While the above speculation makes a weak case for a selectionist explanation of broad-tailed degree distributions in metabolic networks, another line of evidence makes a more solid case against it. One can ask whether power-law degree distributions might not be features of many or all large chemical reaction networks, whether or not part of an organism, whether or not they have a biological function which benefits from a robust network diameter. If so, then metabolic network degree distributions would join the club of other power-laws (such as ZipPs law of word frequency distributions in natural languages) whose existence does not owe credit to a benefit they provide. There is indeed evidence supporting this possibility.
Gleiss and collaborators19 have compiled publicly available information on a class of large chemical reaction networks that exist not only outside the living, but on spatial scales many orders of magnitude larger than organisms. These are the chemical reaction networks of planetary atmospheres, networks whose structure is largely determined by the photochemistry of their component substrates. The available data stems not only from earth's atmosphere, but also from other solar planets including Venus and Jupiter, planets with chemically diverse atmospheres. These planets' atmospheres have been explored through remote spectroscopic sensing methods and by planetary probes. The chemical reaction networks in these atmospheres, despite being vastly different in chemistry, have a degree distribution consistent with a power law.19 This suggests that power-law distributions may be very general features of chemical reaction networks. The reasons why we observe them in cellular reaction networks may have nothing to do with the robustness they may provide.
Although such comparisons to 'self-assembled' networks suggest an important influence of chemistry on metabolic network structure, another aspect of metabolic networks should not be overlooked. Metabolic networks have a history. They have not been assembled in their present state at once. They have grown, perhaps over a billion years, as organisms increased their metabolic and biosynthetic abilities. In understanding their structure, we have to take this history of biological networks into account.
We may never know enough about the history of life and metabolism to distinguish between different ways in which metabolism might have grown. However, we can address the key prediction of many network growth models I discussed above. Are highly connected metabolites old metabolites? The answer will contain a speculative element, because the oldest metabolites are those that arose in the earliest days of the living, close to life's origins. In addition, life forms as different as bacteria and humans have core metabolisms with a very similar structure. This suggests that the growth of metabolism has essentially been completed at the time the common ancestor of extant life emerged. Because this common ancestor does no longer exist, the detailed structure of its metabolism will remain in the dark forever. However, various hypotheses about life's origin make predictions on the chemical compounds expected to have been part of early organisms. There are several of these hypotheses, and they are complementary in the respect most important here: They emphasize the origins of different aspects of life's chemistry. Some emphasize the origins of the earliest genetic material, RNA. Others make postulates about the composition of the earliest proteins. Yet others ask about the earliest metabolites in energy metabolism. Each of them makes a statement about a different aspect of early life's chemistry.
Figure 1 shows the twelve most highly connected metabolites of the E. coli metabolic network graph.14 Every single one of them has been part of early organisms according to at least one origin-of-life hypothesis. Colored in green are compounds such as coenzyme A thought to have been a part of early RNA-based organisms.20 The RNA moieties such compounds
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