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Advances for Biomarker Discovery in Neuroproteomics using Mass Spectrometry: From Method Development to Clinical Application
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Analytical Chemistry.
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 [en]
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: urn:nbn:se:uu:diva-180109ISBN: 978-91-554-8457-6 (print)OAI: oai:DiVA.org:uu-180109DiVA: diva2:548253
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
List of papers
1. Mining ventricular cerebrospinal fluid from patients with traumatic brain injury using hexapeptide ligand libraries to search for trauma biomarkers
Open this publication in new window or tab >>Mining ventricular cerebrospinal fluid from patients with traumatic brain injury using hexapeptide ligand libraries to search for trauma biomarkers
2010 (English)In: Journal of chromatography. B, ISSN 1570-0232, E-ISSN 1873-376X, Vol. 878, no 22, 2003-2012 p.Article in journal (Refereed) Published
Abstract [en]

Traumatic brain injury (TBI) is an acute event resulting from external force to the brain and is a major cause of death and disability associated with high health care costs in the western world. Additional injuries, originating from the secondary molecular events after the initial intensive care, may be limited by the use of objective biomarkers to provide the best treatment and patient prediction outcome. In this study, hexapeptide ligand libraries (HLL) have been used for the enrichment of suggested protein biomarkers for TBI in cerebrospinal fluid (CSF). HLL have the potential to enrich low abundant proteins and simultaneously reduce the high abundant proteins, rendering a sample with significantly reduced dynamic range. The CSF proteome from two TBI inflicted patients have been extensively mapped using a large initial sample volume obtained by extraventricular drainage. Shotgun proteomics, in combination with isoelectric focusing (IEF) and nano-LC-MS/MS, identified 339 unique proteins (MudPIT scoring p ≤ 0.05) with a protein overlap of 130 between the patients. As much as 45% of the proteins reported in the literature to be associated with degenerative/regenerative processes occurring after a trauma to the head were identified. Out of the most prominent potential protein biomarkers, such as neuron specific enolase, glial fibrillary acidic protein, myelin basic protein, creatine kinase B-type and S-100β, all except myelin basic protein were detected in the study. This study shows the possibility of using HLL as a tool for screening of low abundant protein biomarkers in human CSF.

Place, publisher, year, edition, pages
Elsevier, 2010
Keyword
Cerebrospinal fluid, hexapeptide ligand library, traumatic brain injury, proteomics, mass spectrometry
National Category
Analytical Chemistry
Research subject
Chemistry with specialization in Analytical Chemistry
Identifiers
urn:nbn:se:uu:diva-126988 (URN)10.1016/j.jchromb.2010.05.036 (DOI)000280210300014 ()20542479 (PubMedID)
Available from: 2010-07-02 Created: 2010-07-02 Last updated: 2017-12-12Bibliographically approved
2. Cloud-point extraction and delipidation of porcine brain proteins in combination with bottom-up mass spectrometry approaches for proteome analysis
Open this publication in new window or tab >>Cloud-point extraction and delipidation of porcine brain proteins in combination with bottom-up mass spectrometry approaches for proteome analysis
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2010 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 9, no 8, 3903-3911 p.Article in journal (Refereed) Published
Abstract [en]

In this study, temperature-induced phase fractionation also known as cloud-point extraction (CPE) with the nonionic surfactant Triton X-114 was used to simultaneously extract hydrophobic and hydrophilic proteins from porcine brain tissue. Various protein precipitation/delipidation procedures were investigated to efficiently remove lipids and detergents while retaining maximum protein recoveries. The best performing delipidation method was then used in combination with CPE to compare three different mass spectrometry (MS) based "bottom-up" proteomic approaches for protein analysis of the porcine brain. In the first approach, the intact proteins were initially separated by one-dimensional (1D) gel electrophoresis. The excised protein bands were digested with trypsin, and the peptides were separated by reversed phase nanoliquid chromatography (RP-nanoLC) followed by electrospray ionization (ESI) tandem mass spectrometry (MS/MS) analysis. The other bottom-up proteomic approaches were based on first enzymatical digestion of the proteins followed by RP-nanoLC separation in combination with matrix assisted laser desorption/ionization time-of-flight tandem mass spectrometry (MALDI-TOF/TOF MS) or on the combination of in-solution isoelectric focusing (IEF) with ESI-nanoLC-MS/MS of the IEF separated peptides. In total, we found and unambiguously identified 331 unique proteins. The overlap between different techniques was about 10%, showing that the use of multiple proteomic approaches is beneficial to yield a better coverage of the proteome. Furthermore, the overlap between the CPE extracted hydrophilic and hydrophobic proteins was rather small (9-16%), indicating an efficient sample preparation technique to extract and separate hydrophilic and hydrophobic proteins from brain tissue. The percentage of identified membrane proteins was 27%, which is in accordance to the fact that about one-third of all genes in various organisms encode for this class of proteins. The results indicate that cloud point extraction is a promising sample preparation tool, which allows simultaneous in depth studies of brain derived membrane proteins as well as hydrophilic proteins. This technique can be very useful when studying human central nervous system (CNS) tissue or animal models of neurological diseases.

Place, publisher, year, edition, pages
ACS, 2010
Keyword
cloud-point extraction (CPE), delipidation, central nervous system (CNS), brain, bottom-up proteomics, membrane proteins (MPs), mass spectrometry (MS)
National Category
Chemical Sciences
Research subject
Analytical Chemistry
Identifiers
urn:nbn:se:uu:diva-130276 (URN)10.1021/pr100116k (DOI)000280583700014 ()20586484 (PubMedID)
Available from: 2010-09-08 Created: 2010-09-06 Last updated: 2017-12-12Bibliographically approved
3. Analysis of membrane and hydrophilic proteins simultaneously derived from the mouse brain using cloud-point extraction
Open this publication in new window or tab >>Analysis of membrane and hydrophilic proteins simultaneously derived from the mouse brain using cloud-point extraction
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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.

Keyword
Cloud-point extraction (CPE), Brain, Proteomics, Membrane proteins (MPs), Mass spectrometry (MS), iTRAQ
National Category
Chemical Sciences
Identifiers
urn:nbn:se:uu:diva-154958 (URN)10.1007/s00216-011-5037-9 (DOI)000291037800016 ()21553125 (PubMedID)
Available from: 2011-06-14 Created: 2011-06-14 Last updated: 2017-12-11Bibliographically approved
4. Comparative study of label and label-free techniques using shotgun proteomics for relative protein quantification
Open this publication in new window or tab >>Comparative study of label and label-free techniques using shotgun proteomics for relative protein quantification
2013 (English)In: Journal of chromatography. B, ISSN 1570-0232, E-ISSN 1873-376X, Vol. 928, 83-92 p.Article in journal (Refereed) Published
Abstract [en]

The analytical performance of three different strategies, iTRAQ (isobaric tag for relative and absolute quantitation), dimethyl labeling (DML) and label free (LF) for relative protein quantification using shotgun proteomics have been evaluated. The methods have been explored using samples containing (i) Bovine proteins in known ratios and (ii) Bovine proteins in known ratios spiked into E.Coli. The latter case mimics the actual conditions in a typical biological sample with a few differentially expressed proteins and a bulk of proteins with unchanged ratios. Additionally, the evaluation was performed on both Q-TOF and LTQ-FTICR mass spectrometers. LF LTQ-FTICR was found to have the highest proteome coverage (94 %) while the highest accuracy based on the artificially regulated proteins was found for DML LTQ-FTICR (54%). A good linearity (r2: 0.61-0.96) was shown for all methods within selected dynamic ranges. All methods were found to consistently underestimate bovine protein ratios when matrix proteins were added. However LF LTQ-FTICR was more tolerant towards a compression effect.  A single peptide was demonstrated to be sufficient for a reliable quantification using iTRAQ. A ranking system utilizing several parameters important for quantitative proteomics demonstrated that the overall performance of the five different methods were; DML LTQ-FTICR > iTRAQ QTOF > LF LTQ-FTICR > DML Q-TOF > LF Q-TOF.

Keyword
Relative quantification, Proteomics, Mass spectrometry, Stable isotope labeling, Label free
National Category
Analytical Chemistry
Research subject
Analytical Chemistry
Identifiers
urn:nbn:se:uu:diva-180105 (URN)10.1016/j.jchromb.2013.03.027 (DOI)000319236700011 ()
Note

De två (2) sista författarna delar sistaförfattarskapet.

Available from: 2012-08-29 Created: 2012-08-29 Last updated: 2017-12-07Bibliographically approved
5. Proteomic analysis of cerebrospinal fluid from neuropathic pain patients reveals proteins with potential role in spinal cord stimulation
Open this publication in new window or tab >>Proteomic analysis of cerebrospinal fluid from neuropathic pain patients reveals proteins with potential role in spinal cord stimulation
Show others...
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Spinal cord stimulation (SCS) is a widely used mode of therapy in neuropathic pain of peripheral origin. Despite its well-established clinical use, the underlying physiological mechanisms behind the beneficial analgesic effects of SCS still remain only partially known.  In this study, a proteomic approach was used to compare the protein concentration in cerebrospinal fluid (CSF) from responsive human patients (n=12). The comparison was made between samples taken during at two different timepoints. The first sample was taken when the stimulator had been off for 48 h, the second sample was taken after the stimulator had been used for three weeks. In total, 419 proteins could be identified (P<0.05) and relatively quantified using a shotgun proteomic approach based on immunoaffinity fractionation, multiplexed dimethyl labeling and reversed phase nanoliquid chromatography in combination with electrospray ionization high resolution tandem mass spectrometry. Statistical analysis (P<0.01) revealed two significantly down-regulated proteins; Co2 (P=0.0046), Ibp6 (P=0.0071) and five up-regulated proteins; Lynx1 (P=0.000048), Klk6 (P=0.00058), Angt (P=0.00057), A4 (P=0.0052) and Sap3 (P=0.0076) during the on state. Lynx1was the most significantly and consistently increased protein in all patients. Lynx1 is a modulator of the nicotinic acetylcholine receptor activity in the central nervous system previously described in mice. This study reports for the first time the possible involvement of Lynx1 in SCS-induced analgesia in humans.

Keyword
Neuropathic pain, Cerebrospinal fluid, Spinal cord stimulation, Stable isotope labeling, Quantification, Proteomics, Mass spectrometry
National Category
Analytical Chemistry Neurosciences Anesthesiology and Intensive Care
Research subject
Neuroscience; Analytical Chemistry
Identifiers
urn:nbn:se:uu:diva-180108 (URN)
Available from: 2012-08-29 Created: 2012-08-29 Last updated: 2013-01-23

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