Molecular Typing of Invasive Staphylococcus aureus from the Emerging Infections Program (EIP) Using Whole-Genome Sequencing
Background: The CDC has performed surveillance for invasive Staphylococcus aureus (iSA) infections through the Emerging Infections Program (EIP) since 2004. SCC mec and spa typing for clonal complex (CC) assignment and genomic markers have been used to characterize isolates. In 2019, whole-genome se...
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| creator | Campbell, Davina McAllister, Gillian Jackson, Kelly See, Isaac Halpin, Alison Lutgring, Joseph Epson, Erin Petit, Susan Ray, Susan Schaffner, William Dumyati, Ghinwa Ewing, Thomas Adamczyk, Michelle Gargis, Amy |
| description | Background:
The CDC has performed surveillance for invasive
Staphylococcus aureus
(iSA) infections through the Emerging Infections Program (EIP) since 2004. SCC
mec
and
spa
typing for clonal complex (CC) assignment and genomic markers have been used to characterize isolates. In 2019, whole-genome sequencing (WGS) of isolates began, allowing for high-resolution assessment of genomic diversity. Here, we evaluate the reliability of SCC
mec
typing,
spa
typing, and CC assignment using WGS data compared to traditional methods to ensure that backwards compatibility is maintained.
Methods:
S. aureus
isolates were obtained from a convenience sample of iSA cases reported through the EIP surveillance system. Overall, 78 iSA isolates with diverse s
pa
repeat patterns, CCs, SCC
mec
types, and antimicrobial susceptibility profiles were sequenced (MiSeq, Illumina). Real-time PCR and Sanger sequencing were used as the SCC
mec
and
spa
typing reference methods, respectively.
spa-
MLST mapping (Ridom SpaServer) served as the reference method for CC assignment. WGS assembly and multilocus sequence typing (MLST) were performed using the CDC QuAISAR-H pipeline. WGS-based MLST CCs were assigned using eBURST and SCC
mec
types using SCC
mec
Finder.
spa
types were assigned from WGS assemblies using BioNumerics. For isolate subtyping, previously published and validated canonical single-nucleotide polymorphisms (canSNPs) as well as the presence of the Panton-Valentine leukocidin (PVL) toxin and arginine catabolic mobile element (ACME) virulence factor were assessed for all genome assemblies.
Results:
All isolates were assigned WGS-based s
pa
types, which were 100% concordant (78 of 78) with Sanger-based
spa
typing. SCC
mec
Finder assigned 91% of isolates (71 of 78) SCC
mec
types, which were 100% concordant with reference method results. Also, 7 isolates had multiple cassettes predicted or an incomplete SCC
mec
region assembly. Using WGS data, 96% (75 of 78) of isolates were assigned CCs; 3 isolates had unknown sequence types that were single-locus variants of established sequence types. Overall, 70 isolates had CCs assigned by the reference method; 100% (70 of 70) concordance was observed with WGS-based CCs. Analysis of canSNPs placed 42% (33 of 78) of isolates into CC8, with 17 (52%) of these isolates classified as USA300. PVL and ACME were not accurate markers for inferring the USA300 subtype as 24% (4 of 17) of isolates did not contain these markers.
Conclusions:
S. aureus
CCs, SC |
| doi_str_mv | 10.1017/ice.2020.560 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2898345361</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2898345361</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1030-2477aafba8ed32e6bacb1190180e52048252a494eed7b5cf96628b76ca28336b3</originalsourceid><addsrcrecordid>eNotkF1LwzAUhoMoOKd3_oCANwp25qNNk0uROQsTB27oXUmz062jbWbSDoZ_3pR59cI57wc8CN1SMqGEpk-VgQkjjEwSQc7QiCaJioTk8TkaEalUJBn_vkRX3u8IIalSdIR-320Npq-1w8vjvmo32JY4aw_aVwfAn53eb4-1NdaY3mPdOwhSOtvgbgt42oDbDJmsLcF0lW09Xji7cbrB99Ns8YBXfnh_bcNINIPWNqETfnpoTbhfo4tS1x5u_nWMVq_T5ctbNP-YZS_P88hQwknE4jTVuiy0hDVnIAptCkoVoZJAwkgsWcJ0rGKAdVokplRCMFmkwmgmORcFH6O7U-_e2bDtu3xne9eGyZxJFfgkXNDgejy5jLPeOyjzvasa7Y45JfmANw948wFvHvDyP0yybnQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2898345361</pqid></control><display><type>article</type><title>Molecular Typing of Invasive Staphylococcus aureus from the Emerging Infections Program (EIP) Using Whole-Genome Sequencing</title><source>Cambridge Journals Online</source><source>ProQuest Central Essentials</source><source>ProQuest Central (Alumni)</source><source>ProQuest Central</source><creator>Campbell, Davina ; McAllister, Gillian ; Jackson, Kelly ; See, Isaac ; Halpin, Alison ; Lutgring, Joseph ; Epson, Erin ; Petit, Susan ; Ray, Susan ; Schaffner, William ; Dumyati, Ghinwa ; Ewing, Thomas ; Adamczyk, Michelle ; Gargis, Amy</creator><creatorcontrib>Campbell, Davina ; McAllister, Gillian ; Jackson, Kelly ; See, Isaac ; Halpin, Alison ; Lutgring, Joseph ; Epson, Erin ; Petit, Susan ; Ray, Susan ; Schaffner, William ; Dumyati, Ghinwa ; Ewing, Thomas ; Adamczyk, Michelle ; Gargis, Amy</creatorcontrib><description>Background:
The CDC has performed surveillance for invasive
Staphylococcus aureus
(iSA) infections through the Emerging Infections Program (EIP) since 2004. SCC
mec
and
spa
typing for clonal complex (CC) assignment and genomic markers have been used to characterize isolates. In 2019, whole-genome sequencing (WGS) of isolates began, allowing for high-resolution assessment of genomic diversity. Here, we evaluate the reliability of SCC
mec
typing,
spa
typing, and CC assignment using WGS data compared to traditional methods to ensure that backwards compatibility is maintained.
Methods:
S. aureus
isolates were obtained from a convenience sample of iSA cases reported through the EIP surveillance system. Overall, 78 iSA isolates with diverse s
pa
repeat patterns, CCs, SCC
mec
types, and antimicrobial susceptibility profiles were sequenced (MiSeq, Illumina). Real-time PCR and Sanger sequencing were used as the SCC
mec
and
spa
typing reference methods, respectively.
spa-
MLST mapping (Ridom SpaServer) served as the reference method for CC assignment. WGS assembly and multilocus sequence typing (MLST) were performed using the CDC QuAISAR-H pipeline. WGS-based MLST CCs were assigned using eBURST and SCC
mec
types using SCC
mec
Finder.
spa
types were assigned from WGS assemblies using BioNumerics. For isolate subtyping, previously published and validated canonical single-nucleotide polymorphisms (canSNPs) as well as the presence of the Panton-Valentine leukocidin (PVL) toxin and arginine catabolic mobile element (ACME) virulence factor were assessed for all genome assemblies.
Results:
All isolates were assigned WGS-based s
pa
types, which were 100% concordant (78 of 78) with Sanger-based
spa
typing. SCC
mec
Finder assigned 91% of isolates (71 of 78) SCC
mec
types, which were 100% concordant with reference method results. Also, 7 isolates had multiple cassettes predicted or an incomplete SCC
mec
region assembly. Using WGS data, 96% (75 of 78) of isolates were assigned CCs; 3 isolates had unknown sequence types that were single-locus variants of established sequence types. Overall, 70 isolates had CCs assigned by the reference method; 100% (70 of 70) concordance was observed with WGS-based CCs. Analysis of canSNPs placed 42% (33 of 78) of isolates into CC8, with 17 (52%) of these isolates classified as USA300. PVL and ACME were not accurate markers for inferring the USA300 subtype as 24% (4 of 17) of isolates did not contain these markers.
Conclusions:
S. aureus
CCs, SCC
mec
, and
spa
types can be reliably determined using WGS. Incorporation of canSNP analysis represents a more efficient method for CC8 assignment than the use of genomic markers alone. WGS allows for the replacement of multiple typing methods for increased laboratory efficiency, while maintaining backward compatibility with historical typing nomenclature.
Funding:
None
Disclosures:
None</description><identifier>ISSN: 0899-823X</identifier><identifier>EISSN: 1559-6834</identifier><identifier>DOI: 10.1017/ice.2020.560</identifier><language>eng</language><publisher>Cambridge: Cambridge University Press</publisher><subject>Disease control ; Genomes ; Genomics ; Health surveillance ; Methods ; Staphylococcus infections ; Surveillance ; Toxins</subject><ispartof>Infection control and hospital epidemiology, 2020-10, Vol.41 (S1), p.s71-s72</ispartof><rights>2020 by The Society for Healthcare Epidemiology of America. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2898345361/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2898345361?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21387,21388,23255,27923,27924,33529,33702,33743,43658,43786,43804,64384,64388,72240,73875,74054,74073</link.rule.ids></links><search><creatorcontrib>Campbell, Davina</creatorcontrib><creatorcontrib>McAllister, Gillian</creatorcontrib><creatorcontrib>Jackson, Kelly</creatorcontrib><creatorcontrib>See, Isaac</creatorcontrib><creatorcontrib>Halpin, Alison</creatorcontrib><creatorcontrib>Lutgring, Joseph</creatorcontrib><creatorcontrib>Epson, Erin</creatorcontrib><creatorcontrib>Petit, Susan</creatorcontrib><creatorcontrib>Ray, Susan</creatorcontrib><creatorcontrib>Schaffner, William</creatorcontrib><creatorcontrib>Dumyati, Ghinwa</creatorcontrib><creatorcontrib>Ewing, Thomas</creatorcontrib><creatorcontrib>Adamczyk, Michelle</creatorcontrib><creatorcontrib>Gargis, Amy</creatorcontrib><title>Molecular Typing of Invasive Staphylococcus aureus from the Emerging Infections Program (EIP) Using Whole-Genome Sequencing</title><title>Infection control and hospital epidemiology</title><description>Background:
The CDC has performed surveillance for invasive
Staphylococcus aureus
(iSA) infections through the Emerging Infections Program (EIP) since 2004. SCC
mec
and
spa
typing for clonal complex (CC) assignment and genomic markers have been used to characterize isolates. In 2019, whole-genome sequencing (WGS) of isolates began, allowing for high-resolution assessment of genomic diversity. Here, we evaluate the reliability of SCC
mec
typing,
spa
typing, and CC assignment using WGS data compared to traditional methods to ensure that backwards compatibility is maintained.
Methods:
S. aureus
isolates were obtained from a convenience sample of iSA cases reported through the EIP surveillance system. Overall, 78 iSA isolates with diverse s
pa
repeat patterns, CCs, SCC
mec
types, and antimicrobial susceptibility profiles were sequenced (MiSeq, Illumina). Real-time PCR and Sanger sequencing were used as the SCC
mec
and
spa
typing reference methods, respectively.
spa-
MLST mapping (Ridom SpaServer) served as the reference method for CC assignment. WGS assembly and multilocus sequence typing (MLST) were performed using the CDC QuAISAR-H pipeline. WGS-based MLST CCs were assigned using eBURST and SCC
mec
types using SCC
mec
Finder.
spa
types were assigned from WGS assemblies using BioNumerics. For isolate subtyping, previously published and validated canonical single-nucleotide polymorphisms (canSNPs) as well as the presence of the Panton-Valentine leukocidin (PVL) toxin and arginine catabolic mobile element (ACME) virulence factor were assessed for all genome assemblies.
Results:
All isolates were assigned WGS-based s
pa
types, which were 100% concordant (78 of 78) with Sanger-based
spa
typing. SCC
mec
Finder assigned 91% of isolates (71 of 78) SCC
mec
types, which were 100% concordant with reference method results. Also, 7 isolates had multiple cassettes predicted or an incomplete SCC
mec
region assembly. Using WGS data, 96% (75 of 78) of isolates were assigned CCs; 3 isolates had unknown sequence types that were single-locus variants of established sequence types. Overall, 70 isolates had CCs assigned by the reference method; 100% (70 of 70) concordance was observed with WGS-based CCs. Analysis of canSNPs placed 42% (33 of 78) of isolates into CC8, with 17 (52%) of these isolates classified as USA300. PVL and ACME were not accurate markers for inferring the USA300 subtype as 24% (4 of 17) of isolates did not contain these markers.
Conclusions:
S. aureus
CCs, SCC
mec
, and
spa
types can be reliably determined using WGS. Incorporation of canSNP analysis represents a more efficient method for CC8 assignment than the use of genomic markers alone. WGS allows for the replacement of multiple typing methods for increased laboratory efficiency, while maintaining backward compatibility with historical typing nomenclature.
Funding:
None
Disclosures:
None</description><subject>Disease control</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Health surveillance</subject><subject>Methods</subject><subject>Staphylococcus infections</subject><subject>Surveillance</subject><subject>Toxins</subject><issn>0899-823X</issn><issn>1559-6834</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNotkF1LwzAUhoMoOKd3_oCANwp25qNNk0uROQsTB27oXUmz062jbWbSDoZ_3pR59cI57wc8CN1SMqGEpk-VgQkjjEwSQc7QiCaJioTk8TkaEalUJBn_vkRX3u8IIalSdIR-320Npq-1w8vjvmo32JY4aw_aVwfAn53eb4-1NdaY3mPdOwhSOtvgbgt42oDbDJmsLcF0lW09Xji7cbrB99Ns8YBXfnh_bcNINIPWNqETfnpoTbhfo4tS1x5u_nWMVq_T5ctbNP-YZS_P88hQwknE4jTVuiy0hDVnIAptCkoVoZJAwkgsWcJ0rGKAdVokplRCMFmkwmgmORcFH6O7U-_e2bDtu3xne9eGyZxJFfgkXNDgejy5jLPeOyjzvasa7Y45JfmANw948wFvHvDyP0yybnQ</recordid><startdate>202010</startdate><enddate>202010</enddate><creator>Campbell, Davina</creator><creator>McAllister, Gillian</creator><creator>Jackson, Kelly</creator><creator>See, Isaac</creator><creator>Halpin, Alison</creator><creator>Lutgring, Joseph</creator><creator>Epson, Erin</creator><creator>Petit, Susan</creator><creator>Ray, Susan</creator><creator>Schaffner, William</creator><creator>Dumyati, Ghinwa</creator><creator>Ewing, Thomas</creator><creator>Adamczyk, Michelle</creator><creator>Gargis, Amy</creator><general>Cambridge University Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>S0X</scope></search><sort><creationdate>202010</creationdate><title>Molecular Typing of Invasive Staphylococcus aureus from the Emerging Infections Program (EIP) Using Whole-Genome Sequencing</title><author>Campbell, Davina ; McAllister, Gillian ; Jackson, Kelly ; See, Isaac ; Halpin, Alison ; Lutgring, Joseph ; Epson, Erin ; Petit, Susan ; Ray, Susan ; Schaffner, William ; Dumyati, Ghinwa ; Ewing, Thomas ; Adamczyk, Michelle ; Gargis, Amy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1030-2477aafba8ed32e6bacb1190180e52048252a494eed7b5cf96628b76ca28336b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Disease control</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Health surveillance</topic><topic>Methods</topic><topic>Staphylococcus infections</topic><topic>Surveillance</topic><topic>Toxins</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Campbell, Davina</creatorcontrib><creatorcontrib>McAllister, Gillian</creatorcontrib><creatorcontrib>Jackson, Kelly</creatorcontrib><creatorcontrib>See, Isaac</creatorcontrib><creatorcontrib>Halpin, Alison</creatorcontrib><creatorcontrib>Lutgring, Joseph</creatorcontrib><creatorcontrib>Epson, Erin</creatorcontrib><creatorcontrib>Petit, Susan</creatorcontrib><creatorcontrib>Ray, Susan</creatorcontrib><creatorcontrib>Schaffner, William</creatorcontrib><creatorcontrib>Dumyati, Ghinwa</creatorcontrib><creatorcontrib>Ewing, Thomas</creatorcontrib><creatorcontrib>Adamczyk, Michelle</creatorcontrib><creatorcontrib>Gargis, Amy</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>ProQuest Healthcare Administration Database</collection><collection>PML(ProQuest Medical Library)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>SIRS Editorial</collection><jtitle>Infection control and hospital epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Campbell, Davina</au><au>McAllister, Gillian</au><au>Jackson, Kelly</au><au>See, Isaac</au><au>Halpin, Alison</au><au>Lutgring, Joseph</au><au>Epson, Erin</au><au>Petit, Susan</au><au>Ray, Susan</au><au>Schaffner, William</au><au>Dumyati, Ghinwa</au><au>Ewing, Thomas</au><au>Adamczyk, Michelle</au><au>Gargis, Amy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Molecular Typing of Invasive Staphylococcus aureus from the Emerging Infections Program (EIP) Using Whole-Genome Sequencing</atitle><jtitle>Infection control and hospital epidemiology</jtitle><date>2020-10</date><risdate>2020</risdate><volume>41</volume><issue>S1</issue><spage>s71</spage><epage>s72</epage><pages>s71-s72</pages><issn>0899-823X</issn><eissn>1559-6834</eissn><abstract>Background:
The CDC has performed surveillance for invasive
Staphylococcus aureus
(iSA) infections through the Emerging Infections Program (EIP) since 2004. SCC
mec
and
spa
typing for clonal complex (CC) assignment and genomic markers have been used to characterize isolates. In 2019, whole-genome sequencing (WGS) of isolates began, allowing for high-resolution assessment of genomic diversity. Here, we evaluate the reliability of SCC
mec
typing,
spa
typing, and CC assignment using WGS data compared to traditional methods to ensure that backwards compatibility is maintained.
Methods:
S. aureus
isolates were obtained from a convenience sample of iSA cases reported through the EIP surveillance system. Overall, 78 iSA isolates with diverse s
pa
repeat patterns, CCs, SCC
mec
types, and antimicrobial susceptibility profiles were sequenced (MiSeq, Illumina). Real-time PCR and Sanger sequencing were used as the SCC
mec
and
spa
typing reference methods, respectively.
spa-
MLST mapping (Ridom SpaServer) served as the reference method for CC assignment. WGS assembly and multilocus sequence typing (MLST) were performed using the CDC QuAISAR-H pipeline. WGS-based MLST CCs were assigned using eBURST and SCC
mec
types using SCC
mec
Finder.
spa
types were assigned from WGS assemblies using BioNumerics. For isolate subtyping, previously published and validated canonical single-nucleotide polymorphisms (canSNPs) as well as the presence of the Panton-Valentine leukocidin (PVL) toxin and arginine catabolic mobile element (ACME) virulence factor were assessed for all genome assemblies.
Results:
All isolates were assigned WGS-based s
pa
types, which were 100% concordant (78 of 78) with Sanger-based
spa
typing. SCC
mec
Finder assigned 91% of isolates (71 of 78) SCC
mec
types, which were 100% concordant with reference method results. Also, 7 isolates had multiple cassettes predicted or an incomplete SCC
mec
region assembly. Using WGS data, 96% (75 of 78) of isolates were assigned CCs; 3 isolates had unknown sequence types that were single-locus variants of established sequence types. Overall, 70 isolates had CCs assigned by the reference method; 100% (70 of 70) concordance was observed with WGS-based CCs. Analysis of canSNPs placed 42% (33 of 78) of isolates into CC8, with 17 (52%) of these isolates classified as USA300. PVL and ACME were not accurate markers for inferring the USA300 subtype as 24% (4 of 17) of isolates did not contain these markers.
Conclusions:
S. aureus
CCs, SCC
mec
, and
spa
types can be reliably determined using WGS. Incorporation of canSNP analysis represents a more efficient method for CC8 assignment than the use of genomic markers alone. WGS allows for the replacement of multiple typing methods for increased laboratory efficiency, while maintaining backward compatibility with historical typing nomenclature.
Funding:
None
Disclosures:
None</abstract><cop>Cambridge</cop><pub>Cambridge University Press</pub><doi>10.1017/ice.2020.560</doi><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 0899-823X |
| ispartof | Infection control and hospital epidemiology, 2020-10, Vol.41 (S1), p.s71-s72 |
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| source | Cambridge Journals Online; ProQuest Central Essentials; ProQuest Central (Alumni); ProQuest Central |
| subjects | Disease control Genomes Genomics Health surveillance Methods Staphylococcus infections Surveillance Toxins |
| title | Molecular Typing of Invasive Staphylococcus aureus from the Emerging Infections Program (EIP) Using Whole-Genome Sequencing |
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