Collective motions and specific effectors: a statistical mechanics perspective on biological regulation

Abstract

Background: The interaction of a multiplicity of scales in both time and space is a fundamental feature of biological systems. The complementation of macroscopic (entire organism) and microscopic (molecular biology) views with a mesoscopic level of analysis able to connect the different planes of investigation is urgently needed. This will allow to both obtain a general frame of reference for rationalizing the burden of data coming from high throughput technologies and to derive effective operational views on biological systems.

Results: The network paradigm in which microscopic level elements (nodes) are each other related by functional links so giving rise to both global (entire network) and local (specific) behavior is a promising metaphor to try and develop a statistical mechanics inspired approach for biological systems. Here we show the application of this paradigm to different systems going from yeast metabolism to murine macrophages response to immune stimulation.

Conclusions: The need to complement the purely molecular view with mesoscopic approaches is evident in all the studied examples that in turn demonstrate the untenability of the simple ergodic approach dominant in molecular biology in which the data coming from huge ensemble of cells are considered as relative to a single 'average' cell.

Figure 1

The metabolic network of yeast is depicted in the figure, the enzymatic reactions correspond to edges, while the nodes point to the metabolites. The yellow signs indicate the analyzed mutations.

Figure 2

The picture reports the microarray derived differential gene expression values correspondent to two samples of the same cell kind. They refer to 22690 ORFs and span four order of magnitudes of expression levels.

Figure 3

The first component of the variation in time of different gene choice is reported as for free growing yeast colonies. Pc1small corresponds to a choice of 60 genes connected to ribogenesis, pc1whole to the entire genome, pc1rand to a random extraction of 275 genes. It is worth noting the superposition of the time courses and the practical invariance of the percent of explained variance of the extracted mode.

Figure 4

A simplified schema of a dipole gas is reported: in the absence of an external field the dipoles only display local order with a statistical tendency of opposite polarities to come close each other (panel a). In panels b) and c) an increasingly powerful external field acts on the system inducing a global order of the dipoles.

Figure 5

The LPS stimulus processing pathway.

Figure 6

The figure reports four different gene choices correspondent to different mesoscopic views on the gene regulation system (see text). The graphs have the Pearson correlation coefficient r with t0 state vector as ordinate and time (hours) as abscissa and report the dynamical response to LPS stimulus for each genotype, a lower value of r corresponds to a more marked response.