Background-free upconversion-encoded microspheres for mycotoxin detection based on a rapid visualization method
Methods for detecting mycotoxins are very important because of the great health hazards of mycotoxins. However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food qua...
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| Veröffentlicht in: | Analytical and bioanalytical chemistry 2020, Vol.412 (1), p.81-91 |
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| creator | Yang, Minye Cui, Meihui Wang, Weixun Yang, Yaodong Chang, Jin Hao, Jianye Wang, Hanjie |
| description | Methods for detecting mycotoxins are very important because of the great health hazards of mycotoxins. However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food quality. Here we constructed a quantitative fluorescence image analysis based on multicolor upconversion nanocrystal (UCN)-encoded microspheres for detection of ochratoxin A and zearalenone. The background-free encoding image signal of UCN-doped microspheres was captured by fluorescence microscopy under near-infrared excitation, whereas the detection image signal of phycoerythrin-labeled secondary antibodies conjugated to the microspheres was captured under blue light excitation. We custom-wrote an algorithm to analyze the two images for the same sample in 10 s, and only the gray value in the red channel of the secondary probe confirmed the quantity. The results showed that this novel detection platform performed feasible and reliable fluorescence image measurements by this method. Additionally, the limit of detection of was 0.34721 ng/mL for ochratoxin A and 0.41162 ng/mL for zearalenone. We envision that this UCN encoding strategy will be usefully applied for fast, accurate, and convenient testing of multiple food contaminants to ensure the safety of the food. |
| doi_str_mv | 10.1007/s00216-019-02206-1 |
| format | Article |
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However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food quality. Here we constructed a quantitative fluorescence image analysis based on multicolor upconversion nanocrystal (UCN)-encoded microspheres for detection of ochratoxin A and zearalenone. The background-free encoding image signal of UCN-doped microspheres was captured by fluorescence microscopy under near-infrared excitation, whereas the detection image signal of phycoerythrin-labeled secondary antibodies conjugated to the microspheres was captured under blue light excitation. We custom-wrote an algorithm to analyze the two images for the same sample in 10 s, and only the gray value in the red channel of the secondary probe confirmed the quantity. The results showed that this novel detection platform performed feasible and reliable fluorescence image measurements by this method. Additionally, the limit of detection of was 0.34721 ng/mL for ochratoxin A and 0.41162 ng/mL for zearalenone. We envision that this UCN encoding strategy will be usefully applied for fast, accurate, and convenient testing of multiple food contaminants to ensure the safety of the food.</description><identifier>ISSN: 1618-2642</identifier><identifier>EISSN: 1618-2650</identifier><identifier>DOI: 10.1007/s00216-019-02206-1</identifier><identifier>PMID: 31953713</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Analytical Chemistry ; Antibodies ; Background noise ; Biochemistry ; blue light ; Characterization and Evaluation of Materials ; Chemistry ; Chemistry and Materials Science ; Coding ; Contaminants ; detection limit ; Excitation ; Fluorescence ; Fluorescence microscopy ; Food ; Food contamination ; Food Contamination - analysis ; Food quality ; Food safety ; Food Science ; Health aspects ; Health hazards ; Image analysis ; Image detection ; Image processing ; Immunoassay - methods ; Laboratory Medicine ; Limit of Detection ; Methods ; microparticles ; Microspheres ; Monitoring/Environmental Analysis ; Mycotoxins ; Nanocrystals ; Nanoparticles - chemistry ; Ochratoxin A ; Ochratoxins - analysis ; Paper in Forefront ; Safety and security measures ; Signal to noise ratio ; Upconversion ; Zearalenone ; Zearalenone - analysis</subject><ispartof>Analytical and bioanalytical chemistry, 2020, Vol.412 (1), p.81-91</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2020</rights><rights>COPYRIGHT 2020 Springer</rights><rights>Analytical and Bioanalytical Chemistry is a copyright of Springer, (2020). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c512t-7c0c681ede4c03d9408fec86a9f07f16ad5baa35bc284e2bfeb1f5aa133d79533</citedby><cites>FETCH-LOGICAL-c512t-7c0c681ede4c03d9408fec86a9f07f16ad5baa35bc284e2bfeb1f5aa133d79533</cites><orcidid>0000-0001-9400-814X</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/s00216-019-02206-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00216-019-02206-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31953713$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Minye</creatorcontrib><creatorcontrib>Cui, Meihui</creatorcontrib><creatorcontrib>Wang, Weixun</creatorcontrib><creatorcontrib>Yang, Yaodong</creatorcontrib><creatorcontrib>Chang, Jin</creatorcontrib><creatorcontrib>Hao, Jianye</creatorcontrib><creatorcontrib>Wang, Hanjie</creatorcontrib><title>Background-free upconversion-encoded microspheres for mycotoxin detection based on a rapid visualization method</title><title>Analytical and bioanalytical chemistry</title><addtitle>Anal Bioanal Chem</addtitle><addtitle>Anal Bioanal Chem</addtitle><description>Methods for detecting mycotoxins are very important because of the great health hazards of mycotoxins. However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food quality. Here we constructed a quantitative fluorescence image analysis based on multicolor upconversion nanocrystal (UCN)-encoded microspheres for detection of ochratoxin A and zearalenone. The background-free encoding image signal of UCN-doped microspheres was captured by fluorescence microscopy under near-infrared excitation, whereas the detection image signal of phycoerythrin-labeled secondary antibodies conjugated to the microspheres was captured under blue light excitation. We custom-wrote an algorithm to analyze the two images for the same sample in 10 s, and only the gray value in the red channel of the secondary probe confirmed the quantity. The results showed that this novel detection platform performed feasible and reliable fluorescence image measurements by this method. Additionally, the limit of detection of was 0.34721 ng/mL for ochratoxin A and 0.41162 ng/mL for zearalenone. We envision that this UCN encoding strategy will be usefully applied for fast, accurate, and convenient testing of multiple food contaminants to ensure the safety of the food.</description><subject>Algorithms</subject><subject>Analytical Chemistry</subject><subject>Antibodies</subject><subject>Background noise</subject><subject>Biochemistry</subject><subject>blue light</subject><subject>Characterization and Evaluation of Materials</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Coding</subject><subject>Contaminants</subject><subject>detection limit</subject><subject>Excitation</subject><subject>Fluorescence</subject><subject>Fluorescence microscopy</subject><subject>Food</subject><subject>Food contamination</subject><subject>Food Contamination - analysis</subject><subject>Food quality</subject><subject>Food safety</subject><subject>Food Science</subject><subject>Health aspects</subject><subject>Health hazards</subject><subject>Image analysis</subject><subject>Image detection</subject><subject>Image processing</subject><subject>Immunoassay - methods</subject><subject>Laboratory Medicine</subject><subject>Limit of Detection</subject><subject>Methods</subject><subject>microparticles</subject><subject>Microspheres</subject><subject>Monitoring/Environmental Analysis</subject><subject>Mycotoxins</subject><subject>Nanocrystals</subject><subject>Nanoparticles - chemistry</subject><subject>Ochratoxin A</subject><subject>Ochratoxins - analysis</subject><subject>Paper in Forefront</subject><subject>Safety and security measures</subject><subject>Signal to noise ratio</subject><subject>Upconversion</subject><subject>Zearalenone</subject><subject>Zearalenone - analysis</subject><issn>1618-2642</issn><issn>1618-2650</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkk1v1DAQhiMEoqXwBzigSFy4pMzYsZM9loovqRIXOFuOPd66JHawk4ry6_HullYgBPLBI88zr2bGb1U9RzhFgO51BmAoG8BNA4yBbPBBdYwS-4ZJAQ_v4pYdVU9yvgJA0aN8XB1x3AjeIT-u4httvm5TXINtXCKq19nEcE0p-xgaCiZasvXkTYp5vqREuXYx1dONiUv87kNtaSGzFLgedC5oCXSd9Oxtfe3zqkf_Q-_TEy2X0T6tHjk9Znp2e59UX969_Xz-obn49P7j-dlFYwSypekMGNkjWWoNcLtpoXdkeqk3DjqHUlsxaM3FYFjfEhscDeiE1si57cps_KR6ddCdU_y2Ul7U5LOhcdSB4poVawFawVrW_x_lLcrCIxT05R_oVVxTKIPsqB67sli8p7Z6JOWDi0vSZieqziSyXoDYd3j6F6ocS2XdMZDz5f23AnYo2P1FTuTUnPyk041CUDtDqIMhVDGE2htC7Xp5cdvxOkxk70p-OaAA_ADkkgpbSvcj_UP2J3wXwIk</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Yang, Minye</creator><creator>Cui, Meihui</creator><creator>Wang, Weixun</creator><creator>Yang, Yaodong</creator><creator>Chang, Jin</creator><creator>Hao, Jianye</creator><creator>Wang, Hanjie</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><general>Springer Nature B.V</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>3V.</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8BQ</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>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>F28</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KB.</scope><scope>KR7</scope><scope>L7M</scope><scope>LK8</scope><scope>L~C</scope><scope>L~D</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P64</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0001-9400-814X</orcidid></search><sort><creationdate>2020</creationdate><title>Background-free upconversion-encoded microspheres for mycotoxin detection based on a rapid visualization method</title><author>Yang, Minye ; Cui, Meihui ; Wang, Weixun ; Yang, Yaodong ; Chang, Jin ; Hao, Jianye ; Wang, Hanjie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c512t-7c0c681ede4c03d9408fec86a9f07f16ad5baa35bc284e2bfeb1f5aa133d79533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Analytical Chemistry</topic><topic>Antibodies</topic><topic>Background noise</topic><topic>Biochemistry</topic><topic>blue light</topic><topic>Characterization and Evaluation of Materials</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Coding</topic><topic>Contaminants</topic><topic>detection limit</topic><topic>Excitation</topic><topic>Fluorescence</topic><topic>Fluorescence microscopy</topic><topic>Food</topic><topic>Food contamination</topic><topic>Food Contamination - 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Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Analytical and bioanalytical chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Minye</au><au>Cui, Meihui</au><au>Wang, Weixun</au><au>Yang, Yaodong</au><au>Chang, Jin</au><au>Hao, Jianye</au><au>Wang, Hanjie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Background-free upconversion-encoded microspheres for mycotoxin detection based on a rapid visualization method</atitle><jtitle>Analytical and bioanalytical chemistry</jtitle><stitle>Anal Bioanal Chem</stitle><addtitle>Anal Bioanal Chem</addtitle><date>2020</date><risdate>2020</risdate><volume>412</volume><issue>1</issue><spage>81</spage><epage>91</epage><pages>81-91</pages><issn>1618-2642</issn><eissn>1618-2650</eissn><abstract>Methods for detecting mycotoxins are very important because of the great health hazards of mycotoxins. However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food quality. Here we constructed a quantitative fluorescence image analysis based on multicolor upconversion nanocrystal (UCN)-encoded microspheres for detection of ochratoxin A and zearalenone. The background-free encoding image signal of UCN-doped microspheres was captured by fluorescence microscopy under near-infrared excitation, whereas the detection image signal of phycoerythrin-labeled secondary antibodies conjugated to the microspheres was captured under blue light excitation. We custom-wrote an algorithm to analyze the two images for the same sample in 10 s, and only the gray value in the red channel of the secondary probe confirmed the quantity. The results showed that this novel detection platform performed feasible and reliable fluorescence image measurements by this method. Additionally, the limit of detection of was 0.34721 ng/mL for ochratoxin A and 0.41162 ng/mL for zearalenone. We envision that this UCN encoding strategy will be usefully applied for fast, accurate, and convenient testing of multiple food contaminants to ensure the safety of the food.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>31953713</pmid><doi>10.1007/s00216-019-02206-1</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-9400-814X</orcidid></addata></record> |
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| subjects | Algorithms Analytical Chemistry Antibodies Background noise Biochemistry blue light Characterization and Evaluation of Materials Chemistry Chemistry and Materials Science Coding Contaminants detection limit Excitation Fluorescence Fluorescence microscopy Food Food contamination Food Contamination - analysis Food quality Food safety Food Science Health aspects Health hazards Image analysis Image detection Image processing Immunoassay - methods Laboratory Medicine Limit of Detection Methods microparticles Microspheres Monitoring/Environmental Analysis Mycotoxins Nanocrystals Nanoparticles - chemistry Ochratoxin A Ochratoxins - analysis Paper in Forefront Safety and security measures Signal to noise ratio Upconversion Zearalenone Zearalenone - analysis |
| title | Background-free upconversion-encoded microspheres for mycotoxin detection based on a rapid visualization method |
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