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ScienceWeek
MEDICAL BIOLOGY: ON CLINICAL PROTEOMICS
The following points are made by L.A. Liotta et al (Nature 2003 425:905):
1) The blood contains a treasure trove of previously unstudied biomarkers that could reflect the ongoing physiologic state of all tissues. Every cell in the body leaves a record of its physiological state in the products it sheds to the blood, either as waste or as signals to neighboring cells. What some may view as a cellular refuse is really a diagnostic gold mine.
2) Routine laboratory blood tests sample only a minute fraction of this potential repository, and there are few specific markers for life-threatening diseases such as cancer. The current biomarker repertoire cannot detect treatable early-stage cancer and often misclassifies common benign conditions. In the face of the urgent need for better disease markers, it is unfortunate that the number of new markers submitted for regulatory approval has virtually dried up.
3) It is time to rethink our approach to biomarker discovery. The quest for a single biomarker for a particular disease has the illusion of analytical simplicity, but makes little sense from a biological perspective. For example, cancer is caused by intrinsically deranged cells of the host -- not an external infectious agent. Why should we expect the cancer cell to generate a unique new protein? It is not surprising that we have failed to find an accurate single marker for a disease as heterogeneous as cancer, which comes in hundreds of types and stages and is a product of the tumour-host microenvironment. Instead, why not take advantage of the very complexity of the disease? Genomics researchers have moved beyond one-gene-at-a-time analysis, and are profiling thousands of gene transcripts to generate entire patterns of information. We should be doing the same with protein biomarkers.
4) The relative cellular abundance of tens of thousands of different proteins, along with their cleaved or modified forms, is a reflection of ongoing physiological and pathological events. For example, cells that succumb to programmed cell death will leave behind a different protein signature from cells dying of oxygen starvation or infectious insult. As tissues are perfused by blood and lymph, proteins and protein fragments passively or actively enter the circulation. Thus, the complex chemistry of the tumour-host microenvironment should generate unique signatures in the blood macroenvironment.
5) The serum proteome is a complex mixture predominated by high-abundance resident proteins, such as albumin and other carrier proteins, together with proteins that originate from circulating blood cells. Although proteins entering the blood from the surrounding tissue are much less abundant, it is this fraction that is likely to contain most of the undiscovered biomarkers.(1-5)
References (abridged):
1. Anderson, N. L. & Anderson, N. G. Mol. Cell Proteom. 1, 845-867 (2002)
2. Petricoin, E. F. et al. Lancet 359, 572-577 (2002)
3. Tirumalai, R. et al. Mol. Cell Proteom. 2, 1096-1103 (2003)
4. Liu, J. & Ferrari, M. Dis. Markers 18, 175-183 (2002)
5. Mehta, A. et al. Dis. Markers 19, 1-10 (2003)
Nature http://www.nature.com/nature
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ON PROTEOMICS
The following points are made by Ruedi Aebersold (Nature 2003 422:115):
1) One of the most striking results obtained from completed genome sequencing projects is the knowledge of the precise number of genes in the genome of a species. Although the number of genes ana lysed to date is relatively small -- ranging from a few hundred for bacteria to tens of thousands for mammalian species -- the number of possible products encoded by these genes is much higher. In particular, the number of encoded proteins is enormous, as the same gene can generate multiple protein products that differ as a result of combinatorial splicing, processing and modification.
2) Given a species, as the universe of its biological processes and the molecules that constitute these processes is finite and knowable, there are several important consequences for experimental biology. First, even the most complex biological phenomena such as development, differentiation, metabolism and memory will be explained using known genes, their products and their interplay with the external conditions that the organism encounters. Second, projects to discover genes and their products in a species have defined end points. So far, although this end point has been reached only for gene discovery (sequencing), at some point in the future all of the gene products of a species --including messenger RNA and proteins -- will also be comprehensively described. Third, once all the possible molecules and activities within a species have been discovered and described, biological experimentation will be transformed from a discovery mode of identifying and describing molecules, to a "browsing" mode, in which the universe of possible events is searched to find constellations that correlate with a particular state or function. Genomics-style biology can therefore be separated into two distinct phases: a discovery phase to characterize the universe; and a browsing phase, in which system-wide biological assays navigate the universe.
3) Proteins are involved in all biological processes and can therefore be considered the functionally most important biological molecules. They are also particularly rich in biological information. In addition to the amino-acid sequence defining a protein, protein properties such as the amount of a protein expressed, its specific activity, state of modification and association with other proteins or molecules of different types are crucial for the description of biological systems. The systematic identification and characterization of proteins, called "proteomics", carries with it huge expectations, such as diagnostic and prognostic markers in blood serum and other body fluids; targets for pharmaceutical drugs; and improving the knowledge of fundamental biological processes. Hence the development of technologies to search the "proteome" routinely and systematically would be a significant achievement.
4) Unfortunately, the same properties that make proteins information-rich also significantly complicate their experimental analysis. There is no experimental platform, even under development, to systematically measure the diverse properties of proteins at high throughput.
Nature http://www.nature.com/nature
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PROTEOMICS: ON COMPUTER SIMULATIONS OF LIVING SYSTEMS
The following points are made by Julian P. Whitelegge (Proc. Nat. Acad. Sci. 2002 99:11564):
1) While the genome contains the coded information that allows an organism to live and reproduce, the essential functions of living cells are accomplished by gene products. Those structures --mainly proteins, although ribonucleic acids are also essential --provide the scaffold, regulatory, and catalytic functions that drive metabolism. Proteomics seeks to measure the expression of all proteins within an organism and monitor changes in response to developmental and environmental cues in health and disease. Because the 30,000 or so human genes sustain life through a considerably larger variety of mature proteins, the technological challenge dramatically exceeds that of genomics. Ultimately, we would like a computer model that mimics life "in silico", allowing accurate projections for metabolic engineering experiments in medicine and the life sciences. This grand experiment is just starting and the race is on to develop high-throughput technology to provide proteome-scale insights, as well as computational systems that allow realistic modeling of simple cells.(1)
2) A central facet of proteomics is the matching of protein data to a corresponding gene providing a direct readout of expression for functional genomics, as opposed to inferences drawn from measurements of messenger RNA that can be misleading, as well as allowing for the measurement of posttranslational modifications. Rapid advances in mass spectrometry technology have driven proteomics to what is clearly the most dramatically expanding arena in the life sciences today. The recent 50th annual meeting of the American Society for Mass Spectrometry (www.asms.org) featured a number of new proteomics sessions to accommodate this interest. Accurate measurement of peptide masses and tandem mass spectrometry (MS-MS) experiments that produce peptide sequence data allow correlation with genomic data using software that translates genes and calculates peptide mass and/or fragment mass data. Measurement of intact protein masses is insufficient to allow assignment of all proteins (2), and thus enzymatic (trypsin) or chemical (CNBr) cleavage is used to break, in a sequence-dependent fashion, whole gene products into manageable pieces, some of which completely match a portion of a translated gene. Early proteomics studies relied on separation of proteins by two-dimensional (2D) gel electrophoresis, for example, followed by identification of individual protein spots after excision from the gel, cleavage reactions, extraction of peptides, and mass spectrometry with database searches (3-5). More recently, others have pioneered a "shotgun" approach whereby whole-cell protein extracts are immediately cleaved and the peptide mixture subjected to separation before mass spectrometry to generate peptide sequence data. Multidimensional chromatography is used to enhance fractionation of the complex peptide mixture from a whole-cell digest, giving rise to the "MudPIT" acronym (Multidimensional Protein Identification Technology). Koller et al.(1) compare the 2D-gel approach to MudPIT, demonstrating the superior detection efficiency of the latter technique, while confirming the complementary nature of the methods.
References (abridged):
1. Koller, A. , Washburn, M. P. , Lange, B. M. , Andon, N. L. , Deciu, C. , Haynes, P. A. , Hays, L. , Schieltz, D. , Ulaszek, R., Wei, J. , et al. (2002) Proc. Natl. Acad. Sci. USA 99, 11969-11974.
2. Gomez, S. M. , Nishio, J. N. , Faull, K. F. & Whitelegge, J. P. (2002) Mol. Cell. Proteomics 1, 45-59.
3. Henzel, W. J. , Billeci, T. M. , Stults, J. T , Wong, S. C. , Grimley, C. & Watanabe, C. (1993) Proc. Natl. Acad. Sci. USA 190, 5011-5015.
4. James, P. , Quadroni, M. , Carafoli, E. & Gonnet, G. (1993) Biochem. Biophys. Res. Commun. 195, 58-64.
5. Mann, M. , Hojrup, P. & Roepstorff, P. (1993) Biol. Mass Spectrom. 22, 338-345.
Proc. Nat. Acad. Sci. http://www.pnas.org
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