Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules

Background
It is generally acknowledged that a functional understanding of a biological system can only be obtained by an understanding of the collective of molecular interactions in form of biological networks. Protein networks are one particular network type of special importance, because proteins form the functional base units of every biological cell. On a mesoscopic level of protein networks, modules are of significant importance because these building blocks may be the next elementary functional level above individual proteins allowing to gain insight into fundamental organizational principles of biological cells.
Results
In this paper, we provide a comparative analysis of five popular and four novel module detection algorithms. We study these module prediction methods for simulated benchmark networks as well as 10 biological protein interaction networks (PINs). A particular focus of our analysis is placed on the biological meaning of the predicted modules by utilizing the Gene Ontology (GO) database as gold standard for the definition of biological processes. Furthermore, we investigate the robustness of the results by perturbing the PINs simulating in this way our incomplete knowledge of protein networks.
Conclusions
Overall, our study reveals that there is a large heterogeneity among the different module prediction algorithms if one zooms-in the biological level of biological processes in the form of GO terms and all methods are severely affected by a slight perturbation of the networks. However, we also find pathways that are enriched in multiple modules, which could provide important information about the hierarchical organization of the system

Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that these models are lacking crucial structural features present in protein interaction networks on a mesoscopic scale. This observation reveals our incomplete understanding of the structural evolution of protein networks on the module level. © 2012 Emmert-Streib.

Tigecycline challenge triggers sRNA production in Salmonella enterica serovar Typhimurium

Background: Bacteria employ complex transcriptional networks involving multiple genes in response to stress, which is not limited to gene and protein networks but now includes small RNAs (sRNAs). These regulatory RNA molecules are increasingly shown to be able to initiate regulatory cascades and modulate the expression of multiple genes that are involved in or required for survival under environmental challenge. Despite mounting evidence for the importance of sRNAs in stress response, their role upon antibiotic exposure remains unknown. In this study, we sought to determine firstly, whether differential expression of sRNAs occurs upon antibiotic exposure and secondly, whether these sRNAs could be attributed to microbial tolerance to antibiotics.

Results: A small scale sRNA cloning strategy of Salmonella enterica serovar Typhimurium SL1344 challenged with half the minimal inhibitory concentration of tigecycline identified four sRNAs (sYJ5, sYJ20, sYJ75 and sYJ118) which were reproducibly upregulated in the presence of either tigecycline or tetracycline. The coding sequences of the four sRNAs were found to be conserved across a number of species. Genome analysis found that sYJ5 and sYJ118 mapped between the 16S and 23S rRNA encoding genes. sYJ20 (also known as SroA) is encoded upstream of the tbpAyabKyabJ operon and is classed as a riboswitch, whilst its role in antibiotic stress-response appears independent of its riboswitch function. sYJ75 is encoded between genes that are involved in enterobactin transport and metabolism. Additionally we find that the genetic deletion of sYJ20 rendered a reduced viability phenotype in the presence of tigecycline, which was recovered when complemented. The upregulation of some of these sRNAs were also observed when S. Typhimurium was challenged by ampicillin (sYJ5, 75 and 118); or when Klebsiella pneumoniae was challenged by tigecycline (sYJ20 and 118).

Conclusions: Small RNAs are overexpressed as a result of antibiotic exposure in S. Typhimurium where the same molecules are upregulated in a related species or after exposure to different antibiotics. sYJ20, a riboswitch, appears to possess a trans-regulatory sRNA role in antibiotic tolerance. These findings imply that the sRNA mediated response is a component of the bacterial response to antibiotic challenge.

Role of the AP2 beta-appendage hub in recruiting partners for clathrin-coated vesicle assembly

Adaptor protein complex 2 alpha and beta-appendage domains act as hubs for the assembly of accessory protein networks involved in clathrin-coated vesicle formation. We identify a large repertoire of beta-appendage interactors by mass spectrometry. These interact with two distinct ligand interaction sites on the beta-appendage (the "top" and "side" sites) that bind motifs distinct from those previously identified on the alpha-appendage. We solved the structure of the beta-appendage with a peptide from the accessory protein Eps15 bound to the side site and with a peptide from the accessory cargo adaptor beta-arrestin bound to the top site. We show that accessory proteins can bind simultaneously to multiple appendages, allowing these to cooperate in enhancing ligand avidities that appear to be irreversible in vitro. We now propose that clathrin, which interacts with the beta-appendage, achieves ligand displacement in vivo by self-polymerisation as the coated pit matures. This changes the interaction environment from liquid-phase, affinity-driven interactions, to interactions driven by solid-phase stability ("matricity"). Accessory proteins that interact solely with the appendages are thereby displaced to areas of the coated pit where clathrin has not yet polymerised. However, proteins such as beta-arrestin (non-visual arrestin) and autosomal recessive hypercholesterolemia protein, which have direct clathrin interactions, will remain in the coated pits with their interacting receptors.

Mechanism of Activation of a G Protein-coupled Receptor, the Human Cholecystokinin-2 Receptor

G protein-coupled receptors (GPCRs) represent a major focus in functional genomics programs and drug development research, but their important potential as drug targets contrasts with the still limited data available concerning their activation mechanism. Here, we investigated the activation mechanism of the cholecystokinin-2 receptor (CCK2R). The three-dimensional structure of inactive CCK2R was homology-modeled on the basis of crystal coordinates of inactive rhodopsin. Starting from the inactive CCK2R modeled structure, active CCK2R (namely cholecystokinin-occupied CCK2R) was modeled by means of steered molecular dynamics in a lipid bilayer and by using available data from other GPCRs, including rhodopsin. By comparing the modeled structures of the inactive and active CCK2R, we identified changes in the relative position of helices and networks of interacting residues, which were expected to stabilize either the active or inactive states of CCK2R. Using targeted molecular dynamics simulations capable of converting CCK2R from the inactive to the active state, we delineated structural changes at the atomic level. The activation mechanism involved significant movements of helices VI and V, a slight movement of helices IV and VII, and changes in the position of critical residues within or near the binding site. The mutation of key amino acids yielded inactive or constitutively active CCK2R mutants, supporting this proposed mechanism. Such progress in the refinement of the CCK2R binding site structure and in knowledge of CCK2R activation mechanisms will enable target-based optimization of nonpeptide ligands.

The Carboxy-Terminal Modulator Protein (CTMP) Regulates Mitochondrial Dynamics

Background: Mitochondria are central to the metabolism of cells and participate in many regulatory and signaling events. They are looked upon as dynamic tubular networks. We showed recently that the Carboxy-Terminal Modulator Protein (CTMP) is a mitochondrial protein that may be released into the cytosol under apoptotic conditions.

Cytosol protein regulation in H295R steroidogenesis model induced by the zearalenone metabolites, α- and β-zearalenol.

a- and b-zearalenol (a-ZOL and b-ZOL, respectively) are metabolites of the mycotoxin zearalenone (ZEN). All three individual mycotoxins have shown to be biological active i.e. being estrogenic and able to stimulate cellular proliferation albeit at different strengths. In this work, cytosol protein expression was determined by using stable-isotope labelling by amino acids in cell culture (SILAC) upon exposure of a-ZOL and b-ZOL to the steroidogenesis cell model H295R. A total of 14 and 5 individual proteins were found to be significantly regulated by a-ZOL and b-ZOL, respectively. Interestingly, there were no common protein regulations by the metabolites or the parent mycotoxin ZEN. Furthermore, the regulated proteins were assigned to networks and groups of actions that also differed from one another suggesting that the three individual mycotoxins may have unique biological activities.

Modeled structure of a G-protein-coupled receptor:The cholecystokinin-1 receptor

The Cholecystokinin-1 receptor (CCK1R) mediates actions of CCK in areas of the central nervous system and of the gut. It is a potential target to treat a number of diseases. As for all G-protein-coupled receptors, docking of ligands into modeled CCK1R binding site should greatly help to understand intrinsic mechanisms of activation. Here, we describe the procedure we used to progressively build a structural model for the CCK1R, to integrated, and on the basis of site-directed mutagenesis data on its binding site. Reliability of the CCK1R model was confirmed by interaction networks that involved conserved and functionally crucial motifs in G-protein-coupled receptors, such as Glu/Asp-Arg-Tyr and Asn-Pro-Xaa-Xaa-Tyr motifs. In addition, the 3-D structure of CCK1R-bound CCK resembled that determined by NMR in a lipid environment. The derived computational model was also used for revealing binding modes of several nonpeptide ligands and for rationalizing ligand structure-activity relationships known from experiments. Our findings indeed support that our "validated CCK1R model" could be used to study the intrinsic mechanism of CCK1R activation and design new ligands.

Detecting sequence dependent transcriptional pauses from RNA and protein number time series

Background: Evidence suggests that in prokaryotes sequence-dependent transcriptional pauses a?ect the dynamics of transcription and translation, as well as of small genetic circuits. So far, a few pause-prone sequences have been identi?ed from in vitro measurements of transcription elongation kinetics.

Results: Using a stochastic model of gene expression at the nucleotide and codon levels with realistic parameter values, we investigate three di?erent but related questions and present statistical methods for their analysis. First, we show that information from in vivo RNA and protein temporal numbers is su?cient to discriminate between models with and without a pause site in their coding sequence. Second, we demonstrate that it is possible to separate a large variety of models from each other with pauses of various durations and locations in the template by means of a hierarchical clustering and a random forest classi?er. Third, we introduce an approximate likelihood function that allows to estimate the location of a pause site.

Conclusions: This method can aid in detecting unknown pause-prone sequences from temporal measurements of RNA and protein numbers at a genome-wide scale and thus elucidate possible roles that these sequences play in the dynamics of genetic networks and phenotype.

Detection of Protein-Protein Interactions Using Protein-Fragment Complementation Assays (PCA)

Protein-protein interactions play a central role in many cellular processes. Their characterisation is necessary in order to analyse these processes and for the functional identification of unknown proteins. Existing detection methods such as the yeast two-hybrid (Y2H) and tandem affinity purification (TAP) method provide a means to answer rapidly questions regarding protein-protein interactions, but have limitations which restrict their use to certain interaction networks; furthermore they provide little information regarding interaction localisation at the subcellular level. The development of protein-fragment complementation assays (PCA) employing a fluorescent reporter such as a member of the green fluorescent protein (GFP) family has led to a new method of interaction detection termed Bimolecular Fluorescent Complementation (BiFC). These assays have become important tools for understanding protein interactions and the development of whole genome interaction maps. BiFC assays have the advantages of very low background signal coupled with rapid detection of protein-protein interactions in vivo while also providing information regarding interaction compartmentalisation. Modified forms of the assay such as the use of combinations of spectral variants of GFP have allowed simultaneous visualisation of multiple competing interactions in vivo. Advantages and disadvantages of the method are discussed in the context of other fluorescence-based interaction monitoring techniques.

Interfacing cellular networks of S. cerevisiae and E. coli: Connecting dynamic and genetic information

Background: In recent years, various types of cellular networks have penetrated biology and are nowadays used omnipresently for studying eukaryote and prokaryote organisms. Still, the relation and the biological overlap among phenomenological and inferential gene networks, e.g., between the protein interaction network and the gene regulatory network inferred from large-scale transcriptomic data, is largely unexplored.

Results: We provide in this study an in-depth analysis of the structural, functional and chromosomal relationship between a protein-protein network, a transcriptional regulatory network and an inferred gene regulatory network, for S. cerevisiae and E. coli. Further, we study global and local aspects of these networks and their biological information overlap by comparing, e.g., the functional co-occurrence of Gene Ontology terms by exploiting the available interaction structure among the genes.

Conclusions: Although the individual networks represent different levels of cellular interactions with global structural and functional dissimilarities, we observe crucial functions of their network interfaces for the assembly of protein complexes, proteolysis, transcription, translation, metabolic and regulatory interactions. Overall, our results shed light on the integrability of these networks and their interfacing biological processes.

Semi-interpenetrating polymer networks incorporating polygalacturonic acid for medical device applications

Background Over 20 million people in the US are living with an implantable medical device [ADDIN RW.CITE{{3114 Higgins,DavidM 2009}}1], with similar figures anticipated for Europe. Complications in the use of medical implants include the Foreign Body Response (FBR) characterised by macrophage adherence and fusion, and device-related infection due to bacterial biofilm formationADDIN RW.CITE{{3124 Harding,JacquelineL 2014}}2. Both can have detrimental consequences on the structural and functional integrity of the medical device [ADDIN RW.CITE{{3101 Anderson,JamesM 2008; 3124 Harding,JacquelineL 2014}}2,3], often necessitating removal; a painful and expensive procedure [ADDIN RW.CITE{{3121 Mah,Thien-FahC 2001}}4]. Materials are sought to attenuate both the FBR and device-related infection, leading to medical devices with improved biocompatibility and performance. Objectives The present work involves development of a semi-interpenetrating network (SIPN) hydrogel containing polygalacturonic acid (PGA), a biopolysaccharide similar in structure to hyaluronic acid. We aim to synthesise, characterise and determine the in vitro biocompatibility of the developed SIPN. Results & Discussion We have successfully incorporated PGA into a poly(HEMA) based hydrogel, which shows favourable swelling and wettability. The surface topography appears altered in comparison to the control material, with pronounced micrometer-scale features. In terms of in vitro performance, the SIPN showed increased protein adsorption, and biofilm formation (Staphylococcus epidermidis and Escherichia coli, up to 1 Log CFU/sample greater than control). However the SIPN displayed minimal cytotoxicity towards L929 fibroblasts, and was resistant to the adherence of RAW 264.7 macrophages. Conclusions The PGA incorporated SIPN lacks cytotoxicity and shows reduced macrophage adherence, however the increased biofilm formation highlights a concern regarding possible device related infection in clinical use. Future work will focus on strategies to reduce bacterial adherence, while maintaining biocompatibility.