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Understanding the impact of air quality on the chemistry of ribonucleic acids that affect human health

Principal Investigator: 
,

University of Texas-Austin

This New Investigator Award study is evaluating changes in different types of RNA molecules inside cells after exposure to ozone and carbonyls.

Funded under
Status: 
In review
Abstract

Abstract for the 2018 HEI Annual Conference

The Role of Air Pollution on RNA Oxidative Stress, Characterization of Stress-Response Enzymes, and Applications toward RNA-Based Biosensors

Lydia M. Contreras, Juan C. Gonzalez, Kevin Baldridge

Mcketta Department of Chemical Engineering, University of Texas at Austin, Texas, USA

Background. We have previously shown that levels of 8-oxoguanosine (8OG) may present a more immediate and consistent measure of cellular stress in air pollution exposure models (Baldridge et al. 2015). However, a mechanistic understanding of the role for RNA oxidation in acute air pollution stress responses has not been investigated. Our main objective in this work is to elucidate underlying biological processes altered in the human lung cell models upon air pollution exposure by functional profiling of stress-induced RNA oxidation transcripts.

Methods. We exposed BEAS-2B lung cell cultures (N = 3) to different levels of air pollution mixtures (4 ppm ozone, 872 ppb acrolein, 698 ppb methacrolein; 0.4 ppm ozone, 872 ppb acrolein, and 698 ppb methacrolein; and 0.4 ppm ozone, 100 ppb acrolein, and 100 ppb methacrolein) for 90 minutes. We extracted total RNAs and treated samples with an antibody against 8OG, with subsequent RT-qPCR analysis of enriched and un-enriched RNA pools for both pollution-exposed and clean-air-control samples. We isolated proteins from BEAS-2B cultures and performed Western blots for both treatment conditions to analyze relevant protein expression. We measured levels of intracellular cholesterol by a colorimetric assay for both treatment conditions. We conducted functional profiling using gene sets differentially enriched (adjusted p-value < 0.05) using Enrichment Map and Cytoscape. For our work related to developing oxidizing-recognizing proteins, we developed a molecular dynamics-based method that screens a library of ~100 modifications already parametrized in CHARMM (Chemistry at Harvard macromolecular mechanics) in collaboration with Dr. Phanourios Tamamis at Texas A&M. The method was subsequently validated using the protein E. PNPase and a set of previously characterized RNA modifications by electrophoretic mobility shift assays (EMSAs). We conducted EMSAs of PNPase with three RNA modifications predicted to improve its binding affinity (N = 3) using 25-mers each containing 6 modifications distributed through the oligonucleotide.

Results. Initial RT-qPCR profiling and Western blotting analysis demonstrate differential expression and oxidation enrichment of RNAs that encode for specific proteins within the cholesterol pathway when exposed to differential levels of pollution mixtures compared to cells exposed to clean air. Moreover, the functional profiling of oxidation transcripts reveals that critical cellular processes such as mRNA splicing, histone modifications, rRNA and tRNA processing, and cell cycle are potentially altered by stress-induced RNA oxidation. Lastly, our efforts to characterize protein binding to modified RNAs have led to a validated high-throughput computational method that has, so far, identified 10 modifications that can increase the binding affinity of PNPase. This model predicts that the sites that interact with the modified RNAs (via H-bonds, salt bridges and van der Walls forces) are localized near the putative binding site of the widely conserved RNA-binding domains in PNPase. These predictions agree with experimental shift assays of PNPase mutants suggesting that binding site multiplicity is involved on the specific interactions of PNPase and modified RNAs.

 
POSTER
 
 
PUBLICATIONS

Mihailovic MK, Chen A, Gonzalez-Rivera JC, Contreras LM. Defective Ribonucleoproteins, Mistakes in RNA Processing, and Diseases. Biochemistry. 2017 Mar 14;56(10):1367-1382. doi: 10.1021/acs.biochem.6b01134. Epub 2017 Feb 28.

Orr AA, Gonzalez-Rivera JC, Wilson M, Bhikha PR, Wang D, Contreras LM, Tamamis P. A high-throughput and rapid computational method for screening of RNA post-transcriptional modifications that can be recognized by target proteins. Methods. 2018 Jul 1;143:34-47. doi: 10.1016/j.ymeth.2018.01.015. Epub 2018 Feb 1.