A detailed network of transcriptome regulation associated with life-span extension in model organisms
Lead Research Organisation:
University College London
Department Name: Genetics Evolution and Environment
Abstract
In worms, flies and mice, it has been known for a long time that reduced feeding can result in longer life-spans, and in recent years, simple manipulations in the way these animals sense and response to sugars through insulin have also been shown to increase life-span. However, we are still a long way from understanding the mechanisms involved in food restriction and disruption of insulin signalling. To make this even more difficult, recent discoveries have shown that the cells that make up worms, flies, mice and even ourselves are much more complicated than we ever imagined. The work proposed would use leading-edge technologies to try to understand the mechanisms associated with longer life-spans in animals such as worms and flies where experiments would take months instead of years (mice) or a lifetime (humans). These new technologies generate huge amounts of data and will give the most detailed view possible of the changes that happen in worms and flies to make them long lived. The identification of similar changes in worms and flies (animals that are separated by millions of years of evolution) would suggest a mechanism that is highly conserved and may exist in other animals like mice or humans.
Technical Summary
Recent work has shown the remarkable conservation of mechanisms that can extend life-span in model organisms. Work in worms, flies and mice has shown that single mutations in the insulin/insulin-like growth factor signalling pathways can result in long-lived animals. Similarly, long standing work has shown that dietary restriction also increases life-span in a range of species. I propose the following related projects to understand the mechanisms that extend life-span:
1. Use tiling array and sequencing technology to give a complete view of the transcriptome in model organisms
2. Use DAM-ID technology to understand the DNA-protein and protein-protein interactions of transcription factors (TFs) that are known to be involved in life-span extension
Most transcriptome data collected on long-lived animals has been limited to detecting changes at the 3‘ end of genes. Whole genome tiling arrays would report the expression of different exons and non-coding RNAs. To understand the role of these elements in longevity, total RNA hybridization to tiling arrays from long-lived worms and flies would be compared to hybridizations using wildtype worms and flies. In addition, little is known about the tissue specificity of changes to exon or non-coding expression, and tissue specific samples in flies would be taken for comparison. It is hoped that given such a detailed view of the transcriptome, we will be able to build a network showing the possible interactions between coding and non-coding transcripts that lead to transcriptional and post-transcriptional changes.
Current knowledge of transcription factor binding is also very limited and methods that report interactions between TFs and DNA do not distinguish between regulation that exists because of DNA-protein or protein-protein interactions. Chimeric proteins containing TFs essential for longevity fused to the Escherichia coli DNA adenine methyltransferase (Dam) domain would be used to identify regions where TFs associate with DNA. These regions are methylated by the Dam domain and can be isolated from unmethylated DNA by restriction enzymes. Chimeric proteins using wildtype TFs would show all interactions, and comparison of DNA methylation profiles of wildtype TFs and mutant TFs that lack DNA binding capability or deletions of domains essential for protein-protein interaction would allow one to distinguish between regulation that exists because of direct DNA-protein interactions or because the TF interacts with another protein that is bound to the DNA. The TF interactions would then be integrated into the regulatory network created for the tiling arrays.
1. Use tiling array and sequencing technology to give a complete view of the transcriptome in model organisms
2. Use DAM-ID technology to understand the DNA-protein and protein-protein interactions of transcription factors (TFs) that are known to be involved in life-span extension
Most transcriptome data collected on long-lived animals has been limited to detecting changes at the 3‘ end of genes. Whole genome tiling arrays would report the expression of different exons and non-coding RNAs. To understand the role of these elements in longevity, total RNA hybridization to tiling arrays from long-lived worms and flies would be compared to hybridizations using wildtype worms and flies. In addition, little is known about the tissue specificity of changes to exon or non-coding expression, and tissue specific samples in flies would be taken for comparison. It is hoped that given such a detailed view of the transcriptome, we will be able to build a network showing the possible interactions between coding and non-coding transcripts that lead to transcriptional and post-transcriptional changes.
Current knowledge of transcription factor binding is also very limited and methods that report interactions between TFs and DNA do not distinguish between regulation that exists because of DNA-protein or protein-protein interactions. Chimeric proteins containing TFs essential for longevity fused to the Escherichia coli DNA adenine methyltransferase (Dam) domain would be used to identify regions where TFs associate with DNA. These regions are methylated by the Dam domain and can be isolated from unmethylated DNA by restriction enzymes. Chimeric proteins using wildtype TFs would show all interactions, and comparison of DNA methylation profiles of wildtype TFs and mutant TFs that lack DNA binding capability or deletions of domains essential for protein-protein interaction would allow one to distinguish between regulation that exists because of direct DNA-protein interactions or because the TF interacts with another protein that is bound to the DNA. The TF interactions would then be integrated into the regulatory network created for the tiling arrays.