Biology Reference
In-Depth Information
Biological Petri Nets
Exhaustive Analysis of the Modular
Structure of the Spliceosomal Assembly
Network: A Petri Net Approach
Ralf H. Bortfeldt
a
,
1
,∗
, Stefan Schuster
a
and Ina Koch
b
,
c
a
Chair of Bioinformatics, Friedrich-Schiller University Jena, Jena, Germany
b
Institute for Computer Science WG Molecular Bioinformatics, Johann Wolfgans Goethe University Frankfurt,
Frankfurt, Germany
c
Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
ABSTRACT:
Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceo-
some assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list
of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often
unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task
to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed
earlier.
Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete
modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural
and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a
functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform
the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted
as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and
complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce
a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions
or reaction sequences, which participate in more than one signaling route.
We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display
involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and
iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network
consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants.
These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on
reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present
knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes,
which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular
conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during
A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling
known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have
previously not been described as connected routes, although their constituents were known. T-clusters divide the network into
∗
Corresponding author: Ralf H. Bortfeldt, Friedrich-Schiller University Jena, Ernst Abbe Platz 2, 07743 Jena, Germany.
E-mail:
ralf.bortfeldt@agrar.hu-berlin.de
.
1
Humboldt-University of Berlin, Breeding Biology and Molecular Genetics Berlin, Germany.
