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Analysis of membrane and hydrophilic proteins simultaneously derived from the mouse brain using cloud-point extraction
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
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2011 (English)In: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 400, no 9, 2827-2836 p.Article in journal (Refereed) Published
Abstract [en]

In this study, a temperature-induced phase fractionation known as cloud-point extraction (CPE) with the non-ionic surfactant Triton X-114 was used to simultaneously extract, concentrate, and fractionate hydrophobic and hydrophilic proteins from mouse brain tissue. Two bottom-up proteomic techniques were used to comprehensively identify the extracted proteins. The first "shotgun"-based approach included tryptic digestion of the proteins followed by reversed-phase nanoliquid chromatography (RP-nanoLC) in combination with electrospray ionization (ESI) tandem mass spectrometry (MS/MS). In the second approach, the extracted intact proteins were first separated by one-dimensional (1D) gel electrophoresis and then in-gel digested with trypsin and analyzed with nanoLC-MS/MS. In total, 1,825 proteins were unambiguously identified and the percentage of membrane proteins was 26% which is at the reported genome expression levels of 20-30%. The protein overlap between the two approaches was high. The majority (77%) of the identifications in the first approach was also found by the second method. The protein overlap between the CPE-extracted hydrophilic and hydrophobic fractions was rather small (16-23%) for both methods, which indicates a good phase separation. A quantitative evaluation of the CPE with iTRAQ labeling and nanoLC-ESI-MS/MS analysis gave iTRAQ ratios at the expected levels and an overall variation of the entire method at 17-31%. The results indicate very reproducible sample preparation and analysis methods that readily can be applied on large-scale sample sets.

Place, publisher, year, edition, pages
2011. Vol. 400, no 9, 2827-2836 p.
Keyword [en]
Cloud-point extraction (CPE), Brain, Proteomics, Membrane proteins (MPs), Mass spectrometry (MS), iTRAQ
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-154958DOI: 10.1007/s00216-011-5037-9ISI: 000291037800016PubMedID: 21553125OAI: oai:DiVA.org:uu-154958DiVA: diva2:422796
Available from: 2011-06-14 Created: 2011-06-14 Last updated: 2017-12-11Bibliographically approved
In thesis
1. Advances for Biomarker Discovery in Neuroproteomics using Mass Spectrometry: From Method Development to Clinical Application
Open this publication in new window or tab >>Advances for Biomarker Discovery in Neuroproteomics using Mass Spectrometry: From Method Development to Clinical Application
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Proteins offer a prominent group of compounds which may be ubiquitously affected in disease and used as biomarkers for early diagnosis, assessing treatment or drug development. Clinical proteomics aim to screen for protein biomarkers by a comprehensive analysis of all proteins expressed in a biological matrix during a certain pathology. Characterization of thousands of proteins in a complex biological matrix is from an analytical point of view a challenging task. Hence, sophisticated methods that are sensitive, specific and robust in a high-throughput manner are required. Mass spectrometry (MS) is able to perform this to a wide extent is.

A prominent source for finding protein biomarkers related to neurological diseases is the central nervous system (CNS) due to close proximity of the pathogenesis. Neuroproteomic analysis of CNS tissue samples is thus likely to reveal novel biomarkers. Cerebrospinal fluid (CSF) bathes the entire CNS and offers a good balance between clinical implementation and usefulness. Both matrices put further requirements on the methodology due to a high dynamic range, low protein concentration and limited sample amount.

The central objective of this thesis was to develop, assess and utilize analytical methods to be used in combination with MS to enable protein biomarker discovery in the CNS. The use of hexapeptide ligand libraries was exemplified on CSF from patients with traumatic brain injury and demonstrated the ability to compress the dynamic range to enable protein profiling in the order of mg/mL to pg/mL. Further, a method based on cloud-point extraction was developed for simultaneous enrichment and fractionation of hydrophobic/hydrophilic proteins in brain tissue. Comparison between label and label-free MS based strategies were carried out, mimicking the true conditions with a few differentially expressed proteins and a bulk of proteins occurring in unchanged ratio. Finally, a clinical application was carried out to explore the molecular mechanism underlying the analgesic effect of spinal cord stimulation (SCS) in patients with neuropathic pain. The CSF concentration of Lynx1 was found to increase upon SCS. Lynx1, acting as a specific modulator of the cholinergic system in the CNS, may act as a potential important molecular explanation of SCS-induced analgesia.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2012. 64 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 966
Keyword
Mass Spectrometry, Biomarker, Proteomics, Central Nervous System, Cerebrospinal Fluid, Traumatic Brain Injury, Cloud-Point Extraction, Neuroproteomics, Relative Quantification, Spinal Cord Stimulation, Neuropathic Pain
National Category
Analytical Chemistry
Research subject
Analytical Chemistry
Identifiers
urn:nbn:se:uu:diva-180109 (URN)978-91-554-8457-6 (ISBN)
Public defence
2012-10-18, Biomedicinskt Centrum, B42, Husargatan 3, Uppsala, 10:15 (English)
Opponent
Supervisors
Available from: 2012-09-26 Created: 2012-08-29 Last updated: 2013-01-23Bibliographically approved

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Wetterhall, MagnusShevchenko, GannaArtemenko, Konstantin ASjödin, Marcus O.D.Bergquist, Jonas

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