Network representations and methods for the analysis of chemical and biochemical pathways

Sandefur, Conner I.; Mincheva, Maya; Schnell, Santiago

doi:10.1039/c3mb70052f

Cited by 23 publications

(21 citation statements)

References 75 publications

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“…Before proceeding to the details of our results, it is worth noting the well known challenges associated with the introduction of statistical artifacts when coarse-graining real-world systems to generate graphical representations 51,52 . For example, bipartite network representations of biochemistry (treating reactions and substrates as two disjoint sets of nodes) have information that cannot be recovered from unipartite representations (which treat only substrates as nodes).…”

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confidence: 99%

Universal scaling across biochemical networks on Earth

Kim

Smith

Mathis

et al. 2017

Preprint

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Attempts to identify universal properties of life are limited by the single example of biochemistry on Earth. Using a global database of 28,146 annotated genomes and metagenomes, we report universal scaling laws governing the topology of biochemical networks across levels of organization from individuals, to ecosystems, to the biosphere as a whole. We show the three domains of life are topologically distinguishable, while nonetheless conforming to the same universal scaling laws. Comparing real biochemical networks to networks composed of randomly sampled biochemical reactions reveals the observed scaling is not a product of shared biochemistry alone, but is instead attributable to universal constraints on how global biochemistry is partitioned into individuals. The reemergence of the same regularities across levels of organization hints at general principles governing biochemical network architecture.There is increasing interest in whether life has universal properties, not tied to its specific chemical instantiation (1). Universal biology, if it exists, would have important implications for constraining the origins of life, engineering synthetic life and guiding the search for life beyond Earth (2, 3). Systems biology provides promising tools for uncovering such general principles. One approach has been to study the topology of organismal metabolic networks, revealing common 'scale-free' structure for all three domains of life (4). Another approach is identification of scaling laws describing remarkable consistency in scaling of biomass, biodiversity, and metabolic rate (5-9). However, so far it has been difficult to unify these patterns across all levels of organization where living processes persist, from individuals to ecosystems to the biosphere. A more convincing case for universal biology would be made by demonstrating all life on Earth shares similar properties, independent of biochemical diversity or level of organization. Here we show biochemical networks conform to universal scaling laws governing their global topology, which tightly constrain not only the network structure of individuals, but also that of ecosystems and the biosphere as a whole.

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confidence: 99%

Universal scaling across biochemical networks on Earth

Kim

Smith

Mathis

et al. 2017

Preprint

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“…Showing that patterns exist, for example that the distribution of motifs differs from a random one [10] is a first step; the next will be to show how the patterns have evolved to function in relation to a particular environment. A quantitative description of why a process is effective, or a simulation that selects for that process [2],[11]–[14], helps us to understand how it works.…”

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confidence: 99%

The Ecology of Collective Behavior

Gordon

2014

PLoS Biol

102

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“…It also depends on the methods used to identify statistical significant subgraphs as network motifs. In the literature, the power and limitations of different network motifs identification approaches is an active area of research [see, Sandefur et al (2013) for a recent review]. We employed the normalized z-score, which identifies subgraphs as overrepresented or underrepresented motifs if they have z-score values greater or less than zero, respectively (Milo et al, 2004).…”

Section: Discussionmentioning

confidence: 99%

Metabolic network motifs can provide novel insights into evolution: The evolutionary origin of Eukaryotic organelles as a case study

Shellman

Chen

Lin

et al. 2014

Computational Biology and Chemistry

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Phylogenetic trees are typically constructed using genetic and genomic data, and provide robust evolutionary relationships of species from the genomic point of view. We present an application of network motif mining and analysis of metabolic pathways that when used in combination with phylogenetic trees can provide a more complete picture of evolution. By using distributions of three-node motifs as a proxy for metabolic similarity, we analyze the ancestral origin of Eukaryotic organelles from the metabolic point of view to illustrate the application of our motif mining and analysis network approach. Our analysis suggests that the hypothesis of an early proto-Eukaryote could be valid. It also suggests that a δ- or ε-Proteobacteria may have been the endosymbiotic partner that gave rise to modern mitochondria. Our evolutionary analysis needs to be extended by building metabolic network reconstructions of species from the phylum Crenarchaeota, which is considered to be a possible archaeal ancestor of the eukaryotic cell. In this paper, we also propose a methodology for constructing phylogenetic trees that incorporates metabolic network signatures to identify regions of genomically-estimated phylogenies that may be spurious. We find that results generated from our approach are consistent with a parallel phylogenetic analysis using the method of feature frequency profiles.

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Network representations and methods for the analysis of chemical and biochemical pathways

Cited by 23 publications

References 75 publications

Universal scaling across biochemical networks on Earth

Universal scaling across biochemical networks on Earth

The Ecology of Collective Behavior

Metabolic network motifs can provide novel insights into evolution: The evolutionary origin of Eukaryotic organelles as a case study

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