Habitat variability does not generally promote metabolic network modularity in flies and mammals

Abstract

The evolution of species habitat range is an important topic over a wide range of research fields. In higher organisms, habitat range evolution is generally associated with genetic events such as gene duplication. However, the specific factors that determine habitat variability remain unclear at higher levels of biological organization (e.g., biochemical networks). One widely accepted hypothesis developed from both theoretical and empirical analyses is that habitat variability promotes network modularity; however, this relationship has not yet been directly tested in higher organisms. Therefore, I investigated the relationship between habitat variability and metabolic network modularity using compound and enzymatic networks in flies and mammals. Contrary to expectation, there was no clear positive correlation between habitat variability and network modularity. As an exception, the network modularity increased with habitat variability in the enzymatic networks of flies. However, the observed association was likely an artifact, and the frequency of gene duplication appears to be the main factor contributing to network modularity. These findings raise the question of whether or not there is a general mechanism for habitat range expansion at a higher level (i.e., above the gene scale). This study suggests that the currently widely accepted hypothesis for habitat variability should be reconsidered.

Introduction

The evolution of species habitat range is an important topic of scientific inquiry at several scales of biological research, from fundamental biological processes to ecology (Bridle and Vines, 2007, Root et al., 2003, Roy et al., 2009), particularly in the context of predictions related to biodiversity and climate change. Therefore, understanding the factors that determine species habitat use is a relevant topic for advancing these research fields. In particular, it is important to identify the molecular (microscopic) mechanisms that contribute to determining a species habitat range, because the behavior of a species (macroscopic) may result from complex biological systems. For example, some previous studies (Barrett and Schluter, 2008, Kellermann et al., 2009) suggested the importance of genetic variation to the ability to adapt and exploit new environments. Moreover, recent studies reported that gene duplication promotes habitat variability in flies (Drosophila species; Makino and Kawata, 2012) and mammals (Tamate et al., 2014). This work was inspired by the proposed importance of gene duplication to increasing biological robustness and evolvability (Wagner, 2008), which are themselves related to habitat variability.

However, it remains unclear how these genetic events affect species habitat variability at a higher level of biological organization. In this context, evaluation of modular organization in biological systems (Hartwell et al., 1999) is useful because it is also generally considered to be related to robustness (Hintze and Adami, 2008) and evolvability (Yang, 2001), despite some opinions to the contrary (Hansen, 2003, Holme, 2011). The evolution of modularity in cellular networks has been specifically intriguing to researchers in the context of network biology (Barabási and Oltvai, 2004, Takemoto, 2012a). In particular, a hypothesis has been proposed that variability in natural habitats promotes network modularity. For example, in a theoretical model, Kashtan and Alon (2005) showed that modular networks spontaneously evolved when a fitness peak determined by the environment changes over time in a manner that preserves the same subgoals but in different permutations. Similarly, Lipson et al. (2002) suggested that changing environments could promote modularity. Hintze and Adami (2008) showed that modularity evolves in biological networks (modeled as metabolic networks) to deal with a multitude of functional goals, with the degree of modularity depending on the extent of environmental variability.

In this context, metabolic networks are particularly interesting because metabolic processes are essential for physiological functions and for maintaining homeostasis in living organisms (Takemoto and Oosawa, 2012, Takemoto, 2012a). Metabolic networks also determine the behavior of organisms, such as the space use (Jetz et al., 2004) and feeding rate (Brown et al., 2004) of animals, which may in turn be related to habitat variability. In addition, analyses can be performed using actual empirical data, because metabolic networks are available for a wide diversity of species in databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG; Kanehisa et al., 2014) and the Encyclopedia of Metabolic Pathways (MetaCyc; Caspi et al., 2012). In fact, using network analysis, Parter et al. (2007) showed that variability in natural habitats promotes the modularity observed in metabolic networks. This result clearly supports the predictions derived from theoretical models, and several researchers have actively investigated the ecological interactions underlying metabolic networks according to habitat variability (Chave, 2013, Levy and Borenstein, 2012).

Despite this recent attention to this relationship between modularity and habitat viability, more comprehensive examinations are required to resolve some outstanding questions. Indeed, recent studies have cast doubt on this relationship. For example, several alternative theories for explaining the origin and evolution of modularity have been proposed, including the neutral theories of protein (Solé and Valverde, 2008) and metabolic networks (Takemoto, 2012b), connection-cost theory (Clune et al., 2013), and multiplicative-mutation theory (Friedlander et al., 2013). Furthermore, a study conducted in archaea, a type of prokaryote distinct from bacteria, did not find a positive correlation between habitat variability and metabolic network modularity (Takemoto and Borjigin, 2011). Similarly, in bacteria, no positive correlation was observed using the latest version of the metabolic database (Takemoto, 2013, Zhou and Nakhleh, 2012). In short, the observed associations between metabolic network modularity and habitat variability (Parter et al., 2007) may be the result of an artifact due to lack of available data on metabolic reactions. More importantly, the studies conducted thus far are limited to lower organisms such as bacteria and archaea.

Therefore, the aim of this study was to investigate the relationship between habitat variability and metabolic network modularity in higher organisms, including data from flies (Makino and Kawata, 2012) and mammals (Tamate et al., 2014). In addition to the potential effect on habitat variability in promoting network modularity, an association between gene duplication and habitat variability has also been observed. Given that gene duplication also influences the metabolic network structure (Barabási and Oltvai, 2004, Díaz-Mejía et al., 2007, Papp et al., 2004, Takemoto, 2012a), it is reasonable to hypothesize that habitat variability may be linked to not only gene duplication but also metabolic network modularity. To investigate these relationships, data related to habitat variability were collected from the published literature; data were collected only from species for which metabolic network data are also available (see Section 2). Using these data, I evaluated whether habitat variability increases metabolic network modularity and how the association between gene duplication and habitat variability might influence the modularity of the metabolic network.