Metabolic and Cellular Engineering of Protein Secretion
Supported generously by NSF, the USDA ARS, and the New York State Office
of Science, Technology and Academic Research
The basic metabolic engineering approach is to improve cellular activities by using
recombinant DNA technology. The limited success of this approach can be attributed to the
inability to assign a genetic basis for any particular phenotype. This results from the
epigenetic and multifactorial nature of phenotypes. The manipulation of one gene can have
an affect on several different proteins, and a particular cellular characteristic can be
modulated by several seemingly different genes. We alleviate this bottleneck in the metabolic
engineering paradigm by studying both proteomics and mRNA
expression profiles. This approach helps to identify an underlying
subset of possible genetic targets and provides key information in understanding protein
secretion. This knowledge can be used as a guide in the engineering of organisms
with new or enhanced properties. Currently, we are studying Escherichia coli cells and
Chinese hamster ovary (CHO) cells with enhanced recombinant protein production and secretion. We have
found that a decrease in the protein synthesis rate can offer up to 9-fold improvement
in product secretion in E. coli using the hemolysin pathway and found that certain
alterations of the actin cytoskeleton in CHO cells can enhance secretion two fold.
One of the key issues in such an endeavor is to understand the limits and advantages of such
gene expression profiling technologies. We have been engaged in a significant effort to employ
state-of-the-art shotgun proteomics methods to the understanding of gene expression regulation
of Pseudomonas syringae, a bacterial plant pathogen. Working with colleagues from the ARS
and across campus, we use an in-house database of all
possible translation products based on the genome sequence of this pathogen to anchor open reading
frames and to quantify changes in these proteins using iTRAQ technology. As part of this larger
effort, we hope better understand gene expression regulation in this pathogen.
The tools we develop for the analysis of proteins in Area 1 can
be applied in this study. Further, our results here can provide important clues to the underlying
pathology of some of the diseases we study in Area 3. We are also
developing modeling frameworks for cellular processes in Area 4 which
provide an important foundation for this work.
GFP-expressing Escherichia coli
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