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Universal database search tool for proteomics

View Article: PubMed Central - PubMed

ABSTRACT

Mass spectrometry (MS) instruments and experimental protocols are rapidly advancing, but the software tools to analyze tandem mass spectra are lagging behind. We present a database search tool MS-GF+ that is sensitive (it identifies more peptides than most other database search tools) and universal (it works well for diverse types of spectra, different configurations of MS instruments and different experimental protocols). We benchmark MS-GF+ using diverse spectral datasets: (i) spectra of varying fragmentation methods; (ii) spectra of multiple enzyme digests; (iii) spectra of phosphorylated peptides; (iv) spectra of peptides with unusual fragmentation propensities produced by a novel alpha-lytic protease. For all these datasets, MS-GF+ significantly increases the number of identified peptides compared to commonly used methods for peptide identifications. We emphasize that while MS-GF+ is not specifically designed for any particular experimental set-up, it improves upon the performance of tools specifically designed for these applications (e.g., specialized tools for phosphoproteomics).

No MeSH data available.


Constructing a Directed Acyclic Graph (DAG) in the case of two “amino acids” with real masses 2.012 and 2.996. Assume that only singly-charged b-ion with a real of f set 1.008 contributes to the scoring. The spectrum S is converted into S′ by shifting each peak by 1.008 to the left. Each arrowed line in S′ represents a pair of peaks separated approximately by 2 Da (blue) or 3 Da (red) that form a duo (solid) or does not form a duo (dashed) for a fragment mass tolerance 0.01 Da. A DAG G is constructed from S′. The number in the vertex represents its label. The color of the edge represents its label (0 for dashed grey and 1 for solid black).
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Figure 4: Constructing a Directed Acyclic Graph (DAG) in the case of two “amino acids” with real masses 2.012 and 2.996. Assume that only singly-charged b-ion with a real of f set 1.008 contributes to the scoring. The spectrum S is converted into S′ by shifting each peak by 1.008 to the left. Each arrowed line in S′ represents a pair of peaks separated approximately by 2 Da (blue) or 3 Da (red) that form a duo (solid) or does not form a duo (dashed) for a fragment mass tolerance 0.01 Da. A DAG G is constructed from S′. The number in the vertex represents its label. The color of the edge represents its label (0 for dashed grey and 1 for solid black).

Mentions: Given an extended alphabet , we first explain how to convert a spectrum S into a labeled DAG G. G = (V, E) has a vertex set V = {0, …, M = PrecursorMass(S)} and an edge set . For simplicity, suppose that the set of ion types ℐ = {(1, 0, 1)} (i.e. only singly charged prefix ions with an of f set zero contribute to the scoring). Given a constant δ called a fragment mass tolerance, two peaks of S with m/z x and y form a duo if y − x is approximately equal to a mass of an amino acid, i.e., . The vertex label si and the edge label si,j of G are defined as follows: si = 1 if there exists a peak of mass x satisfying [0.9995 · x] = i and si = 0 otherwise; si,j = 1, if there exists a duo of peaks with masses x and y such that [0.9995 · x] = i and [0.9995 · y] = j, and si,j = 0 otherwise (see Figure 4 for an example).


Universal database search tool for proteomics
Constructing a Directed Acyclic Graph (DAG) in the case of two “amino acids” with real masses 2.012 and 2.996. Assume that only singly-charged b-ion with a real of f set 1.008 contributes to the scoring. The spectrum S is converted into S′ by shifting each peak by 1.008 to the left. Each arrowed line in S′ represents a pair of peaks separated approximately by 2 Da (blue) or 3 Da (red) that form a duo (solid) or does not form a duo (dashed) for a fragment mass tolerance 0.01 Da. A DAG G is constructed from S′. The number in the vertex represents its label. The color of the edge represents its label (0 for dashed grey and 1 for solid black).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036525&req=5

Figure 4: Constructing a Directed Acyclic Graph (DAG) in the case of two “amino acids” with real masses 2.012 and 2.996. Assume that only singly-charged b-ion with a real of f set 1.008 contributes to the scoring. The spectrum S is converted into S′ by shifting each peak by 1.008 to the left. Each arrowed line in S′ represents a pair of peaks separated approximately by 2 Da (blue) or 3 Da (red) that form a duo (solid) or does not form a duo (dashed) for a fragment mass tolerance 0.01 Da. A DAG G is constructed from S′. The number in the vertex represents its label. The color of the edge represents its label (0 for dashed grey and 1 for solid black).
Mentions: Given an extended alphabet , we first explain how to convert a spectrum S into a labeled DAG G. G = (V, E) has a vertex set V = {0, …, M = PrecursorMass(S)} and an edge set . For simplicity, suppose that the set of ion types ℐ = {(1, 0, 1)} (i.e. only singly charged prefix ions with an of f set zero contribute to the scoring). Given a constant δ called a fragment mass tolerance, two peaks of S with m/z x and y form a duo if y − x is approximately equal to a mass of an amino acid, i.e., . The vertex label si and the edge label si,j of G are defined as follows: si = 1 if there exists a peak of mass x satisfying [0.9995 · x] = i and si = 0 otherwise; si,j = 1, if there exists a duo of peaks with masses x and y such that [0.9995 · x] = i and [0.9995 · y] = j, and si,j = 0 otherwise (see Figure 4 for an example).

View Article: PubMed Central - PubMed

ABSTRACT

Mass spectrometry (MS) instruments and experimental protocols are rapidly advancing, but the software tools to analyze tandem mass spectra are lagging behind. We present a database search tool MS-GF+ that is sensitive (it identifies more peptides than most other database search tools) and universal (it works well for diverse types of spectra, different configurations of MS instruments and different experimental protocols). We benchmark MS-GF+ using diverse spectral datasets: (i) spectra of varying fragmentation methods; (ii) spectra of multiple enzyme digests; (iii) spectra of phosphorylated peptides; (iv) spectra of peptides with unusual fragmentation propensities produced by a novel alpha-lytic protease. For all these datasets, MS-GF+ significantly increases the number of identified peptides compared to commonly used methods for peptide identifications. We emphasize that while MS-GF+ is not specifically designed for any particular experimental set-up, it improves upon the performance of tools specifically designed for these applications (e.g., specialized tools for phosphoproteomics).

No MeSH data available.