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Models of buffering of dosage imbalances in protein complexes.

Veitia RA, Birchler JA - Biol. Direct (2015)

Bottom Line: The buffer effect also appears in higher-order structures provided that there are intermediate subcomplexes in the assembly process.We highlight the importance of protein degradation and/or conformational inactivation for buffering to appear.The models sketched here have experimental support but can be further tested with existing biological resources.

View Article: PubMed Central - PubMed

Affiliation: Institut Jacques Monod, 15 rue Hélène Brion, 75013, Paris, France. veitia.reiner@ijm.univ-paris-diderot.fr.

ABSTRACT

Background: Stoichiometric imbalances in macromolecular complexes can lead to altered function. Such imbalances stem from under- or over-expression of a subunit of a complex consequent to a deletion, duplication or regulatory mutation of an allele encoding the relevant protein. In some cases, the phenotypic perturbations induced by such alterations can be subtle or be lacking because nonlinearities in the process of protein complex assembly can provide some degree of buffering.

Results: We explore with biochemical models of increasing plausibility how buffering can be elicited. Specifically, we analyze the formation of a dimer AB and show that there are particular sets of parameters so that decreasing/increasing the input amount of either A or B translates into a non proportional (buffered) change of AB. The buffer effect also appears in higher-order structures provided that there are intermediate subcomplexes in the assembly process.

Conclusions: We highlight the importance of protein degradation and/or conformational inactivation for buffering to appear. The models sketched here have experimental support but can be further tested with existing biological resources.

No MeSH data available.


Related in: MedlinePlus

Potential impact of buffering of a deletion of an allele encoding a monomer of a heterodimeric transcription factor AB. Upper panel: Schematic representation of a target promoter with 4 binding sites for AB. Lower panel: Graph of the transcriptional response (TR) as a function of the concentration of AB. The “unbuffered situation” was conveniently chosen to elicit a TR = 0.5. The effect of buffering (57 % of AB instead of 50 %) leads to TR = 0.64 when n = 4 and 0.76 when n = 8. Thanks to the strong nonlinearity of the sigmoid, the 7 % of buffering is amplified at the level of TR. The following formula allows the calculation of TR in buffered conditions when the nonbuffered situation elicits a TRunbuffured.
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Fig4: Potential impact of buffering of a deletion of an allele encoding a monomer of a heterodimeric transcription factor AB. Upper panel: Schematic representation of a target promoter with 4 binding sites for AB. Lower panel: Graph of the transcriptional response (TR) as a function of the concentration of AB. The “unbuffered situation” was conveniently chosen to elicit a TR = 0.5. The effect of buffering (57 % of AB instead of 50 %) leads to TR = 0.64 when n = 4 and 0.76 when n = 8. Thanks to the strong nonlinearity of the sigmoid, the 7 % of buffering is amplified at the level of TR. The following formula allows the calculation of TR in buffered conditions when the nonbuffered situation elicits a TRunbuffured.

Mentions: We can now explore what the net effect of buffering would be if AB were a TF eliciting a strongly nonlinear transcriptional output. The process of recognition of a promoter P with n binding sites for AB can be represented by the global reaction P + n(AB) = P(AB)n. If we assume that the saturation fraction of the promoters P(AB)n/PT is proportional to transcription, then the normalized transcriptional response TR can be approximated as the following Hill equation:3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ TR=\frac{{\left[ AB\right]}^n}{K^n+{\left[ AB\right]}^n} $$\end{document}TR=ABnKn+ABnwhere K and n are constants (see further explanations on the assumptions in [27]). The exponent is related to the number of binding sites per promoter and they have been equated here for simplicity. The higher n is, the steeper will be the sigmoid. For steep sigmoidal responses, the extra 8–9 % provided by the buffering of an allele deletion can make the difference between an abnormal and a normal phenotype. Figure 4 shows how the effect of buffering of a deletion with respect to an unbuffered situation that elicits a TR = 0.5. In this case a residual amount of 57 % of AB translates into TR = 0.64 when n = 4 and 0.76 when n = 8. This buffering effect can in principle be enhanced by an extra layer of buffering provided by the fact that a TF can recognize, in addition to its binding sites in cis-regulatory regions, other more abundant sites throughout the accessible chromatin (not leading to transcription, i.e. nonfunctional binding) [28]. Indeed, models considering the existence of binding to such sites show that the concentration of functionally-bound TF (i.e. to cis-regulatory regions) changes by a factor <2X when the TF concentration is either halved or doubled [29].Fig. 4


Models of buffering of dosage imbalances in protein complexes.

Veitia RA, Birchler JA - Biol. Direct (2015)

Potential impact of buffering of a deletion of an allele encoding a monomer of a heterodimeric transcription factor AB. Upper panel: Schematic representation of a target promoter with 4 binding sites for AB. Lower panel: Graph of the transcriptional response (TR) as a function of the concentration of AB. The “unbuffered situation” was conveniently chosen to elicit a TR = 0.5. The effect of buffering (57 % of AB instead of 50 %) leads to TR = 0.64 when n = 4 and 0.76 when n = 8. Thanks to the strong nonlinearity of the sigmoid, the 7 % of buffering is amplified at the level of TR. The following formula allows the calculation of TR in buffered conditions when the nonbuffered situation elicits a TRunbuffured.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
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getmorefigures.php?uid=PMC4537584&req=5

Fig4: Potential impact of buffering of a deletion of an allele encoding a monomer of a heterodimeric transcription factor AB. Upper panel: Schematic representation of a target promoter with 4 binding sites for AB. Lower panel: Graph of the transcriptional response (TR) as a function of the concentration of AB. The “unbuffered situation” was conveniently chosen to elicit a TR = 0.5. The effect of buffering (57 % of AB instead of 50 %) leads to TR = 0.64 when n = 4 and 0.76 when n = 8. Thanks to the strong nonlinearity of the sigmoid, the 7 % of buffering is amplified at the level of TR. The following formula allows the calculation of TR in buffered conditions when the nonbuffered situation elicits a TRunbuffured.
Mentions: We can now explore what the net effect of buffering would be if AB were a TF eliciting a strongly nonlinear transcriptional output. The process of recognition of a promoter P with n binding sites for AB can be represented by the global reaction P + n(AB) = P(AB)n. If we assume that the saturation fraction of the promoters P(AB)n/PT is proportional to transcription, then the normalized transcriptional response TR can be approximated as the following Hill equation:3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ TR=\frac{{\left[ AB\right]}^n}{K^n+{\left[ AB\right]}^n} $$\end{document}TR=ABnKn+ABnwhere K and n are constants (see further explanations on the assumptions in [27]). The exponent is related to the number of binding sites per promoter and they have been equated here for simplicity. The higher n is, the steeper will be the sigmoid. For steep sigmoidal responses, the extra 8–9 % provided by the buffering of an allele deletion can make the difference between an abnormal and a normal phenotype. Figure 4 shows how the effect of buffering of a deletion with respect to an unbuffered situation that elicits a TR = 0.5. In this case a residual amount of 57 % of AB translates into TR = 0.64 when n = 4 and 0.76 when n = 8. This buffering effect can in principle be enhanced by an extra layer of buffering provided by the fact that a TF can recognize, in addition to its binding sites in cis-regulatory regions, other more abundant sites throughout the accessible chromatin (not leading to transcription, i.e. nonfunctional binding) [28]. Indeed, models considering the existence of binding to such sites show that the concentration of functionally-bound TF (i.e. to cis-regulatory regions) changes by a factor <2X when the TF concentration is either halved or doubled [29].Fig. 4

Bottom Line: The buffer effect also appears in higher-order structures provided that there are intermediate subcomplexes in the assembly process.We highlight the importance of protein degradation and/or conformational inactivation for buffering to appear.The models sketched here have experimental support but can be further tested with existing biological resources.

View Article: PubMed Central - PubMed

Affiliation: Institut Jacques Monod, 15 rue Hélène Brion, 75013, Paris, France. veitia.reiner@ijm.univ-paris-diderot.fr.

ABSTRACT

Background: Stoichiometric imbalances in macromolecular complexes can lead to altered function. Such imbalances stem from under- or over-expression of a subunit of a complex consequent to a deletion, duplication or regulatory mutation of an allele encoding the relevant protein. In some cases, the phenotypic perturbations induced by such alterations can be subtle or be lacking because nonlinearities in the process of protein complex assembly can provide some degree of buffering.

Results: We explore with biochemical models of increasing plausibility how buffering can be elicited. Specifically, we analyze the formation of a dimer AB and show that there are particular sets of parameters so that decreasing/increasing the input amount of either A or B translates into a non proportional (buffered) change of AB. The buffer effect also appears in higher-order structures provided that there are intermediate subcomplexes in the assembly process.

Conclusions: We highlight the importance of protein degradation and/or conformational inactivation for buffering to appear. The models sketched here have experimental support but can be further tested with existing biological resources.

No MeSH data available.


Related in: MedlinePlus