A metabolic network in the evolutionary context: multiscale structure and modularity

Abstract

The enormous complexity of biological networks has led to the suggestion that networks are built of modules that perform particular functions and are "reused" in evolution in a manner similar to reusable domains in protein structures or modules of electronic circuits. Analysis of known biological networks has revealed several modules, many of which have transparent biological functions. However, it remains to be shown that identified structural modules constitute evolutionary building blocks, independent and easily interchangeable units. An alternative possibility is that evolutionary modules do not match structural modules. To investigate the structure of evolutionary modules and their relationship to functional ones, we integrated a metabolic network with evolutionary associations between genes inferred from comparative genomics. The resulting metabolic-genomic network places metabolic pathways into evolutionary and genomic context, thereby revealing previously unknown components and modules. We analyzed the integrated metabolic-genomic network on three levels: macro-, meso-, and microscale. The macroscale level demonstrates strong associations between neighboring enzymes and between enzymes that are distant on the network but belong to the same linear pathway. At the mesoscale level, we identified evolutionary metabolic modules and compared them with traditional metabolic pathways. Although, in some cases, there is almost exact correspondence, some pathways are split into independent modules. On the microscale level, we observed high association of enzyme subunits and weak association of isoenzymes independently catalyzing the same reaction. This study shows that evolutionary modules, rather than pathways, may be thought of as regulatory and functional units in bacterial genomes.

Fig. 1.

The excess of genomic associations at various metabolic distances. (A) The cross-clustering coefficient as defined in the text with metabolic (blue) and genomic (orange) links. (B Left) The number of observed (red) and expected (green) associations M between reactions vs. metabolic distance D between reactions. (B Right) The ratio of observed and expected number of associations (M/M^rnd) between reactions at distance D. Notice several-fold excess of observed over expected associations at distance D ≤ 3. (Inset) Probability of observing M > M^rnd in random controls. (C) Same as above but for reactions in linear paths (Inset, log-scale). A pathway is said to be linear if it contains no major “intersections,” i.e., all of its metabolites participate in four or fewer reactions. Notice significant excess of associations between reactions as far as D = 7 metabolic steps apart on linear pathways. Compare B (all pathways) and C (linear pathways) to see that linear pathways demonstrate long-range associations.

Fig. 2.

Examples of inter- and intrapathway modules of genomically associated reactions. (A) Arginine and histidine pathways. Red, arginine biosynthesis module; blue, histidine biosynthesis module; dotted line, arginine plus histidine biosynthesis module; black (spe genes), spermidine/putrescine biosynthesis, not in any cluster. (B) Purine (Lower) and pyrimidine (Upper) pathways. Blue, hybrid purine–pyrimidine module; green, GMP module; black, nonassociated isoenzyme. (C) Fucose and rhamnose pathways and clusters. Fucose pathway, solid lines; rhamnose pathway, dotted lines; colored (red and blue), two clusters. (D) Aromatic amino acids and folate pathways. Folate pathway: dotted (Left); aromatic amino acids, solid (Left); enterochelin, dotted (Right); menaquinone, solid (Right). Interpathway clusters: aromatic/folate, red; enterochelin/menaquinone, blue. (E) Cystein and methionine biosynthesis. (Left and Center) Cysteine. (Right) Methionine. Horizontal, one-carbon metabolism (partial). Clusters are colored in red, blue, and green.

Fig. 3.

Distribution of association scores in isoenzymes (green), subunits (brown), and, for control, all enzymes (blue). Notice that isoenzymes exhibit bimodal distribution, with most isoenzymes being either strongly associated (S > 800) or not associated (S < 200). In contrast, subunits have one peak at S > 800, tending to be much more associated than any other enzymes.