Combined Use of Proteomic Analysis and Enzyme Activity Assays for Metabolic Pathway Analysis of Glycerol Fermentation by Klebsiella pneumoniae Wei Wang, 1 Jibin Sun, 2 Michael Hartlep, 2 Wolf-Dieter Deckwer, 1 An-Ping Zeng 2 1 TU-BCE and 2 Biochemical Engineering Division, German Research Centre for Biotechnology, Mascheroder Weg 1, 38124 Braunschweig, Germany; telephone: 49-531-6181-188; fax: 49-531-6181-751; e-mail: aze@gbf.de Received 2 July 2002; accepted 26 February 2003 DOI: 10.1002/bit.10701 Abstract: The fed-batch fermentation of glycerol to 1,3- propanediol by Klebsiella pneumoniae displayed an un- usual dynamic behavior that can be clearly divided into four distinct phases according to cell growth and CO 2 evolution rate. Metabolism changed significantly during the different phases as reflected by the varied specific rates of substrate consumption and product formation. An assay of activities of the three initial enzymes of glyc- erol metabolism, namely glycerol dehydratase (GDHt), glycerol dehydrogenase (GDH), and 1,3-propanediol- oxidoreductase (PDOR), showed apparently different patterns of expression. To understand the culture dy- namics and patterns of enzyme formation at a more sys- temic level we analyzed the expression patterns of intra- cellular proteins of K. pneumoniae from different phases of the fed-batch fermentation using two-dimensional gel electrophoresis (2DE). Two new enzymes, namely a phosphoenolpyruvate-dependent dihydroxyacetone ki- nase (DHAK II) and a hypothetical oxidoreductase (HOR), which are directly related to glycerol metabolism and 1,3-propanediol formation, were identified among the highly expressed proteins. The changes in expression of these new enzymes and several other proteins identified from the 2DE analysis helped to understand not only the dynamic behavior of the fed-batch fermentation reported in this work but also some previously insufficiently un- derstood phenomena related to this fermentation pro- cess. In particular, we demonstrated the combined use of proteomic analysis and enzyme activity assay data for metabolic pathway analysis and for a better identifica- tion of targets for bioprocess improvement. © 2003 Wiley Periodicals, Inc. Biotechnol Bioeng 83: 525–536, 2003. Keywords: proteomic analysis; pathway analysis; glyc- erol metabolism; 1,3-propanediol; Klebsiella pneu- moniae INTRODUCTION Metabolic pathway analysis is an essential part of metabolic engineering. The main objectives of pathway analysis are the estimation of intracellular metabolic fluxes and the iden- tification of limiting metabolic steps. This should then give hints for optimization of bioprocesses either by improving the cell physiology or the genetic composition of the pro- duction strains. A prerequisite for pathway analysis is the identification of metabolic pathways involved in a biopro- cess. The traditional approach of identifying or finding metabolic pathways for a given microorganism is mainly hypothesis-driven. Hypotheses about metabolism are usu- ally made on the basis of previous knowledge of similar microorganisms and bioprocesses. The hypotheses are then checked by physiological studies and direct enzyme assay. A careful stoichiometric and flux balance analysis of the metabolism can also help to identify pathways as we pre- viously showed for pyruvate metabolism in glycerol fer- mentation by Klebsiella pneumoniae (Menzel et al., 1997; Zeng et al., 1993). The latter has been studied extensively by our group for the microbial production of 1,3- propanediol (for recent reviews, see Biebl et al., 1999; Zeng and Biebl, 2002). 1,3-Propanediol has recently attracted at- tention as a monomer for a promising new polymer, polytri- methylene terephthalate. The rapid accumulation of genomic data and fast devel- opments in proteomic analysis have generated much interest in metabolic pathway analysis. The large amount of geno- mic sequence data make it possible to reconstruct the whole potential metabolic network of an organism (Kanehisa and Goto, 2000; Karp et al., 2000; Ma and Zeng 2002; Overbeek et al., 2000). The analysis of protein expression patterns under experimental conditions given by proteomic analysis can provide much information about functionality and regu- lation of the metabolic network. This approach to the study of metabolic pathways and their regulation may be called data-driving. The rational and purposeful exploration of this Correspondence to: A.-P. Zeng Contract grant sponsors: German Academic Exchange Service (Ph.D. scholarship); European Committee Fifth Framework Project; Deutschen Forschungsgemeinschaft Contract grant numbers: QLK5-1999-01360; Sonderforschungsbereich 578 (project A5) © 2003 Wiley Periodicals, Inc.