REVIEW ARTICLE / HEMATOPOIESIS

The completion of the human genome project and the availability of highly sensitive and accurate mass spectrometers have led to the ongoing proteomics revolution. The proteome represents the population of proteins, whereas the transcriptome describes the population of mRNAs expressed by a cell or tissue. Unlike the genome, the compositions of the proteome and the transcriptome dynamically change with the developmental, hyperplastic, or neoplastic state of the cell. Proteome analysis requires separation of proteins before their identification and characterization. The performance of the analysis depends on the amount of sample protein available and the protein separation technology. Cristea and colleagues (page 3624) in this issue of Blood present a review of the proteomics techniques with emphasis on quantitative proteomics.

The capability to monitor differential expression of a gene product, either at the transcript level or protein level, remains at the heart of physiologic genomics/proteomics. Whereas the transcriptome techniques easily lend themselves to relative quantitation of transcript levels, the proteomics techniques are neither as simple nor as dependable. Also in this issue, Evans and colleagues (page 3751) report on the application of one of the quantitative proteomic techniques for a comparative analysis of hematopoietic stem cell populations. As the authors indicate, their analysis was hampered by the amount of sample protein available, demonstrating one of the still existing fundamental difficulties in applying proteomics to address physiologic questions.

Proteomic and transcriptomic approaches to gene expression analysis each have advantages and disadvantages. Unlike the transcriptomic chip technologies, the proteomic technologies (such as 2-dimensional polyacrylamide gel electrophoresis [2-DE] and isotope-coded affinity tagging [ICAT] in conjunction with mass spectrometry) are not limited to proteins etched on any chip (provided one has a sufficient sample to study) and allow identification of virtually any protein that is detectable (either previously known or unknown). More importantly, the posttranslational modifications (eg, phosphorylation) that may be central to the understanding of gene function are amenable only to investigation by proteomics. Cellular heterogeneity could potentially complicate the interpretation of results generated using either approach. Existing proteomics technologies do not allow analysis at the single-cell level because of the relatively high sample loads required. The advantages of the microarray approach on the other hand are as follows: (1) it is user-friendly; (2) it does not appear to have the problems associated with the core proteomics technology (ie, 2-DE); and (3) most important, as we have recently shown, it facilitates analysis even at the level of single cells.1  One additional issue is that the correlation between transcriptome and proteome has been known to be poor. The discrepancies are usually explained as due to (1) differences in half-lives of transcripts versus proteins, and (2) differences in the sensitivity of the technology used for detection of the respective gene products. It is also important to recognize that some of these discrepancies may be real, in the sense that they may be intrinsic to the biology of the cell type being investigated. Consequently, such discrepancies could be even greater in stem or progenitor cells in which multiple lineage pathways are simultaneously open at the transcriptional level but not necessarily so at the proteome level.1  The transcriptome and proteome analyses of a particular cell type may be revealing complementary stories.

Finally, it may help to mention a few cautionary observations relevant to clinical and postdoctoral fellows in hematology. Because proteomic studies are expensive and fairly complex in terms of the numerous sequential technical choices required, it may not be wise to embark upon a proteomics project without the commitment of adequate time, effort, and resources, and a clear working hypothesis. In any event, to assure the uninitiated reader, proteome science is endowed with an excitement of discovery comparable to the Rover landing on Mars. Yet, the pursuit of proteomics is likely to bear fruit in the more immediate future. All systems go!

1
Seshi B, Kumar S, King D. Multilineage gene expression in human bone marrow stromal cells as evidenced by single-cell microarray analysis.
Blood Cells Mol Dis.
2003
;
31
:
268
-285.
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