Global model fitting to compare survival curves for faecal indicator bacteria and ruminant‐associated genetic markers
Aims To compare decay profiles of ruminant‐ and cattle‐associated molecular markers for faecal contamination and Escherichia coli, facilitating their correct application in water quality studies. Methods and Results We generated decay profiles for cultivable E. coli, a general Bacteroidales genetic...
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| Veröffentlicht in: | Journal of applied microbiology 2017-06, Vol.122 (6), p.1704-1713 |
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| creator | Brooks, L.E. Field, K.G. |
| description | Aims
To compare decay profiles of ruminant‐ and cattle‐associated molecular markers for faecal contamination and Escherichia coli, facilitating their correct application in water quality studies.
Methods and Results
We generated decay profiles for cultivable E. coli, a general Bacteroidales genetic marker (GenBac3), ruminant markers (CF128, Rum2Bac) and cattle markers (CowM2, CowM3) using faeces‐seeded mesocosms, and selected best fitting models for each decay profile. Global model fitting tested for differences between decay profiles. After normalizing for initial concentration, decay curves differed significantly between E. coli and all genetic markers except CowM3. Decay curves for CF128 differed from GenBac3 and Rum2Bac, but Rum2Bac and GenBac3 decay profiles did not differ. Despite similar survival profiles for some markers, highly varied initial concentrations affected time to nondetection.
Conclusions
Decay curves and time until nondetection differed among markers from the same host. However, the Rum2Bac and GenBac3 markers had similar decay profiles and could potentially be investigated further for source allocation using the ratio method.
Significance and Impact of the Study
As the use of genetic markers for microbial source tracking becomes increasingly common, caution is necessary. Both the shape of decay curves and time to nondetect may differ depending on the marker selected, resulting in possible misinterpretation of results and precluding application of a ‘ratio method’ of source allocation. |
| doi_str_mv | 10.1111/jam.13454 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1881449164</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2020905665</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3864-a7b5f1a8be1081cd8e21adcaf1f7a2b09b420bd1d7810772a0f37db7d3e68ae93</originalsourceid><addsrcrecordid>eNqF0cFOFTEUBuDGaATBBS9gmrDBxYW205l2loQgajBuZD05bU9JLzPTa9uBsOMRfEafxMpFFybEbnpy8uWkpz8hB5wd83pO1jAd80a28gXZ5U3XrkSnxMvHWq5apsQOeZPzmjHesLZ7TXaErloouUvuLsZoYKRTdDhSH0oJ8zUtkdo4bSAhzUu6DbdV2Fpgpj4m6gFt7YTZBQulNgzYgikAhdnRtExhhrn8fPgBOUcboKCj1zhjCZZOkG4w5X3yysOY8e3TvUeuPpx_O_u4uvx68ens9HJlG10fD8q0noM2yJnm1mkUHJwFz70CYVhvpGDGcac0Z0oJYL5RzijXYKcB-2aPHG3nblL8vmAuwxSyxXGEGeOSB8EE6-undO1_KdeaS9nzTlZ6-A9dxyXNdZGq-l60kjFR1futsinmnNAPmxTq_vcDZ8Pv4IYa3PAYXLXvniYuZkL3V_5JqoKTLbgLI94_P2n4fPplO_IX1Q-kPQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1899254002</pqid></control><display><type>article</type><title>Global model fitting to compare survival curves for faecal indicator bacteria and ruminant‐associated genetic markers</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><source>Oxford University Press Journals All Titles (1996-Current)</source><creator>Brooks, L.E. ; Field, K.G.</creator><creatorcontrib>Brooks, L.E. ; Field, K.G.</creatorcontrib><description>Aims
To compare decay profiles of ruminant‐ and cattle‐associated molecular markers for faecal contamination and Escherichia coli, facilitating their correct application in water quality studies.
Methods and Results
We generated decay profiles for cultivable E. coli, a general Bacteroidales genetic marker (GenBac3), ruminant markers (CF128, Rum2Bac) and cattle markers (CowM2, CowM3) using faeces‐seeded mesocosms, and selected best fitting models for each decay profile. Global model fitting tested for differences between decay profiles. After normalizing for initial concentration, decay curves differed significantly between E. coli and all genetic markers except CowM3. Decay curves for CF128 differed from GenBac3 and Rum2Bac, but Rum2Bac and GenBac3 decay profiles did not differ. Despite similar survival profiles for some markers, highly varied initial concentrations affected time to nondetection.
Conclusions
Decay curves and time until nondetection differed among markers from the same host. However, the Rum2Bac and GenBac3 markers had similar decay profiles and could potentially be investigated further for source allocation using the ratio method.
Significance and Impact of the Study
As the use of genetic markers for microbial source tracking becomes increasingly common, caution is necessary. Both the shape of decay curves and time to nondetect may differ depending on the marker selected, resulting in possible misinterpretation of results and precluding application of a ‘ratio method’ of source allocation.</description><identifier>ISSN: 1364-5072</identifier><identifier>EISSN: 1365-2672</identifier><identifier>DOI: 10.1111/jam.13454</identifier><identifier>PMID: 28345274</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Animals ; Bacteria ; Bacteria - genetics ; Bacteroidales ; Bacteroidetes - genetics ; Cattle ; Contamination ; Curve fitting ; Decay ; E coli ; Environmental Monitoring - methods ; Escherichia coli ; Escherichia coli - genetics ; faecal indicator bacteria ; Fecal coliforms ; Feces ; Feces - microbiology ; Fresh Water - chemistry ; Fresh Water - microbiology ; Genetic Markers ; indicator species ; Markers ; Mesocosms ; microbial source tracking ; Microbiology ; Microorganisms ; model fitting ; Models, Theoretical ; Normalizing ; Polymerase Chain Reaction - methods ; Quality Control ; Ruminants ; ruminant‐associated genetic markers ; Survival ; Water Microbiology ; Water Quality</subject><ispartof>Journal of applied microbiology, 2017-06, Vol.122 (6), p.1704-1713</ispartof><rights>2017 The Society for Applied Microbiology</rights><rights>2017 The Society for Applied Microbiology.</rights><rights>Copyright © 2017 The Society for Applied Microbiology</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3864-a7b5f1a8be1081cd8e21adcaf1f7a2b09b420bd1d7810772a0f37db7d3e68ae93</citedby><cites>FETCH-LOGICAL-c3864-a7b5f1a8be1081cd8e21adcaf1f7a2b09b420bd1d7810772a0f37db7d3e68ae93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fjam.13454$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fjam.13454$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28345274$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Brooks, L.E.</creatorcontrib><creatorcontrib>Field, K.G.</creatorcontrib><title>Global model fitting to compare survival curves for faecal indicator bacteria and ruminant‐associated genetic markers</title><title>Journal of applied microbiology</title><addtitle>J Appl Microbiol</addtitle><description>Aims
To compare decay profiles of ruminant‐ and cattle‐associated molecular markers for faecal contamination and Escherichia coli, facilitating their correct application in water quality studies.
Methods and Results
We generated decay profiles for cultivable E. coli, a general Bacteroidales genetic marker (GenBac3), ruminant markers (CF128, Rum2Bac) and cattle markers (CowM2, CowM3) using faeces‐seeded mesocosms, and selected best fitting models for each decay profile. Global model fitting tested for differences between decay profiles. After normalizing for initial concentration, decay curves differed significantly between E. coli and all genetic markers except CowM3. Decay curves for CF128 differed from GenBac3 and Rum2Bac, but Rum2Bac and GenBac3 decay profiles did not differ. Despite similar survival profiles for some markers, highly varied initial concentrations affected time to nondetection.
Conclusions
Decay curves and time until nondetection differed among markers from the same host. However, the Rum2Bac and GenBac3 markers had similar decay profiles and could potentially be investigated further for source allocation using the ratio method.
Significance and Impact of the Study
As the use of genetic markers for microbial source tracking becomes increasingly common, caution is necessary. Both the shape of decay curves and time to nondetect may differ depending on the marker selected, resulting in possible misinterpretation of results and precluding application of a ‘ratio method’ of source allocation.</description><subject>Animals</subject><subject>Bacteria</subject><subject>Bacteria - genetics</subject><subject>Bacteroidales</subject><subject>Bacteroidetes - genetics</subject><subject>Cattle</subject><subject>Contamination</subject><subject>Curve fitting</subject><subject>Decay</subject><subject>E coli</subject><subject>Environmental Monitoring - methods</subject><subject>Escherichia coli</subject><subject>Escherichia coli - genetics</subject><subject>faecal indicator bacteria</subject><subject>Fecal coliforms</subject><subject>Feces</subject><subject>Feces - microbiology</subject><subject>Fresh Water - chemistry</subject><subject>Fresh Water - microbiology</subject><subject>Genetic Markers</subject><subject>indicator species</subject><subject>Markers</subject><subject>Mesocosms</subject><subject>microbial source tracking</subject><subject>Microbiology</subject><subject>Microorganisms</subject><subject>model fitting</subject><subject>Models, Theoretical</subject><subject>Normalizing</subject><subject>Polymerase Chain Reaction - methods</subject><subject>Quality Control</subject><subject>Ruminants</subject><subject>ruminant‐associated genetic markers</subject><subject>Survival</subject><subject>Water Microbiology</subject><subject>Water Quality</subject><issn>1364-5072</issn><issn>1365-2672</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqF0cFOFTEUBuDGaATBBS9gmrDBxYW205l2loQgajBuZD05bU9JLzPTa9uBsOMRfEafxMpFFybEbnpy8uWkpz8hB5wd83pO1jAd80a28gXZ5U3XrkSnxMvHWq5apsQOeZPzmjHesLZ7TXaErloouUvuLsZoYKRTdDhSH0oJ8zUtkdo4bSAhzUu6DbdV2Fpgpj4m6gFt7YTZBQulNgzYgikAhdnRtExhhrn8fPgBOUcboKCj1zhjCZZOkG4w5X3yysOY8e3TvUeuPpx_O_u4uvx68ens9HJlG10fD8q0noM2yJnm1mkUHJwFz70CYVhvpGDGcac0Z0oJYL5RzijXYKcB-2aPHG3nblL8vmAuwxSyxXGEGeOSB8EE6-undO1_KdeaS9nzTlZ6-A9dxyXNdZGq-l60kjFR1futsinmnNAPmxTq_vcDZ8Pv4IYa3PAYXLXvniYuZkL3V_5JqoKTLbgLI94_P2n4fPplO_IX1Q-kPQ</recordid><startdate>201706</startdate><enddate>201706</enddate><creator>Brooks, L.E.</creator><creator>Field, K.G.</creator><general>Oxford University Press</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>7QL</scope><scope>7QO</scope><scope>7T7</scope><scope>7TM</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>201706</creationdate><title>Global model fitting to compare survival curves for faecal indicator bacteria and ruminant‐associated genetic markers</title><author>Brooks, L.E. ; Field, K.G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3864-a7b5f1a8be1081cd8e21adcaf1f7a2b09b420bd1d7810772a0f37db7d3e68ae93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Animals</topic><topic>Bacteria</topic><topic>Bacteria - genetics</topic><topic>Bacteroidales</topic><topic>Bacteroidetes - genetics</topic><topic>Cattle</topic><topic>Contamination</topic><topic>Curve fitting</topic><topic>Decay</topic><topic>E coli</topic><topic>Environmental Monitoring - methods</topic><topic>Escherichia coli</topic><topic>Escherichia coli - genetics</topic><topic>faecal indicator bacteria</topic><topic>Fecal coliforms</topic><topic>Feces</topic><topic>Feces - microbiology</topic><topic>Fresh Water - chemistry</topic><topic>Fresh Water - microbiology</topic><topic>Genetic Markers</topic><topic>indicator species</topic><topic>Markers</topic><topic>Mesocosms</topic><topic>microbial source tracking</topic><topic>Microbiology</topic><topic>Microorganisms</topic><topic>model fitting</topic><topic>Models, Theoretical</topic><topic>Normalizing</topic><topic>Polymerase Chain Reaction - methods</topic><topic>Quality Control</topic><topic>Ruminants</topic><topic>ruminant‐associated genetic markers</topic><topic>Survival</topic><topic>Water Microbiology</topic><topic>Water Quality</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Brooks, L.E.</creatorcontrib><creatorcontrib>Field, K.G.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Journal of applied microbiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Brooks, L.E.</au><au>Field, K.G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Global model fitting to compare survival curves for faecal indicator bacteria and ruminant‐associated genetic markers</atitle><jtitle>Journal of applied microbiology</jtitle><addtitle>J Appl Microbiol</addtitle><date>2017-06</date><risdate>2017</risdate><volume>122</volume><issue>6</issue><spage>1704</spage><epage>1713</epage><pages>1704-1713</pages><issn>1364-5072</issn><eissn>1365-2672</eissn><abstract>Aims
To compare decay profiles of ruminant‐ and cattle‐associated molecular markers for faecal contamination and Escherichia coli, facilitating their correct application in water quality studies.
Methods and Results
We generated decay profiles for cultivable E. coli, a general Bacteroidales genetic marker (GenBac3), ruminant markers (CF128, Rum2Bac) and cattle markers (CowM2, CowM3) using faeces‐seeded mesocosms, and selected best fitting models for each decay profile. Global model fitting tested for differences between decay profiles. After normalizing for initial concentration, decay curves differed significantly between E. coli and all genetic markers except CowM3. Decay curves for CF128 differed from GenBac3 and Rum2Bac, but Rum2Bac and GenBac3 decay profiles did not differ. Despite similar survival profiles for some markers, highly varied initial concentrations affected time to nondetection.
Conclusions
Decay curves and time until nondetection differed among markers from the same host. However, the Rum2Bac and GenBac3 markers had similar decay profiles and could potentially be investigated further for source allocation using the ratio method.
Significance and Impact of the Study
As the use of genetic markers for microbial source tracking becomes increasingly common, caution is necessary. Both the shape of decay curves and time to nondetect may differ depending on the marker selected, resulting in possible misinterpretation of results and precluding application of a ‘ratio method’ of source allocation.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>28345274</pmid><doi>10.1111/jam.13454</doi><tpages>10</tpages></addata></record> |
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| ispartof | Journal of applied microbiology, 2017-06, Vol.122 (6), p.1704-1713 |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete; Oxford University Press Journals All Titles (1996-Current) |
| subjects | Animals Bacteria Bacteria - genetics Bacteroidales Bacteroidetes - genetics Cattle Contamination Curve fitting Decay E coli Environmental Monitoring - methods Escherichia coli Escherichia coli - genetics faecal indicator bacteria Fecal coliforms Feces Feces - microbiology Fresh Water - chemistry Fresh Water - microbiology Genetic Markers indicator species Markers Mesocosms microbial source tracking Microbiology Microorganisms model fitting Models, Theoretical Normalizing Polymerase Chain Reaction - methods Quality Control Ruminants ruminant‐associated genetic markers Survival Water Microbiology Water Quality |
| title | Global model fitting to compare survival curves for faecal indicator bacteria and ruminant‐associated genetic markers |
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