Quantitative Proteomics
Quantitative Proteomics - Related Videos
08:11
Quantitative Analysis of Chromatin Proteomes in Disease
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Cited by 4 •
2012
Advances in mass spectrometry have allowed the high throughput analysis of protein expression and modification in a host of tissues. Combined with subcellular fractionation and disease models, quantitative mass spectrometry and bioinformatics can reveal new properties in biological systems. The method described herein analyzes chromatin-associated proteins in the setting of heart disease and is readily applicable to other in vivo models of human disease.
11:38
A Quantitative Glycomics and Proteomics Combined Purification Strategy
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Cited by 18 •
2016
A high-throughput protocol was developed for combined proteomics and glycomics purification and LC-MS/MS quantification in plasma. Deamidation analysis of N-linked glycosylation motifs was specific to deglycosylated sites. Accurate quantitation of N-glycans was achieved by coupling filter aided N-glycan separation to the individuality normalization when labeling with glycan hydrazide tags strategy.
11:12
Identification of protein complexes with quantitative proteomics in S. cerevisiae
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Cited by 4 •
2009
Here we describe a new quantitative proteomics technique for identifying protein complexes in Saccharomyces cerevisiae. In this study, we have used the SILAC method together with affinity purification followed by tandem mass spectrometry to identify with high specificity the binding partners of an ER protein, Scs2p.
09:29
Skeletal Muscle Gender Dimorphism from Proteomics
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Cited by 4 •
2011
A straight-forward set of methods to isolate and determine the identity of the most abundant proteins expressed in skeletal muscle. About 800 spots are discerned on a two-dimensional gel from 10 mg muscle; this allows for the determination of gender-specific protein expression. These methods will give equivalent results in most tissues.
11:53
Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling
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Cited by 38 •
2014
Stable isotope labeling of peptides by reductive dimethylation (ReDi labeling) is a rapid, inexpensive strategy for accurate mass spectrometry-based quantitative proteomics. Here we demonstrate a robust method for preparation and analysis of protein mixtures using the ReDi approach that can be applied to nearly any sample type.
FAQs
Isotope labeling and label-free analysis provide two ways to compare peptide signals between biological samples. Those comparisons can estimate relative protein levels, showing how much abundance changes between samples, or support absolute estimates of protein amount when the analytical design permits. Choosing between them therefore affects how protein differences are expressed and interpreted in a study.
Liquid chromatography separates the peptide mixture before tandem mass spectrometry examines it, creating an ordered analytical workflow rather than treating all peptides as one undifferentiated signal. Tandem mass spectrometry then supplies peptide-level signals that can be compared across samples. This pairing makes the measured differences suitable for estimating changes in protein abundance, modification, or variation.
Measuring protein modifications and variation adds information beyond total protein abundance. A disease-associated change may therefore be examined not only as a difference in how much protein is present, but also as a molecular alteration associated with signaling pathways or protein networks. In medicine, this broader view helps connect molecular changes with observed clinical phenotypes.
Quantitative proteomics can support disease classification by comparing molecular protein patterns across biological samples. The resulting measurements may also identify candidate biomarkers, meaning molecular features associated with a health or disease state. Examining coordinated changes across pathways and protein networks adds context, helping researchers relate classification signals to the molecular basis of clinical phenotypes.
Drug mechanism studies use protein-level measurements to examine molecular changes associated with an intervention, while treatment-response monitoring follows how those measurements vary during therapy. These applications can reveal whether protein patterns change with treatment and can connect the response to signaling pathways and protein networks, supporting interpretation of treatment effects in medicine.
Precision medicine benefits from molecular information that distinguishes biological differences across samples or disease presentations. By measuring protein abundance, modifications, and variation, quantitative proteomics can connect these differences with clinical phenotypes. Its ability to examine pathways and protein networks also supports a more integrated interpretation of biomarkers, disease classes, drug mechanisms, and treatment responses.