bbc 2015

BeNeLux Bioinformatics Conference – Antwerp, December 7-8 2015
Abstract ID: P
Poster
10th Benelux Bioinformatics Conference bbc 2015
P22. MAPPI-DAT: MANAGEMENT AND ANALYSIS FOR HIGH
THROUGHPUT INTERACTOMICS DATA FROM ARRAY-MAPPIT
EXPERIMENTS
Surya Gupta 1,2,3 , Jan Tavernier 1,2 & Lennart Martens 1,2,3 .
Medical Biotechnology Center, VIB, Ghent, Belgium 1 ; Department of Biochemistry, Ghent University, Ghent, Belgium 2 ;
Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium 3 .
INTRODUCTION
Proteins are highly interesting objects of study, involved
in different cellular and molecular functions. Identification
and quantification of these proteins along with their
interacting proteins, nucleic acids and molecules can
provide insight into development and disease mechanisms
at the systems level. Yet studying these interactions is not
trivial. In vivo methods exist to determine these
interactions, but these suffer from several drawbacks [4].
To overcome existing problems, an innovative approach
called MAPPIT (Mammalian Protein-Protein Interaction
Trap) [2] has been established in the Cytokine Receptor
Lab to determine interacting partners of proteins in
mammalian cells. To allow screening of thousands of
interactors simultaneously, MAPPIT has been parallelized
in the array MAPPIT system [3].
AIM
However, no effective pipeline existed to process the highthrough
put data generated from array MAPPIT. We
therefore established an automated high-throughput data
analysis system called MAPPI-DAT (Mappit Array
Protein Protein Interaction- Database & Analysis Tool).
METHODS
In the array-MAPPIT platform the interaction of two
proteins (bait-prey) restores a mutated JAK-STAT
signaling pathway which leads to the expression of
florescence emitting genes. In order to rank the positive
interactions based on fluorescence intensity, RankProd [1]
is used. This method was originally developed to
determine differentially expressed genes in microarray
experiments and is available as R package. To minimize
false positive hits from RankProd output, quartile based
filtration was applied. MySQL platform was used to build
the data management system for the array-MAPPIT
system.
RESULTS
To extend and ease the usage of the analysis pipeline and
database system, an interface has been developed called
MAPPI-DAT. MAPPI-DAT is capable of processing
many thousand data points for each experiment, and
comprising a data storage system that stores the
experimental data in a structured way for meta-analysis.
REFERENCES
[1] Breitling, R., Armengaud, P., Amtmann, A., & Herzyk, P. (2004).
Rank products: A simple, yet powerful, new method to detect
differentially regulated genes in replicated microarray experiments.
FEBS Letters, 573(1-3), 83–92.
[2] Lievens, S., Peelman, F., De Bosscher, K., Lemmens, I., &
Tavernier, J. (2011). MAPPIT: A protein interaction toolbox built on
insights in cytokine receptor signaling. Cytokine and Growth Factor
Reviews, 22(5-6), 321–329.
[3] Lievens, S., Vanderroost, N., Heyden, J. Van Der, Gesellchen, V.,
Vidal, M., Tavernier, J., & Heyden, V. Der. (2009). Array MAPPIT :
High-Throughput Interactome Analysis in Mammalian Cells Array
MAPPIT : High-Throughput Interactome Analysis in Mammalian Cells,
877–886.
[4] S.Gopichandran and S.Ranganathan. (2013). Protein-protein
Interactions and Prediction: A Comprehensive Overview. Protein and
Peptide Letters, 779–789
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