1
|
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] [What about the content of this article? (0)] [Affiliation(s)] [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.
Collapse
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
| | | |
Collapse
|
2
|
Refolo P, Sacchini D, Bloemen B, Grin J, Gutierrez-Ibarluzea I, Hofmann B, Oortwijn W, Raimondi C, Sampietro-Colom L, Sandman L, van der Wilt GJ, Spagnolo AG. On the normativity of evidence - Lessons from philosophy of science and the "VALIDATE" project. Eur Rev Med Pharmacol Sci 2023; 27:11202-11210. [PMID: 38095370 DOI: 10.26355/eurrev_202312_34560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
"Evidence" is a key term in medicine and health services research, including Health Technology Assessment (HTA). Randomized clinical trials (RCTs) have undoubtedly dominated the scene of generating evidence for a long period of time, becoming the hallmark of evidence-based medicine (EBM). However, due to a number of misunderstandings, the lay audience and some researchers have sometimes placed too much trust in RCTs compared to other methods of investigation. One of the principal misunderstandings is to consider RCTs findings as isolated and self-apparent pieces of information. In other words, what has been essentially lacking was the awareness of the value-context of the evidence and, in particular, the value- and theory-ladenness (normativity) of scientific knowledge. This paper aims to emphasize the normativity that exists in the production of scientific knowledge, and in particular in the conduct of RCTs as well as in the performance of HTA. The work is based on some lessons learned from Philosophy of Science and the European project "VALIDATE" (VALues In Doing Assessments of healthcare TEchnologies"). VALIDATE was a three-year EU Erasmus+ strategic partnerships project (2018-2021), in which training in the field of HTA was further optimized by using insights from political science and ethics (in accordance with the recent definition of HTA). Our analysis may reveal useful insights for addressing some challenges that HTA is going to face in the future.
Collapse
Affiliation(s)
- P Refolo
- Research Center for Clinical Bioethics and Medical Humanities, Università Cattolica del Sacro Cuore, Rome, Italy.
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
3
|
Bloemen B, Gand M, Vanneste K, Marchal K, Roosens NHC, De Keersmaecker SCJ. Development of a portable on-site applicable metagenomic data generation workflow for enhanced pathogen and antimicrobial resistance surveillance. Sci Rep 2023; 13:19656. [PMID: 37952062 PMCID: PMC10640560 DOI: 10.1038/s41598-023-46771-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 11/04/2023] [Indexed: 11/14/2023] Open
Abstract
Rapid, accurate and comprehensive diagnostics are essential for outbreak prevention and pathogen surveillance. Real-time, on-site metagenomics on miniaturized devices, such as Oxford Nanopore Technologies MinION sequencing, could provide a promising approach. However, current sample preparation protocols often require substantial equipment and dedicated laboratories, limiting their use. In this study, we developed a rapid on-site applicable DNA extraction and library preparation approach for nanopore sequencing, using portable devices. The optimized method consists of a portable mechanical lysis approach followed by magnetic bead-based DNA purification and automated sequencing library preparation, and resulted in a throughput comparable to a current optimal, laboratory-based protocol using enzymatic digestion to lyse cells. By using spike-in reference communities, we compared the on-site method with other workflows, and demonstrated reliable taxonomic profiling, despite method-specific biases. We also demonstrated the added value of long-read sequencing by recovering reads containing full-length antimicrobial resistance genes, and attributing them to a host species based on the additional genomic information they contain. Our method may provide a rapid, widely-applicable approach for microbial detection and surveillance in a variety of on-site settings.
Collapse
Affiliation(s)
- Bram Bloemen
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
- Department of Information Technology, IDLab, Ghent University, IMEC, 9052, Ghent, Belgium
| | - Mathieu Gand
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Kathleen Marchal
- Department of Information Technology, IDLab, Ghent University, IMEC, 9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium
| | - Nancy H C Roosens
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Sigrid C J De Keersmaecker
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium.
| |
Collapse
|
4
|
Gand M, Bloemen B, Vanneste K, Roosens NHC, De Keersmaecker SCJ. Comparison of 6 DNA extraction methods for isolation of high yield of high molecular weight DNA suitable for shotgun metagenomics Nanopore sequencing to detect bacteria. BMC Genomics 2023; 24:438. [PMID: 37537550 PMCID: PMC10401787 DOI: 10.1186/s12864-023-09537-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/27/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Oxford Nanopore Technologies (ONT) offers an accessible platform for long-read sequencing, which improves the reconstruction of genomes and helps to resolve complex genomic contexts, especially in the case of metagenome analysis. To take the best advantage of long-read sequencing, DNA extraction methods must be able to isolate pure high molecular weight (HMW) DNA from complex metagenomics samples, without introducing any bias. New methods released on the market, and protocols developed at the research level, were specifically designed for this application and need to be assessed. RESULTS In this study, with different bacterial cocktail mixes, analyzed as pure or spiked in a synthetic fecal matrix, we evaluated the performances of 6 DNA extraction methods using various cells lysis and purification techniques, from quick and easy, to more time-consuming and gentle protocols, including a portable method for on-site application. In addition to the comparison of the quality, quantity and purity of the extracted DNA, the performance obtained when doing Nanopore sequencing on a MinION flow cell was also tested. From the obtained results, the Quick-DNA HMW MagBead Kit (Zymo Research) was selected as producing the best yield of pure HMW DNA. Furthermore, this kit allowed an accurate detection, by Nanopore sequencing, of almost all the bacterial species present in a complex mock community. CONCLUSION Amongst the 6 tested methods, the Quick-DNA HMW MagBead Kit (Zymo Research) was considered as the most suitable for Nanopore sequencing and would be recommended for bacterial metagenomics studies using this technology.
Collapse
Affiliation(s)
- Mathieu Gand
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Bram Bloemen
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Nancy H C Roosens
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium
| | - Sigrid C J De Keersmaecker
- Transversal Activities in Applied Genomics, Sciensano, Rue Juliette Wytsman 14, 1050, Brussels, Belgium.
| |
Collapse
|
5
|
Engel J, Blanchet L, Bloemen B, van den Heuvel LP, Engelke UHF, Wevers RA, Buydens LMC. Regularized MANOVA (rMANOVA) in untargeted metabolomics. Anal Chim Acta 2015; 899:1-12. [PMID: 26547490 DOI: 10.1016/j.aca.2015.06.042] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Revised: 06/09/2015] [Accepted: 06/11/2015] [Indexed: 12/14/2022]
Abstract
Many advanced metabolomics experiments currently lead to data where a large number of response variables were measured while one or several factors were changed. Often the number of response variables vastly exceeds the sample size and well-established techniques such as multivariate analysis of variance (MANOVA) cannot be used to analyze the data. ANOVA simultaneous component analysis (ASCA) is an alternative to MANOVA for analysis of metabolomics data from an experimental design. In this paper, we show that ASCA assumes that none of the metabolites are correlated and that they all have the same variance. Because of these assumptions, ASCA may relate the wrong variables to a factor. This reduces the power of the method and hampers interpretation. We propose an improved model that is essentially a weighted average of the ASCA and MANOVA models. The optimal weight is determined in a data-driven fashion. Compared to ASCA, this method assumes that variables can correlate, leading to a more realistic view of the data. Compared to MANOVA, the model is also applicable when the number of samples is (much) smaller than the number of variables. These advantages are demonstrated by means of simulated and real data examples. The source code of the method is available from the first author upon request, and at the following github repository: https://github.com/JasperE/regularized-MANOVA.
Collapse
Affiliation(s)
- J Engel
- Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg 135, Nijmegen, The Netherlands; Translational Metabolic Laboratory at the Department of Laboratory Medicine, Radboud University Medical Centre, Geert Grooteplein 10, Nijmegen, The Netherlands
| | - L Blanchet
- Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg 135, Nijmegen, The Netherlands; Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, Nijmegen, The Netherlands
| | - B Bloemen
- Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg 135, Nijmegen, The Netherlands
| | - L P van den Heuvel
- Translational Metabolic Laboratory at the Department of Laboratory Medicine, Radboud University Medical Centre, Geert Grooteplein 10, Nijmegen, The Netherlands
| | - U H F Engelke
- Translational Metabolic Laboratory at the Department of Laboratory Medicine, Radboud University Medical Centre, Geert Grooteplein 10, Nijmegen, The Netherlands
| | - R A Wevers
- Translational Metabolic Laboratory at the Department of Laboratory Medicine, Radboud University Medical Centre, Geert Grooteplein 10, Nijmegen, The Netherlands
| | - L M C Buydens
- Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg 135, Nijmegen, The Netherlands.
| |
Collapse
|