Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection
Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers. Mi...
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description | Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers.
Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis.
4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as "nuisance" biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms.
The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available biochemical test results, of value in the timely detection of outbreak clones and evolutionarily important genetic events. |
doi_str_mv | 10.1371/journal.pone.0084313 |
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Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis.
4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as "nuisance" biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms.
The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available biochemical test results, of value in the timely detection of outbreak clones and evolutionarily important genetic events.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0084313</identifier><identifier>PMID: 24391936</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Analysis of Variance ; Antibiotics ; Antiinfectives and antibacterials ; Antimicrobial agents ; Antimicrobial resistance ; Biochemical tests ; Biochemistry ; Biology ; Biomarkers ; Clinical isolates ; Clinical microbiology ; Cloning ; Cluster Analysis ; Communicable Diseases, Emerging - diagnosis ; Disease control ; Disease Outbreaks ; Drug resistance ; Drug Resistance, Microbial - genetics ; E coli ; Enterobacteriaceae ; Epidemics ; Epidemiology ; Escherichia coli ; Genetic aspects ; Health surveillance ; Hospitals ; Humans ; Identification ; Klebsiella Infections - diagnosis ; Klebsiella Infections - epidemiology ; Klebsiella pneumoniae ; Klebsiella pneumoniae - genetics ; Laboratories ; Medical schools ; Medicine ; Microbial drug resistance ; Microbiology ; Microorganisms ; Outbreaks ; Phenotype ; Pneumonia ; Public health ; Reproducibility ; Stability analysis ; Staphylococcus infections ; Statistical models ; Studies ; Subpopulations ; Surveillance ; Trends ; Variance analysis ; Womens health</subject><ispartof>PloS one, 2013-12, Vol.8 (12), p.e84313-e84313</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Galar 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. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Galar et al 2013 Galar et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c641t-d43d88a2a5a2c8da811f1dec3dce0cbd44ffefbaabe547e8530c3a330eb380583</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877295/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877295/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53770,53772,79347,79348</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24391936$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Nishiura, Hiroshi</contributor><creatorcontrib>Galar, Alicia</creatorcontrib><creatorcontrib>Kulldorff, Martin</creatorcontrib><creatorcontrib>Rudnick, Wallis</creatorcontrib><creatorcontrib>O'Brien, Thomas F</creatorcontrib><creatorcontrib>Stelling, John</creatorcontrib><title>Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers.
Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis.
4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as "nuisance" biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms.
The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available biochemical test results, of value in the timely detection of outbreak clones and evolutionarily important genetic events.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Analysis of Variance</subject><subject>Antibiotics</subject><subject>Antiinfectives and antibacterials</subject><subject>Antimicrobial agents</subject><subject>Antimicrobial resistance</subject><subject>Biochemical tests</subject><subject>Biochemistry</subject><subject>Biology</subject><subject>Biomarkers</subject><subject>Clinical isolates</subject><subject>Clinical microbiology</subject><subject>Cloning</subject><subject>Cluster Analysis</subject><subject>Communicable Diseases, Emerging - diagnosis</subject><subject>Disease control</subject><subject>Disease Outbreaks</subject><subject>Drug resistance</subject><subject>Drug Resistance, Microbial - genetics</subject><subject>E coli</subject><subject>Enterobacteriaceae</subject><subject>Epidemics</subject><subject>Epidemiology</subject><subject>Escherichia coli</subject><subject>Genetic aspects</subject><subject>Health surveillance</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Identification</subject><subject>Klebsiella Infections - diagnosis</subject><subject>Klebsiella Infections - epidemiology</subject><subject>Klebsiella pneumoniae</subject><subject>Klebsiella pneumoniae - genetics</subject><subject>Laboratories</subject><subject>Medical schools</subject><subject>Medicine</subject><subject>Microbial drug resistance</subject><subject>Microbiology</subject><subject>Microorganisms</subject><subject>Outbreaks</subject><subject>Phenotype</subject><subject>Pneumonia</subject><subject>Public health</subject><subject>Reproducibility</subject><subject>Stability analysis</subject><subject>Staphylococcus infections</subject><subject>Statistical models</subject><subject>Studies</subject><subject>Subpopulations</subject><subject>Surveillance</subject><subject>Trends</subject><subject>Variance analysis</subject><subject>Womens health</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk01v1DAQhiMEoqXwDxBEQkJw2MWOncS5IJWKj5UqVeLriDWxJ7tesnFqOxX99zjdtNqgHlAOiTzPvJ6ZvJMkzylZUlbSd1s7uA7aZW87XBIiOKPsQXJMK5YtioywhwffR8kT77eE5EwUxePkKOOsisHiOPn1wVi1wZ1R0Kb9Bjsbrnv0abCpNl45szMdBEwj4GxtIuSHurf90EIwtvMpdDo1u97ZK0ztEGqH8DvVGFCN8afJowZaj8-m90ny49PH72dfFucXn1dnp-cLVXAaFpozLQRkkEOmhAZBaUM1KqYVElVrzpsGmxqgxpyXKHJGFAPGCNZMkFywk-TlXrdvrZfTaLykvGSM04qUkVjtCW1hK_vYGLhracHImwPr1hJcMKpFybM6p7piiFhzomI5jSBU5KpsalFmRdR6P9021DuMNXbBQTsTnUc6s5FreyWZKMusyqPAm0nA2csBfZC7OGxsW-jQDmPdsWReFSSL6Kt_0Pu7m6g1xAZM19h4rxpF5SkvyyorCR_rXt5DxUePBog-akw8nyW8nSVEJuCfsIbBe7n69vX_2Yufc_b1AbtBaMPG23a4sdQc5Hswus97h83dkCmR4xrcTkOOayCnNYhpLw5_0F3Sre_ZX4aHBW4</recordid><startdate>20131231</startdate><enddate>20131231</enddate><creator>Galar, Alicia</creator><creator>Kulldorff, Martin</creator><creator>Rudnick, Wallis</creator><creator>O'Brien, Thomas F</creator><creator>Stelling, John</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></search><sort><creationdate>20131231</creationdate><title>Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection</title><author>Galar, Alicia ; Kulldorff, Martin ; Rudnick, Wallis ; O'Brien, Thomas F ; Stelling, John</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c641t-d43d88a2a5a2c8da811f1dec3dce0cbd44ffefbaabe547e8530c3a330eb380583</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Analysis of Variance</topic><topic>Antibiotics</topic><topic>Antiinfectives and antibacterials</topic><topic>Antimicrobial agents</topic><topic>Antimicrobial resistance</topic><topic>Biochemical tests</topic><topic>Biochemistry</topic><topic>Biology</topic><topic>Biomarkers</topic><topic>Clinical isolates</topic><topic>Clinical microbiology</topic><topic>Cloning</topic><topic>Cluster Analysis</topic><topic>Communicable Diseases, Emerging - diagnosis</topic><topic>Disease control</topic><topic>Disease Outbreaks</topic><topic>Drug resistance</topic><topic>Drug Resistance, Microbial - genetics</topic><topic>E coli</topic><topic>Enterobacteriaceae</topic><topic>Epidemics</topic><topic>Epidemiology</topic><topic>Escherichia coli</topic><topic>Genetic aspects</topic><topic>Health surveillance</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Identification</topic><topic>Klebsiella Infections - diagnosis</topic><topic>Klebsiella Infections - epidemiology</topic><topic>Klebsiella pneumoniae</topic><topic>Klebsiella pneumoniae - genetics</topic><topic>Laboratories</topic><topic>Medical schools</topic><topic>Medicine</topic><topic>Microbial drug resistance</topic><topic>Microbiology</topic><topic>Microorganisms</topic><topic>Outbreaks</topic><topic>Phenotype</topic><topic>Pneumonia</topic><topic>Public health</topic><topic>Reproducibility</topic><topic>Stability analysis</topic><topic>Staphylococcus infections</topic><topic>Statistical models</topic><topic>Studies</topic><topic>Subpopulations</topic><topic>Surveillance</topic><topic>Trends</topic><topic>Variance analysis</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Galar, Alicia</creatorcontrib><creatorcontrib>Kulldorff, Martin</creatorcontrib><creatorcontrib>Rudnick, Wallis</creatorcontrib><creatorcontrib>O'Brien, Thomas F</creatorcontrib><creatorcontrib>Stelling, John</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers.
Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis.
4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as "nuisance" biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms.
The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available biochemical test results, of value in the timely detection of outbreak clones and evolutionarily important genetic events.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24391936</pmid><doi>10.1371/journal.pone.0084313</doi><tpages>e84313</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Analysis Analysis of Variance Antibiotics Antiinfectives and antibacterials Antimicrobial agents Antimicrobial resistance Biochemical tests Biochemistry Biology Biomarkers Clinical isolates Clinical microbiology Cloning Cluster Analysis Communicable Diseases, Emerging - diagnosis Disease control Disease Outbreaks Drug resistance Drug Resistance, Microbial - genetics E coli Enterobacteriaceae Epidemics Epidemiology Escherichia coli Genetic aspects Health surveillance Hospitals Humans Identification Klebsiella Infections - diagnosis Klebsiella Infections - epidemiology Klebsiella pneumoniae Klebsiella pneumoniae - genetics Laboratories Medical schools Medicine Microbial drug resistance Microbiology Microorganisms Outbreaks Phenotype Pneumonia Public health Reproducibility Stability analysis Staphylococcus infections Statistical models Studies Subpopulations Surveillance Trends Variance analysis Womens health |
title | Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection |
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