Although protein-protein interaction networks determined with high-throughput methods are incomplete, they are commonly used to infer the topology of the complete interactome. These partial networks ...often show a scale-free behavior with only a few proteins having many and the majority having only a few connections. Recently, the possibility was suggested that this scale-free nature may not actually reflect the topology of the complete interactome but could also be due to the error proneness and incompleteness of large-scale experiments.
In this paper, we investigate the effect of limited sampling on average clustering coefficients and how this can help to more confidently exclude possible topology models for the complete interactome. Both analytical and simulation results for different network topologies indicate that partial sampling alone lowers the clustering coefficient of all networks tremendously. Furthermore, we extend the original sampling model by also including spurious interactions via a preferential attachment process. Simulations of this extended model show that the effect of wrong interactions on clustering coefficients depends strongly on the skewness of the original topology and on the degree of randomness of clustering coefficients in the corresponding networks.
Our findings suggest that the complete interactome is either highly skewed such as e.g. in scale-free networks or is at least highly clustered. Although the correct topology of the interactome may not be inferred beyond any reasonable doubt from the interaction networks available, a number of topologies can nevertheless be excluded with high confidence.
BackgroundThe tumor microenvironment (TME) combines features of regulatory cytokines and immune cell populations to evade the recognition by the immune system. Myeloid-derived suppressor cells (MDSC) ...comprise populations of immature myeloid cells in tumor-bearing hosts with a highly immunosuppressive capacity. We could previously identify RIG-I-like helicases (RLH) as targets for the immunotherapy of pancreatic cancer inducing immunogenic tumor cell death and type I interferons (IFN) as key mediators linking innate with adaptive immunity.MethodsMice with orthotopically implanted KrasG12D p53fl/R172H Ptf1a-Cre (KPC) pancreatic tumors were treated intravenously with the RLH ligand polyinosinic-polycytidylic acid (poly(I:C)), and the immune cell environment in tumor and spleen was characterized. A comprehensive analysis of the suppressive capacity as well as the whole transcriptomic profile of isolated MDSC subsets was performed. Antigen presentation capability of MDSC from mice with ovalbumin (OVA)-expressing tumors was investigated in T cell proliferation assays. The role of IFN in MDSC function was investigated in Ifnar1 −/− mice.ResultsMDSC were strongly induced in orthotopic KPC-derived pancreatic cancer, and frequencies of MDSC subsets correlated with tumor weight and G-CSF serum levels, whereas other immune cell populations decreased. Administration of the RLH-ligand induced a IFN-driven immune response, with increased activation of T cells and dendritic cells (DC), and a reduced suppressive capacity of both polymorphonuclear (PMN)-MDSC and monocytic (M)-MDSC fractions. Whole transcriptomic analysis confirmed an IFN-driven gene signature of MDSC, a switch from a M2/G2- towards a M1/G1-polarized phenotype, and the induction of genes involved in the antigen presentation machinery. Nevertheless, MDSC failed to present tumor antigen to T cells. Interestingly, we found MDSC with reduced suppressive function in Ifnar1-deficient hosts; however, there was a common flaw in immune cell activation, which was reflected by defective immune cell activation and tumor control.ConclusionsWe provide evidence that the treatment with immunostimulatory RNA reprograms the TME of pancreatic cancer by reducing the suppressive activity of MDSC, polarizing myeloid cells into a M1-like state and recruiting DC. We postulate that tumor cell-targeting combination strategies may benefit from RLH-based TME remodeling. In addition, we provide novel insights into the dual role of IFN signaling in MDSC’s suppressive function and provide evidence that host-intrinsic IFN signaling may be critical for MDSC to gain suppressive function during tumor development.
The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein ...interaction (PPI) network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs.
For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks.
Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree correlations, biological PPI networks do not actually seem to make use of this possibility.
Abstract
Mammalian-wide interspersed repeats (MIRs) are retrotransposed elements of mammalian genomes. Here, we report the specific binding of zinc finger protein ZNF768 to the sequence motif ...GCTGTGTG (N20) CCTCTCTG in the core region of MIRs. ZNF768 binding is preferentially associated with euchromatin and promoter regions of genes. Binding was observed for genes expressed in a cell type-specific manner in human B cell line Raji and osteosarcoma U2OS cells. Mass spectrometric analysis revealed binding of ZNF768 to Elongator components Elp1, Elp2 and Elp3 and other nuclear factors. The N-terminus of ZNF768 contains a heptad repeat array structurally related to the C-terminal domain (CTD) of RNA polymerase II. This array evolved in placental animals but not marsupials and monotreme species, displays species-specific length variations, and possibly fulfills CTD related functions in gene regulation. We propose that the evolution of MIRs and ZNF768 has extended the repertoire of gene regulatory mechanisms in mammals and that ZNF768 binding is associated with cell type-specific gene expression.
Viruses are the cause of a considerable burden to human, animal and plant health, while on the other hand playing an important role in regulating entire ecosystems. The power of new sequencing ...technologies combined with new tools for processing "Big Data" offers unprecedented opportunities to answer fundamental questions in virology. Virologists have an urgent need for virus-specific bioinformatics tools. These developments have led to the formation of the European Virus Bioinformatics Center, a network of experts in virology and bioinformatics who are joining forces to enable extensive exchange and collaboration between these research areas. The EVBC strives to provide talented researchers with a supportive environment free of gender bias, but the gender gap in science, especially in math-intensive fields such as computer science, persists. To bring more talented women into research and keep them there, we need to highlight role models to spark their interest, and we need to ensure that female scientists are not kept at lower levels but are given the opportunity to lead the field. Here we showcase the work of the EVBC and highlight the achievements of some outstanding women experts in virology and viral bioinformatics.
Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, ...however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary.
In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment.
FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand-alone program and within new systems biology applications. Finally, complex scenarios requiring intervention during the simulation progress can be modelled easily with FERN.
Sequencing of mRNA (RNA-seq) by next generation sequencing technologies is widely used for analyzing the transcriptomic state of a cell. Here, one of the main challenges is the mapping of a sequenced ...read to its transcriptomic origin. As a simple alignment to the genome will fail to identify reads crossing splice junctions and a transcriptome alignment will miss novel splice sites, several approaches have been developed for this purpose. Most of these approaches have two drawbacks. First, each read is assigned to a location independent on whether the corresponding gene is expressed or not, i.e. information from other reads is not taken into account. Second, in case of multiple possible mappings, the mapping with the fewest mismatches is usually chosen which may lead to wrong assignments due to sequencing errors.
To address these problems, we developed ContextMap which efficiently uses information on the context of a read, i.e. reads mapping to the same expressed region. The context information is used to resolve possible ambiguities and, thus, a much larger degree of ambiguities can be allowed in the initial stage in order to detect all possible candidate positions. Although ContextMap can be used as a stand-alone version using either a genome or transcriptome as input, the version presented in this article is focused on refining initial mappings provided by other mapping algorithms. Evaluation results on simulated sequencing reads showed that the application of ContextMap to either TopHat or MapSplice mappings improved the mapping accuracy of both initial mappings considerably.
In this article, we show that the context of reads mapping to nearby locations provides valuable information for identifying the best unique mapping for a read. Using our method, mappings provided by other state-of-the-art methods can be refined and alignment accuracy can be further improved.
http://www.bio.ifi.lmu.de/ContextMap.
Interferons (IFN) play a pivotal role in innate immunity, orchestrating a cell-intrinsic anti-pathogenic state and stimulating adaptive immune responses. The complex interplay between the primary ...response to IFNs and its modulation by positive and negative feedback loops is incompletely understood. Here, we implement the combination of high-resolution gene-expression profiling of nascent RNA with translational inhibition of secondary feedback by cycloheximide. Unexpectedly, this approach revealed a prominent role of negative feedback mechanisms during the immediate (≤60 min) IFNα response. In contrast, a more complex picture involving both negative and positive feedback loops was observed on IFNγ treatment. IFNγ-induced repression of genes associated with regulation of gene expression, cellular development, apoptosis and cell growth resulted from cycloheximide-resistant primary IFNγ signalling. In silico promoter analysis revealed significant overrepresentation of SP1/SP3-binding sites and/or GC-rich stretches. Although signal transducer and activator of transcription 1 (STAT1)-binding sites were not overrepresented, repression was lost in absence of STAT1. Interestingly, basal expression of the majority of these IFNγ-repressed genes was dependent on STAT1 in IFN-naïve fibroblasts. Finally, IFNγ-mediated repression was also found to be evident in primary murine macrophages. IFN-repressed genes include negative regulators of innate and stress response, and their decrease may thus aid the establishment of a signalling perceptive milieu.
Morphogenesis of herpesviral virions is initiated in the nucleus but completed in the cytoplasm. Mature virions contain more than 25 tegument proteins many of which perform both nuclear and ...cytoplasmic functions suggesting they shuttle between these compartments. While nuclear import of herpesviral proteins was shown to be crucial for viral propagation, active nuclear export and its functional impact are still poorly understood. To systematically analyze nuclear export of tegument proteins present in virions of Herpes simplex virus type 1 (HSV1) and Epstein‐Barr virus (EBV), the Nuclear EXport Trapped by RAPamycin (NEX‐TRAP) was applied. Nine of the 22 investigated HSV1 tegument proteins including pUL4, pUL7, pUL11, pUL13, pUL21, pUL37d11, pUL47, pUL48 and pUS2 as well as 2 out of 6 EBV orthologs harbor nuclear export activity. A functional leucine‐rich nuclear export sequence (NES) recognized by the export factor CRM1/Xpo1 was identified in six of them. The comparison between experimental and bioinformatic data indicates that experimental validation of predicted NESs is required. Mutational analysis of the pUL48/VP16 NES revealed its importance for herpesviral propagation. Together our data suggest that nuclear export is an important feature of the herpesviral life cycle required to co‐ordinate nuclear and cytoplasmic processes.
Herpesviral virions contain numerous tegument proteins with important functions both in nucleus and cytoplasm suggesting they shuttle between these compartments. Unlike nuclear import, nuclear export of tegument proteins is poorly understood. Using the Nuclear EXport Trapped by RAPamycin (NEX‐TRAP) assay, nuclear export activity and the relevant export sequences were identified in several Herpes simplex virus type 1 tegument proteins and their Epstein‐Barr virus orthologs. These results indicate an important role of nuclear export for herpesviral propagation and form the basis for future functional analysis.
Recent advances in high-throughput technology have increased the quantity of available data on protein complexes and stimulated the development of many new prediction methods. In this article, we ...present ProCope, a Java software suite for the prediction and evaluation of protein complexes from affinity purification experiments which integrates the major methods for calculating interaction scores and predicting protein complexes published over the last years. Methods can be accessed via a graphical user interface, command line tools and a Java API. Using ProCope, existing algorithms can be applied quickly and reproducibly on new experimental results, individual steps of the different algorithms can be combined in new and innovative ways and new methods can be implemented and integrated in the existing prediction framework. Availability: Source code and executables are available at http://www.bio.ifi.lmu.de/Complexes/ProCope/ Contact: Caroline.Friedel@bio.ifi.lmu.de
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