| Title |
Metabolic De-Isotoping for Improved LC-MS Characterization of Modified RNAs
|
|---|---|
| Published in |
Journal of the American Society for Mass Spectrometry, April 2014
|
| DOI | 10.1007/s13361-014-0889-9 |
| Pubmed ID | |
| Authors |
Collin Wetzel, Siwei Li, Patrick A. Limbach |
| Abstract |
Mapping, sequencing, and quantifying individual noncoding ribonucleic acids (ncRNAs), including post-transcriptionally modified nucleosides, by mass spectrometry is a challenge that often requires rigorous sample preparation prior to analysis. Previously, we have described a simplified method for the comparative analysis of RNA digests (CARD) that is applicable to relatively complex mixtures of ncRNAs. In the CARD approach for transfer RNA (tRNA) analysis, two complete sets of digestion products from total tRNA are compared using the enzymatic incorporation of (16)O/(18)O isotopic labels. This approach allows one to rapidly screen total tRNAs from gene deletion mutants or comparatively sequence total tRNA from two related bacterial organisms. However, data analysis can be challenging because of convoluted mass spectra arising from the natural (13)C and (15) N isotopes present in the ribonuclease-digested tRNA samples. Here, we demonstrate that culturing in (12)C-enriched/(13)C-depleted media significantly reduces the isotope patterns that must be interpreted during the CARD experiment. Improvements in data quality yield a 35 % improvement in detection of tRNA digestion products that can be uniquely assigned to particular tRNAs. These mass spectral improvements lead to a significant reduction in data processing attributable to the ease of spectral identification of labeled digestion products and will enable improvements in the relative quantification of modified RNAs by the (16)O/(18)O differential labeling approach. |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 25% |
| Student > Ph. D. Student | 2 | 17% |
| Researcher | 2 | 17% |
| Student > Master | 1 | 8% |
| Lecturer > Senior Lecturer | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 3 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 17% |
| Chemistry | 2 | 17% |
| Agricultural and Biological Sciences | 2 | 17% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 3 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 July 2014.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#3,428
of 3,833 outputs
Outputs of similar age
#209,562
of 241,713 outputs
Outputs of similar age from Journal of the American Society for Mass Spectrometry
#25
of 30 outputs
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