Title: Heterogeneous distribution of metabolites across plant species
ArXiv ID: 0903.2883
Date: 2009-04-23
Authors: Researchers from original ArXiv paper
📝 Abstract
We investigate the distribution of flavonoids, a major category of plant secondary metabolites, across species. Flavonoids are known to show high species specificity, and were once considered as chemical markers for understanding adaptive evolution and characterization of living organisms. We investigate the distribution among species using bipartite networks, and find that two heterogeneous distributions are conserved among several families: the power-law distributions of the number of flavonoids in a species and the number of shared species of a particular flavonoid. In order to explain the possible origin of the heterogeneity, we propose a simple model with, essentially, a single parameter. As a result, we show that two respective power-law statistics emerge from simple evolutionary mechanisms based on a multiplicative process. These findings provide insights into the evolution of metabolite diversity and characterization of living organisms that defy genome sequence analysis for different reasons.
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Deep Dive into Heterogeneous distribution of metabolites across plant species.
We investigate the distribution of flavonoids, a major category of plant secondary metabolites, across species. Flavonoids are known to show high species specificity, and were once considered as chemical markers for understanding adaptive evolution and characterization of living organisms. We investigate the distribution among species using bipartite networks, and find that two heterogeneous distributions are conserved among several families: the power-law distributions of the number of flavonoids in a species and the number of shared species of a particular flavonoid. In order to explain the possible origin of the heterogeneity, we propose a simple model with, essentially, a single parameter. As a result, we show that two respective power-law statistics emerge from simple evolutionary mechanisms based on a multiplicative process. These findings provide insights into the evolution of metabolite diversity and characterization of living organisms that defy genome sequence analysis for di
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Living organisms produce compounds of many types via their metabolisms which are believed to adaptively shape-shift with changing environment across a long evolutionary history. Elucidation of design principles behind such complex systems is a major goal in natural science. Toward this end, so far, the structure of metabolic networks has been actively investigated using network analysis from the viewpoint of statistical mechanics. As a result, striking structural properties such as scale-free (heterogeneous) connectivity and hierarchical organization have been revealed, and possible origins have been discussed via several models (e.g., reviewed in Refs. (1; 2; 3)). In addition to considering metabolic networks, however, it is also important to consider how metabolites are distributed among species in order to elucidate design principles of metabolisms such as adaptive mechanisms. The metabolite distributions have the following advantages. Since living organisms have specific metabolite compositions due to metabolisms adaptively changing with respect to the environment, we can estimate environmental adaptation (adaptive evolution) using metabolite distributions. Moreover, they are also useful for characterizing species relationships, which are highly linked to ecological systems. In metabolite distributions, thus, identification of structures and construction of a theory (model) for evolutionary mechanisms are key challenges for a deeper understanding of metabolism.
Flavonoids are especially interesting examples when considering metabolite distributions among species. Secondary metabolites including flavonoids, alkanoids, terpenoids, phenolics, and other compounds are widely observed in angiosperms, and are not essential for preserving life unlike basic metabolites such as bases, amino acids, sugars, and fatty acids (building blocks of DNA, protein, carbohydrate, and fat, respectively). However, secondary metabolites play additional roles aiding survival in diverse environments. Therefore, distributions of secondary metabolites are believed to be significantly different among species due to adaptation to environments, implying high species specificity (4). For this reason, secondary metabolites help us to understand environmental adaptation and adaptive evolution. Moreover, secondary metabolites, especially flavonoids, are often used as markers in chemotaxonomy, which is a taxonomic classification based on metabolite compositions of species that has been used for many years (5). However, taxonomic classifications using secondary metabolites at higher levels (e.g. family and order levels) are known to be inherently more difficult than those at lower levels (e.g. species levels) (4).
Although the metabolite distribution provides important insights into metabolism as discussed above, it has not caught as much attention as metabolic networks. This was mainly because knowledge of secondary metabolites was not widely available. In recent years, however, the whole picture of species-flavonoid relationships has become available in the KNApSAcK database (6) and partly in Metabolomics.JP (7). We now can investigate metabolite distributions among species using these websites.
In this paper, we focus on flavonoids, which are a class of secondary metabolites, and investigate metabolite distribution among species. In order to comprehensibly describe species-flavonoid relationships, bipartite networks are utilized. They are useful for representing two different objects, which correspond to species and flavonoids in this case. We first investigate degree distributions in species-flavonoid networks in several families, and show power-law distributions of the number of flavonoids in a species and the number of shared species of a flavonoid. A simple model is next proposed for explaining a possible origin of the heterogeneous distributions (power-law distributions), and it is compared to real data. Furthermore, intuitive descriptions and mathematical evidence are provided for the emergence of heterogeneous distributions. We finally mention the characteristics of well-shared (hub) isoflavonoids in Fabaceae (bean family) as an example. In addition, we discuss the possibility of more effective selection of discriminative metabolites and taxonomic classifications at higher levels by considering this heterogeneous distribution, and speculate on the evolution of flavonoid diversity.
A total of 14378 species-flavonoid pairs were downloaded from Metabolomics.JP (7) (http://metabolomics.jp/wiki/Category:FL)
, in which 4725 species and 6846 identified flavonoid structures are linked by a published journal article. In other words, only published data were utilized. The species-flavonoid pairs are by no means comprehensive: no plant species has been ‘completely’ investigated for its biosynthetic activity, and many flavonoid molecules whose descriptions have yet to be published are also thought to exist.
