حلقة التفوّق المتعددة المواقع هي نموذج مستخدم مراراً في الإشارة الخلوية. هذا النموذج يمكن أن ينتج مجموعة متنوعة من السلوكيات الحيوية مثل الثنائية الثباتية والحساسية الأقصى بدون تأثيرات إيجابية مباشرة. في هذا البحث، نحن ندرس عدد الحالات الثابتة الإيجابية لحلقة التفوّق المتعددة المواقع العامة، وكيف يتغيّر عدد الحالات الثابتة الإيجابية بتغيير المعلمات الحيوية. نظرياً، نظراً لبعض نطاقات المعلمات، هناك على الأقل n+1 حالات ثابتة (إذا كان n زوجياً) أو n (إذا كان n فردياً). ولا يوجد أكثر من 2n-1 حالات ثابتة (وبالتالي، يعني ذلك أنه لن يكون هناك أكثر من ثلاث حالات ثابتة ل n=2، بما في ذلك كاساد المابك المتعددة المستويات). وعند المعلمات القريبة من شروط الثابتية المايكليس-مينتن القياسية، فإن هناك على الأكثر حالات ثابتة n+1. وعند المعلمات البعيدة عن شروط الثابتية المايكليس-مينتن القياسية، فإن هناك على الأكثر حالة ثابتة واحدة.
The multisite phosphorylation-dephosphorylation cycle is a motif repeatedly used in cell signaling. This motif itself can generate a variety of dynamic behaviors like bistability and ultrasensitivity without direct positive feedbacks. In this paper, we study the number of positive steady states of a general multisite phosphorylation-dephosphorylation cycle, and how the number of positive steady states varies by changing the biological parameters. We show analytically that (1) for some parameter ranges, there are at least n+1 (if n is even) or n (if n is odd) steady states; (2) there never are more than 2n-1 steady states (in particular, this implies that for n=2, including single levels of MAPK cascades, there are at most three steady states); (3) for parameters near the standard Michaelis-Menten quasi-steady state conditions, there are at most n+1 steady states; and (4) for parameters far from the standard Michaelis-Menten quasi-steady state conditions, there is at most one steady state.
As a widely used method in metabolic network studies, Monte-Carlo sampling in the steady state flux space is known for its flexibility and convenience of carrying out different purposes, simply by alternating constraints or objective functions, or appending post processes. Recently the concept of a non-linear constraint based on the second thermodynamic law, known as Loop Law, is challenging current sampling algorithms which will inevitably give rise to the internal loops. A generalized method is proposed here to eradicate the probability of the appearance of internal loops during sampling process. Based on Artificial Centered Hit and Run (ACHR) method, each step of the new sampling process will avoid entering loop-forming subspaces. This method has been applied on the metabolic network of Helicobacter pylori with three different objective functions: uniform sampling, optimizing biomass synthesis, optimizing biomass synthesis efficiency over resources ingested. Comparison between results from the new method and conventional ACHR method shows effective elimination of loop fluxes without affecting non-loop fluxes.
In 2000, Gillespie rehabilitated the chemical Langevin equation (CLE) by describing two conditions that must be satisfied for it yield a valid approximation of the chemical master equation (CME). In this work, we construct an original path integral description of the CME, and show how applying Gillespies two conditions to it directly leads to a path integral equivalent to the CLE. We compare this approach to the path integral equivalent of a large system size derivation, and show that they are qualitatively different. In particular, both approaches involve converting many sums into many integrals, and the difference between the two methods is essentially the difference between using the Euler-Maclaurin formula and using Riemann sums. Our results shed light on how path integrals can be used to conceptualize coarse-graining biochemical systems, and are readily generalizable.
Gene expression data for a set of 12 localizations from The Cancer Genome Atlas are processed in order to evaluate an entropy-like magnitude allowing the characterization of tumors and comparison with the corresponding normal tissues. The comparison indicates that the number of available states in gene expression space is much greater for tumors than for normal tissues and points out to a scaling relation between the fraction of available states and the overlapping between the tumor and normal sample clouds.
Systems biology and whole-cell modelling are demanding increasingly comprehensive mathematical models of cellular biochemistry. These models require the development of simplified models of specific processes which capture essential biophysical features but without unnecessarily complexity. Recently there has been renewed interest in thermodynamically-based modelling of cellular processes. Here we present an approach to developing of simplified yet thermodynamically consistent (hence physically plausible) models which can readily be incorporated into large scale biochemical descriptions but which do not require full mechanistic detail of the underlying processes. We illustrate the approach through development of a simplified, physically plausible model of the mitochondrial electron transport chain and show that the simplified model behaves like the full system.
We present a computational procedure to characterize the signs of sensitivities of steady states to parameter perturbations in chemical reaction networks.