11-13 May 2012 Helsingør - Denmark www.networkbio.org

BLAKE BORGESON(1), CUIhONG WAN(2), ANDREW EMILI(2), EDWARD MARCOTTE(1)
1: ThE UNIVERSITY Of TExAS AT AUSTIN, CENTER fOR SYSTEMS AND SYNThETIC BIOLOGY
2: ThE UNIVERSITY Of TORONTO, BANTING AND BEST DEPARTMENT Of MEDICAL RESEARCh
Conservation and Divergence of Protein Complexes Across Evolution
Despite agreement that the vast majority of life’s processes at a cellular level are carried out by complexes
of multiple proteins, knowledge of all the complexes formed in a cell and their members is a distant goal. By
using a new approach developed by collaborators Havugimana and Hart, et al, consisting of 1) subjecting
biological samples to many levels of many types of fractionations, 2) using LC-MS/MS to quantify protein
levels in each fraction, and 3) processing the data through a machine learning pipeline, we identify putative
soluble (non¬membrane) complexes using a high-throughput all-by-all approach. By incorporating additional
functional genomic information into our learning process, we are able to reconstruct maps of complexes that
so far seem to rival in quality those generated using previous, more labor-intensive methods. Here, we apply
the approach to biological samples from many organisms, including human, sea urchin, fly, worm, and multicellular
amoebas, in order to rapidly learn soluble complexes in many species. From such maps we identify
interesting conservation and divergence of complexes not previously well-understood or studied.
abStractS For PoSterS abStractS For PoSterS
ChRISTOPhER A. BARNES, ALESSIO MAIOLICA, RUEDI AEBERSOLD
INSTITUTE Of MOLECULAR SYSTEMS BIOLOGY, ETh züRICh, SWITzERLAND
A Global Kinase-Substrate Network in Yeast Mapped Using In Vitro Phosphorylation and Phosphoproteomics
Kinase inhibitor drugs have been a major focus in the pharmaceuticals industry over the past decade.
Despite extensive development of these inhibitors, their effectiveness has been limited. It is thought that
the difficulties associated with kinase inhibitor drug effectiveness relates to network compensation events
in the cell that allow other kinases to replace the lost function of the inhibited enzyme. To date, it has been
difficult to link kinases to substrates at the amino acid level with methodologies suitable to creating a global
kinase-substrate wiring diagram. Identifying direct kinase-substrate relationships for each kinase could help
researchers to design pharmaceutical solutions that take into account network compensations. The aim
of this project is to identify kinase-substrate relationships in yeast for all of the kinases in S. cerevisiae. In
previous studies in the lab1, experiments were performed where kinases were sequentially deleted, but the
identification of direct kinase-substrate relationships with these deletion studies proved difficult. Here, we
have taken a large library of the most regulated phosphosites from these deletion experiments and synthesized
unphosphorylated peptides suitable for in vitro phosphorylation followed by LC-MS/MS identification of
the phosphorylated product peptides. We use endogenously expressed immunopurified kinases followed by
a phosphopeptide enrichment step prior to mass spectrometry analysis. Our phosphorylation assays have
shown good specificity in vitro as evidenced by the identification of specific known consensus motifs and
we have begun to identify subfamily redundancies in the substrate networks as this yeast phosphorylation
wiring diagram is beginning to emerge.
References:
1. Bodenmiller et al. Sci. Signal. 3, rs4 (2010).
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