scholarly journals Qualitative and Quantitative Characterization of Plasma Proteins When Incorporating Traveling Wave Ion Mobility into a Liquid Chromatography–Mass Spectrometry Workflow for Biomarker Discovery: Use of Product Ion Quantitation As an Alternative Data Analysis Tool for Label Free Quantitation

2014 ◽  
Vol 86 (4) ◽  
pp. 1972-1979 ◽  
Author(s):  
Charlotte E. Daly ◽  
Leong L. Ng ◽  
Amirmansoor Hakimi ◽  
Richard Willingale ◽  
Donald J. L. Jones
2020 ◽  
Vol 21 (16) ◽  
pp. 5903
Author(s):  
Nicolai Bjødstrup Palstrøm ◽  
Lars Melholt Rasmussen ◽  
Hans Christian Beck

In the present study, we evaluated four small molecule affinity-based probes based on agarose-immobilized benzamidine (ABA), O-Phospho-L-Tyrosine (pTYR), 8-Amino-hexyl-cAMP (cAMP), or 8-Amino-hexyl-ATP (ATP) for their ability to remove high-abundant proteins such as serum albumin from plasma samples thereby enabling the detection of medium-to-low abundant proteins in plasma samples by mass spectrometry-based proteomics. We compared their performance with the most commonly used immunodepletion method, the Multi Affinity Removal System Human 14 (MARS14) targeting the top 14 most abundant plasma proteins and also the ProteoMiner protein equalization method by label-free quantitative liquid chromatography tandem mass spectrometry (LC-MSMS) analysis. The affinity-based probes demonstrated a high reproducibility for low-abundant plasma proteins, down to picomol per mL levels, compared to the Multi Affinity Removal System (MARS) 14 and the Proteominer methods, and also demonstrated superior removal of the majority of the high-abundant plasma proteins. The ABA-based affinity probe and the Proteominer protein equalization method performed better compared to all other methods in terms of the number of analyzed proteins. All the tested methods were highly reproducible for both high-abundant plasma proteins and low-abundant proteins as measured by correlation analyses of six replicate experiments. In conclusion, our results demonstrated that small-molecule based affinity-based probes are excellent alternatives to the commonly used immune-depletion methods for proteomic biomarker discovery studies in plasma. Data are available via ProteomeXchange with identifier PXD020727.


2015 ◽  
Vol 87 (22) ◽  
pp. 11301-11308 ◽  
Author(s):  
Ahmed M. Hamid ◽  
Yehia M. Ibrahim ◽  
Sandilya V. B. Garimella ◽  
Ian K. Webb ◽  
Liulin Deng ◽  
...  

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Monika Dzieciatkowska ◽  
Guihong Qi ◽  
Jinsam You ◽  
Kerry G. Bemis ◽  
Heather Sahm ◽  
...  

Cerebrospinal fluid (CSF) has been used for biomarker discovery of neurodegenerative diseases in humans since biological changes in the brain can be seen in this biofluid. Inactivation of A-T-mutated protein (ATM), a multifunctional protein kinase, is responsible for A-T, yet biochemical studies have not succeeded in conclusively identifying the molecular mechanism(s) underlying the neurodegeneration seen in A-T patients or the proteins that can be used as biomarkers for neurologic assessment of A-T or as potential therapeutic targets. In this study, we applied a high-throughput LC/MS-based label-free protein quantification technology to quantitatively characterize the proteins in CSF samples in order to identify differentially expressed proteins that can serve as potential biomarker candidates for A-T. Among 204 identified CSF proteins with high peptide-identification confidence, thirteen showed significant protein expression changes. Bioinformatic analysis revealed that these 13 proteins are either involved in neurodegenerative disorders or cancer. Future molecular and functional characterization of these proteins would provide more insights into the potential therapeutic targets for the treatment of A-T and the biomarkers that can be used to monitor or predict A-T disease progression. Clinical validation studies are required before any of these proteins can be developed into clinically useful biomarkers.


2009 ◽  
Vol 81 (20) ◽  
pp. 8289-8297 ◽  
Author(s):  
Hugh I. Kim ◽  
Hyungjun Kim ◽  
Eric S. Pang ◽  
Ernest K. Ryu ◽  
Luther W. Beegle ◽  
...  

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