The overall objective of """"""""Alveolar DevMAP"""""""" our response to RFA-HL-14-008 Molecular Atlas of Lung Development - Research Center (RC) (U01) is to generate a compendium of the dynamic and regional changes in epigenetic marks, microRNA, mRNA and proteins that happen during alveolar septation, and use this compendium to generate a dynamic temporal regulatory model of normal alveolar septation. To address this objective we have assembled a multidisciplinary group of experts in lung development, genomics, epigenomics, quantitative imaging, systems and computational biology, and biostatistics. The PIs on this proposal group have previously identified mechanisms underlying abnormal alveolarization (Ambalavanan), epigenetic alterations in lung cell phenotype programming (Hagood), and altered developmental coding and non-coding RNA expression profiles in lung fibrosis (Kaminski) and more recently (together with Dr. Bar- Joseph) applied mirDREM, a probabilistic modeling method to reconstruct dynamic regulatory networks to explain how temporal gene expression is jointly regulated by miRNAs and transcription factors in the mouse lung during alveolar septation as well as applied novel approaches for localization and quantitation of tissue gene expression. We will address the objectives of this center by the following Specific Aims:
Specific Aim 1 - to identify changes in coding and non-coding RNAs during alveolar septation Specific Aim 2 - to determine changes in global DNA methylation during alveolar septation Specific Aim 3 - To identify the shifts in transcription factor and proteomic profile during alveolar septation Specific Aim 4 - To use, extend and validate our analytical tools to model dynamic signaling and regulatory networks activated in lung development that will be shared with other members of the consortium In all aims we will we will use samples acquired from laser capture microdissection )LCM) of developing alveoli or fluorescence activated cell sorting (FACS) of dispersed lung cells, collected at tight intervals to allow detailed analysis. Confirmation by quantitative immunohistochemistry and in-situ for transcripts will be included as well as some experimental validations. For this project, samples from the Human Tissue Core (HTC) will be supplied to UAB. Dr. Ambalavanan (Contact PI, UAB) will oversee LCM and FACS at UAB. Samples will be distributed to Dr. Kaminski (Yale) for miRNA and mRNA analysis, Dr. Hagood (UCSD) for DNA methylation, and Dr. Mobley (UAB) for proteomics. Data integration and computational model development will be done by Dr. Bar-Joseph at CMU. The Alveolar DevMAP and computational models developed through these studies will identify regulatory """"""""control points"""""""" in alveolar development. At a minimum, these studies will determine key miRNA, mRNA and DNA methylation control points in lung development using a systems biology approach to evaluate the network of interactions between multiple molecules, pathways, and cells as they converge to determine formation of the alveolar septum.
The molecules and regulatory processes involved in development of the alveoli in the lung are highly complex and we do not have a comprehensive understanding of this process. By identifying changes in genes and proteins that contribute to alveolar septation, followed by development of computational models, we will determine the mechanisms by which alveoli develop in the human lung.
|Olave, Nelida; Lal, Charitharth V; Halloran, Brian et al. (2016) Regulation of alveolar septation by microRNA-489. Am J Physiol Lung Cell Mol Physiol 310:L476-87|
|Sefer, Emre; Kleyman, Michael; Bar-Joseph, Ziv (2016) Tradeoffs between Dense and Replicate Sampling Strategies for High-Throughput Time Series Experiments. Cell Syst 3:35-42|
|Askenazi, David J; Koralkar, Rajesh; Patil, Neha et al. (2016) Acute Kidney Injury Urine Biomarkers in Very Low-Birth-Weight Infants. Clin J Am Soc Nephrol 11:1527-35|
|Clair, Geremy; Piehowski, Paul D; Nicola, Teodora et al. (2016) Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples. Sci Rep 6:39223|
|Lal, Charitharth Vivek; Travers, Colm; Aghai, Zubair H et al. (2016) The Airway Microbiome at Birth. Sci Rep 6:31023|
|Panikkanvalappil, Sajanlal R; James, Masheika; Hira, Steven M et al. (2016) Hyperoxia Induces Intracellular Acidification in Neonatal Mouse Lung Fibroblasts: Real-Time Investigation Using Plasmonically Enhanced Raman Spectroscopy. J Am Chem Soc 138:3779-88|
|Askenazi, David; Saeidi, Behtash; Koralkar, Rajesh et al. (2016) Acute changes in fluid status affect the incidence, associative clinical outcomes, and urine biomarker performance in premature infants with acute kidney injury. Pediatr Nephrol 31:843-51|
|Lal, Charitharth Vivek; Ambalavanan, Namasivayam (2015) Genetic predisposition to bronchopulmonary dysplasia. Semin Perinatol 39:584-91|
|Askenazi, David; Patil, Neha R; Ambalavanan, Namasivayam et al. (2015) Acute kidney injury is associated with bronchopulmonary dysplasia/mortality in premature infants. Pediatr Nephrol 30:1511-8|
|Saeidi, Behtash; Koralkar, Rajesh; Griffin, Russell L et al. (2015) Impact of gestational age, sex, and postnatal age on urine biomarkers in premature neonates. Pediatr Nephrol 30:2037-44|
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