Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension

Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with...
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Autor*in:	Tang, Mengxuan [verfasserIn] Liao, Ningbo [verfasserIn] Tian, Peng [verfasserIn] Shen, Kaisheng [verfasserIn] Liu, Chengwei [verfasserIn] Ruan, Lu [verfasserIn] Wu, Guoping [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce

Übergeordnetes Werk:	Enthalten in: Food microbiology - London : Academic Press, 1984, 110
Übergeordnetes Werk:	volume:110

DOI / URN:	10.1016/j.fm.2022.104165

Katalog-ID:	ELV008890544

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245	1	0	\|a Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension
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520			\|a Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce.
650		4	\|a Norovirus
650		4	\|a Virus elution
650		4	\|a Bentonite coated activated carbon (BCAC)
650		4	\|a Extraction efficiency
650		4	\|a RT-qPCR
650		4	\|a Fresh produce
700	1		\|a Liao, Ningbo \|e verfasserin \|0 (orcid)0000-0003-1914-2319 \|4 aut
700	1		\|a Tian, Peng \|e verfasserin \|4 aut
700	1		\|a Shen, Kaisheng \|e verfasserin \|4 aut
700	1		\|a Liu, Chengwei \|e verfasserin \|4 aut
700	1		\|a Ruan, Lu \|e verfasserin \|4 aut
700	1		\|a Wu, Guoping \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Food microbiology \|d London : Academic Press, 1984 \|g 110 \|h Online-Ressource \|w (DE-627)266877214 \|w (DE-600)1467522-5 \|w (DE-576)253761492 \|x 1095-9998 \|7 nnns
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912			\|a GBV_ILN_31
912			\|a GBV_ILN_32
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_101
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_224
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
936	b	k	\|a 42.30 \|j Mikrobiologie \|q VZ
936	b	k	\|a 58.34 \|j Lebensmitteltechnologie \|q VZ
951			\|a AR
952			\|d 110

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publishDate	2022
allfields	10.1016/j.fm.2022.104165 doi (DE-627)ELV008890544 (ELSEVIER)S0740-0020(22)00189-7 DE-627 ger DE-627 rda eng 570 VZ BIODIV DE-30 fid 42.30 bkl 58.34 bkl Tang, Mengxuan verfasserin aut Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce. Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce Liao, Ningbo verfasserin (orcid)0000-0003-1914-2319 aut Tian, Peng verfasserin aut Shen, Kaisheng verfasserin aut Liu, Chengwei verfasserin aut Ruan, Lu verfasserin aut Wu, Guoping verfasserin aut Enthalten in Food microbiology London : Academic Press, 1984 110 Online-Ressource (DE-627)266877214 (DE-600)1467522-5 (DE-576)253761492 1095-9998 nnns volume:110 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 42.30 Mikrobiologie VZ 58.34 Lebensmitteltechnologie VZ AR 110
spelling	10.1016/j.fm.2022.104165 doi (DE-627)ELV008890544 (ELSEVIER)S0740-0020(22)00189-7 DE-627 ger DE-627 rda eng 570 VZ BIODIV DE-30 fid 42.30 bkl 58.34 bkl Tang, Mengxuan verfasserin aut Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce. Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce Liao, Ningbo verfasserin (orcid)0000-0003-1914-2319 aut Tian, Peng verfasserin aut Shen, Kaisheng verfasserin aut Liu, Chengwei verfasserin aut Ruan, Lu verfasserin aut Wu, Guoping verfasserin aut Enthalten in Food microbiology London : Academic Press, 1984 110 Online-Ressource (DE-627)266877214 (DE-600)1467522-5 (DE-576)253761492 1095-9998 nnns volume:110 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 42.30 Mikrobiologie VZ 58.34 Lebensmitteltechnologie VZ AR 110
allfields_unstemmed	10.1016/j.fm.2022.104165 doi (DE-627)ELV008890544 (ELSEVIER)S0740-0020(22)00189-7 DE-627 ger DE-627 rda eng 570 VZ BIODIV DE-30 fid 42.30 bkl 58.34 bkl Tang, Mengxuan verfasserin aut Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce. Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce Liao, Ningbo verfasserin (orcid)0000-0003-1914-2319 aut Tian, Peng verfasserin aut Shen, Kaisheng verfasserin aut Liu, Chengwei verfasserin aut Ruan, Lu verfasserin aut Wu, Guoping verfasserin aut Enthalten in Food microbiology London : Academic Press, 1984 110 Online-Ressource (DE-627)266877214 (DE-600)1467522-5 (DE-576)253761492 1095-9998 nnns volume:110 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 42.30 Mikrobiologie VZ 58.34 Lebensmitteltechnologie VZ AR 110
allfieldsGer	10.1016/j.fm.2022.104165 doi (DE-627)ELV008890544 (ELSEVIER)S0740-0020(22)00189-7 DE-627 ger DE-627 rda eng 570 VZ BIODIV DE-30 fid 42.30 bkl 58.34 bkl Tang, Mengxuan verfasserin aut Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce. Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce Liao, Ningbo verfasserin (orcid)0000-0003-1914-2319 aut Tian, Peng verfasserin aut Shen, Kaisheng verfasserin aut Liu, Chengwei verfasserin aut Ruan, Lu verfasserin aut Wu, Guoping verfasserin aut Enthalten in Food microbiology London : Academic Press, 1984 110 Online-Ressource (DE-627)266877214 (DE-600)1467522-5 (DE-576)253761492 1095-9998 nnns volume:110 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 42.30 Mikrobiologie VZ 58.34 Lebensmitteltechnologie VZ AR 110
allfieldsSound	10.1016/j.fm.2022.104165 doi (DE-627)ELV008890544 (ELSEVIER)S0740-0020(22)00189-7 DE-627 ger DE-627 rda eng 570 VZ BIODIV DE-30 fid 42.30 bkl 58.34 bkl Tang, Mengxuan verfasserin aut Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce. Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce Liao, Ningbo verfasserin (orcid)0000-0003-1914-2319 aut Tian, Peng verfasserin aut Shen, Kaisheng verfasserin aut Liu, Chengwei verfasserin aut Ruan, Lu verfasserin aut Wu, Guoping verfasserin aut Enthalten in Food microbiology London : Academic Press, 1984 110 Online-Ressource (DE-627)266877214 (DE-600)1467522-5 (DE-576)253761492 1095-9998 nnns volume:110 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 42.30 Mikrobiologie VZ 58.34 Lebensmitteltechnologie VZ AR 110
language	English
source	Enthalten in Food microbiology 110 volume:110
sourceStr	Enthalten in Food microbiology 110 volume:110
format_phy_str_mv	Article
bklname	Mikrobiologie Lebensmitteltechnologie
institution	findex.gbv.de
topic_facet	Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce
dewey-raw	570
isfreeaccess_bool	false
container_title	Food microbiology
authorswithroles_txt_mv	Tang, Mengxuan @@aut@@ Liao, Ningbo @@aut@@ Tian, Peng @@aut@@ Shen, Kaisheng @@aut@@ Liu, Chengwei @@aut@@ Ruan, Lu @@aut@@ Wu, Guoping @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	266877214
dewey-sort	3570
id	ELV008890544
language_de	englisch
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author	Tang, Mengxuan
spellingShingle	Tang, Mengxuan ddc 570 fid BIODIV bkl 42.30 bkl 58.34 misc Norovirus misc Virus elution misc Bentonite coated activated carbon (BCAC) misc Extraction efficiency misc RT-qPCR misc Fresh produce Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension
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topic_title	570 VZ BIODIV DE-30 fid 42.30 bkl 58.34 bkl Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension Norovirus Virus elution Bentonite coated activated carbon (BCAC) Extraction efficiency RT-qPCR Fresh produce
topic	ddc 570 fid BIODIV bkl 42.30 bkl 58.34 misc Norovirus misc Virus elution misc Bentonite coated activated carbon (BCAC) misc Extraction efficiency misc RT-qPCR misc Fresh produce
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title	Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension
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title_full	Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension
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author_browse	Tang, Mengxuan Liao, Ningbo Tian, Peng Shen, Kaisheng Liu, Chengwei Ruan, Lu Wu, Guoping
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author-letter	Tang, Mengxuan
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title_sort	use of bentonite-coated activated carbon for improving the sensitivity of rt-qpcr detection of norovirus from vegetables and fruits: the iso 15216-1:2017 standard method extension
title_auth	Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension
abstract	Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce.
abstractGer	Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce.
abstract_unstemmed	Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10–100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce.
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title_short	Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension
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author2	Liao, Ningbo Tian, Peng Shen, Kaisheng Liu, Chengwei Ruan, Lu Wu, Guoping
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up_date	2024-07-06T21:15:35.504Z
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Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension

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