Prof John Draper
I currently manage the High Resolution Metabolomics Laboratory and am responsible for oversight of Enabling Technologies within IBERS including core facilities for Metabolomics, Next Generation Sequencing, Plant Phenomics and Bioinformatics.
From a technology perspective I am interested in the development of generic, high throughput phenotyping methodologies, based on global metabolite analysis (metabolomics) for use in a range of fields. My lab is concentrating on metabolite fingerprinting & profiling using high resolution mass spectrometry techniques.
I have established a range of collaborations with laboratories interested in the application of metabolomics technology in food & nutrition research & in plant pathology. We have developed high throughput methods (metabolite fingerprinting, data representation & data analysis) for compositional analysis & comparison of food raw materials. Alongside clinical/veterinary institutions & industry partners, we are currently researching methods for determining dietary exposure & individual responses to diet constituents in humans & domesticated animals from blood & urine analysis.
From a fundamental research perspective my team has pioneered the development of Brachypodium distachyon as a new model system for plant functional genomics. Together with local & international collaborators we played a key role in collecting & characterizing Brachypodium distachyon germplasm in terms of karyotype, comparative genomics, tissue culture behavior, transformation efficiency & pathogen interactions.
Currently I am developing a metabolomics platform for both metabolite identification & high throughput phenotyping in grasses & cereals based on the Brachypodium metabolome. A practical application of this research focuses on a study of metabolic reprogramming in B. distachyon, rice & barley during the biotrophic phases of interaction with rice blast. In collaboration with Nick Talbot (Univ. Exeter, UK) this project extends to an analysis of metabolome changes in Magnaporthae grisae during epidermal cell penetration & colonization.
My research is supported by grants from the BBSRC, The Foods Standards Agency & Industry.
Use of biomarkers to assess fruit and vegetables intake. Proceedings of the Nutrition Society Nutrition Society Summer Meeting. Cadair2017.
Diversity and association of phenotypic and metabolomic traits in the close model grasses Brachypodium distachyon, B. stacei and B. hybridum. Annals of Botany 119 (4) pp. 545-561. Cadair2017.
Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial. Lancet Diabetes and Endocrinology 5 (3) pp. 184-195. Cadair2017.
Ultra High Performance Liquid Chromatography-High Resolution Mass Spectrometry plasma lipidomics can distinguish between canine breeds despite uncontrolled environmental variability and non-standardized diets: Plasma lipidome of dog breeds using UHPLC-HRM. Metabolomics 13 15 Cadair2017.
Developing community-based urine sampling methods to facilitate dietary exposure biomarker technology for population assessment. Proceedings of the Nutrition Society 75 (OCE3) E240 Nutrition Society Summer Meeting. Cadair2016.
Quantification of dietary biomarkers in spot urine samples reflects the intake of foods of UK high public health importance. Proceedings of the Nutrition Society 75 (OCE3) E248 Nutrition Society Summer Meeting. Cadair2016.
Characterisation of the main drivers of intra- and inter- breed variability in the plasma metabolome of dogs. Metabolomics 12 (4) 72 Cadair2016.
An Analytical Pipeline for Quantitative Characterization of Dietary Intake: Application To Assess Grape Intake. Journal of Agricultural and Food Chemistry 64 (11) pp. 2423-2431. Cadair2016.
Changes in the human plasma and urinary metabolome associated with acute dietary exposure to sucrose and the identification of potential biomarkers of sucrose intake. Molecular Nutrition and Food Research 60 (2) pp. 444-457. Cadair2016.
The food metabolome: A window over dietary exposure. American Journal of Clinical Nutrition 99 (6) pp. 1286-1308. Cadair2014.
Erratum to: Brachypodium distachyon: making hay with a wild grass: [Trends in Plant Science 13 (2008) 172–177]. Trends in Plant Science 19 (3) pp. 193. Cadair2014.
Merits of random forests emerge in evaluation of chemometric classifiers by external validation. Analytica Chimica Acta 801 ACA232839 pp. 22-33. Cadair2013.
Hydroxylated phenylacetamides derived from bioactive benzoxazinoids are bioavailable in humans after habitual consumption of whole grain sourdough rye bread. Molecular Nutrition and Food Research 57 (10) pp. 1859-1873. Cadair2013.
Dietary exposure biomarker-lead discovery based on Metabolomics analysis of urine samples. Proceedings of the Nutrition Society 72 (3) pp. 352-361. Cadair2013.
Flow infusion electrospray ionisation mass spectrometry for high throughput, non-targeted metabolite fingerprinting: A Review. Metabolomics 9 (1 Supplement) pp. S4–S29. Cadair2013.
Data-driven strategy for the discovery of potential urinary biomarkers of habitual dietary exposure. American Journal of Clinical Nutrition 97 (2 ) pp. 377-389. Cadair2013.
Deciphering systemic wound responses of the pumpkin extrafascicular phloem by metabolomics and stable isotope-coded protein labeling (ICPL). Plant Physiology 160 (4) pp. 2285-99. Cadair2012.
Fourier transform ion cyclotron resonance mass spectrometry for plant metabolite profiling and metabolite identification. Methods in Molecular Biology. Springer Nature pp. 157-176. Cadair2012.
Proline betaine and its biotransformation products in fasting urine samples are potential biomarkers of habitual citrus fruit consumption. British Journal of Nutrition 106 (6) pp. 812-824.2011.
Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods. American Journal of Clinical Nutrition 94 (4) pp. 981-991. Cadair2011.
Metabolite analysis and metabolomics in the study of biotrophic interactions between plants and microbes. In (ed) Annual Plant Reviews. Wiley pp. 25-59. Cadair2011.
Workshop Report Metabolomics and human nutrition. British Journal of Nutrition 105 (8) pp. 1277-1283. Cadair2011.
Development of high throughput plant phenotyping facilities at Aberystwyth. Phenomics Workshop. Plant and Animal Genome XIX Conference . Cadair2011.
Choosing the number of labels in image segmentation. 16th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). Cadair2011.
Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples. Metabolomics 7 (4) pp. 469-484.2011.
The metabolic transition during disease following infection of Arabidopsis thaliana by Pseudomonas syringae pv. tomato. Plant Journal 63 (3) pp. 443-457.2010.
Enhancement of plant metabolite fingerprinting by machine learning. Plant Physiology 153 (4) pp. 1506-1520.2010.
Metabolite fingerprinting of urine suggests breed-specific dietary metabolism differences in domestic dogs. British Journal of Nutrition 103 (8) pp. 1127-1138.2010.
Metabolomic analysis reveals a common pattern of metabolic re-programming during invasion of three host plant species by Magnaporthe grisea. Plant Journal 59 (5) pp. 723-737.2009.
Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'. BMC Bioinformatics 10 (227) 2272009.
Measurement of dietary exposure: a challenging problem which may be overcome thanks to metabolomics? Genes and Nutrition 4 (2) pp. 135-141.2009.
Brachypodium distachyon: making hay with a wild grass. Trends in Plant Science 13 (4) pp. 172-177.2008.
Explanatory signal interpretation and metabolite identification strategies for nominal mass FIE-MS metabolite fingerprints. Nature Protocols 3 pp. 471-485.2008.
Rice blast infection of Brachypodium distachyon as a model system to study dynamic host/pathogen interactions. Nature Protocols 3 pp. 435-445.2008.
High throughput, non-targeted metabolite fingerprinting using nominal mass Flow Injection Electrospray Mass Spectrometry. Nature Protocols 3 pp. 486-504. Cadair2008.
Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data. Nature Protocols 3 pp. 446-470.2008.
Representation, comparison, and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars. Journal of Agricultural and Food Chemistry 55 (9) pp. 3444-3451.2007.
GC-MS Peak Labeling Under ArMet. In (eds) Concepts in Plant Metabolomics. Springer Nature, Dordrecht pp. 19-28.2007.
Soil differentiation using fingerprint Fourier transform infrared spectroscopy, chemometrics and genetic algorithm-based feature selection. Soil Biology and Biochemistry 39 (11) pp. 2888-2896.2007.
Statistical measures for validating plant genotype similarity assessments following multivariate analysis of metabolome fingerprint data. Metabolomics pp. 349-355.2007.
Detecting a difference - assessing generalisability when modelling metabolome fingerprint data in longer term studies of genetically modified plants. Metabolomics 3 (3) pp. 335-347.2007.
Predicting interpretability of metabolome models based on behavior, putative identity, and biological relevance of explanatory signals. Proceedings of the National Academy of Sciences of the United States of America 103 (40) pp. 14865-14870.2006.
Rapid characterization of microbial biodegradation pathways by FT-IR spectroscopy. Journal of Microbiological Methods 67 (2) pp. 273-280.2006.
Alignment of the genomes of brachypodium distachyon and temperate cereals and grasses using bacterial artificial chromosome landing with fluorescence in situ hybridization. Genetics 173 (1) pp. 349-362.2006.
On the interpretation of high throughput MS based metabolomics fingerprints with Random Forest. Second International Symposium, CompLife 2006, Cambridge, UK, September 27-29, 2006. Proceedings. International Symposium, CompLife. Springer Nature pp. 226-235.2006.
The use of chemical profiling for monitoring metabolic changes in artificial soil slurries caused by horizontal gene transfer. Metabolomics pp. 305-315.2005.
Hierarchical metabolomics demonstrates substantial compositional similarity between genetically-modified and conventional potato crops. Proceedings of the National Academy of Sciences of the United States of America 102 (40) pp. 14458-14462.2005.
In planta measurements of oxidative bursts elicited by avirulent and virulent bacterial pathogens suggests that H2O2 is insufficient to elicit cell death in tobacco. Plant, Cell and Environment pp. 548-561.2005.
Comparison of rapid liquid chromatography-electrospray ionization-tandem mass spectrometry methods for determination of glycoalkaloids in transgenic field-grown potatoes. Analytical Biochemistry 336 (2) pp. 178-186.2005.
Models and meiosis in the ’omics era. In (eds) Recent advances in genetics and breeding of the grasses. Polish Academy of Sciences pp. 97-104. Cadair2005.
Prospects for functional genomics in a new model grass. In (ed) Plant Functional Genomics. Taylor & Francis Cadair2004.
A proposed framework for the description of plant metabolomics experiments and their results. Nature Biotechnology 22 (12) pp. 1601-1606.2004.
Potential of metabolomics as a functional genomics tool. Trends in Plant Science 9 (9) pp. 418-425.2004.
Characterization of a proteinase inhibitor from Brachypodium distachyon suggests the conservation of defence signalling pathways between dicotyledonous plants and grasses. Molecular Plant Pathology 5 (4) pp. 267-280.2004.
Laying the cytotaxonomic foundation of a new model grass, Brachypodium distachyon (L.) Beauv. Chromosome Research 12 (4) pp. 397-403.2004.
Magnaporthe grisea interactions with the model grass Brachypodium distachyon closely resemble those with rice (Oryza sativa). Molecular Plant Pathology. Wiley pp. 253-265.2004.
The AoPR10 promoter and certain endogenous PR10 genes respond to oxidative signals in Arabidopsis. Molecular Plant Pathology pp. 267-280.2004.
Food quality and microbial succession in ageing earthworm casts: standard microbial indices and metabolic fingerprinting.2003.
Use of earthworm casts to validate FT-IR spectroscopy as a 'sentinel' technology for high-throughput monitoring of global changes in microbial ecology. Pedobiologia 47 (5-6) 7th International Symposium on Earthworm Ecology. pp. 440-446.2003.
Building the molecular cytogenetic infrastructure of a new model grass. In (eds) Application of Novel Cytogenetic and Molecular Techniques in Genetics and Breeding of the Grasses. Polish Academy of Sciences pp. 77-84. Cadair2003.
Metabolic Engineering, metabolite profiling and machine learning to investigate the phloem-mobile signal in systemic acquired resistance in tobacco.2002.
Brachypodium distachyon. A new model system for functional genomics in grasses. Plant Physiology pp. 1539-1555.2001.
Genomic computing. Explanatory analysis of plant expression profiling data using machine learning. Plant Physiology pp. 943-951.2001.
A loss of resistance to avirulent bacterial pathogens in tobacco is associated with the attenuation of a salicylic acid-potentiated oxidative burst. Plant Journal 23 (5) pp. 309-621. Cadair2000.