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A protein-coated magnetic beads as a tool for the rapid drug-protein binding study. J Pharm Biomed Anal 2009; 52:420-4. [PMID: 19596536 DOI: 10.1016/j.jpba.2009.06.023] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2009] [Revised: 06/09/2009] [Accepted: 06/11/2009] [Indexed: 11/21/2022]
Abstract
A simple and fast method for the determination of the association constant (K(a)) of ligand to human serum albumin (HSA) has been developed by using human serum albumin-coated magnetic beads (HSA-MB). To date, magnetic beads (MB) have been increasingly used as a bioseparation tool, especially for DNA, RNA, protein, enzyme and cell isolation or purification. In this study, HSA-MB were used as a new tool to determine the affinity of known ligands to HSA. The K(a) for l-tryptofan, fenoprofen, ketoprofen, tolbutamide and warfarin obtained from Schathard analysis are consistent with previously reported values. The different K(a) values for ketoprofen after the acetylation of HSA-MB by preincubation with acetylosalicylic acid indicate that these beads can be successfully adapted in combined experiment. In addition, the HSA-MB experiment with phenytoin and valproic acid proved to be a simple method to examine drug displacement effect.
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52
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Callesen AK, Madsen JS, Vach W, Kruse TA, Mogensen O, Jensen ON. Serum protein profiling by solid phase extraction and mass spectrometry: A future diagnostics tool? Proteomics 2009; 9:1428-41. [DOI: 10.1002/pmic.200800382] [Citation(s) in RCA: 80] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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53
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Sparbier K, Wenzel T, Dihazi H, Blaschke S, Müller GA, Deelder A, Flad T, Kostrzewa M. Immuno-MALDI-TOF MS: New perspectives for clinical applications of mass spectrometry. Proteomics 2009; 9:1442-50. [DOI: 10.1002/pmic.200800616] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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54
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Lumbreras B, Porta M, Marquez S, Pollán M, Parker LA, Hernández-Aguado I. Sources of error and its control in studies on the diagnostic accuracy of “-omics” technologies. Proteomics Clin Appl 2009; 3:173-184. [DOI: 10.1002/prca.200800092] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
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55
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Chen H, Qi D, Deng C, Yang P, Zhang X. Preparation of C60-functionalized magnetic silica microspheres for the enrichment of low-concentration peptides and proteins for MALDI-TOF MS analysis. Proteomics 2009; 9:380-7. [DOI: 10.1002/pmic.200800335] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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56
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Integrated multi-level quality control for proteomic profiling studies using mass spectrometry. BMC Bioinformatics 2008; 9:519. [PMID: 19055809 PMCID: PMC2657802 DOI: 10.1186/1471-2105-9-519] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2008] [Accepted: 12/04/2008] [Indexed: 01/28/2023] Open
Abstract
Background Proteomic profiling using mass spectrometry (MS) is one of the most promising methods for the analysis of complex biological samples such as urine, serum and tissue for biomarker discovery. Such experiments are often conducted using MALDI-TOF (matrix-assisted laser desorption/ionisation time-of-flight) and SELDI-TOF (surface-enhanced laser desorption/ionisation time-of-flight) MS. Using such profiling methods it is possible to identify changes in protein expression that differentiate disease states and individual proteins or patterns that may be useful as potential biomarkers. However, the incorporation of quality control (QC) processes that allow the identification of low quality spectra reliably and hence allow the removal of such data before further analysis is often overlooked. In this paper we describe rigorous methods for the assessment of quality of spectral data. These procedures are presented in a user-friendly, web-based program. The data obtained post-QC is then examined using variance components analysis to quantify the amount of variance due to some of the factors in the experimental design. Results Using data from a SELDI profiling study of serum from patients with different levels of renal function, we show how the algorithms described in this paper may be used to detect systematic variability within and between sample replicates, pooled samples and SELDI chips and spots. Manual inspection of those spectral data that were identified as being of poor quality confirmed the efficacy of the algorithms. Variance components analysis demonstrated the relatively small amount of technical variance attributable to day of profile generation and experimental array. Conclusion Using the techniques described in this paper it is possible to reliably detect poor quality data within proteomic profiling experiments undertaken by MS. The removal of these spectra at the initial stages of the analysis substantially improves the confidence of putative biomarker identification and allows inter-experimental comparisons to be carried out with greater confidence.
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Chen H, Xu X, Yao N, Deng C, Yang P, Zhang X. Facile synthesis of C8-functionalized magnetic silica microspheres for enrichment of low-concentration peptides for direct MALDI-TOF MS analysis. Proteomics 2008; 8:2778-84. [DOI: 10.1002/pmic.200700892] [Citation(s) in RCA: 57] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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58
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Engwegen JYMN, Alberts M, Knol JC, Jimenez CR, Depla ACTM, Tuynman H, van Heukelem HA, Snel P, Smits ME, Cats A, Schellens JHM, Beijnen JH. Influence of variations in sample handling on SELDI-TOF MS serum protein profiles for colorectal cancer. Proteomics Clin Appl 2008; 2:936-45. [DOI: 10.1002/prca.200780068] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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59
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Navare A, Zhou M, McDonald J, Noriega FG, Sullards MC, Fernandez FM. Serum biomarker profiling by solid-phase extraction with particle-embedded micro tips and matrix-assisted laser desorption/ionization mass spectrometry. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2008; 22:997-1008. [PMID: 18320548 PMCID: PMC2665883 DOI: 10.1002/rcm.3462] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
One of the main challenges in high-throughput serum profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is the development of proteome fractionation approaches that allow the acquisition of reproducible profiles with a maximum number of spectral features and minimum interferences from biological matrices. This study evaluates a new class of solid-phase extraction (SPE) pipette tips embedded with different chromatographic media for fractionation of model protein digests and serum samples. The materials embedded include strong anion exchange (SAX), weak cation exchange (WCX), C18, C8, C4, immobilized metal affinity chromatography (IMAC) and zirconium dioxide particles. Simple and rapid serum proteome profiling protocols based on these SPE micro tips are described and tested using a variety of MALDI matrices. We show that different types of particle-embedded SPE micro tips provide complementary information in terms of the spectral features detected for beta-casein digests and control human serum samples. The effect of different sample pretreatments, such as serum dilution and ultrafiltration using molecular weight cut-off membranes, and the reproducibility observed for replicate experiments, are also evaluated. The results demonstrate the usefulness of these simple SPE tips combined with offline MALDI-TOF MS for obtaining information-rich serum profiles, resulting in a robust, versatile and reproducible open-source platform for serum biomarker discovery.
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Affiliation(s)
- Arti Navare
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Manshui Zhou
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - John McDonald
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Fernando G. Noriega
- Department of Biology, Florida International University, Miami, FL 33199, USA
| | - M. Cameron Sullards
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Facundo M. Fernandez
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
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60
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Callesen AK, Vach W, Jørgensen PE, Cold S, Tan Q, dePont Christensen R, Mogensen O, Kruse TA, Jensen ON, Madsen JS. Combined Experimental and Statistical Strategy for Mass Spectrometry Based Serum Protein Profiling for Diagnosis of Breast Cancer: A Case-Control Study. J Proteome Res 2008; 7:1419-26. [DOI: 10.1021/pr7007576] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Anne K. Callesen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Werner Vach
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Per E. Jørgensen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Søren Cold
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Qihua Tan
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - René dePont Christensen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Ole Mogensen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Torben A. Kruse
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Ole N. Jensen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Jonna S. Madsen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
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61
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Callesen AK, Vach W, Jørgensen PE, Cold S, Mogensen O, Kruse TA, Jensen ON, Madsen JS. Reproducibility of Mass Spectrometry Based Protein Profiles for Diagnosis of Breast Cancer across Clinical Studies: A Systematic Review. J Proteome Res 2008; 7:1395-402. [DOI: 10.1021/pr800115f] [Citation(s) in RCA: 46] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Anne K. Callesen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Werner Vach
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Per E. Jørgensen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Søren Cold
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Ole Mogensen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Torben A. Kruse
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Ole N. Jensen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | - Jonna S. Madsen
- Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark, Department of Biochemistry, Pharmacology and Genetics, Odense University Hospital, Odense, Denmark, Department of Statistics, University of Southern Denmark, Odense, Denmark, Department of Oncology, Odense University Hospital, Odense, Denmark, and Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
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62
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Meuleman W, Engwegen JY, Gast MCW, Beijnen JH, Reinders MJ, Wessels LF. Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data. BMC Bioinformatics 2008; 9:88. [PMID: 18257918 PMCID: PMC2258289 DOI: 10.1186/1471-2105-9-88] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2007] [Accepted: 02/07/2008] [Indexed: 11/15/2022] Open
Abstract
Background Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result. Results In this paper, we describe the first systematic comparison of a wide range of normalisation methods, using two objectives that should be met by a good method. These objectives are minimisation of inter-spectra variance and maximisation of signal with respect to class separation. The former is assessed using an estimation of the coefficient of variation, the latter using the classification performance of three types of classifiers on real-world datasets representing two-class diagnostic problems. To obtain a maximally robust evaluation of a normalisation method, both objectives are evaluated over multiple datasets and multiple configurations of baseline correction and peak detection methods. Results are assessed for statistical significance and visualised to reveal the performance of each normalisation method, in particular with respect to using no normalisation. The normalisation methods described have been implemented in the freely available MASDA R-package. Conclusion In the general case, normalisation of mass spectra is beneficial to the quality of data. The majority of methods we compared performed significantly better than the case in which no normalisation was used. We have shown that normalisation methods that scale spectra by a factor based on the dispersion (e.g., standard deviation) of the data clearly outperform those where a factor based on the central location (e.g., mean) is used. Additional improvements in performance are obtained when these factors are estimated locally, using a sliding window within spectra, instead of globally, over full spectra. The underperforming category of methods using a globally estimated factor based on the central location of the data includes the method used by the majority of SELDI users.
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Affiliation(s)
- Wouter Meuleman
- Bioinformatics and Statistics, Department of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
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63
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Yao N, Chen H, Lin H, Deng C, Zhang X. Enrichment of peptides in serum by C(8)-functionalized magnetic nanoparticles for direct matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis. J Chromatogr A 2008; 1185:93-101. [PMID: 18262195 DOI: 10.1016/j.chroma.2008.01.047] [Citation(s) in RCA: 73] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2007] [Revised: 01/16/2008] [Accepted: 01/17/2008] [Indexed: 11/27/2022]
Abstract
Human serum contains a complex array of proteolytically derived peptides (serum peptidome), which contain biomarkers of preclinical screening and disease diagnosis. Recently, commercial C(8)-functionalized magnetic beads (1-10 microm) were widely applied to the separation and enrichment of peptides in human serum, prior to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) analysis. In this work, laboratory-prepared C(8)-functionalized magnetic nanoparticles (about 50 nm) were prepared and applied to the fast separation and the enrichment of peptides from serum. At first, the C(8)-magnetic nanoparticles were synthesized by modifying amine-functionalized magnetic nanoparticles with chlorodimethyloctylsilane. These synthesized C(8)-amine-functionalized magnetic particles have excellent magnetic responsibility, high dispersibility and large surface area. Finally, the C(8)-magnetic nanoparticles were successfully applied to fast and efficient enrichment of low-abundance peptides from protein tryptic digestion and human serum followed by MALDI-TOF-MS analysis.
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Affiliation(s)
- Ning Yao
- Department of Chemistry, Fudan University, Shanghai 200433, China
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64
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Tiss A, Smith C, Camuzeaux S, Kabir M, Gayther S, Menon U, Waterfield M, Timms J, Jacobs I, Cramer R. Serum Peptide Profiling using MALDI Mass Spectrometry. Proteomics 2007; 7 Suppl 1:77-89. [PMID: 17893856 DOI: 10.1002/pmic.200700746] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Blood represents a convenient diagnostic specimen for clinical analysis. Serum metabolites and peptides have the potential to serve as reliable indicators of progression from a normal to a diseased state. However, the presence of salts, lipids and high concentrations of protein in blood serum can adversely affect its mass spectrometric profiling, as all of these moieties can hinder the ionisation and detection of diagnostic biomarkers. Several pre-fractionation strategies using chromatographic adsorbents have been employed to desalt samples and remove abundant proteins such as albumin and immunoglobulin. As an alternative to multi-stage fractionation chromatography, we describe in this practical review the adaptation and validation of a simple and fast solid-phase extraction technique using ZipTips. The protocol allows for the purification and concentration of peptides in a few, mostly automated steps, prior to spectral biomarker pattern diagnostics using MALDI MS and MS/MS. It has the added advantages of being suitable for use in a high-throughput and potentially clinical environment, only requiring a few microlitres of serum. We have evaluated, optimised, and standardised a number of analytical parameters ranging from serum storage and handling to automated peptide extraction, crystallisation, spectral acquisition, and signal processing. Using standardised protocols the average CV of serum profiles within- and between-run replicates has been evaluated and found to be around 10 % based on the variability of all detected peaks (more than 100 peaks per profile). The results show that this easy and fast method of using ZipTips, tested over a whole year, is more reproducible and more suitable for serum profile screening than magnetic bead-based methodologies which show higher variability and higher rates of rejected, low-quality spectra upon applying strict data quality control filters.
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Affiliation(s)
- Ali Tiss
- The BioCentre and Department of Chemistry, University of Reading, Reading, UK
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65
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Drake RR, Cazares L, Semmes OJ. Mining the low molecular weight proteome of blood. Proteomics Clin Appl 2007; 1:758-68. [DOI: 10.1002/prca.200700175] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2007] [Indexed: 01/08/2023]
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66
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Luque-Garcia JL, Neubert TA. Sample preparation for serum/plasma profiling and biomarker identification by mass spectrometry. J Chromatogr A 2007; 1153:259-76. [PMID: 17166507 PMCID: PMC7094463 DOI: 10.1016/j.chroma.2006.11.054] [Citation(s) in RCA: 135] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2006] [Revised: 11/06/2006] [Accepted: 11/16/2006] [Indexed: 01/14/2023]
Abstract
In this article, we present an overview of the different strategies for sample preparation for identification by mass spectrometry (MS) of biomarkers from serum and/or plasma. We consider the effects of the variables involved in sample collection, handling and storage, and describe different approaches for removal of high abundance proteins and serum/plasma fractionation. We review the advantages and disadvantages of such techniques as centrifugal ultrafiltration, different formats for solid phase extraction, organic solvent extraction, gel and capillary electrophoresis, and liquid chromatography. We also discuss a variety of current proteomic methods and their main applications for biomarker-related studies.
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Affiliation(s)
| | - Thomas A. Neubert
- Skirball Institute of Biomolecular Medicine and Department of Pharmacology, New York University School of Medicine, New York, NY 10016, USA
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67
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Jimenez CR, El Filali Z, Knol JC, Hoekman K, Kruyt FAE, Giaccone G, Smit AB, Li KW. Automated serum peptide profiling using novel magnetic C18 beads off-line coupled to MALDI-TOF-MS. Proteomics Clin Appl 2007; 1:598-604. [PMID: 21136711 DOI: 10.1002/prca.200600483] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2006] [Indexed: 11/12/2022]
Abstract
Serum peptide profiling by MS is an emerging approach for disease diagnosis and biomarker discovery. A magnetic bead-based method for off-line serum peptide capture coupled to MALDI-TOF-MS has been recently introduced. However, the reagents are not available to the general scientific community. Here, we developed a protocol for serum peptide capture using novel magnetic C18 beads, and automated the procedure on a high-throughput magnetic particle processor. We investigated bead equilibration, peptide binding and peptide elution conditions. The method is evaluated in terms of peaks counts and reproducibility of ion intensities in control serum. Overall, the DynaBead-RPC18-based serum sample processing protocol reported here is reproducible, robust and allows for the detection of ˜200 peptides at m/z 800-4000 of serum that was allowed to clot for 1 h. The average intra-experiment %CV of normalized ion intensities for crude serum and 0.5% TFA/0.15% n-octyl glucoside-treated serum, respectively, were 12% (range 2-38%) and 10% (3-21%) and the inter-experiment %CVs were 24% (10-53%) and 31% (10-59%). Importantly, this method can be used for serum peptide profiling by anyone in possession of a MALDI-TOF instrument. In conjunction with the KingFisher® 96, the whole serum peptide capture procedure is high-throughput (˜20 min per isolation of 96 samples in parallel), thereby facilitating large-scale disease profiling studies.
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Affiliation(s)
- Connie R Jimenez
- OncoProteomics Laboratory, Department of Medical Oncology, VU Medical Center, Amsterdam, The Netherlands; Department of Molecular and Cellular Neurobiology, Center for Medical Systems Biology/Neurogenomics and Cognitive Research, Vrije Universteit, Amsterdam, The Netherlands.
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West-Nørager M, Kelstrup CD, Schou C, Høgdall EV, Høgdall CK, Heegaard NHH. Unravelling in vitro variables of major importance for the outcome of mass spectrometry-based serum proteomics. J Chromatogr B Analyt Technol Biomed Life Sci 2006; 847:30-7. [PMID: 17112795 DOI: 10.1016/j.jchromb.2006.09.048] [Citation(s) in RCA: 61] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2006] [Revised: 09/19/2006] [Accepted: 09/24/2006] [Indexed: 11/24/2022]
Abstract
The use of mass spectrometry (MS) for analysing low-molecular weight proteins and peptides from biological fluids has a great, yet not fully realized, potential for biomarker discovery. To prune MS-data as much as possible for non-relevant non-biological variation the development of standardized protocols for handling and processing the samples before MS and adjusting data after MS to compensate for method-induced variability are warranted. This calls for knowledge about how different variables contribute to MS-based proteome analyses. In addition, identification of the peptides involved in pre-analytical variation will be helpful in evaluating the clinical significance of predictive models derived from MS data. Using human sera, extraction by weak cation-exchange magnetic beads, and analysis by MALDI-TOF MS we here evaluated pre-analytical variation and identify peptides involved in this. The influences of humidity, temperature, and time for preparation of sera on spectral changes were evaluated. Also, the reproducibility of the methods and the effect of a baseline correction procedure were examined. Low temperatures, short handling times, and a baseline correction procedure minimize the contribution of artifacts to sample variability as observed by MS. The complement split product C3f and fragments thereof appear to be sensitive indicators of sample handling induced modifications. Other peptides that are indicative of such variability are fibrin and kininogen fragments. Using strict experimental guidelines as well as standardized sample collection procedures it is possible to obtain reproducible peak intensities and positions in serum mass profiling using magnetic bead-based fractionation and MALDI-TOF MS.
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Affiliation(s)
- Mikkel West-Nørager
- Department of Autoimmunology, Statens Serum Institut, DK-2300 Copenhagen S, Denmark.
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de Noo ME, Tollenaar RAEM, Deelder AM, Bouwman LH. Current status and prospects of clinical proteomics studies on detection of colorectal cancer: Hopes and fears. World J Gastroenterol 2006; 12:6594-601. [PMID: 17075970 PMCID: PMC4125662 DOI: 10.3748/wjg.v12.i41.6594] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Colorectal adenocarcinoma (CRC) is the third most common type of cancer and the fourth most frequent cause of death due to cancer worldwide. Given the natural history of CRC, early diagnosis appears to be the most appropriate tool to reduce disease-related mortality. A field of recent interest is clinical proteomics, which was reported to lead to high sensitivity and specificities for early detection of several solid tumors. This emerging field uses mass spectrometry-based protein profiles/patterns of easy accessible body fluids to distinguish cancer from non-cancer patients. These discrepancies may be a result of: (1) proteins being abnormally produced or shed and added to the serum proteome, (2) proteins clipped or modified as a consequence of the disease process, or (3) proteins subtracted from the proteome owing to disease-related proteolytic degradation pathways. Therefore, protein pattern diagnostics would provide easy and reliable tools for detection of cancer. This paper focuses on the current status of clinical proteomics research in oncology and in colorectal cancer especially, and will reflect on pitfalls and fears in this relatively new area of clinical medicine, which are reproducibility issues and pre-analytical factors, statistical issues, and identification and nature of discriminating proteins/peptides.
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Affiliation(s)
- M E de Noo
- Department of Surgery, K6-R, Leiden University Medical Center, PO Box 9600, Leiden 2300 RC, The Netherlands.
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70
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de Noo ME, Deelder A, van der Werff M, Ozalp A, Mertens B, Tollenaar R. MALDI-TOF serum protein profiling for the detection of breast cancer. Oncol Res Treat 2006; 29:501-6. [PMID: 17068384 DOI: 10.1159/000095933] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
BACKGROUND Proteomic expression profiling has been suggested as a potential tool for the early diagnosis of cancer and other diseases. The objective of our study was to assess the feasibility of this approach for the detection of breast cancer. MATERIALS AND METHODS In a randomized block design pre-operative serum samples obtained from 78 breast cancer patients and 29 controls were used to generate high-resolution MALDI-TOF protein profiles. The spectra generated using C8 magnetic beads assisted mass spectrometry were smoothed, binned and normalized after baseline correction. Linear discriminant analysis with double cross-validation, based on principal component analysis, was used to classify the protein profiles. RESULTS A total recognition rate of 99%, a sensitivity of 100%, and a specificity of 97.0% for the detection of breast cancer were shown. The area under the curve of the classifier was 98.3%, which demonstrates the separation power of the classifier. The first 2 principal components account for most of the between- group separation. CONCLUSIONS Double cross-validation showed that classification could be attributed to actual information in the protein profiles rather than to chance. Although preliminary, the high sensitivity and specificity indicate the potential usefulness of serum protein profiles for the detection of breast cancer.
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Affiliation(s)
- Mirre E de Noo
- Department of Surgery, Leiden University Medical Center, The Netherlands.
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71
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McLachlan A, Borchers M, Velayutham P, Wagner M, Limbach PA. Characterizing the Reproducibility of a Protein Profiling Method for the Analysis of Mouse Bronchoalveolar Lavage Fluid. J Proteome Res 2006; 5:3059-65. [PMID: 17081057 DOI: 10.1021/pr060241r] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The detection of biomarkers in biological fluids has been advanced by the introduction of mass spectrometry screening methods such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS), which enables the detection of the presence and the molecular mass of proteins in unfractionated mixtures. The generation of reproducible mass spectra over the course of an experiment is vital in obtaining data in which differences in protein profiles between diseased and healthy states can be assessed correctly. We have developed a protocol to automate the collection of protein profiling data from a large number of samples using MALDI-TOFMS, and we used these samples to characterize the technical reproducibility of the method. This protocol has been used for the analysis of proteins found in bronchoalveolar lavage fluid samples from mice with the ultimate goal of enabling the discovery of differential expression patterns predictive of the development of chronic obstructive pulmonary disease. Samples were purified using magnetic bead-based technology and analyzed on an AnchorChip target plate. Our results demonstrate that the number of peaks detected reproducibly decreases significantly as sample size increases, which motivates the need for technical replicates to be explicitly included in the analysis of MALDI-TOF-based protein profiling studies.
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Affiliation(s)
- Anne McLachlan
- Rieveschl Laboratories for Mass Spectrometry, Department of Chemistry, P.O. Box 210172, University of Cincinnati, Cincinnati, Ohio 45221, USA
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Solassol J, Jacot W, Lhermitte L, Boulle N, Maudelonde T, Mangé A. Clinical proteomics and mass spectrometry profiling for cancer detection. Expert Rev Proteomics 2006; 3:311-20. [PMID: 16771703 DOI: 10.1586/14789450.3.3.311] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
A key challenge in the clinical proteomics of cancer is the identification of biomarkers that would enable early detection, diagnosis and monitoring of disease progression to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer a unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and mass spectrometry is one of the most interesting new approaches for cancer diagnostics using proteomic profiling. This review presents two technologies in this field, surface-enhanced laser desorption/ionization time-of-flight and Clinprot, and aims to summarize the results of studies obtained with the first of them for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems, and still requires some efforts to be standardized and validated.
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Affiliation(s)
- Jérôme Solassol
- Hôpital Arnaud de Villeneuve, Laboratoire de Biologie Cellulaire- INSERM U540, 371 Avenue du Doyen Giraud, 34295 Montpellier Cedex 5, France.
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de Noo ME, Mertens BJA, Ozalp A, Bladergroen MR, van der Werff MPJ, van de Velde CJH, Deelder AM, Tollenaar RAEM. Detection of colorectal cancer using MALDI-TOF serum protein profiling. Eur J Cancer 2006; 42:1068-76. [PMID: 16603345 DOI: 10.1016/j.ejca.2005.12.023] [Citation(s) in RCA: 61] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2005] [Accepted: 12/19/2005] [Indexed: 01/07/2023]
Abstract
Serum protein profiling is a promising approach for classification of cancer versus non-cancer samples. The objective of our study was to assess the feasibility of mass spectrometry based protein profiling for the discrimination of colorectal cancer (CRC) patients from healthy individuals. In a randomized block design, pre-operative serum samples obtained from 66 colorectal cancer patients and 50 controls were used to generate MALDI-TOF protein profiles. After pre-processing of the spectra, linear discriminant analysis with double cross-validation was used to classify protein profiles. A total recognition rate (92.6%), sensitivity (95.2%) and specificity (90.0%) for the detection of CRC were shown. The area under the curve of the classifier was 97.3%, and demonstrated the high, significant separation power of the classifier. Double cross-validation shows that classification can be attributed to information in the protein profile. Although preliminary, the high sensitivity and specificity indicate the potential usefulness of serum protein profiles for the detection of colorectal cancer.
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Affiliation(s)
- Mirre E de Noo
- Department of Surgery, K6-R, Leiden University Medical Center, Albinusdreef 2, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
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