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A multi-scale approach reveals that NF-κB cRel enforces a B-cell decision to divide.

Shokhirev MN, Almaden J, Davis-Turak J, Birnbaum HA, Russell TM, Vargas JA, Hoffmann A - Mol. Syst. Biol. (2015)

Bottom Line: B-lymphocyte population dynamics, which are predictive of immune response and vaccine effectiveness, are determined by individual cells undergoing division or death seemingly stochastically.Combining modeling and experimentation, we found that NF-κB cRel enforces the execution of a cellular decision between mutually exclusive fates by promoting survival in growing cells.We show that a multi-scale modeling approach allows for the prediction of dynamic organ-level physiology in terms of intra-cellular molecular networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biochemistry, Signaling Systems Laboratory, UCSD, La Jolla, CA, USA San Diego Center for Systems Biology, UCSD, La Jolla, CA, USA Bioinformatics and Systems Biology Graduate Program, UCSD, La Jolla, CA, USA.

No MeSH data available.


In silico increases in the coefficient of variability or average protein abundances differentially affect population dynamicsA–K The cell-to-cell distribution of total IKK (green), NF-κB cRel/NF-κB p50 (blue), both NF-κB C,50 and total IKK (purple), non-NF-κB proteins (orange), or all proteins (gray) was varied (A). Specifically, the protein production (B, D–G) was increased (Total IKK mean ×1.5, cRel/p50 induction ×1.5, or protein production ×1.5), or the coefficient of variation (C, H–K) was doubled, and the population dynamics and maximum relative cell count (D, H), mean number of times a progenitor is expected to divide given the observed fraction of dividers in each generation (E, I), average generation 1,2,… division times (F, J), and the number of in silico cell surviving at the end of the simulation (G, K) were compared. Error bars = SD. No error bars are shown for D, E, G, H, I, and K as they represent one global feature for each simulation.
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fig08: In silico increases in the coefficient of variability or average protein abundances differentially affect population dynamicsA–K The cell-to-cell distribution of total IKK (green), NF-κB cRel/NF-κB p50 (blue), both NF-κB C,50 and total IKK (purple), non-NF-κB proteins (orange), or all proteins (gray) was varied (A). Specifically, the protein production (B, D–G) was increased (Total IKK mean ×1.5, cRel/p50 induction ×1.5, or protein production ×1.5), or the coefficient of variation (C, H–K) was doubled, and the population dynamics and maximum relative cell count (D, H), mean number of times a progenitor is expected to divide given the observed fraction of dividers in each generation (E, I), average generation 1,2,… division times (F, J), and the number of in silico cell surviving at the end of the simulation (G, K) were compared. Error bars = SD. No error bars are shown for D, E, G, H, I, and K as they represent one global feature for each simulation.

Mentions: Utilizing the multi-scale model, we explored how the average and the variability of protein abundances within the molecular network may affect the population response. In this analysis, we distinguished between negative regulators of NF-κB signaling (the IκBs), the positive regulators (IKK and the NF-κB monomers RelA, p50, and cRel), or both, as well as apoptosis and cell-cycle regulators, or all proteins (Fig8A). Increased average abundance (Fig8B) was achieved by increasing the translation rate or the total protein abundance (if constant) by 10 or 50%, respectively, while increased protein variability (Fig8C) was achieved by doubling the coefficient of variation (CV) of the translation rate or total protein abundance (if constant). As expected, moderately increasing the average protein abundance resulted in dramatic changes to the population dynamics (Fig8D), as long as the positive regulators were among those affected (blue, purple, and gray conditions). Our analysis indicates that this is primarily caused by an increase in the number of division rounds that progenitors underwent (Fig8E), as well as due to typically shorter interdivision times (Fig8F). Meanwhile, increasing the expression of negative regulators of NF-κB (IκBs) decreased the population response (Fig8D), decreased propensity to divide (Fig8E), and resulted in typically longer cell-cycle duration (Fig8F). Furthermore, increasing the positive regulators alone and to a lesser extent the cell-cycle/apoptosis proteins resulted in an accumulation of non-dividing and surviving cells (Fig8G; blue, orange), while increasing negative regulators (IκBs) tended to decrease survival (Fig8G; red versus green, purple versus blue, gray versus orange).


A multi-scale approach reveals that NF-κB cRel enforces a B-cell decision to divide.

Shokhirev MN, Almaden J, Davis-Turak J, Birnbaum HA, Russell TM, Vargas JA, Hoffmann A - Mol. Syst. Biol. (2015)

In silico increases in the coefficient of variability or average protein abundances differentially affect population dynamicsA–K The cell-to-cell distribution of total IKK (green), NF-κB cRel/NF-κB p50 (blue), both NF-κB C,50 and total IKK (purple), non-NF-κB proteins (orange), or all proteins (gray) was varied (A). Specifically, the protein production (B, D–G) was increased (Total IKK mean ×1.5, cRel/p50 induction ×1.5, or protein production ×1.5), or the coefficient of variation (C, H–K) was doubled, and the population dynamics and maximum relative cell count (D, H), mean number of times a progenitor is expected to divide given the observed fraction of dividers in each generation (E, I), average generation 1,2,… division times (F, J), and the number of in silico cell surviving at the end of the simulation (G, K) were compared. Error bars = SD. No error bars are shown for D, E, G, H, I, and K as they represent one global feature for each simulation.
© Copyright Policy - open-access
Related In: Results  -  Collection

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fig08: In silico increases in the coefficient of variability or average protein abundances differentially affect population dynamicsA–K The cell-to-cell distribution of total IKK (green), NF-κB cRel/NF-κB p50 (blue), both NF-κB C,50 and total IKK (purple), non-NF-κB proteins (orange), or all proteins (gray) was varied (A). Specifically, the protein production (B, D–G) was increased (Total IKK mean ×1.5, cRel/p50 induction ×1.5, or protein production ×1.5), or the coefficient of variation (C, H–K) was doubled, and the population dynamics and maximum relative cell count (D, H), mean number of times a progenitor is expected to divide given the observed fraction of dividers in each generation (E, I), average generation 1,2,… division times (F, J), and the number of in silico cell surviving at the end of the simulation (G, K) were compared. Error bars = SD. No error bars are shown for D, E, G, H, I, and K as they represent one global feature for each simulation.
Mentions: Utilizing the multi-scale model, we explored how the average and the variability of protein abundances within the molecular network may affect the population response. In this analysis, we distinguished between negative regulators of NF-κB signaling (the IκBs), the positive regulators (IKK and the NF-κB monomers RelA, p50, and cRel), or both, as well as apoptosis and cell-cycle regulators, or all proteins (Fig8A). Increased average abundance (Fig8B) was achieved by increasing the translation rate or the total protein abundance (if constant) by 10 or 50%, respectively, while increased protein variability (Fig8C) was achieved by doubling the coefficient of variation (CV) of the translation rate or total protein abundance (if constant). As expected, moderately increasing the average protein abundance resulted in dramatic changes to the population dynamics (Fig8D), as long as the positive regulators were among those affected (blue, purple, and gray conditions). Our analysis indicates that this is primarily caused by an increase in the number of division rounds that progenitors underwent (Fig8E), as well as due to typically shorter interdivision times (Fig8F). Meanwhile, increasing the expression of negative regulators of NF-κB (IκBs) decreased the population response (Fig8D), decreased propensity to divide (Fig8E), and resulted in typically longer cell-cycle duration (Fig8F). Furthermore, increasing the positive regulators alone and to a lesser extent the cell-cycle/apoptosis proteins resulted in an accumulation of non-dividing and surviving cells (Fig8G; blue, orange), while increasing negative regulators (IκBs) tended to decrease survival (Fig8G; red versus green, purple versus blue, gray versus orange).

Bottom Line: B-lymphocyte population dynamics, which are predictive of immune response and vaccine effectiveness, are determined by individual cells undergoing division or death seemingly stochastically.Combining modeling and experimentation, we found that NF-κB cRel enforces the execution of a cellular decision between mutually exclusive fates by promoting survival in growing cells.We show that a multi-scale modeling approach allows for the prediction of dynamic organ-level physiology in terms of intra-cellular molecular networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biochemistry, Signaling Systems Laboratory, UCSD, La Jolla, CA, USA San Diego Center for Systems Biology, UCSD, La Jolla, CA, USA Bioinformatics and Systems Biology Graduate Program, UCSD, La Jolla, CA, USA.

No MeSH data available.