Pilot 3: Computational Tools For Identifying Compositional Shifts In The CF Gut Microbiome
P.I.: Elhanan Borenstein, PhD
Assistant Professor of Genome Sciences
Adjunct Assistant Professor of Computer Science
External Professor, The Santa Fe Institute
Abstract: Cystic fibrosis (CF) is often associated with diseases of the intestinal tract, ultimately leading to malnutrition and poor growth. This persistent growth failure resists nutrient and enzyme replacement therapy, suggesting that factors other than inadequate nutrient intake or malabsorption may contribute to malnutrition in children with CF. Specifically, it has been suggested that the CF gut microbiome may influence growth and clinical outcomes through its effects on host metabolism, nutrition, and immune function.
To examine this hypothesis, the Cystic Fibrosis Research Translation Center at UW is currently characterizing the gut microbiomes of children with and without CF, using massively parallel next-generation sequencing methods, with additional efforts underway. These initiatives are generating exciting metagenomic data, mapping, for the first time, the previously uncharted composition of the CF gut microbiome. However, considering the numerous factors affecting the composition of the gut microbiome and the overall functional uniformity across samples, standard comparative analysis may fail to detect significant patterns. Advanced computational methods are therefore required to sift through this ultra-high-throughput data and pinpoint potential functional capacities of the microbiome that may be associated with CF and with clinical outcomes.
In this pilot project we will therefore develop a suite of novel computational methods for identifying associations between the composition of the microbiome and specific host phenotypes such as CF status and clinical parameters. These methods are especially tailored to identify subtle differences in highly-multidimensional data with a relatively small sample size – a common setting in comparative metagenomic analysis. We will focus on three complementary methods: First, we will develop a "Gene Set" based method for improved identification of over- and under-represented functional categories in the microbiome, inspired by microarray analysis. Second, we will develop a computational framework for co-occurrence-based grouping of genes in the microbiome and for dimension reduction, offering a more natural alternative to pathway-based grouping and accounting for inter-gene dependencies. Finally, we will develop a computational framework for simultaneously analyzing species and gene abundances, and for harnessing these two data sources in an integrated manner. Each of these methods aims to address specific weaknesses of standard comparative metagenomic analysis and to enhance the statistical power of such studies. We will further make the methods developed in this pilot project available to the research community both as an open source and as a web-application for wide accessibility.
Applying these tools to study the microbiomes of children with and without CF will allow us to obtain novel insights into functional shifts in the CF microbiome and their role in CF-related growth failure. The methods developed in this pilot study and their application to CF would lay the foundation for a large-scale study aimed at developing a comprehensive computational framework for improved comparative metagenomic analysis for studying the microbiome's contribution to CF and to other human diseases.
Pilot 4: Biochemical Mechanisms Mediating Impaired Insulin Secretion in Mouse Models of Cystic Fibrosis
P.I.: Ian Sweet, PhD
Metabolism, Endocrinology and Nutrition
Research Associate Professor
Director, Islet Core, UW DERC
Affiliate Investigator, Benaroya Research Institute
Cystic fibrosis (CF) is a congenital disease arising from mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) and affects about 30,000 people nationwide. Mutations of the CFTR gene affect functioning of the chloride ion channels in epithelial cell membranes, leading to the many symptoms of CF. As CF patients age, there is an increased incidence of diabetes mellitus, occurring in almost half the patients with the disease. This form of diabetes has features of both type 1 and type 2 diabetes and is called Cystic Fibrosis Related Diabetes (CFRD). The most conceptually attractive factor responsible for the increased incidence of diabetes is diminished insulin secretion due to impaired beta cell function. We have obtained preliminary data showing that insulin secretion is significantly decreased in islets from CFTR knockout mice. Based on these data, we hypothesize that the loss of CFTR function is related to a loss in cAMP-stimulated insulin secretion. The PI of this application has been Director of the Islet Cell Functional Analysis Core, part of an NIDDK-funded Diabetes Research Center, for the last 10 years, and has established and validated a wide array of assays specifically to characterize biochemical mechanisms regulating islet secretory function involving metabolic, electrogenic and signaling factors. We propose to use these assays, as well as assays available through the Inflammation Core of the CF Research and Translation Center, to characterize and study the properties of islets from mouse models of CF that indicate the role of CFTR mutations in CFRD. To accomplish this, we will carry out 2 specific aims, one that will focus on in vitro experiments designed to determine the intracellular mechanisms mediating the impaired secretory function due to the CFTR mutation. The second aim will focus on in vivo conditions where it will be determined whether conditions resulting from the development of CF (as simulated by infecting mice with Pseudomonas aeruginosa) further decrease secretory function. The results of these studies will provide data that has both fundamental and clinical implications and will support a future R01 application to be submitted by the PI.
Pilot 5: Role of Islet Amyloid and Il-1β Signaling in β-cell Loss in Cystic Fibrosis-Related Diabetes
P.I.: Rebecca Hull, PhD
Metabolism, Endocrinology and Nutrition
Research Assistant Professor of Medicine
Srinath Sanda, MD
Associate Professor, Pediatrics
University of California at San Fransisco
This proposal seeks to determine the role of ILβ in the pathogenesis of cystic fibrosis related diabetes (CFRD). CFRD is a unique form of diabetes and new treatments are needed to improve the morbidity and mortality of cystic fibrosis patients. Therefore the goals of this grant proposal are directly relevant to the mission of the National Institute of Diabetes, Digestive, and Kidney Diseases. The grant proposal consists of 2 broad aims. First we will compare the degree of amyloid deposition between autopsy pancreas sections from CFRD patients, CF patients without diabetes and age-matched controls. Subjects with type 2 diabetes, and appropriately-matched subjects without type 2 diabetes will serve as positive and negative controls for the measurements of interest. We anticipate that CFRD patients will show extensive deposition of islet amyloid, together with decreased β-cell area, reduced insulin expression, and increased β-cell apoptosis. Second we will analyze the same samples for evidence that the IL-1β pathway is active. In particular we will stain for IL-1β, IL-1Ra, NF-κB, MyD88, and CCL2. Aim 2: Do pancreatic sections from patients with CFRD show evidence of IL-1β activation? We will also determine whether correlations exist between these markers of the IL-1β pathway and measured obtained in Aim1, namely islet amyloid deposition, β-cell area and measures of β-cell apoptosis and replication. We anticipate that IL-1β activation will be a major feature of the islet in CFRD, suggesting that this pathway may play a role in the pathogenesis of islet dysfunction in this patient population.