Systems biotechnology for strain improvement.

Various high-throughput experimental techniques are routinely used for generating large amounts of omics data. In parallel, in silico modelling and simulation approaches are being developed for quantitatively analyzing cellular metabolism at the systems level. Thus informative high-throughput analysis and predictive computational modelling or simulation can be combined to generate new knowledge through iterative modification of an in silico model and experimental design. On the basis of such global cellular information we can design cells that have improved metabolic properties for industrial applications. This article highlights the recent developments in these systems approaches, which we call systems biotechnology, and discusses future prospects.

[1]  A. Burgard,et al.  Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions. , 2001, Biotechnology and bioengineering.

[2]  S. Junne,et al.  Transcriptional analysis of product‐concentration driven changes in cellular programs of recombinant Clostridium acetobutylicumstrains , 2003, Biotechnology and bioengineering.

[3]  B. Palsson,et al.  The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Dong-Eun Lee,et al.  Global Analyses of Transcriptomes and Proteomes of a Parent Strain and an l-Threonine-Overproducing Mutant Strain , 2003, Journal of bacteriology.

[5]  B. Palsson,et al.  An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR) , 2003, Genome Biology.

[6]  Hiroaki Kitano,et al.  Next generation simulation tools: the Systems Biology Workbench and BioSPICE integration. , 2003, Omics : a journal of integrative biology.

[7]  Karl Sanford,et al.  Genomics to fluxomics and physiomics - pathway engineering. , 2002, Current opinion in microbiology.

[8]  Manor Askenazi,et al.  Integrating transcriptional and metabolite profiles to direct the engineering of lovastatin-producing fungal strains , 2003, Nature Biotechnology.

[9]  Sang Yup Lee,et al.  Proteome profiling and its use in metabolic and cellular engineering , 2003, Proteomics.

[10]  B. Palsson,et al.  Genome-scale models of microbial cells: evaluating the consequences of constraints , 2004, Nature Reviews Microbiology.

[11]  Thomas Szyperski,et al.  Intracellular Carbon Fluxes in Riboflavin-Producing Bacillussubtilis during Growth on Two-Carbon Substrate Mixtures , 2002, Applied and Environmental Microbiology.

[12]  J. Ohnishi,et al.  Efficient 40°C fermentation of l-lysine by a new Corynebacterium glutamicum mutant developed by genome breeding , 2003, Applied Microbiology and Biotechnology.

[13]  G. Church,et al.  Genome-Scale Metabolic Model of Helicobacter pylori 26695 , 2002, Journal of bacteriology.

[14]  Sang Yup Lee,et al.  Engineering Escherichia coli for Increased Productivity of Serine-Rich Proteins Based on Proteome Profiling , 2003, Applied and Environmental Microbiology.

[15]  B. Palsson,et al.  Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. , 2003, Genome research.

[16]  Masaru Tomita,et al.  E-CELL: software environment for whole-cell simulation , 1999, Bioinform..

[17]  Wolfgang Wiechert,et al.  Modeling and simulation: tools for metabolic engineering. , 2002, Journal of biotechnology.

[18]  V. Gavrilovic,et al.  Genome shuffling of Lactobacillus for improved acid tolerance , 2002, Nature Biotechnology.

[19]  Eve Syrkin Wurtele,et al.  Functional genomics: high-throughput mRNA, protein, and metabolite analyses. , 2002, Metabolic engineering.

[20]  G. Church,et al.  Analysis of optimality in natural and perturbed metabolic networks , 2002 .

[21]  Sang Yup Lee,et al.  MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis , 2003, Bioinform..

[22]  Markus J. Herrgård,et al.  Integrating high-throughput and computational data elucidates bacterial networks , 2004, Nature.

[23]  Kiran Raosaheb Patil,et al.  Use of genome-scale microbial models for metabolic engineering. , 2004, Current opinion in biotechnology.

[24]  A. Burgard,et al.  Optknock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization , 2003, Biotechnology and bioengineering.

[25]  S. Lee,et al.  Combined transcriptome and proteome analysis of Escherichia coli during high cell density culture. , 2003, Biotechnology and bioengineering.

[26]  Patrick Lincoln,et al.  BioSPICE: access to the most current computational tools for biologists. , 2003, Omics : a journal of integrative biology.

[27]  M. Mavrovouniotis,et al.  Simplification of Mathematical Models of Chemical Reaction Systems. , 1998, Chemical reviews.

[28]  A. Pühler,et al.  Genome-wide analysis of the L-methionine biosynthetic pathway in Corynebacterium glutamicum by targeted gene deletion and homologous complementation. , 2003, Journal of biotechnology.

[29]  Guy Plunkett,et al.  Engineering a reduced Escherichia coli genome. , 2002, Genome research.

[30]  V. Vinci,et al.  Improvement of microbial strains and fermentation processes , 2000, Applied Microbiology and Biotechnology.

[31]  Stephen S Fong,et al.  Metabolic gene–deletion strains of Escherichia coli evolve to computationally predicted growth phenotypes , 2004, Nature Genetics.

[32]  Markus J. Herrgård,et al.  Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. , 2004, Genome research.

[33]  Igor Goryanin,et al.  Mathematical simulation and analysis of cellular metabolism and regulation , 1999, Bioinform..

[34]  J. Ohnishi,et al.  A novel methodology employing Corynebacterium glutamicum genome information to generate a new L-lysine-producing mutant , 2001, Applied Microbiology and Biotechnology.

[35]  Michael Y. Galperin,et al.  Genomes back-to-back: when sequencing race is a good thing. , 2004, Environmental microbiology.

[36]  J. Stelling Mathematical models in microbial systems biology. , 2004, Current opinion in microbiology.

[37]  Seok Jae Lee,et al.  Enhanced Production of Insulin-Like Growth Factor I Fusion Protein in Escherichia coli by Coexpression of the Down-Regulated Genes Identified by Transcriptome Profiling , 2003, Applied and Environmental Microbiology.

[38]  J. Ohnishi,et al.  Efficient 40 degrees C fermentation of L-lysine by a new Corynebacterium glutamicum mutant developed by genome breeding. , 2003, Applied microbiology and biotechnology.

[39]  Mee-Jung Han,et al.  Proteome Analysis of Metabolically EngineeredEscherichia coli Producing Poly(3-Hydroxybutyrate) , 2000, Journal of bacteriology.

[40]  K. Shimizu,et al.  Fermentation characteristics and protein expression patterns in a recombinant Escherichia coli mutant lacking phosphoglucose isomerase for poly(3-hydroxybutyrate) production , 2003, Applied Microbiology and Biotechnology.

[41]  C. Wittmann,et al.  Modeling and experimental design for metabolic flux analysis of lysine-producing Corynebacteria by mass spectrometry. , 2001, Metabolic engineering.

[42]  R. Brent,et al.  Modelling cellular behaviour , 2001, Nature.

[43]  R. Aebersold,et al.  Proteomics: the first decade and beyond , 2003, Nature Genetics.

[44]  Thomas Hermann,et al.  Using functional genomics to improve productivity in the manufacture of industrial biochemicals. , 2004, Current opinion in biotechnology.

[45]  Masaru Tomita,et al.  Toward large-scale modeling of the microbial cell for computer simulation. , 2004, Journal of biotechnology.

[46]  Stephen G. Oliver,et al.  1 Introduction to Functional Analysis of the Yeast Genome , 1998 .

[47]  G. Stephanopoulos,et al.  Exploiting biological complexity for strain improvement through systems biology , 2004, Nature Biotechnology.

[48]  Pedro Mendes,et al.  GEPASI: a software package for modelling the dynamics, steady states and control of biochemical and other systems , 1993, Comput. Appl. Biosci..

[49]  J. Nielsen,et al.  Impact of 'ome' analyses on inverse metabolic engineering. , 2004, Metabolic engineering.

[50]  Sang Yup Lee,et al.  The genome sequence of the capnophilic rumen bacterium Mannheimia succiniciproducens , 2004, Nature Biotechnology.

[51]  C. Wittmann,et al.  In-Depth Profiling of Lysine-Producing Corynebacterium glutamicum by Combined Analysis of the Transcriptome, Metabolome, and Fluxome , 2004, Journal of bacteriology.

[52]  George M Church,et al.  On the complete determination of biological systems. , 2003, Trends in biotechnology.

[53]  Gregory Stephanopoulos,et al.  Metabolic engineering by genome shuffling , 2002, Nature Biotechnology.

[54]  J. Edwards,et al.  Systems Properties of the Haemophilus influenzaeRd Metabolic Genotype* , 1999, The Journal of Biological Chemistry.