Agilent Measurement Journal - Issue 3 - 2007 - (Page 57)

Deﬁning metabolomics and the metabolome R Rice is a primary food source for more than 3 billion people worldwide. Approximately 600 million people derive more than half of their calories from rice, and it is the third largest commercial crop behind wheat and corn. In 2005, an estimated 50 percent of the potential yield of the world rice crop was lost to diseases caused by bacteria, fungi and viruses. In Africa and Asia, the most serious bacterial infection in rice is bacterial leaf blight (BLB), caused by Xanthomonas oryzae pv. oryzae (Xoo). Breeding and deployment of resistant rice cultivars carrying major resistance genes has been the most effective approach to combating BLB; one such gene, Xa21, has been successfully cloned into the rice variety Taipei 309 (TP309). PXO99 is a bacterial strain of Xoo that spreads rapidly from rice plant to rice plant. Infected leaves develop lesions, become yellow, and wilt in a matter of days (Figure 1). TP309 PX099 TP309-Xa21 PX099 Metabolomics is the comparative analysis of metabolites — the intermediate or ﬁnal products of cellular metabolism — found in sets of similar biological samples. By measuring the “abundance proﬁles” of these metabolites, metabolomics can identify potential biomarkers and identify the effects drugs or diseases have on known or unexpected biological pathways. Metabolomics is a small molecule analysis problem (molecular weight <1500), often of highly complex samples in which the analyte’s chemical identity is usually unknown. The biological matrices containing the analytes typically include serum, plasma, erythrocytes, urine and cells. Due to the diverse physico-chemical properties of the analytes and orders-of-magnitude concentration ranges, metabolite detection requires a variety of extraction and analytical techniques. The domain of this work is the metabolome, which is considered to be the small-molecule chemical equivalent of the genome. It represents the collection of all metabolites in a biological organism. Because the metabolome is closely associated with the genotype of an organism, metabolomics can play an important role in unraveling genotype/phenotype relationships. Summarizing sample extraction and analysis workﬂows Several key steps in metabolomics require careful consideration when planning an experiment. When performing either generic or targeted sample extractions, the method must effectively yield either a comprehensive or speciﬁc set of cellular or bioﬂuid metabolites while excluding components that are not intended for analysis such as proteins and other compounds with high molecular weight. The extracted sample or analyte must also be in a state that is compatible with the downstream analytical techniques. Figure 1. These rice leaves show both diseased and healthy states. In collaboration with Dr. Oliver Fiehn and Dr. Pamela Ronald, our scientiﬁc partners at the University of California, Davis (UCD), we applied metabolomics methods to differentiate two rice genotypes: one susceptible (TP309) and the other resistant (TP309_ Xa21) to infection by BLB. This work was facilitated by Agilent’s University Grants Program, and the following is the ﬁrst example of a joint metabolomics research project. Agilent Measurement Journal 57

Table of Contents Feed for the Digital Edition of Agilent Measurement Journal - Issue 3 - 2007

Applying Ingenuity to the Measurement of Emerging Technologies Contents Emerging Innovations Department Delivering Bigger Benefits by Optimizing Customer Workflows Measuring Material Properties at the Nanoscale Utilizing In Situ Atomic Force Microscopy in Life Science, Pharmaceutical and other Bio-Related Applications WiMAX™: Plotting a New Path to Global Mobility Addressing the Triple Complexity of Triple-Play Networks What Next for Mobile Telephony? Exploring the Inner Workings of Tire-Pressure Monitoring Systems Developing, Assessing and Applying a High-Resolution Thin-Film Magnetic Probe Making Accurate Settling-Time Measurements Using a Vector Network Analyzer Applying Metabolomics Methods to the Study of Bacterial Leaf Blight in Rice Plants Measuring Stream Dynamics with Fiber Optics survey

Agilent Measurement Journal - Issue 3 - 2007

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