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Fraiture MA, Gobbo A, Guillitte C, Marchesi U, Verginelli D, De Greve J, D'aes J, Vanneste K, Papazova N, Roosens NH. Pilot market surveillance of GMM contaminations in alpha-amylase food enzyme products: A detection strategy strengthened by a newly developed qPCR method targeting a GM Bacillus licheniformis producing alpha-amylase. FOOD CHEMISTRY. MOLECULAR SCIENCES 2024; 8:100186. [PMID: 38179151 PMCID: PMC10762378 DOI: 10.1016/j.fochms.2023.100186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/16/2023] [Accepted: 12/02/2023] [Indexed: 01/06/2024]
Abstract
Using high-throughput metagenomics on commercial microbial fermentation products, DNA from a new unauthorized genetically modified microorganism (GMM), namely the GM B. licheniformis strain producing alpha-amylase (GMM alpha-amylase2), was recently discovered and characterized. On this basis, a new qPCR method targeting an unnatural association of sequences specific to the GMM alpha-amylase2 strain was designed and developed in this study, allowing to strengthen the current GMM detection strategy. The performance of the newly developed qPCR method was assessed for its specificity and sensitivity to comply with the minimum performance requirements established by the European Network of GMO Laboratories for GMO analysis. Moreover, the transferability of the in house validated qPCR method was demonstrated. Finally, its applicability was confirmed by a pilot market surveillance of GMM contaminations conducted for the first time on 40 alpha-amylase food enzyme products labelled as containing alpha-amylase. This pilot market surveillance allowed also to highlight numerous contaminations with GMM alpha-amylase2, including frequent cross-contaminations with other GMM strains previously characterized. In addition, the presence of full-length AMR genes, raising health concerns, was also reported.
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Affiliation(s)
- Marie-Alice Fraiture
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
| | - Andrea Gobbo
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
| | - Chloé Guillitte
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
| | - Ugo Marchesi
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana “M.Aleandri”, Unità Operativa Semplice a valenza Direzionale – Ricerca e controllo degli organismi geneticamente modificati, via Appia Nuova 1411, 00178 Roma, Italia
| | - Daniela Verginelli
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana “M.Aleandri”, Unità Operativa Semplice a valenza Direzionale – Ricerca e controllo degli organismi geneticamente modificati, via Appia Nuova 1411, 00178 Roma, Italia
| | - Joke De Greve
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
| | - Jolien D'aes
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
| | - Kevin Vanneste
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
| | - Nina Papazova
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
| | - Nancy H.C. Roosens
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050 Brussels, Belgium
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Tay AP, Didi K, Wickramarachchi A, Bauer DC, Wilson LOW, Maselko M. Synsor: a tool for alignment-free detection of engineered DNA sequences. Front Bioeng Biotechnol 2024; 12:1375626. [PMID: 39070163 PMCID: PMC11272466 DOI: 10.3389/fbioe.2024.1375626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 06/18/2024] [Indexed: 07/30/2024] Open
Abstract
DNA sequences of nearly any desired composition, length, and function can be synthesized to alter the biology of an organism for purposes ranging from the bioproduction of therapeutic compounds to invasive pest control. Yet despite offering many great benefits, engineered DNA poses a risk due to their possible misuse or abuse by malicious actors, or their unintentional introduction into the environment. Monitoring the presence of engineered DNA in biological or environmental systems is therefore crucial for routine and timely detection of emerging biological threats, and for improving public acceptance of genetic technologies. To address this, we developed Synsor, a tool for identifying engineered DNA sequences in high-throughput sequencing data. Synsor leverages the k-mer signature differences between naturally occurring and engineered DNA sequences and uses an artificial neural network to classify whether a DNA sequence is natural or engineered. By querying suspected sequences against the model, Synsor can identify sequences that are likely to have been engineered. Using natural plasmid and engineered vector sequences, we showed that Synsor identifies engineered DNA with >99% accuracy. We demonstrate how Synsor can be used to detect potential genetically engineered organisms and locate where engineered DNA is being introduced into the environment by analysing genomic and metagenomic data from yeast and wastewater samples, respectively. Synsor is therefore a powerful tool that will streamline the process of identifying engineered DNA in poorly characterized biological or environmental systems, thereby allowing for enhanced monitoring of emerging biological threats.
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Affiliation(s)
- Aidan P. Tay
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW, Australia
- Applied Biosciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia
| | - Kieran Didi
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW, Australia
| | - Anuradha Wickramarachchi
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW, Australia
| | - Denis C. Bauer
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW, Australia
- Applied Biosciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia
| | - Laurence O. W. Wilson
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW, Australia
- Applied Biosciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia
| | - Maciej Maselko
- Applied Biosciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW, Australia
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Fraiture MA, Gobbo A, Guillitte C, Barhdadi S, Gau C, Philipp P, Marmin L, Marchesi U, Verginelli D, Papazova N, Vanhee C, Roosens NH. Development and validation of a ddPCR assay to detect and quantify tobacco DNA in smoke and smokeless tobacco and tobacco-free products. Heliyon 2024; 10:e32964. [PMID: 39005892 PMCID: PMC11239587 DOI: 10.1016/j.heliyon.2024.e32964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 06/10/2024] [Accepted: 06/12/2024] [Indexed: 07/16/2024] Open
Abstract
The last decade, smoke and smokeless products claiming to be tobacco-free, including herbal cigarettes and herbal shisha, became available on the European market and gained popularity. This study proposes a new digital droplet PCR (ddPCR) method, designed based on a previously developed real-time PCR (qPCR) method being currently used by the U.S. Food and Drug Administration (FDA) to specifically detect the presence of tobacco DNA in targeting a sequence from the Nicotiana tabacum nia-1 gene. To ensure a harmonized and reliable control by enforcement laboratories, both of these qPCR and ddPCR methods were then evaluated and validated for their compliance to an international standard. First, the performance of these PCR-based methods was successfully assessed as specific and sensitive, and in line with minimum performance requirements from international standard. Secondly, the transferability to external laboratory was confirmed for these PCR-based methods. Finally, the applicability of these PCR-based methods was demonstrated using 7 ground tobacco reference materials from the Tobacco Research Center (TRC) Toronto University as well as 6 commercial smokeless and tobacco-free smoke and smokeless products. Based on this study, the previously developed qPCR method was confirmed as complying with international standard, ensuring a efficient and harmonize use by enforcement laboratories for tobacco control on the European market. Moreover, this study proposed to enforcement laboratories the possibility to use a ddPCR method, enabling the simultaneous detection and absolute quantification of tobacco DNA as well as a limited impact of PCR inhibitors.
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Affiliation(s)
- Marie-Alice Fraiture
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Andrea Gobbo
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Chloé Guillitte
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Sophia Barhdadi
- Sciensano, Medicines and Health Products, rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Céline Gau
- Laboratoire SCL de Strasbourg, Chemin du routoir, 67400, Illkirch-Graffenstaden, France
| | - Patrick Philipp
- Laboratoire SCL de Strasbourg, Chemin du routoir, 67400, Illkirch-Graffenstaden, France
| | - Lucas Marmin
- Laboratoire SCL de Strasbourg, Chemin du routoir, 67400, Illkirch-Graffenstaden, France
| | - Ugo Marchesi
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana "M.Aleandri", Unità Operativa Semplice a Valenza Direzionale - Ricerca e Controllo degli Organismi Geneticamente Modificati, via Appia Nuova 1411, 00178, Roma, Italy
| | - Daniela Verginelli
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana "M.Aleandri", Unità Operativa Semplice a Valenza Direzionale - Ricerca e Controllo degli Organismi Geneticamente Modificati, via Appia Nuova 1411, 00178, Roma, Italy
| | - Nina Papazova
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Céline Vanhee
- Sciensano, Medicines and Health Products, rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Nancy H.C. Roosens
- Sciensano, Transversal Activities in Applied Genomics (TAG), rue Juliette Wytsman 14, 1050, Brussels, Belgium
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Gand M, Navickaite I, Bartsch LJ, Grützke J, Overballe-Petersen S, Rasmussen A, Otani S, Michelacci V, Matamoros BR, González-Zorn B, Brouwer MSM, Di Marcantonio L, Bloemen B, Vanneste K, Roosens NHCJ, AbuOun M, De Keersmaecker SCJ. Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes. Front Microbiol 2024; 15:1336532. [PMID: 38659981 PMCID: PMC11042533 DOI: 10.3389/fmicb.2024.1336532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 02/29/2024] [Indexed: 04/26/2024] Open
Abstract
Metagenomic sequencing is a promising method that has the potential to revolutionize the world of pathogen detection and antimicrobial resistance (AMR) surveillance in food-producing environments. However, the analysis of the huge amount of data obtained requires performant bioinformatics tools and databases, with intuitive and straightforward interpretation. In this study, based on long-read metagenomics data of chicken fecal samples with a spike-in mock community, we proposed confidence levels for taxonomic identification and AMR gene detection, with interpretation guidelines, to help with the analysis of the output data generated by KMA, a popular k-mer read alignment tool. Additionally, we demonstrated that the completeness and diversity of the genomes present in the reference databases are key parameters for accurate and easy interpretation of the sequencing data. Finally, we explored whether KMA, in a two-step procedure, can be used to link the detected AMR genes to their bacterial host chromosome, both detected within the same long-reads. The confidence levels were successfully tested on 28 metagenomics datasets which were obtained with sequencing of real and spiked samples from fecal (chicken, pig, and buffalo) or food (minced beef and food enzyme products) origin. The methodology proposed in this study will facilitate the analysis of metagenomics sequencing datasets for KMA users. Ultimately, this will contribute to improvements in the rapid diagnosis and surveillance of pathogens and AMR genes in food-producing environments, as prioritized by the EU.
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Affiliation(s)
- Mathieu Gand
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Indre Navickaite
- Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
| | - Lee-Julia Bartsch
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin, Germany
| | - Josephine Grützke
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin, Germany
| | | | - Astrid Rasmussen
- Bacterial Reference Center, Statens Serum Institute, Copenhagen, Denmark
| | - Saria Otani
- National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Valeria Michelacci
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
| | | | - Bruno González-Zorn
- Department of Animal Health, Complutense University of Madrid, Madrid, Spain
| | - Michael S. M. Brouwer
- Wageningen Bioveterinary Research Part of Wageningen University and Research, Lelystad, Netherlands
| | - Lisa Di Marcantonio
- Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale”, Teramo, Italy
| | - Bram Bloemen
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | | | - Manal AbuOun
- Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
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Targeted High-Throughput Sequencing Enables the Detection of Single Nucleotide Variations in CRISPR/Cas9 Gene-Edited Organisms. Foods 2023; 12:foods12030455. [PMID: 36765984 PMCID: PMC9914749 DOI: 10.3390/foods12030455] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 01/09/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
Similar to genetically modified organisms (GMOs) produced by classical genetic engineering, gene-edited (GE) organisms and their derived food/feed products commercialized on the European Union market fall within the scope of European Union Directive 2001/18/EC. Consequently, their control in the food/feed chain by GMO enforcement laboratories is required by the competent authorities to guarantee food/feed safety and traceability (2003/1829/EC; 2003/1830/EC). However, their detection is potentially challenging at both the analytical and interpretation levels since this requires methodological approaches that can target and detect a specific single nucleotide variation (SNV) introduced into a GE organism. In this study, we propose a targeted high-throughput sequencing approach, including (i) a prior PCR-based enrichment step to amplify regions of interest, (ii) a sequencing step, and (iii) a data analysis methodology to identify SNVs of interest. To investigate if the performance of this targeted high-throughput sequencing approach is compatible with the performance criteria used in the GMO detection field, several samples containing different percentages of a GE rice line carrying a single adenosine insertion in OsMADS26 were prepared and analyzed. The SNV of interest in samples containing the GE rice line could successfully be detected, both at high and low percentages. No impact related to food processing or to the presence of other crop species was observed. The present proof-of-concept study has allowed us to deliver the first experimental-based evidence indicating that the proposed targeted high-throughput sequencing approach may constitute, in the future, a specific and sensitive tool to support the safety and traceability of the food/feed chain regarding GE plants carrying SNVs.
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