Review of the Maldi-MS Technique - Coursework Example

I. REVIEW OF THE MALDI-MS TECHNIQUE Mass spectrometry (MS) is a technique used to measure the mass-to-charge ratio of particles (Jensen, Shevchenko,& Mann, 1997). MS is useful for the determination of masses, elemental composition of single and multiple components of a mixture and the chemical structure of elements and compounds. The procedure for carrying out a mass spectrometry analysis is possible with three sets of basic instruments: ion source, mass analyzer and, ion detector. There are five general steps for determining the mass-to-charge ratios: (1) sample loading and vaporization, (2) ionization of sample components to produce ions, (3) separation of ions by electromagnetic field to their mass-to-charge ratios, (4) detection of ion signals and, (5) processing of the signals into mass spectra. The ionization of the analytes is a crucial step in mass spectrometry. Two methods are used: electron spray ionization and matrix-assisted laser desorption ionization (MALDI) (Figure 1). In MALDI, the analyte is mixed with matrix, molecules that have strong absorbance at the laser wavelength, and placed onto a metal plate (Karas, Bachmann, & Hillenkamp, 1985). A laser beam is then introduced which results in a burst of ions. The presence of the matrix refreshes the laser burst, and enhances the isolation of the sample ions. Figure 1. Schematic diagram for MALDI technique (adapted from Gates, 2004). Protein and peptide analyses are the most common applications of MALDI, with the most number of technical developments in the past years (Hillenkamp & Katalinic, 2007). MALDI is the leading application for proteomics profiling and imaging. Other analytes studied are nucleic acids, glycans, lipids, and synthetic polymers. Each of these analytes may have limitations in their analysis due to their structural properties, which can interfere with the ionization efficiency. The spatial distribution of drugs, metabolites, and proteins in intact tissues is also made possible with imaging mass spectrometry (Caldwell & Caprioli, 2005). MALDI-MS is therefore a valuable technique that can address a broad range of applications in the biomedical field. Since MALDI-MS tissue profiling permits the detection of more than a thousand peptides and proteins from many tissue types, it is very useful in detecting disease processes. Tissue profiling and imaging permits the direct acquisition of mass spectra from intact tissues that are either freshly prepared or come from tissue storage banks (Djidja, et al., 2010). Recently, tissue blocks that have been embedded in paraffin were used in protein profiling of several cancers. These studies showed that MALDI-MS is also effective in studying peptide and protein profiles in old tissues. MALDI-MS analysis of tissue micro-array (TMA) blocks has been utilized to study chemical organization and features of tumours (McDonnel & Heeren, 2007), lipid and protein localization in tumours (Walch, Rauser, Deininger, & Hofler, 2008), tumour progression, and to provide correct diagnosis and staging of cancers (Djidja, et al., 2010). MALDI-MS on TMA was used to study the protein profiles in breast cancer (Sanders, et al., 2008), prostate cancer (Schwamborn, Krieg, Reska, Jakse, Knuechel, & Wellmann, 2007), renal (Gregson, 2009) and lung cancers (Groseclose, Massion, Chaurand, & Caprioli, 2008). A little over a decade after MALDI-MS was introduced, its advantages over other methods of molecular analysis made it a popular choice (Jensen, Shevchenko, & Mann, 1997). First, the sample requirement for MALDI-MS is minimal and preparation is rapid. The mass spectra of even heterogeneous samples can be obtained within a short period. Due to the large number of samples that can be analyzed at a single time (high-throughput analyses), MALDI-MS is used to screen samples prior to more meticulous and time-consuming assays. MALDI is also used with other mass spectrometry derived techniques like MALDI-MSI-IMS (MALDI-mass spectrometry imaging-ion mobility separation) (Djidja, et al., 2010). However, despite the notable technical advances, there are also some disadvantages of the technique (Jensen, Shevchenko, & Mann, 1997). Workers observe that most mass spectrometry techniques, MALDI included, detect almost everything in peptide mixtures, which makes finding and identifying the peptide of interest based on mass data very difficult (Veenstra, 2007). This is truer for peptides of proteins that are low in abundance. To increase selectivity means additional multi-dimensional separation techniques, which can increase the number of analyses for a single peptide. Other challenges are also present (Parker, Pearson, Anderson, & Borchers, 2010). Analysis of a large number of biomolecules requires high resolving power of the mass spectrometer. Some analytes are suppressed and others are preferentially ionized (suppression), which makes MALDI-MS unsuitable for quantitative analysis. For quantitative analysis, matrix material has to be chosen carefully, and the ionization efficiency of the analytes needs to be determined. To reduce suppression effects, the sample analytes mixture has to be simplified; among the simplification procedures is sample fractionation, which is a basic protocol in protein/peptide purification. However, once the limitations are removed through technical adjustments and when the protein targets are identified , then the appropriate biomarker of interest can be isolated or enriched using immunological techniques(Reid, Parker, & Borchers, 2007) (Anderson, Anderson, Haines, Hardie, Olafson, & Pearson, 2004). Careful calibration of experimental parameters must also be performed, and the reproducibility of the analysis has to be ascertained to come up with reliable results. Other techniques for analysis of mixtures, especially of proteins, are available. Some of these techniques have been used in classical studies like the gel-based techniques: SDS polyacrylamide gel electrophoresis, gel filtration, and Western blotting. Other techniques make use of chromatographic columns like high-pressure liquid chromatography (HPLC), or plain liquid chromatography. Immunology-based methods are also major contributions highly specific molecular identification. Although these methods can isolate pure protein components, these techniques are limited by the amount of samples that can be isolated and identified at a single measurement. Nevertheless, one should always remember that the choice of method depends on the objective of the analysis. However, for complex mixtures where a large amount of information is required in a limited time, then mass spectrometry should be the chosen method. Information including the identification of disease states, structural properties, and relative abundance of several molecules of interest can be obtained rapidly with MALDI-MS. Advanced applications of the technology are foreseen like disease diagnosis, early disease detection, and assessment of therapeutic therapy based on proteomic data (Franck, et al., 2009 ). Currently, the cost of equipment and the low availability of skilled technicians limit the use of MALDI-MS to research laboratories. The challenge is to develop modifications in MALDI-MS that will make it more specific, user-friendly and routinely used in clinical diagnosis. Word count: 1071 II. REVIEW OF FLOW CYTOMETRY TECHNIQUE Flow cytometry is a method where the chemical and physical characteristics of the single cells that comprise a large mixture of cells are individually examined (Carter & Ormerod, 2000; Weaver & Stetler-Stevenson, 2005). The cells in the mixture are forced to flow in single file in a fluid stream through a narrow passage and past a sensor (Figure 2). The measurement of parameters on each cell is the most important feature of flow cytometry. Cellular parameters are measured by the presence of fluorescent probes or fluorescent dyes that are attached to specific antibodies and ligands on the cell surface. Many probes and dyes for a myriad of biological compounds are available, and are used to directly estimate the amount of specific cellular parameters or characteristics such as calcium flux, cytoplasmic determinants, and cancer cells. When a light beam coming from a laser lamp or an arc lamp hits the dye, the dye fluoresces. The strength of the fluorescence corresponds to the concentration of the cell to which the dye was attached. Another important function of flow cytometry is cell sorting, or the separation of the cells into different categories. Cell sorting is a means to separate and group cells for cloning, construction of gene libraries and functional and morphological studies. Figure 2. Diagram of a generic flow cytometer (Weaver & Stetler-Stevenson, 2005). Flow cytometry is performed in six steps: (1) extraction of cells and suspension of cells in particle-free saline buffer; (2) addition or labelling with strongly fluorescent dyes specific molecules that can be found on the cell surface; (3) forcing the cells to pass in single file through a narrow aperture with the help of high pressure and hydrodynamic focusing; (4) Illumination of the cells with a laser beam, one cell at a time in order to excite the dye labels enough for them to fluoresce, (5) collection and detection of fluorescence with a photomultiplier tube, and (6) data analysis. The steps are carried out by three major components in the flow cytometer: the fluidic, optical, and electrical systems. Flow cytometry has many applications, especially in clinical situations that require the characterization of irregular cell populations (Weaver & Stetler-Stevenson, 2005). Flow cytometry is primarily used in immunology, haematology, transplantation, and hematopathology procedures. It is ideal for studying biological fluids like blood or bone marrow suspensions, but it can also be used in solid tissues, after single-cell suspensions are produced. Defining cell population phenotypes and abnormality can result in the diagnosis and staging of malignant cancers, and point to immunodeficiency cases. The technique can also be used to count the number of stem cells and identify histocompatibility factors in a patient’s blood especially before organ transplantation is carried out. Other applications in the medical field include the measure of abnormal DNA content, surface markers for myeloid and lymphoid tumours (Beverly & Varmus, 2009), solid tumour DNA content (El-Naggar & Vielh, 2005), and the estimation of cellular DNA content of paraffin embedded tumours (Huang, et al., 2008). The latter technique has been very useful in the study of archival tissues that have been previously been diagnosed. The ability to fingerprint a human tumour based on relevant prognosis helps to provide the basis for treatment (Huang, et al., 2008). Paraffin reactive antibodies for biomarkers have been developed to diagnose B-cell lymphomas using multiparameter flow cytometry (Xu, McKenna, & Kroft, 2002). Flow cytometry was also found to be a convenient means to estimate the size of the nuclear genome of plants (Dolezel,et al., 1998). There are many advantages offered by flow cytometry. It is a quantitative technique and used to quantify cell into different types, and different parameters at a single period. There are many kinds of samples that can be analyzed; blood suspensions, bone marrow, biopsy materials and tissues. The number of dyes available permits the analysis of hundreds of biological molecules. Biotechnology also utilizes flow cytometry for quantifying genomic sequence information, and the interaction between biomolecules and cellular function (Weaver & Stetler-Stevenson, 2005). The automation of sample handling and increased throughput makes the study of different stages of drug discovery easier. Flow cytometry is an important tool in biotechnology, and can be applied in areas of, but not limited to, protein engineering, protein-protein interactions, vaccine development, and cellular interactions. However, there are some limitations to use of flow cytometry techniques (Carter & Ormerod, 2000). The flow cytometer is a complex machine and requires skilful preparation and staining of cells. The electronic, fluidic, and optical systems of the flow cytometer need to be designed well. The choice of a light source will also determine if excitation levels are sufficient to produce fluorescence. Systematic errors are introduced when there is poor sample preparation. Staining should be specific and cell population should be alive, since dead cells will produce erroneous fluorescence especially when antibodies are used. Antibodies are taken up non-specifically by dead cells. pH and temperature control should be tight because drifts in these conditions will affect the emission of the fluorochromes, thereby affecting the reproducibility of results. Moreover, electronic and optical noise are also factors that affect the data (Carter & Ormerod, 2000). In some cases, flow cytometry is also less sensitive. Direct immunofluorescence measurement is more sensitive than flow cytometry (Uelinger, et al., 2008). A trait that is difficult to measure in single cells using several techniques is the difference between apoptosis and necrosis (Yasuhara, et al., 2003). The COMET assay was more consistent in identifying necrotic cells compared to flow cytometry. Flow cytometry was also not as sensitive as Fluorescence In Situ Hybridization and p57 immunostaining techniques in detecting products of conception (POC) (Kipp, et al., 2010). Although flow cytometry does not do well in a few analyses, it compares relatively well with chemiluminescence in estimating the cellular production of reactive oxygen species (ROS) in semen compared with flow cytometric measurements (Aziz, et al., 2010). With flow cytometry, it was possible to identify the contribution of the different cells in semen to global ROS production. Flow cytometry is also more sensitive in detection of some diseases. Bone marrow biopsy and flow cytometry were used to detect minimal residual disease (MRD) in patients in remission for chronic lymphocytic leukaemia. Flow cytometry was more sensitive and was able to detect MRD and predict the relapse of chronic lymphocytic leukaemia (Maloum, et al., 2006). Thus, for many applications, flow cytometry is a more viable option than the other techniques that employ fluorescence for detection. Word Count: 1071 REFERENCES 1. Anderson, N., Anderson, N., Haines, L., Hardie, D., Olafson, R., & Pearson, T. (2004). Mass spectrometric quantitation of peptides and proteins using Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA). Journal of Proteome Research, 3(2):235-44. 2. Andersson, L., & Porath, J. (1986 ). Isolation of phosphoproteins by immobilized metal (Fe3+) affinity chromatography. Analytical Biochemistry, 154(1):250-254 3. Aziz, N., Novotny, J., Oborna, I., Fingerova, H., Brezinova, J., & Svobodova, M. (2010). Comparison of chemiluminescence and flow cytometry in the estimation of reactive oxygen and nitrogen species in human semen. Fertility and Sterility, Retrieved from http://www.biomedsearch.com/nih/Comparison-chemiluminescence-flow-cytometry-in/20413114.html. 4. Beverly, L., & Varmus, H. (2009). MYC-induced myeloid leukemogenesis is accelerated by all six members of the anti-apoptotic BCL family. Oncogene , 28(9):1274-1279. 5. Caldwell, R., & Caprioli, R. (2005). Tissue profiling by mass spectrometry: a review of methodology and applications. Molecular and Cellular Proteomics, 4:394-401. 6. Carter, N., & Ormerod, M. (2000). Introduction to the principles of flow cytometry. In M. Ormerod, Flow Cytometry:Third Edition. A practical approach (276 pages). Oxford: Oxford University Press. 7. Djidja, M., Clause, E., Snel, M., Francese, S., Scriven, P., Carolan, V., et al. (2010). Novel molecular tumour classification using MALDI–mass spectrometry imaging of tissue micro-array. Analytical and Bioanalytical Chemistry, 397:587-601. 8. Dolezel, J., Greilhuber, J. L., Meister, A., Lysak, M., Nardi, L., & Obermayer, R. (1998). Plant genome size estimation by flow cytometry: interlaboratory comparison. Annals of Botany , 82(supp1):17-26. 9. El-Naggar, A., & Vielh, P. (2005). Solid tumor DNA content analysis. In T. Hawley, & R. Hawley (Eds.), Methods in Molecular Biology: Flow Cytometry Protocols (pp. 355-370). Totowa, New Jersey: Humana Press Inc. 10. Franck, J., Arafah, K., Elayed, M., Bonnel, D., Vergara, D., Jacquet, A., et al. (2009 ). MALDI imaging mass spectrometry: state of the art technology in clinical proteomics. Molecular and Cellular Proteomics, 8(9):2023. 11. Gates, P. (2004, January 24). Mass Spectrometry Resource. Retrieved December 22, 2010, from University of Bristol, School of Chemistry: http://www.chm.bris.ac.uk/ms/theory/maldi-ionisation.html 12. Gregson, C. (2009). Optimization of MALDI tissue imaging and correlation with immunohistochemistry in rat kidney sections. Bioscience Horizons, 2(2):134-146. 13. Groseclose, M., Massion, P., Chaurand, P., & Caprioli, R. (2008). High-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue microarrays using MALDI imaging mass spectrometry. Proteomics, 8(18):3715-3724. 14. Hillenkamp, F., & Katalinic, J. (2007). MALDI-MS: a practical guide to instrumentation, methods and applications. Weinheim: WILEY-VCH Verlag GmbH & Co. KGaA. 15. Huang, Q., Yu, C., Zhang, X., & Goyal, R. (2008). Comparison of DNA histograms by standard flow cytometry and image cytometry on sections in Barretts adenocarcinoma. BMC Clinical Pathology , 8:5-13. 16. Jensen, O., Shevchenko, A., & Mann, M. (1997). Protein analysis by mass spectrometry. In Protein Structure: A Practical Approach (pp. 29-58). New York: Oxford University Press. 17. Karas, M., Bachmann, D., & Hillenkamp, F. (1985). Influence of wavelength in high-irradiance ultraviolet laser desorption mass spectrometry of organic molecules. Analytical Chemistry, 57:2935-2939. 18. Kipp, B., Ketterling, R., Oberg, T., Cousin, M., Plagge, A., Wiktor, A., et al. (2010). Comparison of fluorescence in situ hybridization, p57 immunostaining, flow cytometry, and digital image analysis for diagnosing molar and nonmolar products of conception. American Society for Clinical Pathology, 133:196-204. 19. Maloum, K., Charlotte, F., Divine, M., Cazin, B., Lesty, C., & Merle-Beral, H. (2006). A comparison of the sensitivity of flow cytometry and bone marrow biopsy in the detection of minimal residual disease in chronic lymphocytic leukemia. Haematologica, 91(6):860-861. 20. McDonnel, L., & Heeren, R. (2007). Imaging mass spectrometry. Mass Spectrometry Reviews, 26: 606-643. 21. Parker, C., Pearson, T., Anderson, N., & Borchers, C. (2010). Mass-spectrometry-based clinical proteomics – a review and prospective. Analyst, 135(8):1830–1838. 22. Reid, J., Parker, C., & Borchers, C. (2007). Protein arrays for biomarker discovery. Current Opinion in Molecular Therapy, 9:216-221. 23. Sanders, M., Dias, E., Xu, B., Mobley, J., Billheimer, D., Roder, H., et al. (2008). Differentiating proteomic biomarkers in breast cancer by laser capture microdissection and MALDI-MS. Journal of Proteome Research, 7(4):1500-1507 . 24. Schwamborn, K., Krieg, R., Reska, M., Jakse, G., Knuechel, R., & Wellmann, A. (2007). Identifying prostate carcinoma by MALDI-Imaging. International Journal of Medicine, 20: 155-159. 25. Uelinger, F., Barkema, H., OHandley, R., Parenteau, M., Parrington, L., VanLeeuwen, J., et al. (2008). Comparison of flow cytometry and immunofluorescence microscopy for the detection of Giardia duodenalis in bovine fecal samples. Journal of Veterinary Diagnostic Investigation, 20(2):178-185. 26. Veenstra, T. (2007). Global and targeted quantitative proteomics for biomarker discovery. Journalof Chromatography B, 847(1):3-11. 27. Walch, A., Rauser, S., Deininger, S., & Hofler, H. (2008). MALDI imaging mass spectrometry for direct tissue analysis:a new frontier for molecular histology. Histochemistry and Cellular Biology, 130:421-434. 28. Weaver, J., & Stetler-Stevenson, M. (2005). Flow cytometry in the biomedical arena. In J. Walker, & R. Rapley (Eds.), Medical Biomethods Handbook (pp. 531-553). Totowa, New Jersey: Humana Press, Inc. 29. Xu, Y., McKenna, R., & Kroft, S. (2002). Comparison of multiparameter flow cytometry with cluster analysis and immunohistochemistry for the detection of CD10 in diffuse large B-cell lymphomas. Modern Pathology, 15(4):413-419. 30. Yasuhara, S., Zhu, Y., Matsui, T., Tipirneni, N., Yasuhara, Y., Kaneki, M., et al. (2003). Comparison of COMET assay, electron microscopy, and flow cytometry for detection of apoptosis. Journal of Histochemistry and Cytochemistry, 51(7):873-885. Read More