posted on 2016-02-20, 08:51authored byAlexander Schäfer, Christine von Toerne, Silke Becker, Hakan Sarioglu, Susanne Neschen, Melanie Kahle, Stefanie M. Hauck, Marius Ueffing
Protein expression analysis is one of the most powerful
tools to
further the understanding of biological systems. Progress in the field
of mass spectrometry has shifted focus from gel-based approaches to
the upcoming LC-selected reaction monitoring (SRM) technique which
combines high technical accuracy with absolute quantification of proteins
and the capability for high-throughput analyses. Due to these properties,
LC-SRM has the potential to become the foundation for biomarker analysis,
targeted hypothesis driven proteomic studies and contribute to the
field of systems biology. While the performance of LC-SRM applied
to samples from various bodily fluids, particularly plasma, and microorganisms
has been extensively investigated, there is only little experience
with its application to animal tissue samples. Here, we show that
a conventional one-dimensional LC-SRM workflow applied to mouse liver
tissue suffers from a shortcoming in terms of sensitivity for lower
abundance proteins. This problem could be solved through the extension
of the standard workflow by an additional dimension of separation
at the peptide level prior to online LC-SRM. For this purpose, we
used off-gel electrophoresis (OGE) which is also shown to outperform
strong cation exchange (SCX) in terms of resolution, gain of signal
intensity, and predictability of separation. The extension of the
SRM workflow by a high resolving peptide separation technique is an
ideal combination as it allows the addition of stable isotope standards
directly after trytic digestion and will increase the dynamic range
of protein abundances amenable by SRM in animal tissue.