The urinary proteomics 7 4-2010
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THE URINARY PROTEOMICS:A TOOL TO DISCOVER NEW AND POTENT BIOMARKERS FOR KIDNEY DAMAGE
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The urinary proteomics 7 4-2010
- 1. THE URINARY PROTEOMICS:A TOOL TO DISCOVER NEW AND POTENT BIOMARKERS FOR KIDNEY DAMAGE By Prof. Moustafa Rizk Prof. of Clinical Pathology Faculty of Medicine, University of Alexandria Wednesday 07/04/2010 5:12 AM1
- 3. What is proteomics? Proteomics is the systematic study of proteomes, which describes the entire protein content of one or all cells of an organism as well as of bodily fluids such as blood, urine and sweat. While the genome of an organism is considered to be mostly static, the proteome shows dynamic properties with protein profiles changing depending on a variety of extra- and intracellular stimuli (i.e. cell cycle, temperature, differentiation, stress, apoptotic signals) 5:12 AM3
- 4. TYPES OF PROTEOMICS 1-Expression proteomics, : This is the qualitative and quantitative study of the expression of total proteins under two different conditions. For example, expression proteomics of normal cells and diseased cells can be compared to understand the protein that is responsible for the diseased state or the protein that is expressed due to disease. 3-Functional Proteomics:This is an assembly type of proteomic method to analyze and understand the properties of macromolecular networks involved in the life activities of a cell. 4-Clinical proteomics, a comparative approach of normal and abnormal status of cells, tissues or bodily fluids , is still a promising new analytic discipline with the following main aims: (i) discovery of biomarkers allowing early detection, risk management or therapeutic monitoring of diseases for the establishment of individualized treatment procedures. (ii) identification of protein targets for the development of new mechanistic intervention therapies with the promise of an improved clinical outcome. 5:12 AM4 2-Structural Proteomics:Structural proteomics, as the name indicates, is about the structural aspects, including the three- dimensional shape and structural complexities, of functional proteins
- 5. So a major goal in the field of clinical proteomics is to identify disease biomarkers in biological fluids that can be measured relatively inexpensively for early diagnosis of disease. 5:12 AM5
- 6. An important challenge in this process is to develop a rational means of reducing the complexity of the proteome of body-fluid samples to enhance the detectability of relatively low-abundance proteins that may have special pathophysiological significance. 5:12 AM6
- 7. Most of the focus thus far has been on proteomics of blood (serum or plasma) . Because urine can be collected noninvasively in large amounts, it provides an attractive alternative to blood plasma as a potential source of disease biomarkers . 5:12 AM7
- 8. The increasing number of patients suffering from chronic renal failure represents one of the major challenges which the nephrologists are facing worldwide. For a better therapeutic outcome of this disease, earlier detection is urgently warranted in routine clinical practice. 5:12 AM8
- 9. Origin of urinary proteins and peptides : 1- Glomerular filtration 2- Tubular secretion 3- Epithelial cells shed from the kidney and urinary tract 4- Secreted exosomes 5- Semen. 5:12 AM9
- 10. . Glomerular filtration Tubular reabsor. 5:12 AM10
- 11. Urinary exosomes containing apical membrane and intracellular fluid are normally secreted into the urine from all nephron segments, and may carry protein markers of renal dysfunction and structural injury. Derived from all cell types that face the urinary space including glomerular podocytes, renal tubule cells, and the cells lining the urinary drainage system 5:12 AM11
- 12. Process of exosome formation and release into the urine Hoorn, E. J., Pisitkun, T and Knepper, M. A. (2005) Prospects for urinary proteomics: exosomes as a source of urinary biomarkers. Nephrology (Carlton) 10, 283–290 1- Apical membrane proteins undergo endocytosis followed by targeting to the MVB. 2- The membrane proteins are segregated initially in the MVB outer membrane and then are internalized by membrane invagination, encapsulating cytosolic proteins in the process. 3- After accumulation of numerous internal vesicles, the outer membrane of the MVB fuses with the apical plasma membrane releasing its internal vesicles, called exosomes, into the urinary space. 4- Exosomes contain both membrane and cytosolic proteins. Multivesicular bodies 5:12 AM12
- 13. Urine sample collection, storage, and processing procedures for isolation of urinary exosomes Sample collection (protease inhibitor) solution (volume per 50 ml urine) 1.67 ml of 100 mM sodium azide (NaN3) 2.5 ml PMSF (2 mg/ml in isopropyl alcohol, stable 4°C for several months) 50 µl Leupeptin (1 mg/ml in ddH2O, stable 1 week at 4°C, 6 months at -20°C) Collection If possible, determine the collection time and volume. Collect the first or second morning urine, 10~100 ml . First morning urine: first urine after waking (no fluid or fruits after 9 PM the prior evening). Second morning urine: Discard the first urine. Collect the next voided urine. May have breakfast and undergo regular activity between first and second morning urine. Can also use random urine samples Storage Add sample collection (protease inhibitor) solution If possible, process samples immediately (refrigerate at 4 °C). If the urine samples cannot be processed immediately, the samples should be frozen at -80 °C (NOT -20 °C). 50 ml of urine samples are aliquoted in 50 ml tubes and stored at -80°C as soon as possible after collection. Defrosting and processing Frozen urine samples should be thawed at room temperature (requires 3 hrs for a 50 ml urine sample). Avoid prolonged thawing on ice (4 °C). While urine is defrosting (i.e., is still a mixture of ice and water), extensively and vigorously vortex for one minute. After sample completely thaws, vigorously vortex for an additional 30 sec, then proceed to differential centrifugation for urinary exosome isolation. Insufficient vortexing will result in major loss of urinary exosomes. 5:12 AM13
- 14. Classifications of exosomal identified proteins from renal epithelia 1 - Glomerular podocytes (podocin and podocalyxin) 2 - Proximal tubule (e.g., megalin, cubilin, APN, AQP1) 3 - Ascending limb of Henle (e.g., THP, CD9) 4 - Distal convoluted tubule (e.g., NCC), 5 - Collecting duct (e.g., AQP2, mucin-1, and the Rh type C ) 6 - Transitional epithelium of the urinary bladder ( uroplakin-1 and -2) Thus, proteomic analysis of urine can potentially provide insight into the physiological or pathophysiological processes in every epithelial cell type facing the urinary space. 5:12 AM14
- 15. Naturally occurring human urinary peptides and proteins Establishment of a high resolution proteome database ranging from 800–17,000 Da from over 3,600 individual samples using capillary electrophoresis coupled to mass spectrometry, yielding an average of 1,500 peptides per sample. All processed data were deposited in an SQL database, currently containing 5,010 relevant unique urinary peptides that serve as classifiers for diagnosis and monitoring of diseases, including kidney and vascular diseases. Of these, 352 have been sequenced to date. Nature Precedings : hdl:10101/npre.2007.1219.1 : Posted 11 Oct 2007 5:12 AM15
- 16. Nature Precedings : hdl:10101/npre.2007.1219.1 : Posted 11 Oct 2007 CE-MS data from 28 different pre-selected pathophysiological conditions 5:12 AM16
- 17. Distribution of native peptides identified with respect to their protein precursor (described by SwissProt protein name and gene symbol). Comparison of peptides to other references) A database of naturally occurring human urinary peptides and proteins for use in clinical applications Nature Precedings : hdl:10101/npre.2007.1219.1 : Posted 11 Oct 2007 5:12 AM17
- 18. HC=healthy control; CRD= chronic renal disease; MNGN=membranous glomerulonephritis; FSGS=focal segmental glomerulosclerosis; MCD=minimal change disease; SLE=systemic lupus erythematosus; IgAN=IgA nephropathy, DN=diabetic nephropathy; CAD=coronary artery disease; NTx=renal transplantation; LTx=liver transplantation; HSCT=hematopoietic stem cell transplantation; PTLD=post-transplant lymphoproliferative disorders; Fanconi=Fanconi’s syndrome; AD=Alzheimer’s disease; DM=diabetes mellitus. 5:12 AM18
- 19. HC=healthy control; CRD= chronic renal disease; MNGN=membranous glomerulonephritis; FSGS=focal segmental glomerulosclerosis; MCD=minimal change disease; SLE=systemic lupus erythematosus; IgAN=IgA nephropathy, DN=diabetic nephropathy; CAD=coronary artery disease; NTx=renal transplantation; LTx=liver transplantation; HSCT=hematopoietic stem cell transplantation; PTLD=post-transplant lymphoproliferative disorders; Fanconi=Fanconi’s syndrome; AD=Alzheimer’s disease; DM=diabetes mellitus. 5:12 AM19
- 20. Proteomics is increasingly used in the discovery of renal biomarkers mostly in: 1 - Cancer screening 2 - Glomerular diseases in native kidneys 3 - Acute rejection 4 - BK virus nephropathy as a complication in kidney transplants Early detection of graft rejection Specific new biomarker candidates for other renal disease detected by proteomic analysis 5- Predict the need for operation in newborns presenting with unilateral uretero-pelvic junction obstruction with high significance 5:12 AM20
- 21. Cancer screening 1- Renal cell carcinoma (RCC) is the sixth leading cause of cancer death and is responsible for 11,000 deaths per year in the US. 2- In this study, a comprehensive proteomic analysis to identify biological processes involved in clear cell RCC (ccRCC). 3- Urinary markers of RCC were investigated which could be applied to high-risk patients, or to those being followed for recurrence, for early diagnosis and treatment, thereby substantially reducing mortality of this disease. Pathway analysis of kidney cancer using proteomics and metabolic profiling.Bertrand Perroud, et al Mol Cancer. 2006; 5: 64. 5:12 AM21
- 22. Using 2-dimensional electrophoresis and mass spectrometric analysis, 31 proteins were identified which were differentially expressed with a high degree of significance in ccRCC as compared to adjacent non- malignant tissue, and some of these were confirmed by immunoblotting, immunohistochemistry, and comparison to published transcriptomic data. Pathway analysis of kidney cancer using proteomics and metabolic profiling.Bertrand Perroud, et al Mol Cancer. 2006; 5: 64. Blue : Underexpression Black: Equal expression Red : Overexpression 5:12 AM22
- 23. A highthroughput proteomic approach was applied to the evaluation of urine samples from type 2 diabetic patients and identified a protein profile that accurately predicted nephropathy in advance of an increase in albuminuria. These results warrant further studies to determine the applicability of this approach within other populations, and, more specifically, within other larger cohorts of diabetic patients with prospectively collected samples. Finally,further characterization and evaluation of the proteins in the biomarker profile are needed to demonstrate whether they are biologically important in the development of nephropathy. Prediction of Diabetic Nephropathy Using Urine Proteomic Profiling 10 Years Prior to Development of Nephropathy.Diabetes Care 30:638–643, 2007 5:12 AM23
- 24. 5:12 AM24
- 25. Detection of Acute Tubulointerstitial Rejection by Proteomic Analysis of Urinary Samples in Renal Transplant Recipients A distinct urinary polypeptide pattern identified 16 out of 17 cases of acute tubolointerstitial rejection, but was absent in two cases of vascular rejection. Urinary tract infection resulted in a different polypeptide pattern that allowed to differentiate between infection and acute rejection in all cases.. Detection of acute rejection by CE-MS offers a promising non-invasive tool for the surveillance of renal allograft recipients.. 5:12 AM25
- 26. Copyright restrictions may apply. Mosley, K. et al. Rheumatology 2006 45:1497-1504; doi:10.1093/rheumatology/kel351 Candidate biomarker discovery Urine samples from inactive (n= 49) and active (n= 26) lupus nephritis patients 5:12 AM26
- 27. Gel based and gel free proteomics methods in urinary proteome analyses: 5:12 AM27
- 28. Urine collection methods advantages and disadvantages for urine proteome analysis 5:12 AM28
- 29. Several methods have been used to search for biomarkers in urine samples: 1- Two-dimensional electrophoresis 2- Surface-enhanced laser desorption/ionization time- of-flight (SELDI-TOF) 3- Capillary electrophoresis. 4- Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) to identify -β2 microglobulin (B2M) in the urine as a potential biomarker in acute rejection for kidney transplant recipients. 5- Another method recently introduced is iTRAQ. (Multiplexed Isobaric Tagging Technology) 5:12 AM29
- 30. 5:12 AM30
- 31. Ionization Source Electrospray Ionisation (ESI) Matrix Assisted Laser Desorption Ionisation (MALDI) 5:12 AM31
- 32. Electrospray Ionization 5:12 AM32
- 33. Electrospray Ionisation (ESI) 5:12 AM33
- 35. ESI characteristics: 1. Soft ionization method 2. Provides molecular weight information. 3. Suitable for analyzing large bio- or synthetic polymers. 5:12 AM35
- 36. Matrix Assisted Laser Desorption Ionization 5:12 AM36
- 37. MALDI characteristics 1. Soft ionization method, so results predominantly in the generation of singly charged ions hence the spectra are relatively easy to interpret. 2. Provides molecular weight information. 3. MALDI deals well with thermolabile, non-volatile organic compounds especially those of high molecular mass 4. MALDI is used successfully for the analysis of proteins, peptides, glycoproteins, oligosaccharides, and oligonucleotides. 5:12 AM37
- 38. Types of Mass Analyzers • Sector Mass Analyzers • Time Of Flight (TOF) • Quadrupole • Quadrupole Ion Trap • Ion Cyclotron Resonance 5:12 AM38
- 39. 5:12 AM39
- 40. Time Of Flight Mass Analyzer 5:12 AM40
- 41. The firing of a laser at the sample / matrix mixture. Protein Chips SELDI- TOFhow_proteins_are_ionised_SELDI.pps 5:12 AM41
- 42. Quadrupole Mass Analyzer acts as a mass selective filter. 5:12 AM42
- 43. Quadrupole Ion Trap Mass Analyzer 5:12 AM43
- 44. Ion Cyclotron Resonance 5:12 AM44
- 45. FT Time domain signal Ion Cyclotron Resonance Mass Analyzer 5:12 AM45
- 48. What is a mass spectrum? Mass spectrum: graphic representation of ions separated according to their m/z ratio. It is a plot of relative abundance versus mass-to- charge ratio (mz). 5:12 AM48
- 50. Summary of the proteomic platforms used for urine analysis, their advantages and disadvantages. 5:12 AM50
- 51. Conclusion 1- The adequate diagnosis of complex diseases e.g., renal disease with a single biomarker seems to be an illusion. 2- A Multiple biomarker assay could deliver a better and a more individualized diagnosis and allow therapeutic strategies that delay or prevent the progression of the disease. 3- Due to many limitations and uncertainties, urinary proteomics at present cannot replace invasive standardized diagnostic procedures such as the renal biopsy, but holds great promise and potential for future highly improved diagnosis and care of the patient in nephrology. 5:12 AM51
- 52. www3.niddk.nih.gov THANK YOU Prof./ Moustafa rizk 30/04/09 5:12 AM52
- 53. Copyright restrictions may apply. Thongboonkerd, V. Nephrol. Dial. Transplant. 2010 25:11-16; doi:10.1093/ndt/gfp476 Schematic summary of methodologies and applications of renal and urinary proteomics 5:12 AM53
Editor's Notes
- DNA Basics.. Inside the nucleus, most of the DNA exists as a double helix.. The genetic information is stored in the sequences of nucleotide bases (A, T, G or C) that form the rungs of the ladder. Each rung is formed by a pair of nucleotide bases touching each other, one base attached to one strand backbone, and the other attached to the other strand backbone. An "A" nucleotide always pairs with a "T," and a "G" always pairs with a "C." In order to synthesize a protein, the cell reads the genetic information of the gene for that protein by "transcribing" a molecule of RNA from the gene. For transcription, the strands of the DNA double helix must partially separate so that the bases that form RNA can assemble according to the rules of complementary basepairing.. The transcribed strand of RNA acts as a "messenger" that carries the genetic information from storage in the nucleus to the protein manufacturing modules in the cytoplasm. The protein folds into a functional three-dimensional structure that depends on the linear sequence of amino acids. Proteins are large biological molecules made of subunits called amino acids that are attached to one another in chains, like the cars of a train. There are twenty different kinds of amino acids used in proteins, and most proteins contain hundreds of these subunits. Each protein has a specific number and sequence of amino acids, and this sequence determines what properties that protein will have. In order for a cell to synthesize a specific protein, it must access an "information bank" in which amino acid sequences are stored; this information bank is comprised of the organism's genes, which contain the amino acid sequences encoded in molecules of deoxyribonucleic acid (DNA). The identification of these targets should be carried out at the genomic, transcriptomic, proteomic and metabolomic level.
- What is Proteomics? In contrast, proteomics focuses on the identification, localization, and functional analysis of the protein make-up of the cell. The proteins present in a cell, together with their function, sub-cellular location, and perhaps even structure, change dramatically with the organism, and the conditions faced by their host cells including: age, checkpoint in the cell cycle, and external or internal signaling events. Thus, there are many proteomes for each organism and consequently, the quantity and complexity of the data derived from the sequencing and mapping of the human proteome are estimated to be at least three times greater than that involved in the human genome project. Acquiring, analyzing, and interpreting these vast data sets requires a series of well-integrated, high-throughput technologies to lead the researcher from experimental design to biological insight. The field of proteomics is particularly important because most diseases are manifested at the level of protein activity. Consequently, proteomics seeks to correlate directly the involvement of specific proteins, protein complexes and their modification status in a given disease state.Such knowledge will provide a fast track to commercialization and will speed up the identification of new drug targets that can be used to diagnose and treat diseases.
- Expression Proteomics: This is the qualitative and quantitative study of the expression of total proteins under two different conditions. For example, expression proteomics of normal cells and diseased cells can be compared to understand the protein that is responsible for the diseased state or the protein that is expressed due to disease. Using this method disease-specific protein can be identified and characterized by comparing the protein-expression profile of the entire proteome or of the subproteome between the two samples. For example, tumor tissue samples from a cancer patient and the same type of tissue from a normal person can be analyzed for differential protein expression. Using two-dimensional gel electrophoresis, mass spectrometry combined with chromatography and microarray techniques, additional proteins that are expressed in the cancer tissues or the proteins, which are absent, or those, which are over expressed and under-expressed can be identified and characterized. Identification of these proteins will give valuable information about the molecular biology of tumor formation. Structural Proteomics:Structural proteomics, as the name indicates, is about the structural aspects, including the three-dimensional shape and structural complexities, of functional proteins. This includes the structural prediction of a protein when its amino acid sequence is determined directly by sequencing or from the gene with a method called homology modeling. This can be carried out by doing a homology search and computational methods of protein structural studies and predictions. Apart from this, structural proteomics can map out the structure and function of protein complexes present in a specific cellular organelle. It is possible to identify all the proteins present in a complex system such as ribosomes, membranes, or other cellular organelles and to characterize or predict all the proteins and protein interactions that can be possible between these proteins and protein complexes. Structural proteomics of a specific organelle or protein complex can give information regarding supra-molecular assemblies and their molecular architecture in cells, organelles, and in molecular complexes. Functional Proteomics:This is an assembly type of proteomic method to analyze and understand the properties of macromolecular networks involved in the life activities of a cell. With these methods it will be possible to identify specific protein molecules and their role in individual metabolic activities and their contribution to the metabolic network that operates in the system. This forms one of the major objectives of functional proteomics. For example, the recent elucidation of the protein network involved in the functioning of a nuclear pore complex has led to the identification of novel proteins involved in the translocation of macromolecules between the cytoplasm and nucleus through these complex pores. Functional proteomics is yielding large databases of interacting proteins, and extensive pathway maps of these interactions are being scored and deciphered by novel high-throughput technologies. However, traditional methods of screening have not been very successful in identifying protein-protein interactionsand their inhibitors. The identification and measurement of changes in the concentration of specific proteins that cells make as a result of their genetic response to specific toxicants, and how these proteins are related to each other and to the specific biological condition of the cell, also fall under functional proteomics.
- Proteomics thus holds significant promise for the discovery of diagnostic or prognostic protein markers, for the detection of new therapeutic targets and as a powerful tool to further our understanding of basic biological processes and mechanisms. The subject, called targeted proteomics, therefore involves the integration of a number of technologies including the selective targeting of proteins with activities of interest, multi-step sample preparation, and mass spectrometry. Examining changes in these proteins within cells under different physiological conditions will offer insights into understanding cellular and molecular mechanisms that cannot currently be obtained through traditional biological studies that usually focus on the detailed analysis of individual biomolecules.
- Profiling of these thousands of proteins and peptides (polypeptides) using high resolution capillary electrophoresis coupled mass spectrometry (CE-MS) allows better understanding and in depth diagnosis of most known diseases. We have established a proteomic database of human urinary polypeptides. This library can be used as a rich source of biomarkers for a wide range of diseases. More than 3,300 urine samples were analysed CE-MS, yielding an average of 1,500 polypeptides per sample. All these CE-MS data were processed to identify and quantify individual peptides. The resulting database currently contains 4,954 different urinary peptides that can be used to build robust classifier models for diagnosis, stratification, and monitoring of a wide range of diseases, such as prostate and bladder cancer as well as kidney and vascular diseases. Two-dimensional gel electrophoresis is a powerful and widely used method for the analysis of complex protein mixtures extracted from cells, tissues or biological fluids. This technique permits separation and characterization of proteins according to their charge/ion strength and molecular weight, in two consecutive gel electrophoresis steps: proteins are first separated by isoelectric focussing, according to their isoelectric points and then distinguished according to their molecular weights in SDS-polyacrylamide gel electrophoresis. 2-D gel-electrophoresis is generally labour- and time-intensive and without strict standardization in the applied reagents, apparatus and software for the analysis usually not routinely applicable in clinical settings. Gel-free proteome analysis Reduced sample requirement, high throughput and automation are also important conditions for the integration of proteomics in routine laboratories. For this reason, different methods have been developed, which effectively couple high-end mass spectrometry to array formats, to capillary electrophoresis or to chromatography. The surface-enhanced laser desorption/ionization (SELDI) technique offers such an opportunity for urine analysis. Small amounts of native urine samples can be applied to the surface of a SELDI ProteinChip without prior concentration or precipitation of the urinary proteins . The bound proteins may then be directly analysed by MALDI-TOF-MS . Also CE-MS coupled the high-resolution properties of capillary electrophoresis (CE) with the powerful identification ability of the electrospray time-of-flight MS to profile and sequence urinary proteins. Liquid chromatography coupled to mass spectrometry (LC-MS) also offers a gel-free alternative for sensitive urine proteome analysis. Thus, protein profiles or single identified proteins may be characterized as disease-specific protein pattern or biomarkers which, however, must be validated in controlled retro- and prospective clinical studies.
- The use of urinary biomarkers to diagnose disease is a long-standing practice. Ancient clinicians detected glucose in the urine by tasting it or observing whether it attracted ants.The presence of albumin in the urine has been measured as an indicator of renal disease for centuries and in early times could be detected via the so-called “foam test” to determine whether albumin was present in the urine in large amounts. Even today clinicians frequently shake a urine sample to determine whether it develops a froth, prima facie evidence for a high level of protein, which often is indicative of glomerular disease. In that tradition, studies to identify biomarkers of disease in the urine have been an underlying component of investigative medicine throughout the 20th century and the early 21st century. These studies have been based on knowledge of the pathophysiology of disease to identify putative biomarkers that could be tested in clinical trials.
- Origin of urine proteins: in the urinary system high molecular weight proteins (> 40 kDa) are hold back in the glomerular part, whereas the low molecular weight proteins are absorbed in tubulus. Glomerular proteinuria led to increased release of high molecular weight proteins and tubular proteinuria is characterized by high excretion of low molecular weight proteins.
- Recently, exosomes containing both membrane and cytosolic proteins were isolated from normal human urine by differential centrifugation, and exosomal proteins related to kidney diseases were identified by LC-MS/MS . Exosomal protein biomarkers might be clinically useful biomarkers; Du Cheyron et al reported that NHE3, a membrane protein increased in acute tubule necrosis (ATN) patients but not in prerenal azotemia or acute glomerular diseases . We thought that this urinary compartment, containing a reduced protein complexity and depleted predominant proteins, might be used for biomarker discovery, particularly for proteins that might indicate structural renal disease.In present study, Fetuin-A was located in the cytoplasm of damaged proximal tubules that were attached on the basement membrane and at even higher concentration in proximal tubule cells that had detached from the tubule basement membrane. While exosomal Fetuin-A may be synthesized by the kidney, it may also appear in the urine as result of incomplete proximal tubule processing in proteinuria states (a form of overflow proteinuria) or released during tubular cell apoptosis.
- Capillary electrophoresis coupled to mass spectrometry (CE-MS) enables reproducible and robust high-resolution analysis of several thousand low-molecular-weight urinary proteins/ peptides in less than an hour 1. This approach has been used to analyze urine samples from healthy volunteers and patients with various diseases. The high number of datasets analyzed using identical conditions on the same instruments allows the establishment of a low-molecular-weight proteome database that can serve as a basis for the diagnosis, classification, and monitoring of a wide range of diseases using proteome analysis. The data were evaluated using Mosaiques Visu26 resulting in a list of peptides/proteins defined by mass, migration time, and ion-counts, serving as a measure of relative abundance. Different charge states of identical peptides/proteins were combined and included as a single identification in the database. A list of tentatively identified peptides of any sample is obtained and subsequently calibrated using “internal standards”, peptides generally present in urine. This allows the digital compilation of individual datasets into a specific “disease group” that can be compared to any desired “control group”, enabling the identification of statistically significant changes that result in the definition of potential biomarkers. Only datasets that fulfilled all quality control criteria were subsequently utilized and included in the database,which currently includes CE-MS data from 28 different pre-selected pathophysiological conditions .
- All urine samples were prepared identically and analyzed by CE-MS analysis, using identical instruments. Analysis resulted in individual data sets containing information on generally 1,200-2,000 peptides and proteins per sample. All information recommended by the “minimum information about proteomics experiments” (MIAPE) guidelines about proteome analysis using CE and MS is recorded, and available upon request. The data were evaluated using MosaiquesVisu , resulting in a list of peptides/proteins defined by mass, migration time, and ion-counts, serving as a measure of relative abundance. Different charge states of identical peptides/proteins were combined and included as a single identification in the database. A list of tentatively identified peptides of any sample is obtained and subsequently calibrated using “internal standards”, peptides generally present in urine. This allows the digital compilation of individual datasets into a specific “disease group” that can be compared to any desired “control group”, enabling the identification of statistically significant changes that result in the definition of potential biomarkers. Only datasets that fulfilled all quality control criteria were subsequently utilized and included in the database, which currently includes CE-MS data from 28 different pre-selected pathophysiological conditions .
- All detected peptides and proteins in the 3,687 human urine samples that passed all quality control criteria (on average, 1,724 peptides/proteins were detected in each individual urine sample, ranging from 983 to 4,094) were deposited in a Microsoft SQL database and subsequently matched for further analysis and comparison of individual samples. This process resulted in the definition of 116,869 different peptides and proteins. Each peptide was assigned a unique identification number (Protein ID). As described Previously, several of these peptides appeared sporadically, being observed in only one or a few samples. To eliminate such peptides of apparently low significance, only those present in more than 20% of the urine samples in at least one group (samples from patients with same disease) were further investigated. This noise-filtering process reduced the number of peptides available for analysis significantly: applying these limits, 5,010 “relevant” different peptides characterized by molecular mass [Da] and normalized CE migration time [min] could be detected.
- Table 2: Compendium of all patients and healthy controls of the human urinary proteome database, which were used for the establishment of training- and test-sets. Additionally, all sensitivities and specificities including their confidence interval are shown.
- A), the low molecular weight range between 4500 and 7000 Da in 10 urine samples from each studied group (10 from DM-NP, 10 from DM-WNP, and 10 from WDM-NP patients and 10 from healthy controls) illustrated in gel view in the left panel. The mass peak with m/z 6188 differentiating DM-NP from the other groups is highlighted with the box. The right panel indicates the mass spectral view from the same mass peak. (B), gel view from the middle molecular weight range, 10 000–18 000. Boxes indicate the peak masses m/z 11 774 and 14 766 found to be differentially excreted in DM-NP patient urines.
- Gel based and gel free proteomics methods in urinary proteome analyses: Gel based urine analysis using 2D gel electrophoresis proteins will be separated according to their masses and pIs. After in-gel enzymatic digestion of the proteins the tryptic product can be analyzed by mass spectrometry. The identification can be performed by data bank search. Gel-free urinary proteome analysis. ProteinChip coupled to MALDI-TOF-MS (SELDI-TOF-MS) technology. Different types of ProteinChip surfaces are available. The chips are spotted with different chromatographic surfaces for urine protein binding. Bound proteins are then ionized with mass spectrometry resulting in protein profiles. CE-MS coupled the high-resolution properties of capillary electrophoresis (CE) and the powerful identification ability of the electrospray time-of-flight MS to profile urinary proteins. The resulting protein pattern can be used for diseases discrimination. Liquid chromatography coupled to mass spectrometry (LC-MS) offers also a gel free alternative for urine proteome analysis. Dihazi et al. (11)
- During standard electrospray ionisation, the sample is dissolved in a polar, volatile solvent and pumped through a stainless steel capillary. A high voltage of 3 or 4 kV is applied to the tip of the capillary, and as a consequence of this strong electric field, the sample is dispersed into an aerosol of highly charged droplets, a process that is aided by a nebulising gas flowing around the outside of the capillary. This gas, usually nitrogen, helps to direct the spray emerging from the capillary tip towards the mass spectrometer.
- The charged droplets diminish in size by solvent evaporation, assisted by a warm flow of nitrogen known as the drying gas which passes across the front of the ionisation source. Eventually charged sample ions, free from solvent, are released from the droplets, some of which pass through a sampling cone or orifice into the analyser of the mass spectrometer.
- This is the electrospray needle –This is the orifice plate, with the tiny one millimetre central hole through which the test sample passes. .
- MALDI is based on the bombardment of sample molecules with a laser light to bring about sample ionisation. The sample is pre-mixed with a highly absorbing matrix compound and dried on plate. The matrix transforms the laser energy into excitation energy for the sample, which leads to sample ionization. In this way energy transfer is efficient and in the mean time the sample molecules are spared excessive direct energy that may otherwise cause decomposition.
- Sector analyzers uses an electromagnet to deflect ions that are flying through the mass analyzer. Deflection is dependent on their mass-to-charge ratios, deflecting the more charged & lighter ions more. Only ions of specific m/z ratio are capaple of reaching the detector ond are represented in the mass spectrum. Sector instruments have higher resolution and greater mass range than quadrupole instruments, but require larger vacuum pumps and often scan more slowly
- Time-of-flight (TOF) analyzer uses an electric field to accelerate the ions in the fligt tube through the same potential, and then measures the time they take to reach the detector. If the particles all have the same charge, then their velocities will depend only on their masses. Lighter ions will reach the detector first. This requires that the starting time (the time at which the ions leave the ion source) is well defined. Therefore ions are either formed by pulsed ionization method (MALDI). Properties of ToF analyzers: - very simple by using fixed voltages and not requiring a magnetic field - drawback of poor mass resolution, less then 500 - very high transmission efficiencies,
- Quadrupole mass analyzer consists of four parallel poles or rods. Mass sorting depends on ion motion resulting from simultaneously applied constant and radiofrequency potentials on the Quadrupole rods which can be set to pass only a selected m/z ratio. All other ions do not have a stable transit through quadrupole mass analyzer and will colloide with the rods, never reaching the detector. Analysis is accomplished by systemically changing the field strength thereby changing m/z transmitted through the analyzer. A quadrupole mass analyzer acts as a mass selective filter.
- The quadrupole ion trap works on the same physical principles as the QMS, but the ions are trapped and sequentially ejected. Ions are trapped in a three-dimensional quadrupole ion storage device. For detection of the ions, the RF and DC potentials are gradually altered resulting in ejection of the ions in order of increasing m/z. (mass-selective ejection). This 'stream' of ions is focussed onto the detector of the instrument to produce the mass Recently developed mass analyzer with special capabilities - Sensitive - Relatively inexpensive - fast scan rates
- Ions characterized by a specific mass-to-charge ratio and affected by a magnetic field move in a circular path at a given cyclotron frequency which is mass dependent. By applying a radio-frequency voltage at the same frequency as the cyclotron frequency, the ions absorb energy and are accelerated to larger cyclotron radius When the rf signal is terminated, the cyclotron radius remains at its larger state. This phenomenon provides the basis for ion cyclotron resonance mass spectrometry because ions having a different cyclotron frequency are not accelerated.
- When the radio-frequency current is turned off, each packet of ions of a specific m/q induces an image current that is detected by a pair of electrodes in the analyzer cell. At this larger orbit, they come close to the electrodes to induce a signal The decay over time of the image current is transformed from the time domain into a frequency domain signal by a Fourier transform. FT-ICR having the highest recorded mass resolution of all mass spectrometers. - very expensive, typically for specialized research applications
- ion beam hits a conversion dynode (made of semiconductor material) - electrons released, accelerated to next dynode - intensifying cascade of 106-108 fold An electron multiplier (continuous dynode electron multiplier) is a vacuum-tube structure that multiplies incident charges. In a process called secondary emission, a single electron can, when bombarded on metal (or PbO coated surface) induce emission of roughly 1 to 3 electrons. If an electric potential is applied between this metal plate and yet another, the emitted electrons will accelerate to the next metal plate and induce secondary emission of still more electrons. This can be repeated a number of times, resulting in a large shower of electrons all collected by a metal anode.
- The output of the mass spectrometer shows a plot of relative intensity vs the mass-to charge ratio (m/z). The most intense peak in the spectrum is termed the base peak and all others are reported relative to it's intensity. The peaks themselves are typically very sharp, and are often simply represented as vertical lines. The process of fragmentation follows simple and predictable chemical pathways and the ions which are formed will reflect the most stable cations and radical cations which that molecule can form. The highest molecular weight peak observed in a spectrum will typically represent the parent molecule, minus an electron, and is termed the molecular ion (M+).
- The m/z values of the ions are plotted against their intensities to show the number of components in the sample, the molecular mass of each component, and the relative abundance of the various components in the sample.
- The following diagram displays the mass spectra of three simple gaseous compounds, carbon dioxide, propane and cyclopropane. The molecules of these compounds are similar in size, CO2 and propane both have the same mass of 44 amu, and cyclopropane has a mass of 42 amu. Even though these compounds are very similar in molecular mass, it is a simple matter to identify them from their individual mass spectra.