Abstract
BackgroundProteins interacting with each other as a complex play an important role in many molecular processes and functions. Directly detecting protein complexes is still costly, whereas many protein-protein interaction (PPI) maps for model organisms are available owing to the fast development of high-throughput PPI detecting techniques. These binary PPI data provides fundamental and abundant information for inferring new protein complexes. However, PPI data from different experiments do not overlap very much usually. The main reason is that the functions of proteins can activate only on certain environment or stimulus. In a short, PPI is condition-specific. Therefore specifying the conditions on when complexes are present is necessary for a deep understanding of their behaviours. Meanwhile, proteins have various interaction ways and control mechanisms to form different kinds of complexes. Thus the discovery of a certain type of complexes should depend on their own distinct biological or topological characteristics. We do not attempt to find all kinds of complexes by using certain features. Here, we integrate transcription regulation data (TR), gene expression data (GE) and protein-protein interaction data at the systems biology level to discover a special kind of protein complex called conditional co-regulated protein complexes. A conditional co-regulated protein complex has three remarkable features: the coding genes of the member proteins share the same transcription factor (TF), under a certain condition the coding genes express co-ordinately and the member proteins interact mutually as a complex to implement a common biological function.ResultsA framework of discovering the conditional co-regulated protein complexes is proposed. Testing on the Yeast data sets under the Cell Cycle, DNA Damage and Dauxic Shift conditions, we identified a total of 29 conditional co-regulated complexes, among which the coding genes in 14 complexes show a strong association with their TFs activity. Based on the close relationship among co-regulation, co-expression and protein-protein interactions in the conditional co-regulated protein complexes, 39 novel TRs were predicted and explained. ConclusionsThis paper was initiated to study conditional co-regulated protein complexes by integrating multiple data sources. Taking into consideration the influence of TFs activity on the protein interactions, we found that the expression coherence of the protein complexes’ coding genes changed in accordance to their TFs’ activity, which implied that the proteins’ interactions also changed in response to the environments. Based on the three features of conditional co-regulated protein complexes, new transcriptional regulation interactions were predicted.
Highlights
Proteins interacting with each other as a complex play an important role in many molecular processes and functions
The common protein-protein interaction (PPI) between the two different mass-spectrometry approaches stands at 1,728 pairs, which correspond to only 27.5% of PPI detected by tandem affinity purification (TAP) or only 19.2% of PPI detected by highthroughput mass-spectrometric protein complex identification [5]
If the corresponding coding genes of the proteins in the PPI cannot be found in the gene expression data (GE) dataset over all conditions, we excluded those proteins from the PPI data
Summary
Proteins interacting with each other as a complex play an important role in many molecular processes and functions. Many protein-protein interaction (PPI) networks of model organisms such as yeast, fruit fly and so on have been mapped They provide fundamental and abundant data for computational approaches to the inference of new type protein complexes. Most of computational approaches mainly use large-scale statistically oriented study or exact local topological analysis of protein complexes The former ones could acquire the information about the global structural features including particular degree distribution [6], clustering properties [7] and possible hierarchical structure of the examined networks [8] and the later ones were focused on the discovery of functional motifs [9], themes [10], and modules [11]. In order to understand the behaviours and functions of protein complexes precisely, it’s necessary to take the condition-specific features into account
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