Bridging the Gap between Fluxomics and Industrial Biotechnology. (22nd November 2010)

• Record Type: Journal Article
• Authors: Feng, Xueyang; Page, Lawrence; Rubens, Jacob; Chircus, Lauren; Colletti, Peter; Pakrasi, Himadri B.; Tang, Yinjie J.
• Other Names: Sá-Correia Isabel Academic Editor.
• Is Part Of: Journal of biomedicine and biotechnology. Volume 2010(2010)
• Publication Date: 2010-11-22
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Medicine; Biology; Biotechnology; Médecine; Biologie; Biotechnologie; Biology; Biotechnology; Medicine; Biotechnology; Biomedicine; Electronic journals; Periodical; Periodicals; Electronic journals; 610
• DOI: 10.1155/2010/460717
• Languages: English
• ISSNs: 1110-7243

Abstract

Abstract : Metabolic flux analysis is a vital tool used to determine the ultimate output of cellular metabolism and thus detect biotechnologically relevant bottlenecks in productivity. 13 C-based metabolic flux analysis ( 13 C-MFA) and flux balance analysis (FBA) have many potential applications in biotechnology. However, noteworthy hurdles in fluxomics study are still present. First, several technical difficulties in both 13 C-MFA and FBA severely limit the scope of fluxomics findings and the applicability of obtained metabolic information. Second, the complexity of metabolic regulation poses a great challenge for precise prediction and analysis of metabolic networks, as there are gaps between fluxomics results and other omics studies. Third, despite identified metabolic bottlenecks or sources of host stress from product synthesis, it remains difficult to overcome inherent metabolic robustness or to efficiently import and express nonnative pathways. Fourth, product yields often decrease as the number of enzymatic steps increases. Such decrease in yield may not be caused by rate-limiting enzymes, but rather is accumulated through each enzymatic reaction. Fifth, a high-throughput fluxomics tool hasnot been developed for characterizing nonmodel microorganisms and maximizing their application in industrial biotechnology. Refining fluxomics tools and understanding these obstacles will improve our ability to engineer highlyefficient metabolic pathways in microbial hosts.