Abstract
The myth of detecting, quantifying and identifying every single metabolite produced by a living cell is still far from reality, mainly because of current analytical limitations, in particular the variability and losses introduced when using different sampling, sample preparation and detection methods. In addition, a more accurate quantification of metabolites is required in order to obtain a more powerful metabolomics dataset, and isotope-tag designed for metabolomics seems to be the latest and most feasible approach for a global quantification of metabolites. These were some of the highlights of the 1st Australasian Symposium on Metabolomics held in Auckland, New Zealand.
On 5 July 2009, some 125 professionals from across the globe gathered in Auckland, New Zealand, for the first-ever Australasian Symposium on Metabolomics – the first international convening of practitioners of metabolomics held in that region. The symposium was co-organized by Silas Villas-Bôas, a Senior Lecturer in Microbiology at the School of Biological Sciences, University of Auckland, and Ute Roessner, a node leader of Metabolomics Australia and the Australian Centre for Plant Functional Genomics, based at the School of Botany, University of Melbourne.
For an unprecedented few days, the cream of the Australasian metabolomics cadre – a relatively small, but growing group of professionals – enjoyed the rare opportunity of meeting and learning from each other and from overseas groups; discussing, clarifying and planning their common goals and diverse experiences; acknowledging the obstacles to success and sharing realistic strategies for overcoming them.
The symposium was constructed around six topical sessions: human and mammalian metabolomics; plant metabolomics; microbial metabolomics; fluxomics and systems biology; advances in analytical methods and data analysis, scheduled over 2 days. Each session began with a keynote lecture presentation by an academic or research scientist, followed by various short oral presentations. The symposium also had three plenary lectures of general interest, given by invited speakers renowned in their fields. It started on Sunday 5 July, with the opening lecture by David Wishart (University of Alberta, Canada) speaking about the Canadian initiative for a comprehensive characterization of the human metabolome, followed by interesting lectures by Lars Nielsen (University of Queensland, Australia), on Monday 6 July, who talked about genome-scale metabolic modeling in mammalian systems, and by Paul Chambers (The Australian Wine Research Institute, Adelaide, Australia), who gave the last plenary lecture, on the morning of Tuesday 7 July, about the application of systems biology to industrial yeasts.
The title of the works presented in the symposium ranged widely, from metabolomics of model organisms, such as Saccharomyces cerevisiae, Escherichia coli, Arabidopsis thaliana and Mus musculus, to novel analytical approaches using new-generation MS, to different approaches for data handling and interpretation, metabolomics of cancer cells, juvenile pig plasma, Sauvignon Blanc grape juice, snake venoms and the application of metabolomics to study transport-induced stress in sheep.
Participants agree that analytical methods for coverage of full metabolomes are still far from being a reality and there was a general consensus that accurate quantification of metabolites is important information usually missing in metabolomics studies. As pointed out by Professor Wishart, the metabolomics field has a lot to benefit from new analytical approaches designed for quantitative metabolite profiling based on differential isotope labeling. Professor Wishart talked about a chemical derivatization strategy developed by Guo and Li at the University of Alberta, Canada, based on dansylation reaction for absolute and relative quantification of amine- and phenol-containing metabolites in complex samples Citation[1]. Instead of adding an isotope analogue of each metabolite of interest, this new strategy is focused on a differential isotope-labeling derivatization reaction to introduce an isotope tag to metabolites in one sample and another mass-difference isotope tag to the same metabolites in another comparative sample (e.g., sample replicate or standard solution), followed by mixing the two labeled samples for MS analysis. This way, each metabolite can be relatively quantified based on its own isotope-labeled internal standard and it could even be absolutely quantified if the comparative sample is a standard solution with known concentrations of metabolites.
Another opinion shared by a great majority of the symposium delegates was that, despite the analytical side of metabolomics being well advanced, data analysis and consequent biological interpretation of the data remain major bottlenecks in metabolome analysis. However, a great number of software and strategies presenting distinct capabilities have been developed recently by different companies and institutions and some have been presented and demonstrated during the symposium (i.e., AnalyzerPro® for GC–MS and LC–MS data mining from SpectralWorks Ltd; MarkerView™ for metabolomics and protein/peptide biomarker profiling from Applied Biosystems; the new Mass Profiler Professional from Agilent Technology; the Pathway Activity Profiling [PAPi] approach for interpretation of metabolomics data presented by Aggio et al. from the University of Auckland in New Zealand; the Metabolome-Express Project for processing, visualization and biological interpretation of GC–MS metabolomics data presented by Carroll et al. from the Australian National University, Australia).
Concerns were raised regarding the impact of sample preparation and analytical methodologies on the biological interpretation of metabolomics data. It is clear today that different analytical methods favor the detection of different groups of metabolites and Duportet et al. (University of Auckland, New Zealand) presented disturbing findings using different methods to extract intracellular metabolites from different microbial cell models, which resulted in very distinct metabolite profiles depending on the extraction procedure used. The different metabolite profiles resulted in contrasting biological interpretation of metabolomics data generated from the same set of samples. This is a problem that has to be seriously considered in any metabolomics based study. This problem was also highlighted by Jens Krömer from the Australian Institute for Bioengineering and Nanotechnology (University of Queensland, Australia) who also stressed the variability introduced by inappropriate quenching of cell metabolism and losses of intracellular metabolites during quenching.
In addition to the exciting scientific presentations, the symposium offered great opportunities for networking, mingling and meetings. Breaks between the lectures were held among booths from commercial companies or large institutions either providing instrumentation and small equipment for metabolomics research or offering service and advice to beginners in the field. During each lunch break, time was given to examine 37 posters presenting examples covering the breath of applications of metabolomics in biological sciences.
Lastly, the symposium would not have happened without the generous financial support of various vendors and institutions, such as Bioplatforms Australia, Metabolomics Australia, Agilent Technologies Inc, the Institute for Innovation in Biotechnology, AgResearch Ltd, Shimadzu Scientific Instruments Pty Ltd, Thermo Scientific, Applied Biosystems Inc., Biocrates Life Sciences, Bruker Corporation and the International Conference Fund of the Royal Society of New Zealand. But most of all we need to thank the delegates who have shared their work and contributed to scientific discussions, providing the basis for knowledge exchange and the prerequisite for new ideas to be born in order to improve metabolomics technologies or apply them more efficiently to answer the question of interest. Due to the extremely positive feedback we received during and after the symposium, we have decided to repeat this meeting next year. The Metabolomics Australia node at The University of Melbourne has kindly offered to host the 2nd Australasian Symposium on Metabolomics in Victoria, Australia in 2010. We are looking forward to seeing you there!
Study of the dynamic changes of molecules within a cell over time (metabolic flux). It is essentially a neologism of flux balance analysis with a wider and more systematic framework
New field of life science focused on the interdisciplinary study of complex interactions in biological systems and how these interactions give rise to the function and behavior of that system (e.g., the enzymes and metabolites in a metabolic pathway)
The collection of all relevant metabolic information of an organism and their compilation in a mathematical language, allowing various types of in silico analyses to be performed. A metabolic model allows for an in-depth insight into comprehending the molecular mechanisms of a particular organism, especially correlating the genome with molecular phenotype
An isotope-labeled chemical tag added to a specific group of metabolites through a chemical derivatization reaction. An isotope tag has the ability to distinguish an analyte encoded with a non-native isotope from those not encoded with the isotope or from those encoded with a different isotope
The complete stopping of cell metabolism usually performed during or immediately after sampling. It is an essential step in sample preparation for metabolome ana lysis
Financial & competing interests disclosure
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.
Bibliography
- Guo K , LiL. Differential 12C-/13C-isotope dansylation labeling and fast liquid chromatography/mass spectrometry for absolute and relative quantification of metabolome. Anal. Chem. 81(10), 3919–3932 (2009).