Obesity is one of the dramatic health issues affecting developed and developing nations, and exercise is a well-established intervention strategy. While exercise-by-genotype interactions have been shown in humans, overall little is known. Using the natural negative geotaxis of Drosophila melanogaster, an important model organism for the study of genetic interactions, a novel exercise machine, the TreadWheel, can be used to shed light on this interaction. The mechanism for inducing exercise with the TreadWheel is inherently gentle, thus minimizing possible confounding effects of other stressors. Using this machine, we were able to assess large cohorts of adult flies from eight genetic lines for their response to exercise after one week of training. We measured their triglyceride, glycerol, protein, glycogen, glucose content, and body weight, as well as their climbing ability and feeding behavior in response to exercise. Exercised flies showed decreased stored triglycerides, glycogen, and body weight, and increased stored protein and climbing ability. In addition to demonstrating an overall effect of TreadWheel exercise on flies, we found significant interactions of exercise with genotype, sex, or genotype-by-sex effects for most of the measured phenotypes. We also observed interaction effects between exercise, genotype, and tissue (abdomen or thorax) for metabolite profiles, and those differences can be partially linked to innate differences in the flies' persistence in maintaining activity during exercise bouts. In addition, we assessed gene expression levels for a panel of 13 genes known to be associated with respiratory fitness and found that many responded to exercise. With this study, we have established the TreadWheel as a useful tool to study the effect of exercise in flies, shown significant genotype-specific and sex-specific impacts of exercise, and have laid the ground work for more extensive studies of how genetics, sex, environment, and aging interact with exercise to influence metabolic fitness in Drosophila.
An organism's phenotype is the product of its environment and genotype, but an ancestor’s environment can also be a contributing factor. The recent increase in caloric intake and decrease in physical activity of developed nations' populations is contributing to deteriorating health and making the study of the longer term impacts of a changing lifestyle a priority. The dietary habits of ancestors have been shown to affect phenotype in several organisms, including humans, mice, and the fruit fly. Whether the ancestral dietary effect is purely environmental or if there is a genetic interaction with the environment passed down for multiple generations, has not been determined previously. Here we used the fruit fly, Drosophila melanogaster, to investigate the genetic, sex-specific, and environmental effects of a high fat diet for three generations’ on pupal body weights across ten genotypes. We also tested for genotype-specific transgenerational effects on metabolic pools and egg size across three genotypes. We showed that there were substantial differences in transgenerational responses to ancestral diet between genotypes and sexes through both first and second descendant generations. Additionally, there were differences in phenotypes between maternally and paternally inherited dietary effects. We also found a treated organism’s reaction to a high fat diet was not a consistent predictor of its untreated descendants’ phenotype. The implication of these results is that, given our interest in understanding and preventing metabolic diseases like obesity, we need to consider the contribution of ancestral environmental experiences. However, we need to be cautious when drawing population-level generalization from small studies because transgenerational effects are likely to exhibit substantial sex and genotype specificity.
Model organisms are important in many areas of chemical biology. In metabolomics, model organisms can provide excellent samples for methods development as well as the foundation of comparative phylometabolomics, which will become possible as metabolomics applications expand. Comparative studies of conserved and unique metabolic pathways will help in the annotation of metabolites as well as provide important new targets of investigation in biology and biomedicine. However, most chemical biologists are not familiar with genetics, which needs to be considered when choosing a model organism. In this review we summarize the strengths and weaknesses of several genetic systems, including natural isolates, recombinant inbred lines, and genetic mutations. We also discuss methods to detect targets of selection on the metabolome.
Annotating the genomes of multiple organisms allows us to study their genes as well as the evolution of those genes. While many eukaryotic genome assemblies already include computational gene predictions, these predictions can benefit from review and refinement through manual gene annotation. The Genomics Education Partnership (GEP; thegep.org) has developed an annotation protocol for protein-coding genes that enables undergraduate students and other researchers to create high-quality gene annotations that can be utilized in subsequent scientific investigations. For example, this protocol has been utilized by the GEP faculty to engage undergraduate students in the comparative annotation of genes involved in the insulin signaling pathway in 28 Drosophila species, using D. melanogaster as the informant genome. Students construct gene models using multiple lines of computational and experimental evidence including expression data (e.g., RNA-Seq), sequence similarity (e.g., BLAST, multiple sequence alignments), and computational gene predictions. For quality control, each gene is annotated by at least two students working independently, followed by reconciliation of the submitted gene models by a more experienced student. This article provides an overview of the annotation protocol and describes how discrepancies in student submitted gene models are resolved to produce a final, high-quality gene set suitable for subsequent analyses. This annotation protocol can be adapted to other scientific questions (e.g., expansion of the Drosophila Muller F element) and other species (e.g., parasitoid wasps) to provide additional opportunities for undergraduate students to participate in genomics research. These student annotation efforts can substantially improve the quality of gene annotations in publicly available genomic databases.
Understanding plant‐insect interactions is an active area of research in both ecology and evolution. Much attention has been focused on the impact of secondary metabolites in the host plant or fungi on these interactions. Plants and fungi contain a variety of biologically active compounds, and the secondary metabolite profile can vary significantly between individual samples. However, many experiments characterize the biological effects of only a single secondary metabolite or a subset of these compounds. Here, we develop an exhaustive extraction protocol using an accelerated solvent extraction protocol to recover the complete suite of cyclopeptides and other secondary metabolites found in Amanita phalloides (death cap mushrooms) and compare its efficacy to the “Classic” extraction method used in earlier works. We demonstrate that our extraction protocol recovers the full suite of cyclopeptides and other secondary metabolites in A. phalloides unlike the “Classic” method that favors polar cyclopeptides. Based on these findings, we provide recommendations for how to optimize protocols to ensure exhaustive extracts and also the best practices when using natural extracts in ecological experiments.
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