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Editorial |
1 Department of Clinical Biochemistry, Cambridge University Teaching Hospitals, Addenbrooke"s Hospital, Cambridge, United Kingdom
2 Ludwig Institute for Cancer Research, and Department of Biochemistry and Molecular Biology, University College, London, United Kingdom
3 Centre for Nephrology and Department of Physiology, Royal Free and University, College Medical School, London, United Kingdom
aAddress correspondence to this author at: Box 232, Hills Road, Cambridge CB2 2QR, United Kingdom. E-mail agwn2{at}cam.ac.uk.
The "urinary peptidome" promises to be a resource at least as dynamic and informative as the "urinary proteome". Given that neither approach has so far given up many clinical pearls, this may not be saying much. But one likely pathway for urinary peptidomics is set out in the paper by Fiedler et al. (1) in this issue of Clinical Chemistry. These workers have combined high-throughput technology with a study of the basic problems that will need to be overcome to transform a promising approach into something more durable. Although they are not the first to use some of the techniques (2)(3), and although numerous problems remain, this study is required reading for all those interested in this area.
Urine, as a matrix, must be one of the least desirable biological fluids for both peptidomic and proteomic work. It is important to recall some basic biology: The composition of urine is by its design highly variable. Indeed the variability of its composition is a major way in which the "milieu interieur" is kept more or less constant in the face of environmental and nutritional changes. Urine volume, salt composition and pH can, and do, vary widely in health. In disease there is frequently proteinuria and, if that were not enough, urine is often infected even in apparently healthy individuals. Having said that, urine is also the source of one of clinical chemistry’s oldest chemical biomarkers: Bence Jones protein.
The urinary peptidome and indeed the urinary proteome are, to some extent "subtractive" (4). The filtered plasma "peptidome" is normally processed by the proximal renal tubule. The proximal tubule removes substantial but ill-defined amounts of peptides and proteins from the filtrate. When this process is ineffective, as in the renal Fanconi syndromes, very large quantities of plasma peptides are found in urine (5). It is what is left of the filtrate after proximal tubular processing, perhaps after even further processing, that we actually measure in urine when proximal tubular processing is intact. Although we do not have a full description of the range and efficiency of reabsorption of peptides by the normal tubule, urine from patients with normal renal function might also be an attractive specimen for peptide analysis for the following reason: It may be relatively enriched with peptides compared to albumin since the latter are hardly filtered by the normal renal glomerulus.
The urinary peptidome is likely to provide information that is qualitatively different from the proteome for at least 2 reasons: Urinary peptides will be derived in part from the highly dynamic plasma peptidome, which in turn partly reflects minute-by-minute endocrine function. There exists a dynamic intratubular peptidome with peptides both released and acting locally within the tubule (6). The latter is still poorly understood and current peptidomic techniques are probably too insensitive to sample these adequately in urine. It is worth remembering that we already have some urinary peptide biomarkers of disease, none clinically brilliant and none discovered by a peptidomic approach. These include urinary telopeptides as markers of collagen turnover (7). Identification of such known biomarkers could help validate particular peptidomic approaches as part of "proof-of-principle" studies.
To use urine as a source of reliable peptide biomarkers in disease, Fiedler et al. (1) have begun to define how variables within urine itself ("endogenous variables" in their terminology), such as salt composition and pH, influence peptide recoveries. They have also examined how sample-processing variables ("exogenous variables"), such as freeze-thaw cycles, affect results. They have developed the use of highly automated, microscale, solid-phase adsorption on hydrophobic, metal-ion, or ion-exchange beads and followed this with fairly conventional matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Their findings are revealing: A single freeze-thaw cycle produced dramatic changes in the intensity of several urinary peptides. In fact, most of the endogenous and exogenous variables they examined altered peptide ion intensities. By careful selection of these variables, their effects have been reduced and the work-up of urine been made reproducible.
Unfortunately all experimental findings by Fiedler et al. are defined by the small subset of peptides examined, fewer than 10 from an overall set of some 427, which itself must represent only a subset of the overall peptidome. This brings us to 3 outstanding problems: (a) As is the case for proteins, the range of peptide concentrations in urine spans several orders of magnitude (8); (b) we still cannot quantify most of the peptides; and (c) beyond their mass measurement, we do not know their structure (3). Of course, some might argue that knowledge of the structures does not matter provided there are reproducible differences in signals between disease states and healthy individuals. Lack of such knowledge makes validation more difficult because there is no physiological hypothesis to help give confidence in findings. Furthermore, few peptide biomarkers are likely to be "all-or-none". We need calibration curves to express ion intensities in molar terms. This will not be easy but there are already several competing technologies in proteomics. Clearly, robust bioinformatics are needed to exploit urine as a potentially rich source of information, as exemplified by other work that has used similar peptidomic technology with apparent success (3).
A significant potential difficulty that Fiedler et al. do not deal with is the presence of large quantities of uromodulin ("Tamm-Horsfall protein") in urine (9). Indeed uromodulin is the major single protein in healthy urine. The problem is that, depending on salts and pH, uromodulin forms fibrils that form sediment in low g conditions; this matters because uromodulin is known to bind several low–molecular-weight proteins and, by implication, plasma peptides that enter the tubular filtrate.
For the moment Fiedler et al. have quite reasonably side-stepped the above problems of detection and (to some extent) quantification. This is significant because after some apparent initial success and excitement caused by studies using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) as a diagnostic tool, clinical proteomics has come in for criticism (10), partly because some of the techniques employed had not been tested rigorously. With their meticulous study Fiedler et al. seem to be taking on board the lessons learned from this early proteomic work. To use Check’s analogy (11), it reminds the clinical community that before starting to run we need to learn to walk. For the clinical peptidomic and proteomic dreams to come true we must first face and solve some tough biotechnological (not yet medical) challenges. Whether the approach used by Fiedler et al. is the definitive answer remains to be seen; it is likely that there will be several depending on the questions being asked, but first we need this sort of study to show us at least one route. Jurgens et al. (12) have offered a different method to address some of the problems of complexity and dynamic range. Each approach will have to be reproducible in the face of the highly variable matrix presented by urine and the additional variation imposed by sample processing. Then we can face the medical challenges.
References
The following articles in journals at HighWire Press have cited this article:
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  L. F. Quintana, J. M. Campistol, M. P. Alcolea, E. Banon-Maneus, A. Sol-Gonzalez, and P. R. Cutillas Application of Label-free Quantitative Peptidomics for the Identification of Urinary Biomarkers of Kidney Chronic Allograft Dysfunction Mol. Cell. Proteomics, July 1, 2009; 8(7): 1658 - 1673. [Abstract] [Full Text] [PDF]
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