Nicola Neretti, Ph.D. - US grants

[unreadable] DESCRIPTION (provided by applicant): Funding is sought for a five year mentored training period at Brown University for Dr. Nicola Neretti to transition from physics to independent investigator in computational biology. The candidate has a Physics PhD from Brown University, and has been working in the field of signal processing and machine learning. During the past year he has been part of a collaborative project with Dr. John Sedivy (Department of Molecular and Cell Biology and Biochemistry) which resulted in a published paper about the analysis of gene expression array data to target c-Myc-activated genes with a correlation-based method. He has established other productive collaborations with members of the Center for Computational Molecular Biology (CCMB) at Brown University. The principal mentor will be Dr. Marc Tatar (Department of Ecology and Evolutionary Biology). The secondary mentors will be Dr. Charles Lawrence (Dep. Applied Mathematics) and Dr. John Sedivy. The work plan for the five years is to split the training/research effort evenly between computation and biology. For the training requirements the candidate plans to attend courses and workshops in genetics, biochemistry, molecular biology, bioinformatics, and related fields. Dr. Neretti also plans to complete lab rotations in the laboratory of Dr. Marc Tatar and Dr. John Sedivy, to acquire first hand experience in generating the biological data he will later analyze. The main focus of the research effort will be to use microarray data in time course experiments with a high temporal resolution to elucidate the complex interactions among genes and develop novel analytic techniques in functional genomic. In particular, the candidate proposes to integrate the results of gene clustering/graph analysis (e.g. correlation and tagged correlation based clustering) obtained from the time course data with the information available in genetic/pathway databases relevant to the process of senescence. This will allow the evaluation of given hypotheses about functional relationships among genes and the identification of novel dependencies, which can then be directly tested via experiments in model systems of aging. By using this approach the candidate proposes to address key questions in aging research such as what transcriptional changes are under the control of a nutrient sensing system, the temporal and hierarchical relationship of these changes, the magnitude of change that is biologically relevant, and whether genes within a functional metabolic network are co-regulated at the transcriptional level. [unreadable] [unreadable] [unreadable] [unreadable] [unreadable] [unreadable]

? DESCRIPTION (provided by applicant): Retrotransposable elements (RTEs) comprise approximately 45% of the human genome. RTEs are mobile DNA elements that can insert into new genomic positions using a copy and paste mechanism. This process, termed retrotransposition, can be deleterious at multiple levels by causing mutagenesis and genome structural instability, triggering epigenetic changes, and disrupting normal patterns of gene regulation. Numerous single- gene mutations in humans have been documented to result from germline retrotransposition. Organisms have evolved multiple transcriptional and post-transcriptional silencing mechanisms to protect their genomes against RTEs. Until recently RTEs were thought to be silent in the soma, however, new evidence points to activity in the brain and in cancer cells. Indeed, initial indications are that somatic retrotransposition is much more frequent than previously anticipated. We have reported that retrotransposition is activated during aging and cellular senescence, and hypothesized that it may represent a hitherto unappreciated molecular aging process. The long-term goal of our research is to determine the impact of retrotransposition on genome integrity during aging. As a first step, our objective in this proposal is to study, using high throughput DNA and RNA sequencing methods, the mobilization of RTEs during cellular senescence and aging, and their impact on the transcriptome. In Aim 1 we will perform genome-wide high-throughput DNA sequencing of in senescent cells to determine where new insertions occur and to evaluate whether these events have the potential to exert deleterious effects by disrupting regions of the genome important for cell function. We have evidence that many new insertions likely occur in individual post-mitotic cells after they have ceased dividing. To comprehensively profile the spectrum and frequency of these events we will use single-cell whole genome DNA sequencing. In Aim 2 we will perform these same studies in the mouse to investigate to what degree different tissues are affected by increased retrotransposition with age. In Aim 3 we will investigate the effects of RTEs derepression and transposition on the transcriptome of senescent cells and in the aging mouse. Our research will employ innovative state-of-the-art high-throughput sequencing strategies, and we will develop new bioinformatics tools to integrate and validate the output from multiple algorithms. The information obtained will address the question: To what extent is retrotransposition damaging to the genomes of somatic cells in our bodies, and is this a plausible mechanism of aging? The experience gained and tools developed will be highly informative for future studies aimed at examining these processes directly in aging tissues. Our efforts will also inform us whether proof-of-principle studies using interventions that inhibit retrotransposition should be investigated as potential therapeutics for age-associated diseases.

Project Summary Evidence exists that the risk for a wide range of chronic diseases increases with age. For many of these diseases effective pharmacological interventions are lacking. Hence, any intervention that can slow aging can also reduce the potential of contracting such illnesses. Although several compounds are currently under investigation for their life span extending effects, the complexity of the aging phenotype makes this search difficult. In this project we combine two emerging strategies for drug discovery, namely in silico pharmacology and the use of invertebrate whole-animal models. Aim 1 will provide a collection of candidate compounds by performing a large-scale bioinformatics screen of over 1,300 pharmacological agents. To do this we will utilize a novel gene list comparison algorithm we have developed to identify significant associations between expression changes induced by drug treatment and expression changes observed in interventions that extend healthspan. Aim 2 will test the effect of drugs identified in Aim 1 in Drosophila melanogaster. Flies will be fed each compound over the course of their adult life, and their life span as well as their response to stressors will be monitored and compared to that of flies on control food. The proposed work will develop an important new bioinformatics strategy to screen for longevity drugs and has the potential to identify several novel compounds that extend life span. Aim 3 will utilize the same data collected in Aim 1 but will use a complementary approach in which shared regulatory elements will be identified in the promoters of the genes in the common signatures between drugs and healthspan interventions.