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Article ; Online: Recent advances in computational algorithms and software for large-scale glycoproteomics.

Polasky, Daniel A / Nesvizhskii, Alexey I

2022 Volume 72, Page(s) 102238

Abstract: Glycoproteomics, or characterizing glycosylation events at a proteome scale, has seen rapid advances in methods for analyzing glycopeptides by tandem mass spectrometry in recent years. These advances have enabled acquisition of far more comprehensive and ...

Abstract	Glycoproteomics, or characterizing glycosylation events at a proteome scale, has seen rapid advances in methods for analyzing glycopeptides by tandem mass spectrometry in recent years. These advances have enabled acquisition of far more comprehensive and large-scale datasets, precipitating an urgent need for improved informatics methods to analyze the resulting data. A new generation of glycoproteomics search methods has recently emerged, using glycan fragmentation to split the identification of a glycopeptide into peptide and glycan components and solve each component separately. In this review, we discuss these new methods and their implications for large-scale glycoproteomics, as well as several outstanding challenges in glycoproteomics data analysis, including validation of glycan assignments and quantitation. Finally, we provide an outlook on the future of glycoproteomics from an informatics perspective, noting the key challenges to achieving widespread and reproducible glycopeptide annotation and quantitation.
MeSH term(s)	Software ; Algorithms ; Glycosylation ; Glycopeptides ; Polysaccharides/analysis
Chemical Substances	Glycopeptides ; Polysaccharides
Language	English
Publishing date	2022-12-14
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	1439176-4
ISSN	1879-0402 ; 1367-5931
ISSN (online)	1879-0402
ISSN	1367-5931
DOI	10.1016/j.cbpa.2022.102238
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Article ; Online: Detecting diagnostic features in MS/MS spectra of post-translationally modified peptides.

Geiszler, Daniel J / Polasky, Daniel A / Yu, Fengchao / Nesvizhskii, Alexey I

Nature communications

2023 Volume 14, Issue 1, Page(s) 4132

Abstract: Post-translational modifications are an area of great interest in mass spectrometry-based proteomics, with a surge in methods to detect them in recent years. However, post-translational modifications can introduce complexity into proteomics searches by ... ...

Abstract	Post-translational modifications are an area of great interest in mass spectrometry-based proteomics, with a surge in methods to detect them in recent years. However, post-translational modifications can introduce complexity into proteomics searches by fragmenting in unexpected ways, ultimately hindering the detection of modified peptides. To address these deficiencies, we present a fully automated method to find diagnostic spectral features for any modification. The features can be incorporated into proteomics search engines to improve modified peptide recovery and localization. We show the utility of this approach by interrogating fragmentation patterns for a cysteine-reactive chemoproteomic probe, RNA-crosslinked peptides, sialic acid-containing glycopeptides, and ADP-ribosylated peptides. We also analyze the interactions between a diagnostic ion's intensity and its statistical properties. This method has been incorporated into the open-search annotation tool PTM-Shepherd and the FragPipe computational platform.
MeSH term(s)	Tandem Mass Spectrometry ; Peptides ; Glycopeptides ; Cysteine ; N-Acetylneuraminic Acid
Chemical Substances	Peptides ; Glycopeptides ; Cysteine (K848JZ4886) ; N-Acetylneuraminic Acid (GZP2782OP0)
Language	English
Publishing date	2023-07-12
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-39828-0
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Article ; Online: Multiattribute Glycan Identification and FDR Control for Glycoproteomics.

Polasky, Daniel A / Geiszler, Daniel J / Yu, Fengchao / Nesvizhskii, Alexey I

Molecular & cellular proteomics : MCP

2022 Volume 21, Issue 3, Page(s) 100205

Abstract: Rapidly improving methods for glycoproteomics have enabled increasingly large-scale analyses of complex glycopeptide samples, but annotating the resulting mass spectrometry data with high confidence remains a major bottleneck. We recently introduced a ... ...

Abstract	Rapidly improving methods for glycoproteomics have enabled increasingly large-scale analyses of complex glycopeptide samples, but annotating the resulting mass spectrometry data with high confidence remains a major bottleneck. We recently introduced a fast and sensitive glycoproteomics search method in our MSFragger search engine, which reports glycopeptides as a combination of a peptide sequence and the mass of the attached glycan. In samples with complex glycosylation patterns, converting this mass to a specific glycan composition is not straightforward; however, as many glycans have similar or identical masses. Here, we have developed a new method for determining the glycan composition of N-linked glycopeptides fragmented by collisional or hybrid activation that uses multiple sources of information from the spectrum, including observed glycan B-type (oxonium) and Y-type ions and mass and precursor monoisotopic selection errors to discriminate between possible glycan candidates. Combined with false discovery rate estimation for the glycan assignment, we show that this method is capable of specifically and sensitively identifying glycans in complex glycopeptide analyses and effectively controls the rate of false glycan assignments. The new method has been incorporated into the PTM-Shepherd modification analysis tool to work directly with the MSFragger glyco search in the FragPipe graphical user interface, providing a complete computational pipeline for annotation of N-glycopeptide spectra with false discovery rate control of both peptide and glycan components that is both sensitive and robust against false identifications.
MeSH term(s)	Glycopeptides/chemistry ; Glycosylation ; Polysaccharides/analysis ; Proteomics/methods ; Tandem Mass Spectrometry
Chemical Substances	Glycopeptides ; Polysaccharides
Language	English
Publishing date	2022-01-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2075924-1
ISSN	1535-9484 ; 1535-9476
ISSN (online)	1535-9484
ISSN	1535-9476
DOI	10.1016/j.mcpro.2022.100205
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Article ; Online: MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics.

Polasky, Daniel A / Geiszler, Daniel J / Yu, Fengchao / Li, Kai / Teo, Guo Ci / Nesvizhskii, Alexey I

Molecular & cellular proteomics : MCP

2023 Volume 22, Issue 5, Page(s) 100538

Abstract: Posttranslational modifications of proteins play essential roles in defining and regulating the functions of the proteins they decorate, making identification of these modifications critical to understanding biology and disease. Methods for enriching and ...

Abstract	Posttranslational modifications of proteins play essential roles in defining and regulating the functions of the proteins they decorate, making identification of these modifications critical to understanding biology and disease. Methods for enriching and analyzing a wide variety of biological and chemical modifications of proteins have been developed using mass spectrometry-based proteomics, largely relying on traditional database search methods to identify the resulting mass spectra of modified peptides. These database search methods treat modifications as static attachments of a mass to particular position in the peptide sequence, but many modifications undergo fragmentation in tandem mass spectrometry experiments alongside, or instead of, the peptide backbone. While this fragmentation can confound traditional search methods, it also offers unique opportunities for improved searches that incorporate modification-specific fragment ions. Here, we present a new labile mode in the MSFragger search engine that provides the flexibility to tailor modification-centric searches to the fragmentation observed. We show that labile mode can dramatically improve spectrum identification rates of phosphopeptides, RNA-crosslinked peptides, and ADP-ribosylated peptides. Each of these modifications presents distinct fragmentation characteristics, showcasing the flexibility of MSFragger labile mode to improve search for a wide variety of biological and chemical modifications.
MeSH term(s)	Proteomics/methods ; Protein Processing, Post-Translational ; Proteins/metabolism ; Tandem Mass Spectrometry/methods ; Phosphopeptides/metabolism ; Databases, Protein
Chemical Substances	Proteins ; Phosphopeptides
Language	English
Publishing date	2023-03-31
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2075924-1
ISSN	1535-9484 ; 1535-9476
ISSN (online)	1535-9484
ISSN	1535-9476
DOI	10.1016/j.mcpro.2023.100538
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Article: Efficient Analysis of Proteome-wide FPOP Data by FragPipe.

Ramírez, Carolina Rojas / Espino, Jessica Arlett / Jones, Lisa M / Polasky, Daniel A / Nesvizhskii, Alexey I

bioRxiv : the preprint server for biology

2023

Abstract: Monitoring protein structure before and after perturbations can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows monitoring of structural rearrangements by ... ...

Abstract	Monitoring protein structure before and after perturbations can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP datasets. Our workflow combines the speed of MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 50% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.
Language	English
Publishing date	2023-06-05
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.06.01.543263
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Article ; Online: IonQuant Enables Accurate and Sensitive Label-Free Quantification With FDR-Controlled Match-Between-Runs.

Yu, Fengchao / Haynes, Sarah E / Nesvizhskii, Alexey I

Molecular & cellular proteomics : MCP

2021 Volume 20, Page(s) 100077

Abstract: Missing values weaken the power of label-free quantitative proteomic experiments to uncover true quantitative differences between biological samples or experimental conditions. Match-between-runs (MBR) has become a common approach to mitigate the missing ...

Abstract	Missing values weaken the power of label-free quantitative proteomic experiments to uncover true quantitative differences between biological samples or experimental conditions. Match-between-runs (MBR) has become a common approach to mitigate the missing value problem, where peptides identified by tandem mass spectra in one run are transferred to another by inference based on m/z, charge state, retention time, and ion mobility when applicable. Though tolerances are used to ensure such transferred identifications are reasonably located and meet certain quality thresholds, little work has been done to evaluate the statistical confidence of MBR. Here, we present a mixture model-based approach to estimate the false discovery rate (FDR) of peptide and protein identification transfer, which we implement in the label-free quantification tool IonQuant. Using several benchmarking datasets generated on both Orbitrap and timsTOF mass spectrometers, we demonstrate superior performance of IonQuant with FDR-controlled MBR compared with MaxQuant (19-38 times faster; 6-18% more proteins quantified and with comparable or better accuracy). We further illustrate the performance of IonQuant and highlight the need for FDR-controlled MBR, in two single-cell proteomics experiments, including one acquired with the help of high-field asymmetric ion mobility spectrometry separation. Fully integrated in the FragPipe computational environment, IonQuant with FDR-controlled MBR enables fast and accurate peptide and protein quantification in label-free proteomics experiments.
MeSH term(s)	Algorithms ; Databases, Protein ; Escherichia coli Proteins ; HeLa Cells ; Humans ; Peptides ; Proteins ; Proteomics/methods ; Saccharomyces cerevisiae Proteins ; Single-Cell Analysis ; Software
Chemical Substances	Escherichia coli Proteins ; Peptides ; Proteins ; Saccharomyces cerevisiae Proteins
Language	English
Publishing date	2021-04-02
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2075924-1
ISSN	1535-9484 ; 1535-9476
ISSN (online)	1535-9484
ISSN	1535-9476
DOI	10.1016/j.mcpro.2021.100077
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Article ; Online: Efficient Analysis of Proteome-Wide FPOP Data by FragPipe.

Rojas Ramírez, Carolina / Espino, Jessica A / Jones, Lisa M / Polasky, Daniel A / Nesvizhskii, Alexey I

Analytical chemistry

2023 Volume 95, Issue 44, Page(s) 16131–16137

Abstract: Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows for ...

Abstract	Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows for monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent-accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and a lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP data sets. Our workflow, implemented as part of the FragPipe computational platform, combines the speed of the MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 150% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.
MeSH term(s)	Proteome ; Peptides ; Mass Spectrometry/methods ; Solvents ; Oxidation-Reduction
Chemical Substances	Proteome ; Peptides ; Solvents
Language	English
Publishing date	2023-10-25
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1508-8
ISSN	1520-6882 ; 0003-2700
ISSN (online)	1520-6882
ISSN	0003-2700
DOI	10.1021/acs.analchem.3c02388
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Implementing the MSFragger Search Engine as a Node in Proteome Discoverer.

Chang, Hui-Yin / Haynes, Sarah E / Yu, Fengchao / Nesvizhskii, Alexey I

Journal of proteome research

2022 Volume 22, Issue 2, Page(s) 520–525

Abstract: Here, we describe the implementation of the fast proteomics search engine MSFragger as a processing node in the widely used Proteome Discoverer (PD) software platform. PeptideProphet (via the Philosopher tool kit) is also implemented as an additional PD ... ...

Abstract	Here, we describe the implementation of the fast proteomics search engine MSFragger as a processing node in the widely used Proteome Discoverer (PD) software platform. PeptideProphet (via the Philosopher tool kit) is also implemented as an additional PD node to allow validation of MSFragger open (mass-tolerant) search results. These two nodes, along with the existing Percolator validation module, allow users to employ different search strategies and conveniently inspect search results through PD. Our results have demonstrated the improved numbers of PSMs, peptides, and proteins identified by MSFragger coupled with Percolator and significantly faster search speed compared to the conventional SEQUEST/Percolator PD workflows. The MSFragger-PD node is available at https://github.com/nesvilab/PD-Nodes/releases/.
MeSH term(s)	Search Engine/methods ; Proteome/metabolism ; Algorithms ; Tandem Mass Spectrometry/methods ; Software ; Databases, Protein
Chemical Substances	Proteome
Language	English
Publishing date	2022-12-08
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2078618-9
ISSN	1535-3907 ; 1535-3893
ISSN (online)	1535-3907
ISSN	1535-3893
DOI	10.1021/acs.jproteome.2c00485
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Article ; Online: Proteogenomics: concepts, applications and computational strategies.

Nesvizhskii, Alexey I

Nature methods

2014 Volume 11, Issue 11, Page(s) 1114–1125

Abstract: Proteogenomics is an area of research at the interface of proteomics and genomics. In this approach, customized protein sequence databases generated using genomic and transcriptomic information are used to help identify novel peptides (not present in ... ...

Abstract	Proteogenomics is an area of research at the interface of proteomics and genomics. In this approach, customized protein sequence databases generated using genomic and transcriptomic information are used to help identify novel peptides (not present in reference protein sequence databases) from mass spectrometry-based proteomic data; in turn, the proteomic data can be used to provide protein-level evidence of gene expression and to help refine gene models. In recent years, owing to the emergence of new sequencing technologies such as RNA-seq and dramatic improvements in the depth and throughput of mass spectrometry-based proteomics, the pace of proteogenomic research has greatly accelerated. Here I review the current state of proteogenomic methods and applications, including computational strategies for building and using customized protein sequence databases. I also draw attention to the challenge of false positive identifications in proteogenomics and provide guidelines for analyzing the data and reporting the results of proteogenomic studies.
MeSH term(s)	Databases, Nucleic Acid ; Databases, Protein ; Genetic Variation ; Genomics/methods ; High-Throughput Nucleotide Sequencing ; Mass Spectrometry ; Protein Isoforms/genetics ; Proteome/genetics ; Proteomics/methods ; Sequence Analysis, Protein/methods
Chemical Substances	Protein Isoforms ; Proteome
Language	English
Publishing date	2014-11
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Review
ZDB-ID	2169522-2
ISSN	1548-7105 ; 1548-7091
ISSN (online)	1548-7105
ISSN	1548-7091
DOI	10.1038/nmeth.3144
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Efficient Analysis of Proteome-Wide FPOP Data by FragPipe

Rojas Ramírez, Carolina / Espino, Jessica A. / Jones, Lisa M. / Polasky, Daniel A. / Nesvizhskii, Alexey I.

Analytical Chemistry. 2023 Oct. 25, v. 95, no. 44 p.16131-16137

2023

Abstract	Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows for monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent-accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and a lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP data sets. Our workflow, implemented as part of the FragPipe computational platform, combines the speed of the MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 150% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.
Keywords	analytical chemistry ; mass spectrometry ; oxidation ; peptides ; photochemistry ; protein structure
Language	English
Dates of publication	2023-1025
Size	p. 16131-16137.
Publishing place	American Chemical Society
Document type	Article ; Online
ZDB-ID	1508-8
ISSN	1520-6882 ; 0003-2700
ISSN (online)	1520-6882
ISSN	0003-2700
DOI	10.1021/acs.analchem.3c02388
Database	NAL-Catalogue (AGRICOLA)

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