Project description:Developing organisms have evolved a wide range of mechanisms for coping with recurrent environmental challenges. How they cope with rare or unforeseen challenges is, however, unclear as are the implications to their unchallenged offspring. Here we investigate these questions by confronting the development of the fly, D. melanogaster, with artificial tissue distributions of toxic stress that are not expected to occur during fly development. We show that under a wide range of toxic scenarios, this challenge can lead to modified development which may coincide with increased tolerance to an otherwise lethal condition. Part of this response was mediated by suppression of Polycomb group genes, which in turn leads to de-repression of developmental regulators and their expression in new domains. Importantly, some of the developmental alterations were epigenetically inherited by subsequent generations of unchallenged offspring. These results show that the environment can induce alternative patterns of development that are stable across multiple generations. Measuring differences in RNA levels between larvae that were exposed to a toxic challenge and unchallenged larvae. measuring differences in RNA levels between F3 larvae with or without past exposure to the challenge in F1 generation.
Project description:Developing organisms have evolved a wide range of mechanisms for coping with recurrent environmental challenges. How they cope with rare or unforeseen challenges is, however, unclear as are the implications to their unchallenged offspring. Here we investigate these questions by confronting the development of the fly, D. melanogaster, with artificial tissue distributions of toxic stress that are not expected to occur during fly development. We show that under a wide range of toxic scenarios, this challenge can lead to modified development which may coincide with increased tolerance to an otherwise lethal condition. Part of this response was mediated by suppression of Polycomb group genes, which in turn leads to de-repression of developmental regulators and their expression in new domains. Importantly, some of the developmental alterations were epigenetically inherited by subsequent generations of unchallenged offspring. These results show that the environment can induce alternative patterns of development that are stable across multiple generations.
Project description:The mutation in the C9orf72 gene with a hexanucleotide repeat has been reported multiple times to be the most common genetic cause of FTD and ALS (Frontotemporal Dementia and Amyotrophic Lateral Sclerosis), both of which are devastating neurodegenerative diseases having no cures currently. Our lab previously created fruit fly models expressing 36(C4G2) repeats, these are highly toxic to adult neurons of fruit flies. This is one of the most commonly used fly models of disease. Like many neurodegenerative diseases, FTD and ALS display selective neuronal vulnerability: only some neuronal populations succumb to disease, even though the toxic species are ubiquitously expressed. Our lab proposes to identify which neuronal populations are selectively depleted in response to the expression of the repeats and analyse which pathways are activated in vulnerable and resistant neuronal populations using our fly model of disease. This is done by scRNA sequencing across multiple time points, tracking disease development. The workflow was first having the flies ready and their brains being dissected. The brains were then dissociated by collagenase and dispase, and the cell suspensions were passed through a 10um cell strainer. The single-cell suspensions were checked for viability and the single-cell libraries were prepared with 10X Chromium 3' platform.
Project description:Transfer RNAs (tRNAs) are vital in determining the specificity of translation. Mutations in tRNAs can result in the mis-incorporation of amino acids into nascent polypeptides in a process known as mistranslation. Here, our goal was to test the impacts of different types of mistranslation in the model organism Drosophila melanogaster, as impact of mistranslation depends on the type of amino acid substitution. We created two fly lines - one expressing a serine tRNA variant with valine anticodon and the other with a serine tRNA variant with a threonine anticodon. Using mass spectrometry, we measure the amount of mistranslation at various points in fly development.
Project description:We report the proteome composition of the Drosophila eye – a compound organ that is highly enriched in membrane proteins. The fly eye is a popular model to study the physiology of vision by means of genetic, pharmacological, and dietary interference.While the eye transcriptome and development-related changes of gene expression profiles have been extensively studied, little is known about the eye proteome.we employed GeLC-MS/MS to identify and rank the abundances of 3516 eye proteins. Moreover, we applied our MS Western method to determine the absolute (molar) abundances of a related set of proteins that are important for photoreceptor structure (including maintenance) and function (phototransduction). Altogether, we provide a comprehensive and expandable proteomics resource that will be valuable for a variety of studies of ocular biochemistry, physiology, and development.
Project description:Drosophila melanogaster is a well-studied genetic model organism with several large-scale transcriptome resources. Here we investigate 7,952 proteins during the fly life cycle from embryo to adult and also provide a high-resolution temporal time course proteome of 5,458 proteins during embryogenesis. We use our large scale data set to compare transcript/protein expression, uncovering examples of extreme differences between mRNA and protein abundance. In the embryogenesis proteome, the time delay in protein synthesis after transcript expression was determined. For some proteins, including the transcription factor lola, we monitor isoform specific expression levels during early fly development. Furthermore, we obtained firm evidence of 268 small proteins, which are hard to predict by bioinformatics. We observe peptides originating from non-coding regions of the genome and identified Cyp9f3psi as a protein-coding gene. As a powerful resource to the community, we additionally created an interactive web interface (http://www.butterlab.org) advancing the access to our data.