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Published online on July 24, 2007, 10.1073/pnas.0609845104
PNAS | July 31, 2007 | vol. 104 | no. 31 | 12663-12668


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PHYSICAL SCIENCES / BIOLOGICAL SCIENCES / STATISTICS / BIOPHYSICS
Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity

Q. K. Beg*, A. Vazquez{dagger},{ddagger}, J. Ernst§, M. A. de Menezes, Z. Bar-Joseph§, A.-L. Barabási||, and Z. N. Oltvai*,**

*Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261; {dagger}The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540; §Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15217; Instituto de Física, Universidade Federal Fluminense, 24210, Rio de Janeiro, Brazil; and ||Department of Physics and Center for Complex Networks Research, University of Notre Dame, Notre Dame, IN 46556

Edited by Gregory A. Petsko, Brandeis University, Waltham, MA, and approved May 31, 2007 (received for review November 7, 2006)

The influence of the high intracellular concentration of macromolecules on cell physiology is increasingly appreciated, but its impact on system-level cellular functions remains poorly quantified. To assess its potential effect, here we develop a flux balance model of Escherichia coli cell metabolism that takes into account a systems-level constraint for the concentration of enzymes catalyzing the various metabolic reactions in the crowded cytoplasm. We demonstrate that the model's predictions for the relative maximum growth rate of wild-type and mutant E. coli cells in single substrate-limited media, and the sequence and mode of substrate uptake and utilization from a complex medium are in good agreement with subsequent experimental observations. These results suggest that molecular crowding represents a bound on the achievable functional states of a metabolic network, and they indicate that models incorporating this constraint can systematically identify alterations in cellular metabolism activated in response to environmental change.

flux balance analysis | metabolic networks | systems biology


Author contributions: Q.K.B. and A.V. contributed equally to this work; Q.K.B., A.V., M.A.d.M., A.-L.B., and Z.N.O. designed research; Q.K.B. and A.V. performed research; Q.K.B. and A.V. contributed new reagents/analytic tools; Q.K.B., A.V., J.E., and Z.B.-J. analyzed data; and Q.K.B., A.V., Z.B.-J., A.-L.B., and Z.N.O. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

This article contains supporting information online at www.pnas.org/cgi/content/full/0609845104/DC1.

{ddagger}To whom correspondence may be addressed. E-mail: vazquez{at}ias.edu

**To whom correspondence may be addressed at: University of Pittsburgh, S701 Scaife Hall, 3550 Terrace Street, Pittsburgh, PA 15261. E-mail: oltvai{at}pitt.edu

© 2007 by The National Academy of Sciences of the USA


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