ArticlePloS one2014
Optimization of plasma sample pretreatment for quantitative analysis using iTRAQ labeling and LC-MALDI-TOF/TOF.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 17 citations in OpenAlex.
- iTRAQ-based proteomics reveals potential markers and treatment pathways for acute Achilles tendon rupture.Journal of orthopaedic surgery and research · 2023Article
- Surgical management of peritoneal metastasis: Opportunities for pharmaceutical research.Journal of controlled release : official journal of the Controlled Release Society · 2023Article
- How to sample a seizure plant: the role of the visualization spatial distribution analysis ofForensic sciences research · 2023Article
- AtTrm5a catalyses 1-methylguanosine and 1-methylinosine formation on tRNAs and is important for vegetative and reproductive growth in Arabidopsis thaliana.Nucleic acids research · 2019Article
- ITRAQ-Based Proteomics Analysis Reveals the Effect of Neoliensinine on KCl-Induced Vascular Smooth Muscle Contraction by Inhibiting Regulatory Light Chain Phosphorylation.Frontiers in pharmacology · 2019Article
- iTRAQ-based proteomic analysis of plasma reveals abnormalities in lipid metabolism proteins in chronic kidney disease-related atherosclerosis.Scientific reports · 2016Article
- Comparative proteomic profiling of refractory/relapsed multiple myeloma reveals biomarkers involved in resistance to bortezomib-based therapy.Oncotarget · 2016Article
- Label-Free Quantitative Proteomics Reveals Differences in Molecular Mechanism of Atherosclerosis Related and Non-Related to Chronic Kidney Disease.International journal of molecular sciences · 2016Article
- Deeper insight into chronic kidney disease-related atherosclerosis: comparative proteomic studies of blood plasma using 2DE and mass spectrometry.Journal of translational medicine · 2015Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome's complexity and the highly dynamic plasma protein concentration range limit the ability of conventional approaches to analyze and identify a large number of proteins, including useful biomarkers. The goal of this paper is to elucidate the best approach for plasma sample pretreatment for MS- and iTRAQ-based analyses. Here, we systematically compared four approaches, which include centrifugal ultrafiltration, SCX chromatography with fractionation, affinity depletion, and plasma without fractionation, to reduce plasma sample complexity. We generated an optimized protocol for quantitative protein analysis using iTRAQ reagents and an UltrafleXtreme (Bruker Daltonics) MALDI TOF/TOF mass spectrometer. Moreover, we used a simple, rapid, efficient, but inexpensive sample pretreatment technique that generated an optimal opportunity for biomarker discovery. We discuss the results from the four sample pretreatment approaches and conclude that SCX chromatography without affinity depletion is the best plasma sample preparation pretreatment method for proteome analysis. Using this technique, we identified 1,780 unique proteins, including 1,427 that were quantified by iTRAQ with high reproducibility and accuracy.
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