{'fraction_non_alphanumeric': 0.01570996978851964, 'fraction_numerical': 0.002416918429003021, 'mean_word_length': 5.786885245901639, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Evolution of Hierarchy in Bacterial Metabolic Networks

Background In self-organized systems, the concept of flow hierarchy is a useful way to characterize the movement of information throughout a network. Hierarchical network organizations are shown to arise when there is a cost of maintaining links in the network. A similar constraint exists in metabolic networks, where costs come from reduced efficiency of nonspecific enzymes or from producing unnecessary enzymes. Previous analyses of bacterial metabolic networks have been used to predict the minimal nutrients that a bacterium needs to grow, its mutualistic relationships with other bacteria, and its major ecological niche. Using flow hierarchy, we can also infer the tradeoffs between growth rate and metabolic efficiency that bacteria make given their environmental constraints. Results Using a comparative approach on 2,935 bacterial metabolic networks, we show that flow hierarchy in bacterial metabolic networks tracks a fundamental tradeoff between growth rate and biomass production, and reflects a bacterium’s realized ecological strategy. Additionally, by inferring the ancestral metabolic networks, we find that hierarchy decreases with distance from the root of the tree, suggesting the important pressure of increased growth rate relative to efficiency in the face of competition. Conclusions Just as hierarchical character is an important structural property in efficiently engineered systems, it also evolves in self-organized bacterial metabolic networks, reflects the life-history strategies of those bacteria, and plays an important role in network organization and efficiency.