Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


7992.pdf (4.78 MB)

ETD Abstract Container

Abstract Header

High Throughput Automated Comparative Analysis of RNAs Using Isotope Labeling and LC-MS/MS

Li, Siwei
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384427990

Abstract Details

2014, PhD, University of Cincinnati, Arts and Sciences: Chemistry.
Mass spectrometry is a powerful technique for the characterization of ribonucleic acids. The focus of this work is developing mass spectrometric methods for high throughput automated analysis of ribonucleic acids (RNAs) by comparative approaches, where only differences within the mass spectral data need to be analyzed. This method allows sequence or modification information from a previously uncharacterized RNA to be obtained by direct comparison with a reference RNA, whose sequence or modification information is known. This simple and rapid method is enabled by the differential labeling of two RNA samples. One sample, the reference RNA, is labeled with 16O during enzymatic digestion. The second sample, the candidate or unknown RNA, is labeled with 18O. By combining the two digests, digestion products that share the same sequence or post-transcriptional modification(s) between the reference and candidate will appear as doublets separated by 2 Da. Sequence or modification differences between the two will generate singlets that can be further characterized to identify how the candidate sequence differs from the reference. I illustrate application of this approach for sequencing individual RNAs and demonstrate how this method can be used to identify sequence-specific differences in RNA modification. Using CARD approach, ca. 80% of the tRNAs from the bacterium Citrobacter koseri can be sequenced using ribonuclease T1 with Escherichia coli tRNAs as the reference. During these studies, a sequence error for Escherichia coli tRNA-Thr1 was discovered, and the correct sequence for that tRNA was confirmed by this method. For many applications, the differences between two samples will be minor meaning that much of the mass spectral data will be doublets with only a few singlets. The challenge in data analysis is to rapidly identify and characterize these singlets. To address this challenge, an algorithm for automated data analysis was developed based on Microsoft Visual Basic for Application (VBA) macro-program, simplifying and automating the examination of LC-MS data for identification of isotopically labeled doublets and singlets. The automated processing steps in this program drastically reduce the need for manual processing of LC-MS data by applying filters to remove thousands of doublets and interferences in the mass spectral data. In addition to these method and algorithm developments, during the course of comparative analysis of RNA, many predicted tRNA digestion products share identical m/z values yet different sequences. These tRNA sequence isomers can hinder the accuracy of unknown tRNA identification. To overcome this limitation, tandem mass spectrometric method was developed to identify those interference-prone singlets based on unique isotopically labeled fragments in tandem mass spectra.
Patrick Limbach, Ph.D. (Committee Chair)
William Heineman, Ph.D. (Committee Member)
Pearl Tsang, Ph.D. (Committee Member)
116 p.
Analytical Chemistry
RNA; Modified nucleosides; Sequencing; LCMS; LCMSMS; Automated Analysis

Recommended Citations

Citations

  • Li, S. (2014). High Throughput Automated Comparative Analysis of RNAs Using Isotope Labeling and LC-MS/MS [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384427990

    APA Style (7th edition)

  • Li, Siwei. High Throughput Automated Comparative Analysis of RNAs Using Isotope Labeling and LC-MS/MS. 2014. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384427990.

    MLA Style (8th edition)

  • Li, Siwei. "High Throughput Automated Comparative Analysis of RNAs Using Isotope Labeling and LC-MS/MS." Doctoral dissertation, University of Cincinnati, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384427990

    Chicago Manual of Style (17th edition)

ucin1384427990
428
© 2014, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.