20 research outputs found
Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines
PolyÂ(ethylene
glycol) (PEG) is one of the most common polymer contaminations
in mass spectrometry (MS) samples. At present, the detection of PEG
and other polymers relies largely on manual inspection of raw data,
which is laborious and frequently difficult due to sample complexity
and retention characteristics of polymer species in reversed-phase
chromatography. We developed a new strategy for the automated identification
of PEG molecules from tandem mass spectrometry (MS/MS) data using
protein identification algorithms in combination with a database containing âPEGâproteinsâ.
Through definition of variable modifications, we extend the approach
for the identification of commonly used PEG-based detergents. We exemplify
the identification of different types of polymers by static nanoelectrospray
tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent
solutions and data analysis using Mascot. Analysis of liquid chromatographyâtandem
mass spectrometry (LCâMS/MS) runs of a PEG-contaminated sample
by Mascot identified 806 PEG spectra originating from four PEG species
using a defined set of modifications covering PEG and common PEG-based
detergents. Further characterization of the sample for unidentified
PEG species using error-tolerant and mass-tolerant searches resulted
in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively.
We further demonstrate the applicability of the strategy for Protein
Pilot and MaxQuant
Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines
PolyÂ(ethylene
glycol) (PEG) is one of the most common polymer contaminations
in mass spectrometry (MS) samples. At present, the detection of PEG
and other polymers relies largely on manual inspection of raw data,
which is laborious and frequently difficult due to sample complexity
and retention characteristics of polymer species in reversed-phase
chromatography. We developed a new strategy for the automated identification
of PEG molecules from tandem mass spectrometry (MS/MS) data using
protein identification algorithms in combination with a database containing âPEGâproteinsâ.
Through definition of variable modifications, we extend the approach
for the identification of commonly used PEG-based detergents. We exemplify
the identification of different types of polymers by static nanoelectrospray
tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent
solutions and data analysis using Mascot. Analysis of liquid chromatographyâtandem
mass spectrometry (LCâMS/MS) runs of a PEG-contaminated sample
by Mascot identified 806 PEG spectra originating from four PEG species
using a defined set of modifications covering PEG and common PEG-based
detergents. Further characterization of the sample for unidentified
PEG species using error-tolerant and mass-tolerant searches resulted
in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively.
We further demonstrate the applicability of the strategy for Protein
Pilot and MaxQuant
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Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines
PolyÂ(ethylene
glycol) (PEG) is one of the most common polymer contaminations
in mass spectrometry (MS) samples. At present, the detection of PEG
and other polymers relies largely on manual inspection of raw data,
which is laborious and frequently difficult due to sample complexity
and retention characteristics of polymer species in reversed-phase
chromatography. We developed a new strategy for the automated identification
of PEG molecules from tandem mass spectrometry (MS/MS) data using
protein identification algorithms in combination with a database containing âPEGâproteinsâ.
Through definition of variable modifications, we extend the approach
for the identification of commonly used PEG-based detergents. We exemplify
the identification of different types of polymers by static nanoelectrospray
tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent
solutions and data analysis using Mascot. Analysis of liquid chromatographyâtandem
mass spectrometry (LCâMS/MS) runs of a PEG-contaminated sample
by Mascot identified 806 PEG spectra originating from four PEG species
using a defined set of modifications covering PEG and common PEG-based
detergents. Further characterization of the sample for unidentified
PEG species using error-tolerant and mass-tolerant searches resulted
in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively.
We further demonstrate the applicability of the strategy for Protein
Pilot and MaxQuant
Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines
PolyÂ(ethylene
glycol) (PEG) is one of the most common polymer contaminations
in mass spectrometry (MS) samples. At present, the detection of PEG
and other polymers relies largely on manual inspection of raw data,
which is laborious and frequently difficult due to sample complexity
and retention characteristics of polymer species in reversed-phase
chromatography. We developed a new strategy for the automated identification
of PEG molecules from tandem mass spectrometry (MS/MS) data using
protein identification algorithms in combination with a database containing âPEGâproteinsâ.
Through definition of variable modifications, we extend the approach
for the identification of commonly used PEG-based detergents. We exemplify
the identification of different types of polymers by static nanoelectrospray
tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent
solutions and data analysis using Mascot. Analysis of liquid chromatographyâtandem
mass spectrometry (LCâMS/MS) runs of a PEG-contaminated sample
by Mascot identified 806 PEG spectra originating from four PEG species
using a defined set of modifications covering PEG and common PEG-based
detergents. Further characterization of the sample for unidentified
PEG species using error-tolerant and mass-tolerant searches resulted
in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively.
We further demonstrate the applicability of the strategy for Protein
Pilot and MaxQuant
Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines
PolyÂ(ethylene
glycol) (PEG) is one of the most common polymer contaminations
in mass spectrometry (MS) samples. At present, the detection of PEG
and other polymers relies largely on manual inspection of raw data,
which is laborious and frequently difficult due to sample complexity
and retention characteristics of polymer species in reversed-phase
chromatography. We developed a new strategy for the automated identification
of PEG molecules from tandem mass spectrometry (MS/MS) data using
protein identification algorithms in combination with a database containing âPEGâproteinsâ.
Through definition of variable modifications, we extend the approach
for the identification of commonly used PEG-based detergents. We exemplify
the identification of different types of polymers by static nanoelectrospray
tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent
solutions and data analysis using Mascot. Analysis of liquid chromatographyâtandem
mass spectrometry (LCâMS/MS) runs of a PEG-contaminated sample
by Mascot identified 806 PEG spectra originating from four PEG species
using a defined set of modifications covering PEG and common PEG-based
detergents. Further characterization of the sample for unidentified
PEG species using error-tolerant and mass-tolerant searches resulted
in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively.
We further demonstrate the applicability of the strategy for Protein
Pilot and MaxQuant
Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines
PolyÂ(ethylene
glycol) (PEG) is one of the most common polymer contaminations
in mass spectrometry (MS) samples. At present, the detection of PEG
and other polymers relies largely on manual inspection of raw data,
which is laborious and frequently difficult due to sample complexity
and retention characteristics of polymer species in reversed-phase
chromatography. We developed a new strategy for the automated identification
of PEG molecules from tandem mass spectrometry (MS/MS) data using
protein identification algorithms in combination with a database containing âPEGâproteinsâ.
Through definition of variable modifications, we extend the approach
for the identification of commonly used PEG-based detergents. We exemplify
the identification of different types of polymers by static nanoelectrospray
tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent
solutions and data analysis using Mascot. Analysis of liquid chromatographyâtandem
mass spectrometry (LCâMS/MS) runs of a PEG-contaminated sample
by Mascot identified 806 PEG spectra originating from four PEG species
using a defined set of modifications covering PEG and common PEG-based
detergents. Further characterization of the sample for unidentified
PEG species using error-tolerant and mass-tolerant searches resulted
in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively.
We further demonstrate the applicability of the strategy for Protein
Pilot and MaxQuant
Citrate Boosts the Performance of Phosphopeptide Analysis by UPLC-ESI-MS/MS
Incomplete recovery from the LC column is identified as a major cause for poor detection efficiency of phosphopeptides by LC-MS/MS. It is proposed that metal ions adsorbed on the stationary phase interact with the phosphate group of phosphopeptides via an ion-pairing mechanism related to IMAC (IMAC: immobilized metal ion affinity chromatography). This may result in their partial or even complete retention. Addition of phosphate, EDTA or citrate to the phosphopeptide sample was tested to overcome the detrimental phosphopeptide suppression during gradient LC-MS/MS analysis, while the standard solvent composition (water, acetonitrile, formic acid) of the LC system was left unchanged. With the use of UPLC, a citrate additive was found to be highly effective in increasing the phosphopeptide detection sensitivity. Addition of EDTA was found to be comparable with respect to sensitivity enhancement, but led to fast clogging and destruction of the spray needle and analytical columns due to precipitation. In contrast, a citrate additive is compatible with prolonged and stable routine operation. A 50 mM citrate additive was tested successfully for UPLC-MS analysis of a commercial four-component phosphopeptide mixture, a tryptic β-casein digest, and several digests of the 140 kDa protein SETDB1. In this protein, 27 phosphorylation sites could be identified by UPLC-MS/MS using addition of citrate, including the detection of several phosphopeptides carrying 3â5 pSer/pThr residues, compared to identification of only 10 sites without citrate addition. A 50 mM citrate additive particularly increases the recovery of multiply phosphorylated peptides, thus, extending the scope of phosphopeptide analysis by LC-MS/MS