Abstract
Background: Membranes play a crucial role in cellular functions. Membranes provide a physical barrier, control the trafficking of substances entering and leaving the cell, and are a major determinant of cellular ultra-structure. In
addition, components embedded within the membrane participate in cell signaling, energy transduction, and other critical cellular functions. All these processes must share the limited space in the membrane; thus it represents a
notable constraint on cellular functions. Membrane- and location-based processes have not yet been reconstructed and explicitly integrated into genome-scale models.
Results: The recent genome-scale model of metabolism and protein expression in Escherichia coli (called a ME-model) computes the complete composition of the proteome required to perform whole cell functions. Here we expand the
ME-model to include (1) a reconstruction of protein translocation pathways, (2) assignment of all cellular proteins to one of four compartments (cytoplasm, inner membrane, periplasm, and outer membrane) and a translocation pathway,
(3) experimentally determined translocase catalytic and porin diffusion rates, and (4) a novel membrane constraint that reflects cell morphology. Comparison of computations performed with this expanded ME-model, named iJL1678-ME,
against available experimental data reveals that the model accurately describes translocation pathway expression and the functional proteome by compartmentalized mass.
Conclusion: iJL1678-ME enables the computation of cellular phenotypes through an integrated computation of
proteome composition, abundance, and activity in four cellular compartments (cytoplasm, periplasm, inner and
outer membrane). Reconstruction and validation of the model has demonstrated that the iJL1678-ME is capable
of capturing the functional content of membranes, cellular compartment-specific composition, and that it can be
utilized to examine the effect of perturbing an expanded set of network components. iJL1678-ME takes a notable
step towards the inclusion of cellular ultra-structure in genome-scale models.
addition, components embedded within the membrane participate in cell signaling, energy transduction, and other critical cellular functions. All these processes must share the limited space in the membrane; thus it represents a
notable constraint on cellular functions. Membrane- and location-based processes have not yet been reconstructed and explicitly integrated into genome-scale models.
Results: The recent genome-scale model of metabolism and protein expression in Escherichia coli (called a ME-model) computes the complete composition of the proteome required to perform whole cell functions. Here we expand the
ME-model to include (1) a reconstruction of protein translocation pathways, (2) assignment of all cellular proteins to one of four compartments (cytoplasm, inner membrane, periplasm, and outer membrane) and a translocation pathway,
(3) experimentally determined translocase catalytic and porin diffusion rates, and (4) a novel membrane constraint that reflects cell morphology. Comparison of computations performed with this expanded ME-model, named iJL1678-ME,
against available experimental data reveals that the model accurately describes translocation pathway expression and the functional proteome by compartmentalized mass.
Conclusion: iJL1678-ME enables the computation of cellular phenotypes through an integrated computation of
proteome composition, abundance, and activity in four cellular compartments (cytoplasm, periplasm, inner and
outer membrane). Reconstruction and validation of the model has demonstrated that the iJL1678-ME is capable
of capturing the functional content of membranes, cellular compartment-specific composition, and that it can be
utilized to examine the effect of perturbing an expanded set of network components. iJL1678-ME takes a notable
step towards the inclusion of cellular ultra-structure in genome-scale models.
| Original language | English |
|---|---|
| Journal | BMC Systems Biology |
| Volume | 8 |
| Issue number | 1 |
| Number of pages | 15 |
| ISSN | 1752-0509 |
| DOIs | |
| Publication status | Published - 2014 |
Bibliographical note
This is an Open Access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
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