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Biotechnol Prog. 2005 Sep-Oct;21(5):1401-11.

Proteomic profiling of Escherichia coli proteins under high cell density fed-batch cultivation with overexpression of phosphogluconolactonase.

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  • 1Barnett Institute, Northeastern University, Boston, Massachusetts 02115, USA.


In this study, we used proteomics to better understand the growth on glucose of Escherichia coli in high cell density, fed-batch cultures and the response to overexpression of plasmid-encoded 6-phosphogluconolactonase (PGL). Using liquid chromatography coupled to electrospray mass spectrometry, at least 300 proteins were identified in the cytosolic fraction of the six time points used to monitor the fermentation. The relative abundance changes of selected proteins were obtained by comparing the peak area of the corresponding peptides at a particular m/z (mass over charge ratio) value. During the time course of samples collected during the rapid growth achieved under batch and fed-batch conditions, both the control and recombinant E. coli strains showed up-regulation of proteins participating in the tricarboxylic acid (TCA) cycle, particularly acetyl-CoA synthetase (AcCoAS), malate dehydrogenase (MDH), and succinyl-CoA synthetase (SuccCoAS). In the recombinant strain culture, fumarase was up-regulated until 35 h after inoculation but was not in the control strain culture. In addition, the proteomic measurement detected up-regulation of three well-characterized binding transport proteins in both control and recombinant strains. The up-regulation of TCA cycle enzymes is consistent with the increase in growth rate observed in the cell culture. In addition, up-regulation of these proteins demonstrated the importance of both the pentose-phosphate shunt and TCA cycle to the increased biosynthetic activity required by a high level protein synthesis. This study shows the potential of proteomics using shotgun sequencing (LC/MS of tryptic digests) to measure global changes in protein abundance during a fermentation process and will facilitate the development of robust manufacturing systems.

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