Biochemical engineering. Bridging the gap between gene and product.

century. Biochemical engineers havealways served as a bridge between discoveries involvingenzymes, cells and biomass at the lab scale to implementa-tion of valuable bioproducts on the commercial scale. In thepast 15 years, a plethora of commercial products based uponrecombinant DNA technology has emerged, many of whichare therapeutic proteins. Improvements in bioprocessdesign by the biochemical engineer required more intimateknowledge of the driving forces of the technology: genes,enzymes, and cells. In the same time frame, the training ofbiochemical engineers, which historically provided a holis-tic view of biochemical systems through quantitativeexperimental and mathematical descriptions, expanded toalso include basic understanding of the tenets of molecularbiology. Biochemical engineers have the skills to not onlydevelop processes for chemical and materials based uponmolecular biology, but to influence the conception anddevelopment of new technologies through organization andsynthesis of complex biological phenomena. The profusion of genome-sequencing projects in progresswill lead to the discovery of genes for new enzymes. Asacknowledged by many in the research community, theemerging challenge will be to connect gene to function,genotype to phenotype. The creation of technologies toassess the function of genes as well as the smorgasbord ofnew enzymes discovered will have a direct impact on bio-chemical engineering by enabling the design of newbiocatalysts as well as through the creation of new products.Areas of research such as metabolic engineering—the useof recombinant DNA technology to engineer new cells,organisms, or tissues—will be directly impacted. In the effort to link genome to function, microarray andother technologies have been developed for the analysis ofgene expression at the mRNA level. The next link in thechain, however, between mRNA level and protein level, istenuous. In fact, experimental evidence shows a disparitybetween mRNA levels and those of their correspondingproteins. In groundbreaking work, Hatzimanikatis andLee [1] have shown mathematically that expression pat-terns from both mRNA and proteins are required tounderstand a gene network. In a parallel set of reviews,Lee and co-workers have provided details of genomicanalysis and proteomic analysis. In the first article, Lee andLee (pp 171–175) review the latest technologies forgenome sequencing and for high-throughput techniquesfor investigation of gene expression. With an eye for quan-tification, they comment on computational approaches tosupplement experimental approaches in relating genotypeto phenotype. This review naturally leads to the secondreview on proteomics by Dutt and Lee (pp 176–179). Akey bottleneck in proteomics is the development of tech-nology to quantify synthesis rates, expression levels, andpost-translational modification of proteins accurately in ahigh-throughput manner. The complexity and enormous volume of data resultingfrom the genomic era points to the need for mathematicalapproaches to establish links between genes and theirfunction. Major advances have been made in the ‘down-stream’ part of the chain, that is, the mathematicalmodeling of metabolism from a defined metabolic grid.The group of Nielsen has made significant progress in thearea of modeling of steady–state metabolism through thedevelopment of metabolic network analysis (MNA) [2].MNA combines the widely used metabolic flux analysiswith isotopic labeling experiments for a more reliable esti-mation of intracellular fluxes, as well as analysis of themetabolic pathway structure and compartmentation ofenzymes and metabolites. In their review, Gombert andNielsen (pp180–186) assess critically the steady-state sto-ichiometric mathematical models and the more powerfuldynamic kinetic models. In particular, they highlight thedifficulties in dynamic modeling of regulatory and controlaspects of metabolism, which are currently limited byincomplete characterization. They suggest that theseissues will be resolved with further development of func-tional modeling of genetic networks (e.g. [1]).The heart of biochemical engineering in practice is toenable the commercial production of chemicals, materials,and biomolecules. The National Research Council Reporton Biobased Industrial Products [3], released in late 1999,emphasizes increasing the use of biological raw materialsto make ‘biobased industrial products’, thus helping toachieve long-term sustainability for global economic sys-tems. New technologies and products shaped by the