Investigating the validity of current network analysis on static conglomerate networks by protein network stratification

<p>Abstract</p> <p>Background</p> <p>A molecular network perspective forms the foundation of systems biology. A common practice in analyzing protein-protein interaction (PPI) networks is to perform network analysis on a conglomerate network that is an assembly of all available binary interactions in a given organism from diverse data sources. Recent studies on network dynamics suggested that this approach might have ignored the dynamic nature of context-dependent molecular systems.</p> <p>Results</p> <p>In this study, we employed a network stratification strategy to investigate the validity of the current network analysis on conglomerate PPI networks. Using the genome-scale tissue- and condition-specific proteomics data in <it>Arabidopsis thaliana</it>, we present here the first systematic investigation into this question. We stratified a conglomerate <it>A. thaliana </it>PPI network into three levels of context-dependent subnetworks. We then focused on three types of most commonly conducted network analyses, i.e., topological, functional and modular analyses, and compared the results from these network analyses on the conglomerate network and five stratified context-dependent subnetworks corresponding to specific tissues.</p> <p>Conclusions</p> <p>We found that the results based on the conglomerate PPI network are often significantly different from those of context-dependent subnetworks corresponding to specific tissues or conditions. This conclusion depends neither on relatively arbitrary cutoffs (such as those defining network hubs or bottlenecks), nor on specific network clustering algorithms for module extraction, nor on the possible high false positive rates of binary interactions in PPI networks. We also found that our conclusions are likely to be valid in human PPI networks. Furthermore, network stratification may help resolve many controversies in current research of systems biology.</p

Sorting Signals, N-Terminal Modifications and Abundance of the Chloroplast Proteome

Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that ‘spectral counting’ can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models

The feeding tube of cyst nematodes: characterisation of protein exclusion

Plant parasitic nematodes comprise several groups; the most economically damaging of these are the sedentary endoparasites. Sedentary endoparasitic nematodes are obligate biotrophs and modify host root tissue, using a suite of effector proteins, to create a feeding site that is their sole source of nutrition. They feed by withdrawing host cell assimilate from the feeding site though a structure known as the feeding tube. The function, composition and molecular characteristics of feeding tubes are poorly characterised. It is hypothesised that the feeding tube facilitates uptake of host cell assimilate by acting as a molecular sieve. Several studies, using molecular mass as the sole indicator of protein size, have given contradictory results about the exclusion limits of the cyst nematode feeding tube. In this study we propose a method to predict protein size, based on protein database coordinates in silico. We tested the validity of these predictions using travelling wave ion mobility spectrometry--mass spectrometry, where predictions and measured values were within approximately 6%. We used the predictions, coupled with mass spectrometry, analytical ultracentrifugation and protein electrophoresis, to resolve previous conflicts and define the exclusion characteristics of the cyst nematode feeding tube. Heterogeneity was tested in the liquid, solid and gas phase to provide a comprehensive evaluation of three proteins of particular interest to feeding tube size exclusion, GFP, mRFP and Dual PI. The data and procedures described here could be applied to the design of plant expressed defence compounds intended for uptake into cyst nematodes. We also highlight the need to assess protein heterogeneity when creating novel fusion proteins

S151A δ-sarcoglycan mutation causes a mild phenotype of cardiomyopathy in mice

So far, the role of mutations in the δ-sarcogylcan (Sgcd) gene in causing autosomal dominant dilated cardiomyopathy (DCM) remains inconclusive. A p.S151A missense mutation in exon 6 of the Sgcd gene was reported to cause severe isolated autosomal dominant DCM without affecting skeletal muscle. This is controversial to our previous findings in a large consanguineous family where this p.S151A mutation showed no relevance for cardiac disease. In this study, the potential of the p.S151A mutation to cause DCM was investigated by using two different approaches: (1) engineering and characterization of heterozygous knock-in (S151A-) mice carrying the p.S151A mutation and (2) evaluation of the potential of adeno-associated virus (AAV) 9-based cardiac-specific transfer of p.S151A-mutated Sgcd cDNA to rescue the cardiac phenotype in Sgcd-deficient (Sgcd-null) mice as it has been demonstrated for intact, wild-type Sgcd cDNA. Heterozygous S151A knock-in mice developed a rather mild phenotype of cardiomyopathy. Increased heart to body weight suggests cardiac enlargement in 1-year-old S151A knock-in mice. However, at this age cardiac function, assessed by echocardiography, is maintained and histopathology completely absent. Myocardial expression of p.S151A cDNA, similar to intact Sgcd cDNA, restores cardiac function, although not being able to prevent myocardial histopathology in Sgcd-null mice completely. Our results suggest that the p.S151A mutation causes a mild, subclinical phenotype of cardiomyopathy, which is prone to be overseen in patients carrying such sequence variants. Furthermore, this study shows the suitability of an AAV-mediated cardiac gene transfer approach to analyze whether a sequence variant is a disease-causing mutation

Left ventricular enlargement in coxsackievirus-B3 induced chronic myocarditis - ongoing inflammation and an imbalance of the matrix degrading system

Enteroviruses, especially Coxsackie B3 virus (CVB-3), cause acute viral myocarditis, but the detailed mechanisms leading to chronic left ventricular dysfunction and dilatation remain elusive. Myocardial tissues of CVB-3 infected and sham infected male swr/J mice were analyzed after hemodynamic evaluation on days 4, 7, and 28 p.i. by RT-PCR, gelatin zymography, ELISA, immunohisto-chemistry, sirius red staining, and luxol fast blue staining. In the early phase after infection an abnormal diastolic function was the main hemodynamic finding. CVB-3 infection caused impairment of left ventricular function combined with ventricular dilatation 7 and 28 days post-infection. These hemodynamic findings were associated with relevant upregulation of different cytokines (IL-1beta, IL-6, IL-10, INF-gamma, TNF-alpha) in the acute phase with persistent over-expression of IL-6, IL-10, and INF-gamma in the chronic phase. This virus induced myocardial inflammation was linked to a significant induced MMP/TIMP-system (MMP-2,-3,-8, TIMP-1, uPA, tPA - mRNA-expression, MMP-2-activity) in the acute and chronic phase leading to imbalance in the MMP/TIMP-ratio at day 28. This imbalance in the MMP/TIMP-system was significantly correlated to the development of ventricular dilatation. Viral persistence induces chronic myocardial inflammation and an imbalance of the matrix degrading system, associated with the development of left ventricular dysfunction and dilatation in chronic murine myocarditis

Spatiotemporal modelling of hormonal crosstalk explains the level and patterning of hormones and gene expression in Arabidopsis thaliana wildtype and mutant roots

Patterning in Arabidopsis root development is coordinated via a localized auxin concentration maximum in the root tip, requiring the regulated expression of specific genes. However, little is known about how hormone and gene expression patterning is generated. Using a variety of experimental data, we develop a spatiotemporal hormonal crosstalk model that describes the integrated action of auxin, ethylene and cytokinin signalling, the POLARIS protein, and the functions of PIN and AUX1 auxin transporters. We also conduct novel experiments to confirm our modelling predictions. The model reproduces auxin patterning and trends in wild-type and mutants; reveals that coordinated PIN and AUX1 activities are required to generate correct auxin patterning; correctly predicts shoot to root auxin flux, auxin patterning in the aux1 mutant, the amounts of cytokinin, ethylene and PIN protein, and PIN protein patterning in wild-type and mutant roots. Modelling analysis further reveals how PIN protein patterning is related to the POLARIS protein through ethylene signalling. Modelling prediction of the patterning of POLARIS expression is confirmed experimentally. Our combined modelling and experimental analysis reveals that a hormonal crosstalk network regulates the emergence of patterns and levels of hormones and gene expression in wild-type and mutants