuk4yR3BfKXTbkvlDkWChJ9ur4gu5Fd5VB_gCeKw3A</recordid><startdate>20210120</startdate><enddate>20210120</enddate><creator>Suwono, Beneditta</creator><creator>Eckmanns, Tim</creator><creator>Kaspar, Heike</creator><creator>Merle, Roswitha</creator><creator>Zacher, Benedikt</creator><creator>Kollas, Chris</creator><creator>Weiser, Armin A</creator><creator>Noll, Ines</creator><creator>Feig, Marcel</creator><creator>Tenhagen, Bernd-Alois</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-8688-2926</orcidid><orcidid>https://orcid.org/0000-0001-5021-6510</orcidid></search><sort><creationdate>20210120</creationdate><title>Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017</title><author>Suwono, Beneditta ; Eckmanns, Tim ; Kaspar, Heike ; Merle, Roswitha ; Zacher, Benedikt ; Kollas, Chris ; Weiser, Armin A ; Noll, Ines ; Feig, Marcel ; Tenhagen, Bernd-Alois</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-96313fbd0541e82979e603dc87ba3b5b7140e6935b30f872fc2049245c61147f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Animal populations</topic><topic>Animals</topic><topic>Anti-Bacterial Agents - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suwono, Beneditta</au><au>Eckmanns, Tim</au><au>Kaspar, Heike</au><au>Merle, Roswitha</au><au>Zacher, Benedikt</au><au>Kollas, Chris</au><au>Weiser, Armin A</au><au>Noll, Ines</au><au>Feig, Marcel</au><au>Tenhagen, Bernd-Alois</au><au>Karunasagar, Iddya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-01-20</date><risdate>2021</risdate><volume>16</volume><issue>1</issue><spage>e0244413</spage><epage>e0244413</epage><pages>e0244413-e0244413</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics-ampicillin, cefotaxime, ciprofloxacin and gentamicin-for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33471826</pmid><doi>10.1371/journal.pone.0244413</doi><tpages>e0244413</tpages><orcidid>https://orcid.org/0000-0002-8688-2926</orcidid><orcidid>https://orcid.org/0000-0001-5021-6510</orcidid><oa>free_for_read</oa></addata></record> |
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identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2021-01, Vol.16 (1), p.e0244413-e0244413 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_2479448900 |
source | Publicly Available Content Database; PubMed Central |
subjects | Animal populations Animals Anti-Bacterial Agents - pharmacology Antibiotic resistance Antibiotics Antimicrobial resistance Biology and Life Sciences Biosafety Cefotaxime - pharmacology Ciprofloxacin - pharmacology Cluster Analysis Computer programs Consumer protection Development and progression Drug resistance Drug resistance in microorganisms Drug Resistance, Bacterial - drug effects Drug therapy E coli Editing Epidemiology Escherichia coli Escherichia coli - drug effects Escherichia coli - isolation & purification Escherichia coli infections Escherichia coli Infections - microbiology Escherichia coli Infections - pathology Food Germany Health care Health risks Human populations Humans Infections Infectious diseases Laboratories Medicine and Health Sciences Methodology Microbial Sensitivity Tests Microbiological research Monitoring People and places Populations Poultry - microbiology Public health Reviews Risk assessment Safety Software Surveillance Swine - microbiology Telemedicine Testing Veterinary medicine Visualization Zoonoses |
title | Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017 |
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