Differential Proteomic Analysis of Complex Mixtures by Label-Free nLC MS/MS.

Chromatography, Liquid / methods Complex Mixtures Proteome / analysis Proteomics / methods Tandem Mass Spectrometry / methods
Biomarker discovery Label-free quantification Mass spectrometry Precision-medicine Proteome Proteomics Relative protein quantification

Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2022
Historique:
entrez: 17 2 2022
pubmed: 18 2 2022
medline: 22 2 2022
Statut: ppublish

Résumé

After over two decades of constant evolution, proteomics can be truly considered nowadays as a high-throughput technique. Latest advances performed in sample preparation, instrumentation, and data analysis tools enable proteome-wide detection and quantification of proteins in complex samples.Label-free quantification by nanoscale liquid chromatography coupled online to tandem mass spectrometry (nLC MS /MS ) is a straightforward procedure for relative protein quantification. This approach allows to get deeper insights of what molecular changes are involved in the biological system we want to study in an unbiased manner.This chapter describes methods for sample preparation prior to mass spectrometry analysis. Besides, we describe a standard acquisition method, and some common bioinformatics analyses that help extracting biologically relevant information out of the achieved data.

Identifiants

DOI: 10.1007/978-1-0716-2193-6_5 PMID: 35175593
pubmed: 35175593
doi: 10.1007/978-1-0716-2193-6_5
doi:

Substances chimiques

Complex Mixtures 0
Proteome 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

111-121

Informations de copyright

© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Références

Aebersold R, Mann M (2016) Mass-spectrometric exploration of proteome structure and function. Nature 537(7620):347–355. https://doi.org/10.1038/nature19949
doi: 10.1038/nature19949 pubmed: 27629641
Altelaar AF, Munoz J, Heck AJ (2013) Next-generation proteomics: towards an integrative view of proteome dynamics. Nat Rev Genet 14(1):35–48. https://doi.org/10.1038/nrg3356
doi: 10.1038/nrg3356 pubmed: 23207911
Wisniewski JR, Zougman A, Nagaraj N, Mann M (2009) Universal sample preparation method for proteome analysis. Nat Methods 6(5):359–362. https://doi.org/10.1038/nmeth.1322
doi: 10.1038/nmeth.1322 pubmed: 19377485
Meier F, Brunner AD, Koch S, Koch H, Lubeck M, Krause M, Goedecke N, Decker J, Kosinski T, Park MA, Bache N, Hoerning O, Cox J, Rather O, Mann M (2018) Online parallel accumulation-serial fragmentation (PASEF) with a novel trapped ion mobility mass spectrometer. Mol Cell Proteomics 17(12):2534–2545. https://doi.org/10.1074/mcp.TIR118.000900
doi: 10.1074/mcp.TIR118.000900 pubmed: 30385480 pmcid: 6283298
Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M (2014) Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics 13(9):2513–2526. https://doi.org/10.1074/mcp.M113.031591
doi: 10.1074/mcp.M113.031591 pubmed: 4159666 pmcid: 4159666
Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26(12):1367–1372. https://doi.org/10.1038/nbt.1511
doi: 10.1038/nbt.1511 pubmed: 19029910 pmcid: 19029910
Tyanova S, Temu T, Sinitcyn P, Carlson A, Hein MY, Geiger T, Mann M, Cox J (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13(9):731–740. https://doi.org/10.1038/nmeth.3901
doi: 10.1038/nmeth.3901 pubmed: 27348712 pmcid: 27348712
Huang da W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44–57. https://doi.org/10.1038/nprot.2008.211
doi: 10.1038/nprot.2008.211 pubmed: 19131956 pmcid: 19131956
Huang da W, Sherman BT, Lempicki RA (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37(1):1–13. https://doi.org/10.1093/nar/gkn923
doi: 10.1093/nar/gkn923 pubmed: 19033363
Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD (2019) PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res 47(D1):D419–D426. https://doi.org/10.1093/nar/gky1038
doi: 10.1093/nar/gky1038
Mi H, Muruganujan A, Huang X, Ebert D, Mills C, Guo X, Thomas PD (2019) Protocol update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat Protoc 14(3):703–721. https://doi.org/10.1038/s41596-019-0128-8
doi: 10.1038/s41596-019-0128-8 pubmed: 30804569 pmcid: 6519457
Mi H, Thomas P (2009) PANTHER pathway: an ontology-based pathway database coupled with data analysis tools. Methods Mol Biol 563:123–140. https://doi.org/10.1007/978-1-60761-175-2_7
doi: 10.1007/978-1-60761-175-2_7 pubmed: 19597783 pmcid: 6608593
Kramer A, Green J, Pollard J Jr, Tugendreich S (2014) Causal analysis approaches in ingenuity pathway analysis. Bioinformatics 30(4):523–530. https://doi.org/10.1093/bioinformatics/btt703
doi: 10.1093/bioinformatics/btt703 pubmed: 24336805

Auteurs

Iraide Escobés (I)

Proteomics Platform, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), ProteoRed-ISCIII, CIBERehd, Science and Technology Park of Bizkaia, Derio, Spain.

Mikel Azkargorta (M)

Proteomics Platform, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), ProteoRed-ISCIII, CIBERehd, Science and Technology Park of Bizkaia, Derio, Spain.

Ibon Iloro (I)

Proteomics Platform, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), ProteoRed-ISCIII, CIBERehd, Science and Technology Park of Bizkaia, Derio, Spain.

Felix Elortza (F)

Proteomics Platform, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), ProteoRed-ISCIII, CIBERehd, Science and Technology Park of Bizkaia, Derio, Spain. felortza@cicbiogune.es.

Articles similaires

Proteomic analysis identified proteins that are differentially expressed in the flavonoid and carotenoid biosynthetic pathways of Camellia Nitidissima flowers.

Xing-Wen Zhou, Xiao-Xia Ye, Bao-Jian Ye et al.
1.00
Camellia Flowers Carotenoids Plant Proteins Flavonoids

Integrated multi-omics revealed that dysregulated lipid metabolism played an important role in RA patients with metabolic diseases.

Xiaoting Zhu, Wubin Long, Jing Zhang et al.
1.00
Humans Arthritis, Rheumatoid Lipid Metabolism Male Female

Motif mapping during chickpea germination reveals a complex sequential activation of different proteolytic activities.

Indrani Bera, Michael O'Sullivan, Caitriona Scaife et al.
1.00
Cicer Germination Proteolysis Seeds Plant Proteins

Patient iPSC-derived neural progenitor cells display aberrant cell cycle control, p53, and DNA damage response protein expression in schizophrenia.

Aaron Stahl, Johanna Heider, Richard Wüst et al.
1.00
Humans Induced Pluripotent Stem Cells Schizophrenia Neural Stem Cells DNA Damage

Classifications MeSH

questionsmedicales.fr › Techniques d'investigation › Techniques de chimie analytique › Chromatographie › Chromatographie en phase liquide › Differential Proteomic Analysis of Complex...
questionsmedicales.fr › Mélanges complexes › Differential Proteomic Analysis of Complex...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Protéome › Differential Proteomic Analysis of Complex...
questionsmedicales.fr › Disciplines des sciences naturelles › Chimie › Biochimie › Protéomique › Differential Proteomic Analysis of Complex...
questionsmedicales.fr › Techniques d'investigation › Techniques de chimie analytique › Spectrométrie de masse › Spectrométrie de masse en tandem › Differential Proteomic Analysis of Complex...