{"id":2492,"date":"2010-08-20T20:45:43","date_gmt":"2010-08-20T18:45:43","guid":{"rendered":"http:\/\/localhost\/azgad\/wordpress\/?p=2492"},"modified":"2010-08-20T20:48:19","modified_gmt":"2010-08-20T18:48:19","slug":"omics-analysis-nurtures-the-creation-of-functional-plants-with-clinical-applications","status":"publish","type":"post","link":"https:\/\/azgad.com\/?p=2492","title":{"rendered":"Omics analysis nurtures the creation of functional plants with clinical applications."},"content":{"rendered":"

.
\nPlants produce a wide variety of metabolites from inorganic compounds,
\nsome with useful functions including health-promoting effects. The ability
\nto harness these metabolites by creating \u2018functional plants\u2019 that produce
\nthese compounds in large quantities could therefore be of considerable benefit
\n to society. It is also an intriguing research topic for plant scientists. Progress
\n in this field relies on our understanding of how the hundreds of thousands
\nof unique metabolite compounds are produced in plants. Masami Yokota
\nHirai at the RIKEN Plant Science Center (PSC) is investigating the mechanism
\n of metabolism in plants by linking metabolites to genes through omics
\nanalysis\u2014a combination of metabolome and transcriptome analyses. The
\n knowledge obtained from this approach is leading steadily to the successful
\ndevelopment of functional plants.
\n.
\nCompound synthesis by metabolism in plants<\/strong>
\n.
\nThe word \u2018metabolism\u2019 may remind many people of a reaction in which the proteins or lipids
\nwe consume as food are degraded and converted into energy. Metabolism in plants,
\nhowever, is different from this reaction,\u201d says Masami Yokota Hirai, team leader of the
\nMetabolic Systems Research Team at the RIKEN Plant Science Center (PSC). \u201cMetabolism
\n in plants is a reaction in which inorganic compounds such as nitrogen, phosphorus, and
\nsulfur are absorbed through the roots and light energy is used to produce various organic
\ncompounds including amino acids and sugars such as starch. These organic compounds
\n are called metabolites.\u201d<\/p>\n

. <\/p>\n

The production of compounds such as amino acids, sugars and vitamins, which make up the body
\n of a plant, from inorganic compounds is called \u2018primary metabolism\u2019, whereas the production of
\nmore complex compounds from primary metabolites is called \u2018secondary metabolism\u2019. \u201cA plant is
\nrooted in place and cannot move. To cope with environmental hazards, such as insects, dry
\nweather or salt damage, plants produce secondary metabolites as they are exposed to these
\nstresses. A plant maintains a constant amount of primary metabolites, but produces secondary
\nmetabolites on an as-needed basis.\u201d
\nHirai\u2019s focus on metabolism in plants is motivated by the potential uses of the vast array of metabolites
\n that plants produce. \u201cPlants produce metabolites that specific to the plant species. There are more
\n than 200,000 known unique metabolites, some of which contain nutrient, health-promoting and
\nmedical ingredients.\u201d Examples of secondary metabolites include isoflavone, anthocyanin, menthol,
\ncatechin and capsaicin (Fig. 1). These compounds are drawing attention for their health-promoting
\nfunctions. \u201cEfficient production of useful secondary metabolites will greatly help improve our health.
\nFor this reason, we are working hard to elucidate the metabolic mechanism in plants.\u201d
\n.
\nMetabolome studies<\/strong>
\n.
\n\u201cA metabolic map illustrates how metabolites are produced from inorganic substances through
\nspecific reactions, and can be as complicated as a subway route map. A partial metabolic map
\ndoes not provide enough information to understand the whole picture of metabolism. We need
\nto understand the metabolic system as a whole. To help with this, we have started to take advantage
\n of omics analysis.\u201d
\n.
\nOmics is a science that comprehensively embraces the four disciplines of genomics, transcriptomics,
\nproteomics and metabolomics, and has developed rapidly in the past decade triggered by
\n improvements in genome decoding techniques and processing speed. These improvements have
\n led to some remarkable milestones in genomic research, including sequencing of the complete genomes
\nof the flowering plant Arabidopsis thaliana, rice and soy-bean.<\/p>\n

.<\/p>\n

Similarly, the DNA microarray technique used in transcriptome analysis, the analysis of RNA
\n transcribed from DNA, has also improved dramatically over the past decade. In this technique,
\nhundreds of thousands of single-stranded DNA fragments are fixed in holes or \u2018spots\u2019 on a glass
\n substrate, and fluorescently labeled RNA are dropped onto the substrate surface. RNA
\ncomplementary to a DNA fragment will become bound to the DNA, which causes the combined
\n compound to emit fluorescent light. From the fluorescence intensity of each spot, researchers
\n can determine which genes are being expressed and to what extent. The expression of Arabidopsis
\n genes has been analyzed using this method and the data has been made publicly available via
\nthe At GenExpress database<\/a>.<\/p>\n

.
\nProgress in metabolome analysis, however, lags considerably behind that of genomic and
\n transcriptome analyses. \u201cMetabolome analysis is the least developed part of omics,\u201d says Hirai.
\n\u201cIn metabolome analysis, a mass spectrometer is used to determine the mass of molecules
\nand electrical charges contained in a specimen. From this data we can determine the types
\n and quantities of metabolites in a specimen. The work, however, is extremely difficult.
\nGenomics focuses only on DNA and transcriptomics on RNA, and the same method can
\n be used for all types of organism. In metabolomics, on the other hand, we deal with
\nmetabolites with a wide range of characteristics, such as volatility and water solubility,
\nwhich makes it impossible to conduct investigations under fixed conditions. The
\nmetabolites are also produced in highly variable amounts, tiny to large quantities,
\nand with a wide range of concentrations. So we need to share a single specimen
\n among a number of measuring instruments so that enough data can be collected.\u201d
\nThe DNA microarray technique is almost entirely automated, which allows almost
\nanybody to use it, whereas mass spectroscopy requires a highly skilled operator.
\nThis has obstructed rapid developments in metabolome analysis. Another factor
\n lies with the collected data itself. \u201cThe data obtained by mass spectrometry are
\nplotted on a graph with mass along the horizontal axis and intensity along the
\nvertical axis. A peak in the graph corresponds to a single metabolite. Of the
\n thousand or so peaks that are produced, only about 10% have been assigned
\nto specific metabolites. Most of the metabolites remain unknown. We are at a
\nloss regarding where to begin,\u201d says Hirai.
\n.
\nResearch into metabolomics started in 2000. In Japan, Kazuki Saito, group
\n director of the Metabolomic Function Research Group at the PSC, took the
\ninitiative in research on metabolomics. In those days, Saito was a professor
\n at the Graduate School of Pharmaceutical Sciences at Chiba University, and
\n Hirai attended his laboratory. \u201cI was confident that the research was not only
\n interesting but also very important. However, I had a hard time for about three
\n years because I could not find a way to understand the data itself,\u201d says Hirai,<\/p>\n

.
\nThe world\u2019s first omics analysis<\/strong>
\n.
\nIn 2004, Hirai published a paper on metabolome analysis in the Proceedings
\nof the National Academy of Sciences, USA. The article would become the
\nmost-cited paper in the field of plant biotechnology in 2005. \u201cThis paper is a
\n collection of results obtained from an integrated analysis of the transcriptome
\nand metabolome of A. thaliana. The paper does not provide new information
\non gene functions or metabolite synthesis, so I am not completely satisfied with
\nthe paper because it is a simple description of my research results. But in those
\ndays, few papers could be found on metabolome analysis. I think that the paper
\nwas highly evaluated under such circumstances because I tried to derive
\nsomething new by combining transcriptome analysis with metabolome analysis
\nfor Arabidopsis. It was a pioneering attempt at omics analysis.\u201d
\nInvestigation of all 27,000 Arabidopsis genes shows that there are multiple genes
\nthat express with the same timing. These genes are likely to be involved in the same
\nfunction. If the population of a metabolite increases while a certain gene cluster
\n is expressing and decreases when the gene cluster is not expressing, the metabolite
\n could be associated with the gene cluster. In this way, omics analysis allows
\ngenes to be linked with metabolites, making it possible to understand metabolite
\n function.
\n.
\nOne successful application of omics analysis is the 2007 discovery of a new gene
\nthat makes cruciferous vegetables produce cancer-preventing components.
\nCruciferous vegetables such as broccoli, radish, horse radish and mustard have
\na \u2018spicy\u2019 flavor that has been attributed to pungent components that originate as
\nmetabolites called glucosinolates, among which sulforaphane is known to enhance
\nthe functions of enzymes that detoxify carcinogens. Using Arabidopsis, a member
\n of the cruciferous family, Hirai successfully showed that the gene PMG1
\n controls the synthesis of glucosinolates.
\n.
\n\u201cThrough an integrated analysis of the transcriptome and metabolome of Arabidopsis,
\nwe found a gene cluster that changed with the same pattern. The gene cluster was
\nfound to contain the genes that are known to be involved in the synthesis of glucosinolates.
\n In this way, we looked into the genes, and finally reached PMG1.\u201d
\nIt was also confirmed that the functional enhancement of PMG1 in Arabidopsis promotes
\n glucosinolate synthesis. \u201cAs the amount of glucosinolate increases, the amount of
\n sulforaphane increases. This could allow us to grow vegetables with enhanced
\ncancer-preventing effects.\u201d
\n.
\nA study focusing on gene clusters associated with the synthesis of glucosinolates
\n is now under way. Hirai is interested in the gene BASS5. The base sequence of
\nBASS5 is similar to that of the genes for bile acid transporter, an animal protein. Bile
\nacid transporter is present in the cell membrane and is responsible for the intercellular
\nmovement of bile acids. When the base sequences are similar, their functions are
\nalso often similar. But since there are no bile acids in plants, the role of the proteins
\ncreated by BASS5 is particularly interesting. \u201cThe proteins were thought at first to be
\npresent in the cell membrane where they mediate the intercellular movement of
\n glucosinolates. However, we have come to understand that the proteins are likely
\n to be present not in the cell membrane but on the surface of the cell\u2019s chloroplast.
\nThis demonstrates that secondary metabolites are synthesized not only in the cellular
\n cytoplasm, but also in the chloroplasts. We think BASS5 might be associated with
\nglucosinolate intermediates moving in and out of the chloroplasts.\u201d By omics analysis
\nit was confirmed that glucosinolates are not created when BASS5 function is
\n inhibited. Omics analysis has been demonstrated in this way time and time again
\nto be a very effective tool for elucidating metabolic pathways.
\nHirai is also researching the synthesis of amino acids, particularly methionine, the
\n primary metabolite from which glucosinolates are produced. \u201cAn increase in a metabolite
\nrequires an increase in the supply of its source material, namely amino acids. We
\nshould know how to synthesize amino acids if we are to attempt to create plants
\nthat produce large amounts of useful secondary metabolites.\u201d
\n.
\nMetabolome analysis in full swing <\/strong>
\n.
\n\u201cMetabolome analysis will proceed rapidly in the years to come,\u201d says Hirai with
\nconfidence. This is thanks to an analytical technique called widely targeted metabolome
\nanalysis developed by Yuji Sawada, a special research scientist in the Metabolic
\nSystems Research Team. Associating the thousands of peaks produced by mass
\nspectrometry with metabolites has been one of the obstacles to metabolome research.
\n\u201cIn conventional targeted metabolomics, observations are made with the aim of
\nidentifying a single known kind of metabolite,\u201d says Hirai. \u201cWidely targeted metabolomics
\nis based on the idea that if the number of target metabolites can be increased,
\neventually all metabolites could be targeted, which could lead to full metabolome
\n analysis. In widely targeted metabolomics, all of the peaks in the data correspond
\n to known metabolites. This allows us to proceed to the next stage of the research
\nprogram immediately. Usually, analytical methods are developed by analytical
\nchemists and information scientists, but Dr Sawada and myself are biologists.
\nWidely targeted metabolomics is a very convenient analytical method for biologists.
\n\u201d Widely targeted metabolomics currently handles about 700 target metabolites, a
\n number that will be increased in the near future.
\n.
\nHirai also hopes to develop a new analytical method for omics analysis. \u201cIt is
\nessential to develop additional tools if we are to remain pioneers in this field
\nbecause integrated analysis of transcriptome and metabolome data is now available
\nto everyone. We are now working on developing, by trial and error, a new analytical
\nmethod that can suggest unforeseen results.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

. Plants produce a wide variety of metabolites from inorganic compounds, some with useful functions including health-promoting effects. The ability to harness these metabolites by creating \u2018functional plants\u2019 that produce these compounds in large quantities could therefore be of considerable benefit to society. It is also an intriguing research topic for plant scientists. Progress in … <\/p>\n

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