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Introduction to 'Omics '' and Systems Biology -- IntroductionIntroduction toto ‘‘OmicsOmics’’ and Systems Biology -- DemonstrationDemonstration ofof onon--lineline ‘‘OmicsOmics’’ resourcesresources -- LabLab demonstrationdemonstration ofof modernmodern ProteomicsProteomics Sixue Chen, Ph.D. Department of Botany, Plant Molecular and Cellular Biology Genetics Institute E-mail: [email protected] IntroductionIntroduction toto ‘‘OmicsOmics’’ and Systems Biology Sixue Chen, Ph.D. Department of Botany, Plant Molecular and Cellular Biology Genetics Institute E-mail: [email protected] OutlineOutline What is modern and future biological sciences ? Large scale biology – ‘Omics’: revolution in screening important traits and creation of ‘in silico’ organisms Chen lab research towards plant systems biology, an emerging discipline facilitates rational plant engineering ‘Omics’ modules – example of proteomics in addressing the differences in wheat (C3 plant) and corn (C4 plant) CentralCentral DogmaDogma ofof MolecularMolecular GeneticsGenetics (The guiding principle that controls trait expression) Protein Trait (or phenotype) Translation Seed shape DNA RNA (gene) Transcription Plant height Traits and Phenotypes are Controlled by Molecular Networks Trying to understand life without knowledge of biochemical network would be like trying to understand Shakespeare without knowledge of English grammar. Our Problems • That one gene encodes one protein, which catalyzes one reaction and determines one phenotype is no longer the case. • Manipulating one gene can cause pleiotropic effects ? • How to capture all molecules and their interactions, dynamics, regulations and turnover … ? • How to determine the rate-limiting molecule and step ? How to predict ? . Outline What is modern and future biological sciences ? Large scale biology – ‘Omics’: revolution in screening important traits and creation of ‘in silico’ organisms Chen lab research towards plant systems biology, an emerging discipline facilitates rational plant engineering ‘Omics’ modules – example of proteomics in addressing the differences in wheat (C3 plant) and corn (C4 plant) ‘Omics’ and Systems Biology • “Omics” Systems Biology- – Genomics – the comprehensive “An interdisciplinary study of whole sets of genes & approach for integrating their interactions (DNA experimental data with microarrays) mathematical modeling tools – Proteomics - the study of the full to analyze & predict the set of proteins encoded by a behavior of biological genome systems.” (Henson, 2005) – Metabolomics - the comprehensive study of the small molecules or metabolites – Bioinformatics - the application of computer & statistical techniques to the management of biological information Starvation:Starvation: ImportanceImportance ofof CassavaCassava Cassava (Manihot esculenta) - yucca, manihot, tapioca • cultivated in tropics and sub-tropics for its edible storage root • a major source of dietary energy for more than 700 million people • source for a variety of food stuffs, animal feed and industrial products • major component in micro-economies of more than 150 countries CassavaCassava tuberoustuberous rootsroots developeddeveloped fromfrom fibrousfibrous rootsroots • Tuberous roots develop form fibrous roots through massive cell division and differentiation of parenchyma cell of the secondary xylem • Not all fibrous roots are designated for tuberous root formation ProteomicsProteomics isis thethe approachapproach Fibrous Root 2D gel overlay Protein Identification Tuberous Root Compare physiological Identify Protein map for functions of the two targets for comparison with other types of roots engineering cultivars or tissue types 3D view of Fibrous Gel 3D view of Tuberous Gel ProteinHPLC Identification coupled online with Using 4000 LiquidQTRAP ChromatographyMass Spectrometer Mass Spectrometry Novel Targets for Biotechnological Application Heat shock protein 257 263 263 258 258 257 BioCassava Plus project: it is proposed to increase the yield and protein content of cassava storage roots by four-fold Galactose utilization in yeast Strategy • For each gene or condition change (i.e. delete the gene) and measure the global effect on both mRNA and protein levels. • Integrate mRNA and protein responses with the pathway model and with global network of protein interactions. • Formulate new hypotheses to explain novel observations and refine models. – Science 292: 929-934 (galactose utilization) Combines: literature knowledge, microarray, proteomics, visualization, and network techniques to refine what is known about galactose utilization in yeast. – Genome Res. 13: 244-253 (Genome scale network reconstruction) Galactose metabolism - Science 292: 929-934 Expression measurements WT control Mutant mRNA extraction Reverse transcription and fluorescent labeling of cDNA Hybridization to microarray 1 c 0 D 0 NAs 0 0 Expression measurements Microarray: • a perturbed stain vs. wt + gal, 4 replicates • statistics: maximum- likelihood estimation → 997 significant genes → 16 clusters by self-organizing maps, each cluster contains genes with similar responses over all perturbations. Expression measurements Visualizing the data gal4Δ - Blue line (p-p); Yellow line (p-d); node diameter scales with the magnitude of cha More Systems Biology to follow… Systems Biology Scheme Genome Transcriptome Proteome Metabolome Phenotype (gene) (mRNA) (protein) (metabolite) Environment transcriptomics proteomics metabolomics Representation of data in XML format - molecule identity and structure - quantification - functional status (modification and complex) - localization and dynamics Statistical association, networking and modeling New functions for genes, proteins and metabolites Hypothesis modification Simultation and phenotype explanation In Silico Plant, Prediction and Rational Engineering Outline What is modern and future biological sciences ? Large scale biology – ‘Omics’: revolution in screening important traits and creation of ‘in silico’ organisms Chen lab research towards plant systems biology, an emerging discipline facilitates rational plant engineering ‘Omics’ modules – example of proteomics in addressing the differences in wheat (C3 plant) and corn (C4 plant) Plants Produce Many Chemicals That Are Related to Our Life I. Glucosinolates derived from methionine HC C C Sinigrin Allylglucosinolate 2 H H 2 Gluconap in But-3-enylg lucosinolate HC C C C 2 H H 2 H 2 HC C C C C Glucobrassicanapin Pent-4-enylglucosinolate 2 H H 2 H 2 H 2 H Prog oitrin (2R)-2-Hydroxybut-3-enylg lucosinolate HC C C C 2 H H 2 H OH E p ip rog oitrin (2S)-2-Hydroxybut-3-enylg lucosinolate HC C C C 2 H H OH 2 OH H Nap oleiferin (2R)-2-Hydroxypent-4-enylg lucosinolate HC C C C C 2 H H H 2 OH 2 G lucoibervirin 3-M ethylthiop ropylg lucosinolate HC3 S C C C H 2 H 2 H 2 O HC S C C C C R S OH G lucoerucin 4-M ethylthiobutylg lucosinolate 3 H 2 H 2 H 2 H 2 Glucoberteroin 5-Methylthiop entylg lucosinolate HC S C C C C C HO 3 H H H H H OH 2 2 2 2 2 G lucoiberin 3-M ethylsulp hinylp ropylg lucosinolate HC3 SO C C C H H H N 2 2 2 Glucorap hanin 4-Methylsulp hinylbutylg lucosinolate HC3 SO C C C C H 2 H 2 H 2 H 2 - HC3 SO C C C C C G lucoalvssin 5-M ethylsulp hinylp entylg lucosinolate H H H H H O SO 2 2 2 2 2 3 HC SO C C C C Glucorap henin 4-Methylsulp hinylbut-3-enylg lucosinolate 3 H H H 2 H 2 G lucocheirolin 3-M ethylsulp honylp ropylg lucosinolate HC3 SO2 C C C H 2 H 2 H 2 Glucoerysolin 4-M ethylsulp honylbutylg lucosinolate HC3 SO2 C C C C H 2 H 2 H 2 H 2 glucosinolate II. G lucosinolates derived from p heny lalanine C H 2 Gluconasturtiin Phenethylg lucosinolate C C H H 2 2 H Glucobarbarin 2-Hydroxy-2-p henylethylg lucosinolate HO C C H OH 2 Glucolep ig ram in m -Hydroxybenzylg lucosinolate C H 2 Sinalbin p -Hydroxybenzylg lucosinolate CH3 O HO C H 2 Glucolimnanthin m -Methoxybenzylg lucosinolate C H 2 Glucoaubrietin p -Methoxybenzylg lucosinolate CH3 O C H 2 III. G lucosinolates derived from tryptop han Glucobrassicin Indole-3-ylm ethylg lucosinolate R1 R4=H H R4 2 Neog lucobrassicin n -Methoxyindole-3-ylm ethylg lucosinolate R1=OCH3 R4=H C - Sulp hog lucobrassicin n -Sulp hoindole-3-ylm ethylg lucosinolate R1=SO3 R4=H N R1=H R4=OH R1 4-Methoxyglucobrassicin 4-Methoxyindole-3-ylm ethylg lucosinolate R1=H R4=OCH3 Plant-insect Flavour Defense Anticarcinogenic activities N/S nutrition Growth (IAA) Biofumigation “ I do not like broccoli. And I haven't liked it since I was a little kid and my Goitrogenic mother made me eat it. And I'm property President of the United States and I'm not going to eat any more broccoli.” – George Bush Genetic Engineering Problem: Modulation of glucosinolates affects normal plant growth and development A B C D cyp79f1 Control cyp79f1 Control cyp79f1 35S::CYP79F2 Control EHF G H I cyp83a1 WT 35S::CYP83B1 WT sur1 WT ugt74 atvam Wild type atvam3-4 Wound, pathogen and insect Other factors Sulfur deficiency e.g., K+ ET JA SA AtDof AP2 ATR1 SLIM1 IQD1 Myb28/29 Myb51 shikimate anthranilate chorismate indole-3-glycerolphosphate pathway methionine phenylalanine IAA indole lignin indole-3-acetaldehyde MAM cinnamic acid indole-3-pyruvic acid tryptophan (n)homomethionine tryptamine NIT flavonoids CYP79B2/B3 CYP79F1/F2 CCoAOMT N-hydroxytryptamine coniferaldehyde/ indole-3-acetaldehyde aldoxime aldoxime coniferyl alcohol CYP71A13 indole-3-acetonitrile CYP83B1 CYP83A1 COMT S-alkylthiohydroximate S-alkylthiohydroximate sinapaldehyde/ sinapyl alcohol dihydrocamalexic acid SUR1 SUR1 thiohydroximate thiohydroximate CYP71B15 syringyl sinapate lignin esters S-GT S-GT camalexin desulfoglucosinolate desulfoglucosinolate thiohydroximate-O-sulfate
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