Biomedical Engineering Reference
In-Depth Information
tags) (Boguski et al., 1993; Sharov et al., 2003), SAGE (serial analysis of gene
expression) (Richards et al., 2004; Velculescu et al., 1995), andMPSS (massively
parallel signature sequencing) (Boheler and Tarasov, 2006; Brenner et al.,
2000). Array-based technologies have advanced in parallel. Prominent among
commercially made arrays are those manufactured by Affymetrix. These high-
throughput technologies, combined with whole genome sequences, have
become powerful tools for elucidation of the transcriptome in this, the post-
genome project, era. Visionary use of transcriptome data is illustrated by the
work of Yamanaka and his colleagues. They used digital differential display
(
http://www.ncbi.nlm.nih.gov.ezp-prod1.hul.harvard.edu/UniGene/info_ddd.
shtml
) to compare EST libraries frommES cells and those from various somatic
tissues to identify candidates of the LIF/STAT3-independent factor(s). From
such data, they identified potentially important ESC-specific factors, including
Nanog (Mitsui et al., 2003). From among this set, Yamanaka and his colleagues
tested various combinations of factors to reprogram somatic cells to a pluripo-
tent state (Takahashi and Yamanaka, 2006).
In addition to gene expression data, it is now possible to capture more
comprehensively the repertoire of proteins in ESCs. Recent development in
proteomics research enables the large-scale quantitative analysis of the protein
expressed in a given cell. In parallel with the transcriptome which portrays a
gene expression profile by microarray, the proteome (PROTEins expressed by
genOME) describes the catalogue of the total set of proteins expressed in a cell,
an organization, or an organism. The proteome reflects all aspects of cellular
proteins, including their synthesis, stability, degradation, and PTMs (posttran-
slational modifications). Moreover, understanding the interaction of proteins
within the context of a cellular network is critical for understanding function.
The proteome of ESCs has been characterized using mass spectrometry (MS)-
based protein profiling of both undifferentiated and differentiated ESCs (Elliott
et al., 2004; Nagano et al., 2005; VanHoof et al., 2006). These studies and others
have generated an extensive set of data for ESCs that serves as an initial protein
catalogue complementing mRNA expression data. These data are available for
effective comparison of experimental data across different labs. The HUPO
(Human Proteome Organization) and the ISSCR (International Society for
Stem Cell Research) have established an alliance to provide a platform for
collaboration and communication between scientists in each organization
(
http://www.hupo.org/research/stemcells
/).
An alternative approach to revealing protein dynamics in ESCs involves
identification of protein complexes, which might be either transient or quite
stable. Using affinity purification followed by MS-based peptide microsequen-
cing, Wang et al. characterized putative protein complexes of core pluripotency
factors in ECSs (Wang et al., 2006). To enrich for proteins under native condi-
tions, Wang et al. first employed intracellular metabolic biotin tagging to
identify proteins physically in association with Nanog. A major advantage of
the biotin tagging approach is that it does not rely on the availability of specific
antibodies. Often, high-quality antibodies directed to novel proteins are
