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Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria.

Hui S, Silverman JM, Chen SS, Erickson DW, Basan M, Wang J, Hwa T, Williamson JR - Mol. Syst. Biol. (2015)

Bottom Line: The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters.The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell.Coarse graining may be an effective approach to derive predictive phenomenological models for other 'omics' studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, University of California at San Diego, La Jolla, CA, USA.

No MeSH data available.


Related in: MedlinePlus

Representation of the proteome responses under extreme growth limitations and interpretation of the model parametersThe growth rate-independent component of the protein is represented as ϕQ (the entire gray area), which is composed of the growth rate-independent components of the C-, A-, R-, U-, and S-sectors, and the O-sector. See Supplementary Table S7 for their values. The growth rate-dependent part of a sector σ is labeled as Δφσ, distinguished by the different colors. The colored wedges in the top pie chart show the sizes of these sectors, Δφσ(λ*), under the glucose standard condition (with growth rate λ*). Their values are as follows: 2φC = 0.07, 2φA = 0.06, 2φR = 0.13, 2φU = 0.07, and 2φS = 0.06. The pie charts at the bottom show the sizes of these sectors under the three modes of growth limitations in the extreme limit λ → 0. Theses sizes are governed by two parameters, φmax = 1 − φQ and f ≈ 0.32.
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fig06: Representation of the proteome responses under extreme growth limitations and interpretation of the model parametersThe growth rate-independent component of the protein is represented as ϕQ (the entire gray area), which is composed of the growth rate-independent components of the C-, A-, R-, U-, and S-sectors, and the O-sector. See Supplementary Table S7 for their values. The growth rate-dependent part of a sector σ is labeled as Δφσ, distinguished by the different colors. The colored wedges in the top pie chart show the sizes of these sectors, Δφσ(λ*), under the glucose standard condition (with growth rate λ*). Their values are as follows: 2φC = 0.07, 2φA = 0.06, 2φR = 0.13, 2φU = 0.07, and 2φS = 0.06. The pie charts at the bottom show the sizes of these sectors under the three modes of growth limitations in the extreme limit λ → 0. Theses sizes are governed by two parameters, φmax = 1 − φQ and f ≈ 0.32.

Mentions: The straightforward meanings of the remaining 10 parameters are illustrated by the cartoon in Fig6. The top pie chart in Fig6 represents the proteome fractions for the sectors under the glucose standard condition, with the growth rate-independent fraction of the proteome, φQ (gray area in the top pie chart) being . The growth rate-dependent component includes the remainder of every sector, shown as colored wedges, whose proteome fractions make up the rest of the pie, φmax.


Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria.

Hui S, Silverman JM, Chen SS, Erickson DW, Basan M, Wang J, Hwa T, Williamson JR - Mol. Syst. Biol. (2015)

Representation of the proteome responses under extreme growth limitations and interpretation of the model parametersThe growth rate-independent component of the protein is represented as ϕQ (the entire gray area), which is composed of the growth rate-independent components of the C-, A-, R-, U-, and S-sectors, and the O-sector. See Supplementary Table S7 for their values. The growth rate-dependent part of a sector σ is labeled as Δφσ, distinguished by the different colors. The colored wedges in the top pie chart show the sizes of these sectors, Δφσ(λ*), under the glucose standard condition (with growth rate λ*). Their values are as follows: 2φC = 0.07, 2φA = 0.06, 2φR = 0.13, 2φU = 0.07, and 2φS = 0.06. The pie charts at the bottom show the sizes of these sectors under the three modes of growth limitations in the extreme limit λ → 0. Theses sizes are governed by two parameters, φmax = 1 − φQ and f ≈ 0.32.
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4358657&req=5

fig06: Representation of the proteome responses under extreme growth limitations and interpretation of the model parametersThe growth rate-independent component of the protein is represented as ϕQ (the entire gray area), which is composed of the growth rate-independent components of the C-, A-, R-, U-, and S-sectors, and the O-sector. See Supplementary Table S7 for their values. The growth rate-dependent part of a sector σ is labeled as Δφσ, distinguished by the different colors. The colored wedges in the top pie chart show the sizes of these sectors, Δφσ(λ*), under the glucose standard condition (with growth rate λ*). Their values are as follows: 2φC = 0.07, 2φA = 0.06, 2φR = 0.13, 2φU = 0.07, and 2φS = 0.06. The pie charts at the bottom show the sizes of these sectors under the three modes of growth limitations in the extreme limit λ → 0. Theses sizes are governed by two parameters, φmax = 1 − φQ and f ≈ 0.32.
Mentions: The straightforward meanings of the remaining 10 parameters are illustrated by the cartoon in Fig6. The top pie chart in Fig6 represents the proteome fractions for the sectors under the glucose standard condition, with the growth rate-independent fraction of the proteome, φQ (gray area in the top pie chart) being . The growth rate-dependent component includes the remainder of every sector, shown as colored wedges, whose proteome fractions make up the rest of the pie, φmax.

Bottom Line: The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters.The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell.Coarse graining may be an effective approach to derive predictive phenomenological models for other 'omics' studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, University of California at San Diego, La Jolla, CA, USA.

No MeSH data available.


Related in: MedlinePlus