Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform
With the prevalence of bacterial infections and increasing levels of antibiotic resistance comes the need for rapid and accurate methods for bacterial classification (BC) and antibiotic susceptibility testing (AST). Here we demonstrate the use of the fluid handling technique digital microfluidics (D...
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Veröffentlicht in: | Lab on a chip 2021-10, Vol.21 (21), p.428-4222 |
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description | With the prevalence of bacterial infections and increasing levels of antibiotic resistance comes the need for rapid and accurate methods for bacterial classification (BC) and antibiotic susceptibility testing (AST). Here we demonstrate the use of the fluid handling technique digital microfluidics (DMF) for automated and simultaneous BC and AST using growth metabolic markers. Custom instrumentation was developed for this application including an integrated heating module and a machine-learning-enabled low-cost colour camera for real-time absorbance and fluorescent sample monitoring on multipurpose devices. Antibiotic dilutions along with sample handling, mixing and incubation at 37 °C were all pre-programmed and processed automatically. By monitoring the metabolism of resazurin, resorufin beta-
d
-glucuronide and resorufin beta-
d
-galactopyranoside to resorufin, BC and AST were achieved in under 18 h. AST was validated in two uropathogenic
E. coli
strains with antibiotics ciprofloxacin and nitrofurantoin. BC was performed independently and simultaneously with ciprofloxacin AST for
E. coli
,
K. pneumoniae
,
P. mirabilis
and
S. aureus
. Finally, a proof-of-concept multiplexed system for breakpoint testing of two antibiotics, as well as
E. coli
and coliform classification was investigated with a multidrug-resistant
E. coli
strain. All bacteria were correctly identified, while AST and breakpoint test results were in essential and category agreement with reference methods. These results show the versatility and accuracy of this all-in-one microfluidic system for analysis of bacterial growth and phenotype.
An 'all in one' digital microfluidic system is reported that automates the preparation and testing of samples for antibiotic susceptibility and bacterial classification, relying on three metabolic markers. |
doi_str_mv | 10.1039/d1lc00609f |
format | Article |
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d
-glucuronide and resorufin beta-
d
-galactopyranoside to resorufin, BC and AST were achieved in under 18 h. AST was validated in two uropathogenic
E. coli
strains with antibiotics ciprofloxacin and nitrofurantoin. BC was performed independently and simultaneously with ciprofloxacin AST for
E. coli
,
K. pneumoniae
,
P. mirabilis
and
S. aureus
. Finally, a proof-of-concept multiplexed system for breakpoint testing of two antibiotics, as well as
E. coli
and coliform classification was investigated with a multidrug-resistant
E. coli
strain. All bacteria were correctly identified, while AST and breakpoint test results were in essential and category agreement with reference methods. These results show the versatility and accuracy of this all-in-one microfluidic system for analysis of bacterial growth and phenotype.
An 'all in one' digital microfluidic system is reported that automates the preparation and testing of samples for antibiotic susceptibility and bacterial classification, relying on three metabolic markers.</description><identifier>ISSN: 1473-0197</identifier><identifier>EISSN: 1473-0189</identifier><identifier>DOI: 10.1039/d1lc00609f</identifier><identifier>PMID: 34549763</identifier><language>eng</language><publisher>CAMBRIDGE: Royal Soc Chemistry</publisher><subject><![CDATA[Antibiotics ; Bacteria ; Biochemical Research Methods ; Biochemistry & Molecular Biology ; Chemistry ; Chemistry, Analytical ; Chemistry, Multidisciplinary ; Classification ; E coli ; Fluorescence ; Instruments & Instrumentation ; Life Sciences & Biomedicine ; Machine learning ; Microfluidics ; Monitoring ; Nanoscience & Nanotechnology ; Physical Sciences ; Science & Technology ; Science & Technology - Other Topics ; Technology]]></subject><ispartof>Lab on a chip, 2021-10, Vol.21 (21), p.428-4222</ispartof><rights>Copyright Royal Society of Chemistry 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>29</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000698158100001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c314t-4aab7ba972d993904a6ae9c42c8af83ba3bb94c8120cf3f3d46506d760b0b3993</citedby><cites>FETCH-LOGICAL-c314t-4aab7ba972d993904a6ae9c42c8af83ba3bb94c8120cf3f3d46506d760b0b3993</cites><orcidid>0000-0001-5230-7475 ; 0000-0003-3360-5359 ; 0000-0003-1495-7156</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,27929,27930,39263</link.rule.ids></links><search><creatorcontrib>Sklavounos, Alexandros A</creatorcontrib><creatorcontrib>Nemr, Carine R</creatorcontrib><creatorcontrib>Kelley, Shana O</creatorcontrib><creatorcontrib>Wheeler, Aaron R</creatorcontrib><title>Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform</title><title>Lab on a chip</title><addtitle>LAB CHIP</addtitle><description>With the prevalence of bacterial infections and increasing levels of antibiotic resistance comes the need for rapid and accurate methods for bacterial classification (BC) and antibiotic susceptibility testing (AST). Here we demonstrate the use of the fluid handling technique digital microfluidics (DMF) for automated and simultaneous BC and AST using growth metabolic markers. Custom instrumentation was developed for this application including an integrated heating module and a machine-learning-enabled low-cost colour camera for real-time absorbance and fluorescent sample monitoring on multipurpose devices. Antibiotic dilutions along with sample handling, mixing and incubation at 37 °C were all pre-programmed and processed automatically. By monitoring the metabolism of resazurin, resorufin beta-
d
-glucuronide and resorufin beta-
d
-galactopyranoside to resorufin, BC and AST were achieved in under 18 h. AST was validated in two uropathogenic
E. coli
strains with antibiotics ciprofloxacin and nitrofurantoin. BC was performed independently and simultaneously with ciprofloxacin AST for
E. coli
,
K. pneumoniae
,
P. mirabilis
and
S. aureus
. Finally, a proof-of-concept multiplexed system for breakpoint testing of two antibiotics, as well as
E. coli
and coliform classification was investigated with a multidrug-resistant
E. coli
strain. All bacteria were correctly identified, while AST and breakpoint test results were in essential and category agreement with reference methods. These results show the versatility and accuracy of this all-in-one microfluidic system for analysis of bacterial growth and phenotype.
An 'all in one' digital microfluidic system is reported that automates the preparation and testing of samples for antibiotic susceptibility and bacterial classification, relying on three metabolic markers.</description><subject>Antibiotics</subject><subject>Bacteria</subject><subject>Biochemical Research Methods</subject><subject>Biochemistry & Molecular Biology</subject><subject>Chemistry</subject><subject>Chemistry, Analytical</subject><subject>Chemistry, Multidisciplinary</subject><subject>Classification</subject><subject>E coli</subject><subject>Fluorescence</subject><subject>Instruments & Instrumentation</subject><subject>Life Sciences & Biomedicine</subject><subject>Machine learning</subject><subject>Microfluidics</subject><subject>Monitoring</subject><subject>Nanoscience & Nanotechnology</subject><subject>Physical Sciences</subject><subject>Science & Technology</subject><subject>Science & Technology - Other Topics</subject><subject>Technology</subject><issn>1473-0197</issn><issn>1473-0189</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>HGBXW</sourceid><recordid>eNqNkk1rXCEUhqU0NGmSTfeFC92Ehkl1_F62N80HDGTTrC9HrwaDc52ql5B_HzMTptBVFuIRnkfecxShLwRfEEz1j5FEi7HA2n9AR4RJusBE6Y_7WstD9LmUR4wJZ0J9QoeUcaaloEfI_QJbXQ4QOxuhlOCDhRrS1ME0tlWDCakG25W5WLd5PcZQn7vqSg3TQ7cFuzBV95ChurFbB5uTj3MYm7SJUH3K6xN04CEWd_q2H6P7q99_-pvF6u76tv-5WlhKWF0wACMNaLkctaYaMxDgtGVLq8AraoAao5lVZImtp56OTHAsRimwwYY25Rid7e7d5PR3bhGHdWixY4TJpbkMSy45FVIJ2dBv_6GPac5TS9coxTXllItGfd9RralSsvPDJoc15OeB4OF1-MMlWfXb4V81-HwHPzmTfLHBTdbtBdworQhXpFWYNFq9n-5D3b5Kn-apNvXrTs3F7o1_v4C-AMdOoUA</recordid><startdate>20211026</startdate><enddate>20211026</enddate><creator>Sklavounos, Alexandros A</creator><creator>Nemr, Carine R</creator><creator>Kelley, Shana O</creator><creator>Wheeler, Aaron R</creator><general>Royal Soc Chemistry</general><general>Royal Society of Chemistry</general><scope>BLEPL</scope><scope>DTL</scope><scope>HGBXW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>7U5</scope><scope>8FD</scope><scope>FR3</scope><scope>L7M</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-5230-7475</orcidid><orcidid>https://orcid.org/0000-0003-3360-5359</orcidid><orcidid>https://orcid.org/0000-0003-1495-7156</orcidid></search><sort><creationdate>20211026</creationdate><title>Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform</title><author>Sklavounos, Alexandros A ; Nemr, Carine R ; Kelley, Shana O ; Wheeler, Aaron R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c314t-4aab7ba972d993904a6ae9c42c8af83ba3bb94c8120cf3f3d46506d760b0b3993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Antibiotics</topic><topic>Bacteria</topic><topic>Biochemical Research Methods</topic><topic>Biochemistry & Molecular Biology</topic><topic>Chemistry</topic><topic>Chemistry, Analytical</topic><topic>Chemistry, Multidisciplinary</topic><topic>Classification</topic><topic>E coli</topic><topic>Fluorescence</topic><topic>Instruments & Instrumentation</topic><topic>Life Sciences & Biomedicine</topic><topic>Machine learning</topic><topic>Microfluidics</topic><topic>Monitoring</topic><topic>Nanoscience & Nanotechnology</topic><topic>Physical Sciences</topic><topic>Science & Technology</topic><topic>Science & Technology - Other Topics</topic><topic>Technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sklavounos, Alexandros A</creatorcontrib><creatorcontrib>Nemr, Carine R</creatorcontrib><creatorcontrib>Kelley, Shana O</creatorcontrib><creatorcontrib>Wheeler, Aaron R</creatorcontrib><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Web of Science - Science Citation Index Expanded - 2021</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><jtitle>Lab on a chip</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sklavounos, Alexandros A</au><au>Nemr, Carine R</au><au>Kelley, Shana O</au><au>Wheeler, Aaron R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform</atitle><jtitle>Lab on a chip</jtitle><stitle>LAB CHIP</stitle><date>2021-10-26</date><risdate>2021</risdate><volume>21</volume><issue>21</issue><spage>428</spage><epage>4222</epage><pages>428-4222</pages><issn>1473-0197</issn><eissn>1473-0189</eissn><abstract>With the prevalence of bacterial infections and increasing levels of antibiotic resistance comes the need for rapid and accurate methods for bacterial classification (BC) and antibiotic susceptibility testing (AST). Here we demonstrate the use of the fluid handling technique digital microfluidics (DMF) for automated and simultaneous BC and AST using growth metabolic markers. Custom instrumentation was developed for this application including an integrated heating module and a machine-learning-enabled low-cost colour camera for real-time absorbance and fluorescent sample monitoring on multipurpose devices. Antibiotic dilutions along with sample handling, mixing and incubation at 37 °C were all pre-programmed and processed automatically. By monitoring the metabolism of resazurin, resorufin beta-
d
-glucuronide and resorufin beta-
d
-galactopyranoside to resorufin, BC and AST were achieved in under 18 h. AST was validated in two uropathogenic
E. coli
strains with antibiotics ciprofloxacin and nitrofurantoin. BC was performed independently and simultaneously with ciprofloxacin AST for
E. coli
,
K. pneumoniae
,
P. mirabilis
and
S. aureus
. Finally, a proof-of-concept multiplexed system for breakpoint testing of two antibiotics, as well as
E. coli
and coliform classification was investigated with a multidrug-resistant
E. coli
strain. All bacteria were correctly identified, while AST and breakpoint test results were in essential and category agreement with reference methods. These results show the versatility and accuracy of this all-in-one microfluidic system for analysis of bacterial growth and phenotype.
An 'all in one' digital microfluidic system is reported that automates the preparation and testing of samples for antibiotic susceptibility and bacterial classification, relying on three metabolic markers.</abstract><cop>CAMBRIDGE</cop><pub>Royal Soc Chemistry</pub><pmid>34549763</pmid><doi>10.1039/d1lc00609f</doi><orcidid>https://orcid.org/0000-0001-5230-7475</orcidid><orcidid>https://orcid.org/0000-0003-3360-5359</orcidid><orcidid>https://orcid.org/0000-0003-1495-7156</orcidid></addata></record> |
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subjects | Antibiotics Bacteria Biochemical Research Methods Biochemistry & Molecular Biology Chemistry Chemistry, Analytical Chemistry, Multidisciplinary Classification E coli Fluorescence Instruments & Instrumentation Life Sciences & Biomedicine Machine learning Microfluidics Monitoring Nanoscience & Nanotechnology Physical Sciences Science & Technology Science & Technology - Other Topics Technology |
title | Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform |
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