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Identification of RNA molecules by specific enzyme digestion and mass spectrometry: software for and implementation of RNA mass mapping.

Matthiesen R, Kirpekar F - Nucleic Acids Res. (2009)

Bottom Line: A simple and powerful probability model for ranking RNA matches is proposed.We demonstrate viability of the entire setup by identifying the DNA template of a series of RNAs of biological and of in vitro transcriptional origin in complete microbial genomes and by identifying authentic 16S ribosomal RNAs in a 'small ribosomal subunit RNA' database.Thus, we present a new tool for a rapid identification of unknown RNAs using only a few picomoles of starting material.

View Article: PubMed Central - PubMed

Affiliation: Population Genetics-Instituto de Patologia e Imunologia Molecular da Universidad do Porto, Porto, Portugal. rmatthiesen@ipatimup.pt

ABSTRACT
The idea of identifying or characterizing an RNA molecule based on a mass spectrum of specifically generated RNA fragments has been used in various forms for well over a decade. We have developed software-named RRM for 'RNA mass mapping'-which can search whole prokaryotic genomes or RNA FASTA sequence databases to identify the origin of a given RNA based on a mass spectrum of RNA fragments. As input, the program uses the masses of specific RNase cleavage of the RNA under investigation. RNase T1 digestion is used here as a demonstration of the usability of the method for RNA identification. The concept for identification is that the masses of the digestion products constitute a specific fingerprint, which characterize the given RNA. The search algorithm is based on the same principles as those used in peptide mass fingerprinting, but has here been extended to work for both RNA sequence databases and for genome searches. A simple and powerful probability model for ranking RNA matches is proposed. We demonstrate viability of the entire setup by identifying the DNA template of a series of RNAs of biological and of in vitro transcriptional origin in complete microbial genomes and by identifying authentic 16S ribosomal RNAs in a 'small ribosomal subunit RNA' database. Thus, we present a new tool for a rapid identification of unknown RNAs using only a few picomoles of starting material.

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Mass spectrum of T. thermophilus 16S rRNA digested with RNase T1. Assigned masses are of singly protonated digestion products, these masses were used in the subsequent database search.
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Figure 3: Mass spectrum of T. thermophilus 16S rRNA digested with RNase T1. Assigned masses are of singly protonated digestion products, these masses were used in the subsequent database search.

Mentions: The MALDI spectrum of RNase T1 digested T. thermophilus 16S rRNA with ion signals used in the search is shown in Figure 3. The highest scores are presented in Table 3. It is obvious that we have an unambiguous identification of the correct species with all the 19 best matches being T. thermophilus 16S rRNA. The first match not specifically identified as a Thermus species comes as number 20 and is an uncultured species growing at 57°C with score and Z-score values of 313 and 43, respectively.Figure 3.


Identification of RNA molecules by specific enzyme digestion and mass spectrometry: software for and implementation of RNA mass mapping.

Matthiesen R, Kirpekar F - Nucleic Acids Res. (2009)

Mass spectrum of T. thermophilus 16S rRNA digested with RNase T1. Assigned masses are of singly protonated digestion products, these masses were used in the subsequent database search.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2665245&req=5

Figure 3: Mass spectrum of T. thermophilus 16S rRNA digested with RNase T1. Assigned masses are of singly protonated digestion products, these masses were used in the subsequent database search.
Mentions: The MALDI spectrum of RNase T1 digested T. thermophilus 16S rRNA with ion signals used in the search is shown in Figure 3. The highest scores are presented in Table 3. It is obvious that we have an unambiguous identification of the correct species with all the 19 best matches being T. thermophilus 16S rRNA. The first match not specifically identified as a Thermus species comes as number 20 and is an uncultured species growing at 57°C with score and Z-score values of 313 and 43, respectively.Figure 3.

Bottom Line: A simple and powerful probability model for ranking RNA matches is proposed.We demonstrate viability of the entire setup by identifying the DNA template of a series of RNAs of biological and of in vitro transcriptional origin in complete microbial genomes and by identifying authentic 16S ribosomal RNAs in a 'small ribosomal subunit RNA' database.Thus, we present a new tool for a rapid identification of unknown RNAs using only a few picomoles of starting material.

View Article: PubMed Central - PubMed

Affiliation: Population Genetics-Instituto de Patologia e Imunologia Molecular da Universidad do Porto, Porto, Portugal. rmatthiesen@ipatimup.pt

ABSTRACT
The idea of identifying or characterizing an RNA molecule based on a mass spectrum of specifically generated RNA fragments has been used in various forms for well over a decade. We have developed software-named RRM for 'RNA mass mapping'-which can search whole prokaryotic genomes or RNA FASTA sequence databases to identify the origin of a given RNA based on a mass spectrum of RNA fragments. As input, the program uses the masses of specific RNase cleavage of the RNA under investigation. RNase T1 digestion is used here as a demonstration of the usability of the method for RNA identification. The concept for identification is that the masses of the digestion products constitute a specific fingerprint, which characterize the given RNA. The search algorithm is based on the same principles as those used in peptide mass fingerprinting, but has here been extended to work for both RNA sequence databases and for genome searches. A simple and powerful probability model for ranking RNA matches is proposed. We demonstrate viability of the entire setup by identifying the DNA template of a series of RNAs of biological and of in vitro transcriptional origin in complete microbial genomes and by identifying authentic 16S ribosomal RNAs in a 'small ribosomal subunit RNA' database. Thus, we present a new tool for a rapid identification of unknown RNAs using only a few picomoles of starting material.

Show MeSH