the-treadwheel-interval-training-protocol-for-gently-induced-exercise

The TreadWheel: Interval Training Protocol for Gently Induced Exercise in <em>Drosophila melanogaster</em>

The incidence of complex metabolic diseases has increased as a result of a widespread transition towards lifestyles of increased caloric intake and ...

University of Alabama

There is widespread agreement that science, technology, engineering, and mathematics programs should provide undergraduates with research experience. Practical issues and limited resources, however, make this a challenge. We have developed a bioinformatics project that provides a course-based research experience for students at a diverse group of schools and offers the opportunity to tailor this experience to local curriculum and institution-specific student needs. We assessed both attitude and knowledge gains, looking for insights into how students respond given this wide range of curricular and institutional variables. While different approaches all appear to result in learning gains, we find that a significant investment of course time is required to enable students to show gains commensurate to a summer research experience. An alumni survey revealed that time spent on a research project is also a significant factor in the value former students assign to the experience one or more years later. We conclude: 1) implementation of a bioinformatics project within the biology curriculum provides a mechanism for successfully engaging large numbers of students in undergraduate research; 2) benefits to students are achievable at a wide variety of academic institutions; and 3) successful implementation of course-based research experiences requires significant investment of instructional time for students to gain full benefit.

A course-based research experience: how benefits change with increased investment in instructional time.

Systems biology is an approach to dissection of complex traits that explicitly recognizes the impact of genetic, physiological, and environmental interactions in the generation of phenotypic variation. We describe comprehensive transcriptional and metabolic profiling in Drosophila melanogaster across four diets, finding little overlap in modular architecture. Genotype and genotype-by-diet interactions are a major component of transcriptional variation (24 and 5.3% of the total variation, respectively) while there were no main effects of diet (<1%). Genotype was also a major contributor to metabolomic variation (16%), but in contrast to the transcriptome, diet had a large effect (9%) and the interaction effect was minor (2%) for the metabolome. Yet specific principal components of these molecular phenotypes measured in larvae are strongly correlated with particular metabolic syndrome-like phenotypes such as pupal weight, larval sugar content and triglyceride content, development time, and cardiac arrhythmia in adults. The second principal component of the metabolomic profile is especially informative across these traits with glycine identified as a key loading variable. To further relate this physiological variability to genotypic polymorphism, we performed evolve-and-resequence experiments, finding rapid and replicated changes in gene frequency across hundreds of loci that are specific to each diet. Adaptation to diet is thus highly polygenic. However, loci differentially transcribed across diet or previously identified by RNAi knockdown or expression QTL analysis were not the loci responding to dietary selection. Therefore, loci that respond to the selective pressures of diet cannot be readily predicted a priori from functional analyses.

Systems genomics of metabolic phenotypes in wild-type Drosophila melanogaster.

The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have higher transposon density (25%-50%) than euchromatic reference regions (3%-11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% versus 11%-27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4-3.6 versus 8.4-8.8 genes per block), indicating higher rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu.

Drosophila Muller F Elements Maintain a Distinct Set of Genomic Properties Over 40 Million Years of Evolution.

Genetic and environmental factors influence complex disease in humans, such as metabolic syndrome, and Drosophila melanogaster serves as an excellent model in which to test these factors experimentally. Here we explore the modularity of endophenotypes with an in-depth reanalysis of a previous study by Reed et al. (2014), where we raised 20 wild-type genetic lines of Drosophila larvae on four diets and measured gross phenotypes of body weight, total sugar, and total triglycerides, as well as the endophenotypes of metabolomic and whole-genome expression profiles. We then perform new gene expression experiments to test for conservation of phenotype-expression correlations across different diets and populations. We find that transcript levels correlated with gross phenotypes were enriched for puparial adhesion, metamorphosis, and central energy metabolism functions. The specific metabolites L-DOPA and N-arachidonoyl dopamine make physiological links between the gross phenotypes across diets, whereas leucine and isoleucine thus exhibit genotype-by-diet interactions. Between diets, we find low conservation of the endophenotypes that correlate with the gross phenotypes. Through the follow-up expression study, we found that transcript-trait correlations are well conserved across populations raised on a familiar diet, but on a novel diet, the transcript-trait correlations are no longer conserved. Thus, physiological canalization of metabolic phenotypes breaks down in a novel environment exposing cryptic variation. We cannot predict the physiological basis of disease in a perturbing environment from profiles observed in the ancestral environment. This study demonstrates that variation for disease traits within a population is acquired through a multitude of physiological mechanisms, some of which transcend genetic and environmental influences, and others that are specific to an individual's genetic and environmental context. 

Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila.

Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research. 

The Time Is Right to Focus on Model Organism Metabolomes.

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. 

Genetic and Sex-Specific Transgenerational Effects of a High Fat Diet in Drosophila melanogaster.

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species' demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions.

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.

The TreadWheel: A Novel Apparatus to Measure Genetic Variation in Response to Gently Induced Exercise for Drosophila.

Understanding how and why populations evolve is of fundamental importance to molecular ecology. Restriction site-associated DNA sequencing (RADseq), a popular reduced representation method, has ushered in a new era of genome-scale research for assessing population structure, hybridization, demographic history, phylogeography and migration. RADseq has also been widely used to conduct genome scans to detect loci involved in adaptive divergence among natural populations. Here, we examine the capacity of those RADseq-based genome scan studies to detect loci involved in local adaptation. To understand what proportion of the genome is missed by RADseq studies, we developed a simple model using different numbers of RAD-tags, genome sizes and extents of linkage disequilibrium (length of haplotype blocks). Under the best-case modelling scenario, we found that RADseq using six- or eight-base pair cutting restriction enzymes would fail to sample many regions of the genome, especially for species with short linkage disequilibrium. We then surveyed recent studies that have used RADseq for genome scans and found that the median density of markers across these studies was 4.08 RAD-tag markers per megabase (one marker per 245 kb). The length of linkage disequilibrium for many species is one to three orders of magnitude less than density of the typical recent RADseq study. Thus, we conclude that genome scans based on RADseq data alone, while useful for studies of neutral genetic variation and genetic population structure, will likely miss many loci under selection in studies of local adaptation.

Breaking RAD: an evaluation of the utility of restriction site-associated DNA sequencing for genome scans of adaptation.

Global warming and anthropogenic disturbances significantly influence the biosphere, tremendously increasing species extinction rates. In Central Alabama, we analyzed Drosophilidae species composition change nearly 100 years after the previous survey. We found ten Drosophilid species that were not reported during the last major biodiversity studies, two of which are invasive pests. In addition, we analyzed the influence of seasonal environmental variables characteristic of the subtropical climate zone on  abundance and biodiversity. We found a significant correlation between temperature and abundance of total  as well as for six of the seven most represented species individually, with a maximum abundance at intermediate temperatures (18-26°C). In addition, temperature was positively correlated with biodiversity of . Precipitation produced a significant effect on the abundance of five species of Drosophila, with different optima for each species, but did not affect overall biodiversity. We concluded that in the subtropical climate zone of Central Alabama, seasonal temperature and precipitation changes produce a significant effect on  abundance and biodiversity, while local land use also impacts fly abundance, contributing to an apparent shift in species composition over the last century. We expect global climate change and other anthropogenic factors to further impact  species composition in the subtropical climate zone into the future.

The changing biodiversity of Alabama : important impacts of seasonal variation, urbanization, and invasive species.

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.

Considerations when choosing a genetic model organism for metabolomics studies.

Two recent articles were written in response to our paper "Breaking RAD: An evaluation of the utility of restriction site associated DNA sequencing scans of adaptation." While we agree with some of the comments made by the authors of these two response papers, we still believe caution should be employed in RADseq studies that aim to detect loci that contribute to adaptation. In this rebuttal, we evaluate the key points made in these papers, attempt to identify a middle ground and make suggestions for responsibly conducting future studies to understand the genomewide mechanisms of adaptation.

Responsible RAD: Striving for best practices in population genomic studies of adaptation.

The discordance between genome size and the complexity of eukaryotes can partly be attributed to differences in repeat density. The Muller F element (∼5.2 Mb) is the smallest chromosome in , but it is substantially larger (>18.7 Mb) in  To identify the major contributors to the expansion of the F element and to assess their impact, we improved the genome sequence and annotated the genes in a 1.4-Mb region of the  F element, and a 1.7-Mb region from the D element for comparison. We find that transposons (particularly LTR and LINE retrotransposons) are major contributors to this expansion (78.6%), while  sequences integrated into the  genome are minor contributors (0.02%). Both  and  F-element genes exhibit distinct characteristics compared to D-element genes (, larger coding spans, larger introns, more coding exons, and lower codon bias), but these differences are exaggerated in  Compared to , the codon bias observed in  F-element genes can primarily be attributed to mutational biases instead of selection. The 5' ends of F-element genes in both species are enriched in dimethylation of lysine 4 on histone 3 (H3K4me2), while the coding spans are enriched in H3K9me2. Despite differences in repeat density and gene characteristics,  F-element genes show a similar range of expression levels compared to genes in euchromatic domains. This study improves our understanding of how transposons can affect genome size and how genes can function within highly repetitive domains.

Retrotransposons Are the Major Contributors to the Expansion of the  Muller F Element.

Following similar global efforts to exchange genomic and other biomedical data, global databases in metabolomics have now been established. MetaboLights, the first general purpose, publically available, cross-species, cross-application database in metabolomics, has become the fastest growing data repository at the European Bioinformatics Institute in terms of data volume. Here we present the automated assembly of species metabolomes in MetaboLights, a crucial reference for chemical biology, which is growing through user submissions.

Automated assembly of species metabolomes through data submission into a public repository.

'Multi-omics' datasets obtained from an organism of interest reared under different environmental treatments are increasingly common. Identifying the links among metabolites and transcripts can help to elucidate our understanding of the impact of environment at different levels within the organism. However, many methods for characterizing physiological connections cannot address unidentified metabolites.

Article	Year
A course-based research experience: how benefits change with increased investment in instructional time. CBE life sciences education\| PubMed ID: 24591510	2014
Systems genomics of metabolic phenotypes in wild-type Drosophila melanogaster. Genetics\| PubMed ID: 24671769	2014
Drosophila Muller F Elements Maintain a Distinct Set of Genomic Properties Over 40 Million Years of Evolution. G3 (Bethesda, Md.)\| PubMed ID: 25740935	2015
Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila. G3 (Bethesda, Md.)\| PubMed ID: 26530416	2015
The Time Is Right to Focus on Model Organism Metabolomes. Metabolites\| PubMed ID: 26891337	2016
Genetic and Sex-Specific Transgenerational Effects of a High Fat Diet in Drosophila melanogaster. PloS one\| PubMed ID: 27518304	2016
Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions. The American naturalist\| PubMed ID: 27622873	2016
The TreadWheel: A Novel Apparatus to Measure Genetic Variation in Response to Gently Induced Exercise for Drosophila. PloS one\| PubMed ID: 27736996	2016
Breaking RAD: an evaluation of the utility of restriction site-associated DNA sequencing for genome scans of adaptation. Molecular ecology resources\| PubMed ID: 27860289	2017
The changing biodiversity of Alabama : important impacts of seasonal variation, urbanization, and invasive species. Ecology and evolution\| PubMed ID: 27895896	2016
Considerations when choosing a genetic model organism for metabolomics studies. Current opinion in chemical biology\| PubMed ID: 28025166	2017
Responsible RAD: Striving for best practices in population genomic studies of adaptation. Molecular ecology resources\| PubMed ID: 28382730	2017
Retrotransposons Are the Major Contributors to the Expansion of the Muller F Element. G3 (Bethesda, Md.)\| PubMed ID: 28667019	2017
Automated assembly of species metabolomes through data submission into a public repository. GigaScience\| PubMed ID: 28830114	2017
Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes. Metabolomics : Official journal of the Metabolomic Society\| PubMed ID: 28845148	2016

Laura K. Reed

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