Biological systems respond to extracellular and intracellular signals in
myriad ways by activating diverse signaling pathways. Reversible
covalent post-translational modifications (PTMs) such as
phosphorylation, acetylation and methylation are critical modulators of
these signaling pathways. While phosphorylation is the most extensively
studied PTM, lysine methylation is emerging as a key player in
regulating intracellular signaling pathways. The methylation of lysine
residues is performed by protein lysine (K) methyltransferases (PKMTs).
It is estimated that in the human proteome there are ~50 PKMT and
greater than 25 demethylases (PKDMs) which can reverse the process and
remove the methyl mark away. A lysine residue can be mono, di or tri
methylated.
The degree of methylation is enzyme specific and can define a distinct
biological outcome by recruiting specialized regulatory factor, named
“readers” that specifically recognize distinct modification in a state
(degree of methylation) and in a sequence dependent manner.
In recent years, lysine methylation has been studied in depth in the
context of histones. However, there is a growing appreciation that
non-histone proteins are also subjected to lysine methylation with a
clear role in the regulation of oncogenic and cell differentiation
processes. Most studies aiming to identify lysine methylation events
have focused on only a few target proteins via a candidate-based
approach. We have developed a unique proteomic methodology to identify
new substrates for different PKMTs.
Using a ProtoArray-based proteomic platform, we demonstrated that more
than 9500 unique substrates can be screened in a single experiment in a
reproducible and efficient manner (Levy et al, Epigenetics &
Chromatin, 2011). Employing this system, we identified 118 new targets
for SETD6 and 321 substrates for the related PKMT SETD7. As part of our
research program, we will continue to harness and develop protein and
peptide array proteomic tools towards the goal of understanding how
novel methylation signaling networks impact cancer pathways and cell
differentiation programs.