Rapid identification of a subset of foodborne bacteria in live-cell assays
The detection and identification of microbial pathogens in meat and fresh produce play an essential role in food safety for reducing foodborne illnesses every year. A new approach based on targeting a specific sequence of the 16S rRNA region for each bacterium is proposed and validated. The probe co...
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description | The detection and identification of microbial pathogens in meat and fresh produce play an essential role in food safety for reducing foodborne illnesses every year. A new approach based on targeting a specific sequence of the 16S rRNA region for each bacterium is proposed and validated. The
probe complex
consists of a C60, a conjugated RNA detector which targets a specific 16S rRNA sequence, and a complementary fluorescent reporter. The RNA detectors were designed by integrating NIH nucleotide and Vienna RNA Webservice databases, and their specificities were validated by the RDP database. Probe complexes were synthesized for identifying
E. coli
K12,
E. coli
O157: H7,
S. enterica
,
Y. enterocolitica
,
C. perfringens
, and
L. monocytogenes
. First, under controlled conditions of known bacterial mixtures, the efficiency and crosstalk for identifying the foodborne bacteria were quantified to be above 94% and below 5%, respectively. Second, experiments were designed by inoculating meat products by known numbers of bacteria and measuring the limit of detection. In one experiment, 225 g of autoclaved ground chicken was inoculated with 9
E. coli
O157:H7, where 6.8 ± 1.2 bacteria with 95% confidence interval were recovered. Third, by positionally printing probe complexes in microwells, specific microorganisms were identified with only one fluorophore. The proposed protocol is a cell-based system, can identify live bacteria in 15 min, requires no amplification, and has the potential to open new surveillance opportunities.
Key points
•
The identification of foodborne bacteria is enabled in live-cell assays
.
•
The limit of detection for 100 g of fresh chicken breast inoculated with 4 bacteria is 2.7 ± 1.4 with 95% confidence interval
.
•
The identification of five bacteria in a coded microwell chip is enabled with only one fluorophore
. |
doi_str_mv | 10.1007/s00253-020-10970-9 |
format | Article |
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probe complex
consists of a C60, a conjugated RNA detector which targets a specific 16S rRNA sequence, and a complementary fluorescent reporter. The RNA detectors were designed by integrating NIH nucleotide and Vienna RNA Webservice databases, and their specificities were validated by the RDP database. Probe complexes were synthesized for identifying
E. coli
K12,
E. coli
O157: H7,
S. enterica
,
Y. enterocolitica
,
C. perfringens
, and
L. monocytogenes
. First, under controlled conditions of known bacterial mixtures, the efficiency and crosstalk for identifying the foodborne bacteria were quantified to be above 94% and below 5%, respectively. Second, experiments were designed by inoculating meat products by known numbers of bacteria and measuring the limit of detection. In one experiment, 225 g of autoclaved ground chicken was inoculated with 9
E. coli
O157:H7, where 6.8 ± 1.2 bacteria with 95% confidence interval were recovered. Third, by positionally printing probe complexes in microwells, specific microorganisms were identified with only one fluorophore. The proposed protocol is a cell-based system, can identify live bacteria in 15 min, requires no amplification, and has the potential to open new surveillance opportunities.
Key points
•
The identification of foodborne bacteria is enabled in live-cell assays
.
•
The limit of detection for 100 g of fresh chicken breast inoculated with 4 bacteria is 2.7 ± 1.4 with 95% confidence interval
.
•
The identification of five bacteria in a coded microwell chip is enabled with only one fluorophore
.</description><identifier>ISSN: 0175-7598</identifier><identifier>EISSN: 1432-0614</identifier><identifier>DOI: 10.1007/s00253-020-10970-9</identifier><identifier>PMID: 33185701</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied Genetics and Molecular Biotechnology ; Bacteria ; Bacteria - genetics ; Biomedical and Life Sciences ; Biotechnology ; Buckminsterfullerene ; Chickens ; Colony Count, Microbial ; Confidence intervals ; Controlled conditions ; Crosstalk ; E coli ; Escherichia coli O157 ; Fluorescence ; Food irradiation ; Food Microbiology ; Food safety ; Foodborne Diseases ; Fullerenes ; Health aspects ; Humans ; Life Sciences ; Listeria monocytogenes ; Meat ; Meat products ; Microbial colonies ; Microbial Genetics and Genomics ; Microbiology ; Microorganisms ; Nucleotide sequence ; Nucleotides ; Poultry ; RNA, Ribosomal, 16S - genetics ; rRNA 16S</subject><ispartof>Applied microbiology and biotechnology, 2020-12, Vol.104 (24), p.10571-10584</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2020</rights><rights>COPYRIGHT 2020 Springer</rights><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c513t-213375ccf3bd10a365cc554e26efd4414760c175645e8dabebcee4a64d48dea13</citedby><cites>FETCH-LOGICAL-c513t-213375ccf3bd10a365cc554e26efd4414760c175645e8dabebcee4a64d48dea13</cites><orcidid>0000-0002-6433-8006</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00253-020-10970-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00253-020-10970-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33185701$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cheng, Qingsu</creatorcontrib><creatorcontrib>Parvin, Bahram</creatorcontrib><title>Rapid identification of a subset of foodborne bacteria in live-cell assays</title><title>Applied microbiology and biotechnology</title><addtitle>Appl Microbiol Biotechnol</addtitle><addtitle>Appl Microbiol Biotechnol</addtitle><description>The detection and identification of microbial pathogens in meat and fresh produce play an essential role in food safety for reducing foodborne illnesses every year. A new approach based on targeting a specific sequence of the 16S rRNA region for each bacterium is proposed and validated. The
probe complex
consists of a C60, a conjugated RNA detector which targets a specific 16S rRNA sequence, and a complementary fluorescent reporter. The RNA detectors were designed by integrating NIH nucleotide and Vienna RNA Webservice databases, and their specificities were validated by the RDP database. Probe complexes were synthesized for identifying
E. coli
K12,
E. coli
O157: H7,
S. enterica
,
Y. enterocolitica
,
C. perfringens
, and
L. monocytogenes
. First, under controlled conditions of known bacterial mixtures, the efficiency and crosstalk for identifying the foodborne bacteria were quantified to be above 94% and below 5%, respectively. Second, experiments were designed by inoculating meat products by known numbers of bacteria and measuring the limit of detection. In one experiment, 225 g of autoclaved ground chicken was inoculated with 9
E. coli
O157:H7, where 6.8 ± 1.2 bacteria with 95% confidence interval were recovered. Third, by positionally printing probe complexes in microwells, specific microorganisms were identified with only one fluorophore. The proposed protocol is a cell-based system, can identify live bacteria in 15 min, requires no amplification, and has the potential to open new surveillance opportunities.
Key points
•
The identification of foodborne bacteria is enabled in live-cell assays
.
•
The limit of detection for 100 g of fresh chicken breast inoculated with 4 bacteria is 2.7 ± 1.4 with 95% confidence interval
.
•
The identification of five bacteria in a coded microwell chip is enabled with only one fluorophore
.</description><subject>Applied Genetics and Molecular Biotechnology</subject><subject>Bacteria</subject><subject>Bacteria - genetics</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Buckminsterfullerene</subject><subject>Chickens</subject><subject>Colony Count, Microbial</subject><subject>Confidence intervals</subject><subject>Controlled conditions</subject><subject>Crosstalk</subject><subject>E coli</subject><subject>Escherichia coli O157</subject><subject>Fluorescence</subject><subject>Food irradiation</subject><subject>Food Microbiology</subject><subject>Food safety</subject><subject>Foodborne Diseases</subject><subject>Fullerenes</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Life Sciences</subject><subject>Listeria monocytogenes</subject><subject>Meat</subject><subject>Meat products</subject><subject>Microbial colonies</subject><subject>Microbial Genetics and Genomics</subject><subject>Microbiology</subject><subject>Microorganisms</subject><subject>Nucleotide sequence</subject><subject>Nucleotides</subject><subject>Poultry</subject><subject>RNA, Ribosomal, 16S - 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genetics</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Buckminsterfullerene</topic><topic>Chickens</topic><topic>Colony Count, Microbial</topic><topic>Confidence intervals</topic><topic>Controlled conditions</topic><topic>Crosstalk</topic><topic>E coli</topic><topic>Escherichia coli O157</topic><topic>Fluorescence</topic><topic>Food irradiation</topic><topic>Food Microbiology</topic><topic>Food safety</topic><topic>Foodborne Diseases</topic><topic>Fullerenes</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Life Sciences</topic><topic>Listeria monocytogenes</topic><topic>Meat</topic><topic>Meat products</topic><topic>Microbial colonies</topic><topic>Microbial Genetics and Genomics</topic><topic>Microbiology</topic><topic>Microorganisms</topic><topic>Nucleotide sequence</topic><topic>Nucleotides</topic><topic>Poultry</topic><topic>RNA, Ribosomal, 16S - genetics</topic><topic>rRNA 16S</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cheng, Qingsu</creatorcontrib><creatorcontrib>Parvin, Bahram</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: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech 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>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Natural Science Collection (ProQuest)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Biological Science Collection</collection><collection>ABI/INFORM Global</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database (ProQuest)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Applied microbiology and biotechnology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cheng, Qingsu</au><au>Parvin, Bahram</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Rapid identification of a subset of foodborne bacteria in live-cell assays</atitle><jtitle>Applied microbiology and biotechnology</jtitle><stitle>Appl Microbiol Biotechnol</stitle><addtitle>Appl Microbiol Biotechnol</addtitle><date>2020-12-01</date><risdate>2020</risdate><volume>104</volume><issue>24</issue><spage>10571</spage><epage>10584</epage><pages>10571-10584</pages><issn>0175-7598</issn><eissn>1432-0614</eissn><abstract>The detection and identification of microbial pathogens in meat and fresh produce play an essential role in food safety for reducing foodborne illnesses every year. A new approach based on targeting a specific sequence of the 16S rRNA region for each bacterium is proposed and validated. The
probe complex
consists of a C60, a conjugated RNA detector which targets a specific 16S rRNA sequence, and a complementary fluorescent reporter. The RNA detectors were designed by integrating NIH nucleotide and Vienna RNA Webservice databases, and their specificities were validated by the RDP database. Probe complexes were synthesized for identifying
E. coli
K12,
E. coli
O157: H7,
S. enterica
,
Y. enterocolitica
,
C. perfringens
, and
L. monocytogenes
. First, under controlled conditions of known bacterial mixtures, the efficiency and crosstalk for identifying the foodborne bacteria were quantified to be above 94% and below 5%, respectively. Second, experiments were designed by inoculating meat products by known numbers of bacteria and measuring the limit of detection. In one experiment, 225 g of autoclaved ground chicken was inoculated with 9
E. coli
O157:H7, where 6.8 ± 1.2 bacteria with 95% confidence interval were recovered. Third, by positionally printing probe complexes in microwells, specific microorganisms were identified with only one fluorophore. The proposed protocol is a cell-based system, can identify live bacteria in 15 min, requires no amplification, and has the potential to open new surveillance opportunities.
Key points
•
The identification of foodborne bacteria is enabled in live-cell assays
.
•
The limit of detection for 100 g of fresh chicken breast inoculated with 4 bacteria is 2.7 ± 1.4 with 95% confidence interval
.
•
The identification of five bacteria in a coded microwell chip is enabled with only one fluorophore
.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>33185701</pmid><doi>10.1007/s00253-020-10970-9</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-6433-8006</orcidid></addata></record> |
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source | MEDLINE; SpringerLink Journals - AutoHoldings |
subjects | Applied Genetics and Molecular Biotechnology Bacteria Bacteria - genetics Biomedical and Life Sciences Biotechnology Buckminsterfullerene Chickens Colony Count, Microbial Confidence intervals Controlled conditions Crosstalk E coli Escherichia coli O157 Fluorescence Food irradiation Food Microbiology Food safety Foodborne Diseases Fullerenes Health aspects Humans Life Sciences Listeria monocytogenes Meat Meat products Microbial colonies Microbial Genetics and Genomics Microbiology Microorganisms Nucleotide sequence Nucleotides Poultry RNA, Ribosomal, 16S - genetics rRNA 16S |
title | Rapid identification of a subset of foodborne bacteria in live-cell assays |
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