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A Systematic Analysis of a Mi-RNA Inter-Pathway Regulatory Motif Stefano Di Carlo1*†, Gianfranco Politano1†, Alessandro Savino2† and Alfredo Benso1,2†

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A Systematic Analysis of a Mi-RNA Inter-Pathway Regulatory Motif Stefano Di Carlo1*†, Gianfranco Politano1†, Alessandro Savino2† and Alfredo Benso1,2† Di Carlo et al. Journal of Clinical Bioinformatics 2013, 3:20 JOURNAL OF http://www.jclinbioinformatics.com/content/3/1/20 CLINICAL BIOINFORMATICS RESEARCH Open Access A systematic analysis of a mi-RNA inter-pathway regulatory motif Stefano Di Carlo1*†, Gianfranco Politano1†, Alessandro Savino2† and Alfredo Benso1,2† Abstract Background: The continuing discovery of new types and functions of small non-coding RNAs is suggesting the presence of regulatory mechanisms far more complex than the ones currently used to study and design Gene Regulatory Networks. Just focusing on the roles of micro RNAs (miRNAs), they have been found to be part of several intra-pathway regulatory motifs. However, inter-pathway regulatory mechanisms have been often neglected and require further investigation. Results: In this paper we present the result of a systems biology study aimed at analyzing a high-level inter-pathway regulatory motif called Pathway Protection Loop, not previously described, in which miRNAs seem to play a crucial role in the successful behavior and activation of a pathway. Through the automatic analysis of a large set of public available databases, we found statistical evidence that this inter-pathway regulatory motif is very common in several classes of KEGG Homo Sapiens pathways and concurs in creating a complex regulatory network involving several pathways connected by this specific motif. The role of this motif seems also confirmed by a deeper review of other research activities on selected representative pathways. Conclusions: Although previous studies suggested transcriptional regulation mechanism at the pathway level such as the Pathway Protection Loop, a high-level analysis like the one proposed in this paper is still missing. The understanding of higher-level regulatory motifs could, as instance, lead to new approaches in the identification of therapeutic targets because it could unveil new and “indirect” paths to activate or silence a target pathway. However, a lot of work still needs to be done to better uncover this high-level inter-pathway regulation including enlarging the analysis to other small non-coding RNA molecules. Keywords: Regulatory networks, Network motifs, miRNA, Pathways Background different molecules interact with each other, leading to Systems biology is increasingly highlighting that a a proliferation of biological networks (e.g., protein-protein discrete biological function can only rarely be attributed interaction, metabolic, signaling and transcription-regulatory to a single molecule. Instead, most biological character- networks). Several public and commercial network reposi- istics arise from complex interactions among the cell’s tories including the WikiPathway database [4,5], the numerous constituents, such as proteins, DNA, RNA Ingenuity database [6], and the Kyoto Encyclopedia of and small molecules [1-3]. Understanding the structure Genes and Genomes (KEGG) [7,8], collect large amount and the dynamics of complex intercellular networks that of curated biological networks that can be explored and contribute to the structure and function of a living cell analyzed for high-level systemic analysis. None of these is therefore mandatory. networks is independent, instead they form a complex The fast development of technologies to collect high- network of networks that is responsible for the behavior throughput biological data allows us to determine how of the cell. In this paper we concentrate on the key role that small non-coding RNAs, and in particular micro * Correspondence: [email protected] RNAs (miRNAs), have in this intricate biological network †Equal contributors of networks. 1 Department of Control and Computer Engineering, Politecnico di Torino, Several results have been achieved in the past few Torino, IT, Italy Full list of author information is available at the end of the article years from the research of recurrent motifs in complex © 2013 Di Carlo et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Di Carlo et al. Journal of Clinical Bioinformatics 2013, 3:20 Page 2 of 14 http://www.jclinbioinformatics.com/content/3/1/20 Gene Regulation Networks [9-18], highlighting the cen- in this context called Antagonist miRNAs, targeting and tral role of miRNAs in governing specific regulation down-regulating some of the pathway’s genes. Interest- mechanisms at the network level [19-22]. In order to ingly, we discovered that, in several analyzed networks, move toward the identification of higher-level mecha- the pathway intragenic miRNAs target and silence the nisms of transcriptional regulation, in this paper we per- transcription factors of the PAGs, thus creating a loop formed a systemic analysis on a large set of well known that seems designed to prevent PAGs from interfering biological networks to underline the presence of an with the pathway expression process. Given this charac- inter-network regulatory motif in which miRNAs seem teristic we named this motif as Pathway Protection Loop involved in a high-level regulatory activity among differ- (PPL). ent networks. Rather then searching for pure topological When a PPL is present, its action is carried out in the motifs, available networks have been enriched with bio- following steps: logical information from several public repositories to attempt to link obtained results to selected biological 1. When the pathway is activated, one or more pathway mechanisms [23]. genes co-express one or more intragenic miRNAs. Figure 1 shows the structure of the investigated net- 2. The intragenic miRNAs expressed by the pathway work motif. According to this motif, the successful full target one or more transcription factors of some of activation of a regulatory network (pathway) not only the PAGs. We call these transcription factors depends on the correct expression of the pathway’s Pathway Antagonist Transcription Factors (PATFs). genes, but also on the expression of other genes poten- In some situations, the pathway intragenic miRNA tially belonging to different networks that could interfere may also target the pathway itself, but this or dysregulate (down-regulate or silence) the pathway at mechanism belongs to well-studied intra-pathway some point. We call these genes the Pathway Antagonist regulations that are not the focus of this work. Genes (PAGs). A possible way PAGs may interfere with 3. The down-regulation of the PATFs has a repressive the activity of a pathway is to express a set of miRNAs, effect on the expression of the corresponding PAGs. Pathway 2 (intragenic) miRNA 1 Pathway Antagonist pathway Transcription Factor (PATF) PI3K PDK1 3 Pathway Protection AKT Loop RSK Pathway Antagonist TSC1 Gene (PAG) 5 Antagonist RICTOR miRNA 4 Figure 1 Pathway Protection Loop. Pathway Protection Loop (solid lines indicate active interactions; dashed lines indicate inhibited effects): 1) an activated pathway is host of one or more intragenic miRNAs that are therefore co-expressed with the pathway; 2) the pathway miRNAs target one or more PATF; 3) the down-regulated PATFs down-regulate the corresponding PAGs; 4) the down-regulated PAGs are not able to express the Antagonist miRNAs; 5) the down-regulation of the pathway genes by the Antagonist miRNAs is prevented. Di Carlo et al. Journal of Clinical Bioinformatics 2013, 3:20 Page 3 of 14 http://www.jclinbioinformatics.com/content/3/1/20 4. Down-regulated PAGs have lower ability to express necessary to make the problem manageable with the the Antagonist miRNAs. It is worth here to current tools. remember that miRNAs have a post-transcriptional The final set of considered KEGG pathways is reported regulation role. Intragenic miRNAs that directly in the two files Additional file 1 and Additional file 2 target the PAGs would not actually prevent the provided as additional files to this paper. The KEGG production of the related Antagonist miRNAs since pathway repository contains several classes of networks miRNAs are expressed during transcription. The describing a very large set of biological processes. The only way PPLs can form is therefore by mediating type of biological process, and consequently the involved the PAGs down-regulation through their actors (e.g., genes, proteins, metabolites, etc.) may bias corresponding PATFs [24]. the presence or the absence of PPLs. It has therefore 5. The reduced presence of Antagonist miRNAs been taken into account in our analysis. KEGG already contributes to the successful expression of the categorizes all pathways according to a hierarchical pathway genes, thus closing the protection loop. ontology called the KEGG BRITE hierarchy. We exploi- ted the first hierarchical level of this ontology to cluster An interesting characteristic of PPL is its hierarchical all considered pathways into two main categories related structure: a very small number of intragenic miRNAs to the ability of the corresponding nodes to be involved (usually one or two) is able to “defend” the expression of in miRNA mediated regulatory processes as will be dis- either a large number or even the most important path- cussed in the Statistical Analysis section. The first cat- way genes. egory contains 107 metabolic pathways while the second This paper proposes an extensive systems biology category contains 51 non-metabolic pathways (9 from
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