Predicting Performance and Plasticity in the Development of Respiratory Structures and Metabolic Systems

Abstract

The scaling laws governing metabolism suggest that we can predict metabolic rates across taxonomic scales that span large differences in mass. Yet, scaling relationships can vary with development, body region, and environment. Within species, there is variation in metabolic rate that is independent of mass and which may be explained by genetic variation, the environment or their interaction (i.e., metabolic plasticity). Additionally, some structures, such as the insect tracheal respiratory system, change throughout development and in response to the environment to match the changing functional requirements of the organism. We discuss how study of the development of respiratory function meets multiple challenges set forth by the NSF Grand Challenges Workshop. Development of the structure and function of respiratory and metabolic systems (1) is inherently stable and yet can respond dynamically to change, (2) is plastic and exhibits sensitivity to environments, and (3) can be examined across multiple scales in time and space. Predicting respiratory performance and plasticity requires quantitative models that integrate information across scales of function from the expression of metabolic genes and mitochondrial biogenesis to the building of respiratory structures. We present insect models where data are available on the development of the tracheal respiratory system and of metabolic physiology and suggest what is needed to develop predictive models. Incorporating quantitative genetic data will enable mapping of genetic and genetic-by-environment variation onto phenotypes, which is necessary to understand the evolution of respiratory and metabolic systems and their ability to enable respiratory homeostasis as organisms walk the tightrope between stability and change.

Energy demand and the context-dependent effects of genetic interactions underlying metabolism

“…S1 and Table S5). Significant effects of the nuclear genome at 25°C (Table S5) and in our prior work Greenlee et al 2014) demonstrate the sensitivity of this method to detect both genetic and environmental effects on metabolic rate.…”

“…; Greenlee et al. ) demonstrate the sensitivity of this method to detect both genetic and environmental effects on metabolic rate.…”

“…Larval growth in D. melanogaster proceeds extremely quickly and challenges metabolic processes (Church and Robertson 1966;Tennessen et al 2011). Furthermore, metabolism during growth is estimated to be 40-79% above that of fully developed conspecifics (Parry 1983), and cessation of growth in holometabolous insects is correlated with an ontogenetic decrease in the mass-scaling exponent relating metabolic rate to mass (Glazier 2005;Callier and Nijhout 2012;Greenlee et al 2014;Maino and Kearney 2014). Thus, the cessation of growth in Drosophila likely results in the excess metabolic capacity needed to compensate adult metabolic rate of incompatible, mito-nuclear genotypes.…”

Energy demand and the context-dependent effects of genetic interactions

“…Male metabolic rate was unaffected by mito-nuclear genotype (Supplemental Figure S1 and Table S5). Significant effects of the 2013, , Greenlee et al 2014) demonstrate the sensitivity of this method to detect both genetic and environmental effects on metabolic rate.…”

“…Larval growth in D. melanogaster proceeds extremely quickly and challenges metabolic 370 processes (Church andRobertson 1966, Tennessen et al 2011). Furthermore, metabolism during growth is estimated to be 40% to 79% above that of fully developed conspecifics (Parry 1983), and cessation of growth in holometabolous insects is correlated with an ontogenetic decrease in metabolic rate per unit mass (Glazier 2005, Callier and Nijhout 2012, Greenlee et al 2014, Maino and Kearney 2014. Thus, the cessation of growth in Drosophila likely results in the 375 excess metabolic capacity needed to compensate adult metabolic rate of incompatible, mitonuclear genotypes.…”