Transcript CH 3
Bacteria • • • • Single cells Small size (1-5 mm) Rapid reproduction Genomic and genetic capabilities Bacterial Diversity • 4 billion years of evolution • Ability to thrive in extreme environments • Use nutrients unavailable to other organisms • Tremendous catalytic potential Problem to be Solved: Waste Minimization in the Chemical Industry •Most of our manufactured goods involve chemicals •Chemical industry currently based on chemicals derived from petroleum Not renewable resource Many produce hazardous wastes Use bacteria as the factories of the future Bacteria as Factories Starting materials Harnessing Catalytic Potential of Bacteria Value-added products Starting materials • Use bacteria as self-replicating multistage catalysts for chemical production • Environmentally benign • Renewable starting materials (feedstocks) Potential Feedstocks Characteristics: Candidates • • • • Glucose C6H12O6 Methane CH4 Methanol CH3OH Carbon dioxide/water CO2/H2O Inexpensive Abundant Renewable Source agricultural wastes natural gas, sewage methane atmosphere/photosynthesis Potential Products • Fuels – – – – H2 hydrogen CH4 methane CH3OH methanol CH3CH2OH ethanol Potential Products • Natural products (complex synthesis) – – – – – – – Vitamins Therapeutic agents Pigments Amino acids Viscosifiers Industrial enzymes PHAs (biodegradable plastics) Potential Products • Engineered products – Starting materials for polymers (such as rubber, plastics, fabrics) – Specialty chemicals (chiral) – Bulk chemicals (C4 acids) Problem to Solve • If bacteria are such wonderful alternatives, why are our chemicals still made from environmentally hazardous feedstocks? Bacterial processes are too expensive Nature’s Design Solutions • Competitive advantage in natural niches • Optimized parameters – Low nutrients – Defense systems Opportunity Redesign bacteria with industrially-valuable parameters optimized – Redirect metabolism to specific products – Increase metabolic efficiency – Increase process efficiency This idea has been around for 30 years, why has the problem not been solved? Metabolism as a Network • Metabolism: the complex network of chemical reactions in the cell • Must redesign the network – Understand the connections to achieve end result What’s New? • Genomics – Bacterial genomes small (1000 = human) – Hundreds of bacterial genome sequences available – Provides the blueprint for the organism (the parts list) New platform for redesign What’s New? • Increased understanding of how new kinds of metabolism arose New strategies for redesign Time before present Changing Environmental Niches Selection for novel metabolic capabilities How Build Novel Metabolic Pathways? • Whole metabolic pathways: no single gene or small number of genes confer selective advantage • Cannot build a step at a time Dilemma: how were entire pathways constructed during evolution? Modular Aspect of Metabolism • Metabolic capabilities were built in blocks, like puzzle pieces Strategy: Understand the modules and their connections Redesign in blocks Methanol as an Alternative Biofeedstock • • • • Soluble in water Inexpensive Pure substrate Bacteria that use it well-studied CH3OH chemicals Methylotrophic Bacteria CH3OH (methanol) O2 CO2, H2O, cells Specified product Methylobacterium extorquens AM1 •Grows on one-carbon compounds (methanol, methylamine) •Also grows on multi-carbon compounds (succinate, pyruvate) •Substantial toolkit for genetic analyses •Genome sequence (with UW HGC) •Plant symbiont Clover leaf print showing pink Methylobacterium strains Approach • Define functional modules by experimental and evolutionary analysis methanol MEDH MADH CH OH HCHO 3CH2 NH 3 cytcL amicyanin H4F H4MPT Assimilation Dissimilation MethyleneHCHO H4F Methylene H 4MPT NADH CO2 NADPH Methenyl NADPH H4F Methenyl H4MPT Serine N10-Formyl H4F cycle N5-Formyl H4MPT ATP Formate BIOMASS C3 Compounds Formyl MFR Purines NADH fMet-tRNA 2H x CO2 •Manipulate modules to optimize product •Optimize process parameters CO2 product CO2 Methylotrophy CH3-X HCHO Biosynthesis (assimilation) C3 CO2 Energy metabolism (dissimilation) Biomass PHA (biodegradable plastic) Approach and Results • Identify the components – Identify the genes and enzymes – Determine their function • Results fmdCffs fmdAfmdBorf4 mtdBorfY mch orf5 orf7fae orf17orf9mxaEmxaD mxaD orf19orf20orf21orf22 1 1 2 – Identified over 100 genes – Generated mutants in each – Analyzed which functions are missing • • • • Growth Enzyme activities Measure cofactors Study expression of genes Methanol Methylamine Methanol mxaWFJGIRSACKLDEHB Methylamine mauFBEDACJGLMN pqqABC/DE, pqqFG mxbDM, mxcQE Primary Oxidation Formaldehyde Formaldehyde NAD(P) H4MPT Formaldehyde Biosynthesis fae orf4 (orf7,9,17,19 20,21,22) NAD(P)H MFR H4MPT Formate Oxidation Methenyl Formyl-H4MPT Formyl MFR H4MPT mch fhcABCD Methylene mtdB H4MPT (mtdA) H4MPT Formate H4F, ATP H4F Biosynthesis folBCEKP dyr Purines (spont.) C1 Transfer H4F pathway H4F NAD NADH fdh3ABC cytbred cytbox fdh2ABCD fch NADP NADPH Methylene H4F fdh1AB ftfL Formyl H4F Methenyl H4F mtdA CO2 C1 Assimilation pccAB Propionyl-CoA Methylmalonyl-CoA Methylotrophic Metabolic Modules mcmAB meaBD epm Succinyl-CoA BIOSYNTHESIS TCA Cycle scsAB Succinate kst NADP FADH ppc eno OAA PEP mtkAB qscR (reg.) 2PGA Hydroxypyruvate aKG sga Serine Isobutyryl-CoA Methylsuccinyl-CoA ccr Regeneration Cycle Ethylmalonyl-CoA croA pccAB mclA Malyl-CoA (L)- b mcl NAD NADH Butyryl-CoA hbdB ccr phaA Acetyl-CoA Glycerate hpr ibd2 pccA,B Fumarate Glyoxylate Malate Glyoxylat Serine sgaA e Cycle glc NADPH fumA Malate mdh meaC Methacrylyl-CoA CO2 sdhABCD FAD Fumarate meaA b-hydroxyisobutyryl-CoA Glyoxylate Succinyl-CoA Acetoacetyl-CoACrotonyl-CoA phaA Acetoacetyl-CoA phaB sga Glycine glyA Methylene H4F phaR (reg.) PHB Cycle PHB croR (D)-b-Hydroxybutyryl-CoA Methylotrophic Metabolic Modules Methanol Methanol Oxidation PHA PHA cycle Glyoxylate Regeneration cycle Formaldehyde Serine cycle TCA cycle Methylene H4F H4MPT-linked C1 transfer H4F-linked C1 transfer Formate CELLS FDH2 FDH1 CO2 FDH3 Constraints • Understanding how the system is integrated in time and space • Changing how it works Work in Progress: gene expression • Use genome-wide techniques to assess expression of genes within each module DNA expression microarrays Expression Microarrays (DNA Chips) •Design a segment of DNA complementary to a small stretch of every gene in the genome •Specific to that gene •Can be used to detect that gene •Spot a sample of these DNA molecules in a very small spot (usually on a microscope slide)--common to have 10,000 spots/slide ATGGCTTAAAGATCCCATGGCTA Expression Microarrays (DNA Chips) •Extract RNA from cells, make a DNA copy (cDNA), label with a fluorescent dye •Condition 1: label green •Condition 2: label red •Mix, hybridize to the slide •Each mRNA fragment only binds to the spot containing the gene •If no change in expression: yellow •If expression went up in Condition 1: green •If expression went up in Condition 2: red QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. Expression Microarrays (DNA Chips) QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. •If no change in expression: yellow •If expression went up in Condition 1: green •If expression went up in Condition 2: red •If expression is below the detection limit, no color •Results reported as fold change (difference) Work in Progress: proteomics • Use genome-wide techniques to assess expression of proteins within each module proteomics: proteins Julia Vorholt group •Separate all proteins in cell by size and then by charge •Cut out samples (spots), generate a mass pattern (mass spectrometry) •Use mass to predict peptide •Search genome to identify •Can compare with the same conditions as the microarray Work in Progress: Flux Analysis • Use flux-balance model (Palsson) 2 NADPH G6P 0.29 R5P 0 Biomass yield: 4.98 PP Pathway 0.01 NADH – Mass balance equation for each reaction – Use genome sequence to deduce metabolic pathways – Use optimization techniques to solve for biomass production – Problem: underdetermined F6P E4P a-KG 0.09 0.03 Triose-P 0.04 Citrate 0.35 0 Ac-CoA PEP CO2 2.27 Butyryl-CoA 3.27 Serine Acetyl-CoA Conversion Pathway 1.00 FADH2 Glyoxylate Ac-CoA NADPH Glycine 1.00 NADPH 0.62 2.92 Hydroxybutyryl-CoA 3.21 0.46 6.17 5.55 HCHO 3.84 Methylene-H4F 0.62 NADPH ATP Formate Cell membrane 10.00 CH3OH •Confirm model with 13C-labeling –Steady-state labeling with 13C-substrate (chemostat) –Measure isotoper distribution for amino acids –Deduce fluxes PHB NADH 0 4 H+ext 0.56 HCHO 2e- S. Van Dien Propionyl-CoA 3.27 Serine Cycle Methylene-H4MPT CO2 NADH 2 e- Malyl-CoA 3.27 OAA 2.56 3.17 CO2 NADPH 2 e- 1.00 1.00 Malate 0 0.21 2.83 Succinate 2 NADH Pyruvate 2-PG TCA Cycle 0.09 3-PG 0.35 Succ-CoA 0 0.30 CO2 NADH 2 H+ext 19.3 ATP Work in Progress: overview • Use genome-wide techniques to assess expression of genes within each module – Microarrays: mRNA – Proteomics: proteins • Use flux-based techniques to understand how the pathways work – Metabolic modeling: predictions about flow through each module – Labeling techniques: measure flow through each module BIOMASS CO2 Results: redesign the metabolic network to overproduce a biodegradable plastic Summary Breadth of bacterial diversity provides opportunity Environmentally benign aspects provide impetus New approaches provide strategies Result: increasing number of microbiallybased products over the next several years