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Testing mechanistic models of growth in insects.

ABSTRACT: Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared against other mechanistic growth models. Unlike the other mechanistic models, our growth model predicts energy reserves per biomass to increase with age, which implies a higher production efficiency and energy density of biomass in later instars. These predictions are tested against data compiled from the literature whereby it is confirmed that insects increase their production efficiency (by 24 percentage points) and energy density (by 4 J mg(-1)) between hatching and the attainment of full size. The model suggests that insects achieve greater production efficiencies and enhanced growth rates by increasing specific assimilation and increasing energy reserves per biomass, which are less costly to maintain than structural biomass. Our findings illustrate how the explanatory and predictive power of mechanistic growth models comes from their grounding in underlying biological processes.

SUBMITTER: Maino JL

PROVIDER: S-EPMC4685816 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Testing mechanistic models of growth in insects.

Maino James L JL Kearney Michael R MR

Proceedings. Biological sciences 20151101 1819

Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared a ...[more]

PMID: 26609084

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Project description:Metabolic theories in ecology interpret ecological patterns at different levels through the lens of metabolism, typically applying allometric power scaling laws to describe rates of energy use. This requires a sound theory for metabolism at the individual level. Commonly used mechanistic growth models lack some potentially important aspects and fail to accurately capture a growth pattern often observed in insects. Recently, a new model (MGM-the Maintenance-Growth Model) was developed for ontogenetic and post-mature growth, based on an energy balance that expresses growth as the net result of assimilation and metabolic costs for maintenance and feeding. The most important contributions of MGM are: 1) the division of maintenance costs into a non-negotiable and a negotiable part, potentially resulting in maintenance costs that increase faster than linearly with mass and are regulated in response to food restriction; 2) differentiated energy allocation strategies between sexes and 3) explicit description of costs for finding and processing food. MGM may also account for effects of body composition and type of growth at the cellular level. The model was here calibrated and evaluated using empirical data from an experiment on house crickets growing under ad libitum conditions. The procedure involved parameter estimations from the literature and collected data, using statistical models to account for individual variation in parameter values. It was found that ingestion rate cannot be generally described by a simple allometry, here requiring a more complex description after maturity. Neither could feeding costs be related to ingestion rate in a simplistic manner. By the unusual feature of maintenance costs increasing faster than linearly with body mass, MGM could well capture the differentiated growth patterns of male and female crickets. Some other mechanistic growth models have been able to provide good predictions of insect growth during early ontogeny, but MGM may accurately describe the trajectory until terminated growth.

Project description:Transcriptional profiling of insulin exposed H4IIE cells at different time points (6h-24h) to 100 nM insulin, with untreated solvent control cells (blanks). The central role of hepatic insulin resistance in pandemic metabolic diseases urges investigation of the underlying mechanisms of its development and pathogenesis. Besides genetic susceptibility and lifestyle factors, environmental pollutants are suggested risk factors. In order to appraise the role of the thousands of pollutants we are daily exposed to, stable, robust and high throughput cell-based systems should be developed. In this context, it is of paramount importance to select an in vitro system which mimics in vivo insulin responses as close as possible. Therefore, this study was designed to evaluate if the rat H4IIE hepatoma cell line is a physiologically relevant model to study hepatic insulin responses. DNA microarray analysis, real-time PCR and flow cytometric cell cycle analysis were used to assess the relevance of the insulin response in H4IIE cells. Insulin dose dependently stimulated H4IIE growth. Time dependency of the insulin response was shown with real-time PCR for the known insulin responsive genes: Fasn, Pck1 and Irs2. Based on these results, microarray analysis was performed on H4IIE cells exposed to insulin (100 nM) for 6h and 24h. Genes related to carbohydrate (glycolysis and gluconeogenesis) and lipid metabolism (glycerolipid metabolism, cholesterol synthesis and fatty acid oxidation) were most profoundly afflicted, in accordance with in vivo insulin action in liver. Since changes in carbohydrate and lipid metabolism are pivotal in the pathogenesis of insulin resistance, the presence of a physiological relevant insulin response in H4IIE cells pleads for further testing of its potential use in research on pollutant-driven insulin resistance. Microarray analysis was performed on H4IIE cells exposed to insulin (100 nM) for 6h and 24h. A separate v+2 A-optimal hybridization design was used for each time-point. Using this design each exposure condition is represented by three biological replicates, with each biological replicate analysed in technical duplicate while applying the dye swap principle to correct for dye bias.

Dataset Information

Testing mechanistic models of growth in insects.

Publications

Testing mechanistic models of growth in insects.

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