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Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.
Epigenetic alterations may contribute to the generation of cancer cells in a multi-step process of tumorigenesis following irradiation of normal body cells. Primary human fibroblasts with intact cell cycle checkpoints were used as a model to test whether X-ray irradiation with 2 and 4 Gray induces direct epigenetic effects (within the first cell cycle) in the exposed cells. ELISA-based fluorometric assays were consistent with slightly reduced global DNA methylation and hydroxymethylation, however the observed between-group differences were usually not significant. Similarly, bisulfite pyrosequencing of interspersed LINE-1 repeats and centromeric α-satellite DNA did not detect significant methylation differences between irradiated and non-irradiated cultures. Methylation of interspersed ALU repeats appeared to be slightly increased (one percentage point; p = 0.01) at 6 h after irradiation with 4 Gy. Single-cell analysis showed comparable variations in repeat methylation among individual cells in both irradiated and control cultures. Radiation-induced changes in global repeat methylation, if any, were much smaller than methylation variation between different fibroblast strains. Interestingly, α-satellite DNA methylation positively correlated with gestational age. Finally, 450K methylation arrays mainly targeting genes and CpG islands were used for global DNA methylation analysis. There were no detectable methylation differences in genic (promoter, 5' UTR, first exon, gene body, 3' UTR) and intergenic regions between irradiated and control fibroblast cultures. Although we cannot exclude minor effects, i.e. on individual CpG sites, collectively our data suggest that global DNA methylation remains rather stable in irradiated normal body cells in the early phase of DNA damage response.
Arboreal spiders in deciduous and coniferous trees were investigated on their distribution and diversity. Insecticidal knock-down was used to comprehensively sample spiders from 175 trees from 2001 to 2003 in the Białowieża forest and three remote forests in Poland. We identified 140 species from 9273 adult spiders. Spider communities were distinguished between deciduous and coniferous trees. The richest fauna was collected from Quercus where beta diversity was also highest. A tree-species-specific pattern was clearly observed for Alnus, Carpinus, Picea and Pinus trees and also for those tree species that were fogged in only four or three replicates, namely Betula and Populus. This hitherto unrecognised association was mainly due to the community composition of common species identified in a Dufrene-Legendre indicator species analysis. It was not caused by spatial or temporal autocorrelation. Explaining tree-species specificity for generalist predators like spiders is difficult and has to involve physical and ecological tree parameters like linkage with the abundance of prey species. However, neither did we find a consistent correlation of prey group abundances with spiders nor could differences in spider guild composition explain the observed pattern. Our results hint towards the importance of deterministic mechanisms structuring communities of generalist canopy spiders although the casual relationship is not yet understood.
Some members of the physiological human microbiome occasionally cause life-threatening disease even in immunocompetent individuals. A prime example of such a commensal pathogen is Neisseria meningitidis, which normally resides in the human nasopharynx but is also a leading cause of sepsis and epidemic meningitis. Using N. meningitidis as model organism, we tested the hypothesis that virulence of commensal pathogens is a consequence of within host evolution and selection of invasive variants due to mutations at contingency genes, a mechanism called phase variation. In line with the hypothesis that phase variation evolved as an adaptation to colonize diverse hosts, computational comparisons of all 27 to date completely sequenced and annotated meningococcal genomes retrieved from public databases showed that contingency genes are indeed enriched for genes involved in host interactions. To assess within-host genetic changes in meningococci, we further used ultra-deep whole-genome sequencing of throat-blood strain pairs isolated from four patients suffering from invasive meningococcal disease. We detected up to three mutations per strain pair, affecting predominantly contingency genes involved in type IV pilus biogenesis. However, there was not a single (set) of mutation(s) that could invariably be found in all four pairs of strains. Phenotypic assays further showed that these genetic changes were generally not associated with increased serum resistance, higher fitness in human blood ex vivo or differences in the interaction with human epithelial and endothelial cells in vitro. In conclusion, we hypothesize that virulence of meningococci results from accidental emergence of invasive variants during carriage and without within host evolution of invasive phenotypes during disease progression in vivo.
Comparison of the central human and mouse platelet signaling cascade by systems biological analysis
(2020)
Background
Understanding the molecular mechanisms of platelet activation and aggregation is of high interest for basic and clinical hemostasis and thrombosis research. The central platelet protein interaction network is involved in major responses to exogenous factors. This is defined by systemsbiological pathway analysis as the central regulating signaling cascade of platelets (CC).
Results
The CC is systematically compared here between mouse and human and major differences were found. Genetic differences were analysed comparing orthologous human and mouse genes. We next analyzed different expression levels of mRNAs. Considering 4 mouse and 7 human high-quality proteome data sets, we identified then those major mRNA expression differences (81%) which were supported by proteome data. CC is conserved regarding genetic completeness, but we observed major differences in mRNA and protein levels between both species. Looking at central interactors, human PLCB2, MMP9, BDNF, ITPR3 and SLC25A6 (always Entrez notation) show absence in all murine datasets. CC interactors GNG12, PRKCE and ADCY9 occur only in mice. Looking at the common proteins, TLN1, CALM3, PRKCB, APP, SOD2 and TIMP1 are higher abundant in human, whereas RASGRP2, ITGB2, MYL9, EIF4EBP1, ADAM17, ARRB2, CD9 and ZYX are higher abundant in mouse. Pivotal kinase SRC shows different regulation on mRNA and protein level as well as ADP receptor P2RY12.
Conclusions
Our results highlight species-specific differences in platelet signaling and points of specific fine-tuning in human platelets as well as murine-specific signaling differences.
Objective
The biological interpretation of gene expression measurements is a challenging task. While ordination methods are routinely used to identify clusters of samples or co-expressed genes, these methods do not take sample or gene annotations into account. We aim to provide a tool that allows users of all backgrounds to assess and visualize the intrinsic correlation structure of complex annotated gene expression data and discover the covariates that jointly affect expression patterns.
Results
The Bioconductor package covRNA provides a convenient and fast interface for testing and visualizing complex relationships between sample and gene covariates mediated by gene expression data in an entirely unsupervised setting. The relationships between sample and gene covariates are tested by statistical permutation tests and visualized by ordination. The methods are inspired by the fourthcorner and RLQ analyses used in ecological research for the analysis of species abundance data, that we modified to make them suitable for the distributional characteristics of both, RNA-Seq read counts and microarray intensities, and to provide a high-performance parallelized implementation for the analysis of large-scale gene expression data on multi-core computational systems. CovRNA provides additional modules for unsupervised gene filtering and plotting functions to ensure a smooth and coherent analysis workflow.
Normal human brain development is dependent on highly dynamic epigenetic processes for spatial and temporal gene regulation. Recent work identified wide-spread changes in DNA methylation during fetal brain development. We profiled CpG methylation in frontal cortex of 27 fetuses from gestational weeks 12-42, using Illumina 450K methylation arrays. Sites showing genome-wide significant correlation with gestational age were compared to a publicly available data set from gestational weeks 3-26. Altogether, we identified 2016 matching developmentally regulated differentially methylated positions (m-dDMPs): 1767 m-dDMPs were hypermethylated and 1149 hypomethylated during fetal development. M-dDMPs are underrepresented in CpG islands and gene promoters, and enriched in gene bodies. They appear to cluster in certain chromosome regions. M-dDMPs are significantly enriched in autism-associated genes and CpGs. Our results promote the idea that reduced methylation dynamics during fetal brain development may predispose to autism. In addition, m-dDMPs are enriched in genes with human-specific brain expression patterns and/or histone modifications. Collectively, we defined a subset of dDMPs exhibiting constant methylation changes from early to late pregnancy. The same epigenetic mechanisms involving methylation changes in cis-regulatory regions may have been adopted for human brain evolution and ontogeny.
Freshly cut beech deadwood was enriched in the canopy and on the ground in three cultural landscapes in Germany (Swabian Alb, Hainich-Dun, Schorfheide-Chorin) in order to analyse the diversity, distribution and interaction of wood-inhabiting fungi and beetles. After two years of wood decay 83 MOTUs (Molecular Operational Taxonomic Units) from 28 wood samples were identified. Flight Interception Traps (FITs) installed adjacent to the deadwood enrichments captured 29.465 beetles which were sorted to 566 species. Geographical 'region' was the main factor determining both beetle and fungal assemblages. The proportions of species occurring in all regions were low. Statistic models suggest that assemblages of both taxa differed between stratum and management praxis but their strength varied among regions. Fungal assemblages in Hainich-Dun, for which the data was most comprehensive, discriminated unmanaged from extensively managed and age-class forests (even-aged timber management) while canopy communities differed not from those near the ground. In contrast, the beetle assemblages at the same sites showed the opposite pattern. We pursued an approach in the search for fungus-beetle associations by computing cross correlations and visualize significant links in a network graph. These correlations can be used to formulate hypotheses on mutualistic relationships for example in respect to beetles acting as vectors of fungal spores.
Each positive well in ELISPOT assays contains spots of variable sizes that can range from tens of micrometers up to a millimeter in diameter. Therefore, when it comes to counting these spots the decision on setting the lower and the upper spot size thresholds to discriminate between non-specific background noise, spots produced by individual T cells, and spots formed by T cell clusters is critical. If the spot sizes follow a known statistical distribution, precise predictions on minimal and maximal spot sizes, belonging to a given T cell population, can be made. We studied the size distributional properties of IFN-γ, IL-2, IL-4, IL-5 and IL-17 spots elicited in ELISPOT assays with PBMC from 172 healthy donors, upon stimulation with 32 individual viral peptides representing defined HLA Class I-restricted epitopes for CD8 cells, and with protein antigens of CMV and EBV activating CD4 cells. A total of 334 CD8 and 80 CD4 positive T cell responses were analyzed. In 99.7% of the test cases, spot size distributions followed Log Normal function. These data formally demonstrate that it is possible to establish objective, statistically validated parameters for counting T cell ELISPOTs.
Using Illumina 450K arrays, 1.85% of all analyzed CpG sites were significantly hypermethylated and 0.31% hypomethylated in fetal Down syndrome (DS) cortex throughout the genome. The methylation changes on chromosome 21 appeared to be balanced between hypo- and hyper-methylation, whereas, consistent with prior reports, all other chromosomes showed 3-11times more hyper- than hypo-methylated sites. Reduced NRSF/REST expression due to upregulation of DYRK1A (on chromosome 21q22.13) and methylation of REST binding sites during early developmental stages may contribute to this genome-wide excess of hypermethylated sites. Upregulation of DNMT3L (on chromosome 21q22.4) could lead to de novo methylation in neuroprogenitors, which then persists in the fetal DS brain where DNMT3A and DNMT3B become downregulated. The vast majority of differentially methylated promoters and genes was hypermethylated in DS and located outside chromosome 21, including the protocadherin gamma (PCDHG) cluster on chromosome 5q31, which is crucial for neural circuit formation in the developing brain. Bisulfite pyrosequencing and targeted RNA sequencing showed that several genes of PCDHG subfamilies A and B are hypermethylated and transcriptionally downregulated in fetal DS cortex. Decreased PCDHG expression is expected to reduce dendrite arborization and growth in cortical neurons. Since constitutive hypermethylation of PCDHG and other genes affects multiple tissues, including blood, it may provide useful biomarkers for DS brain development and pharmacologic targets for therapeutic interventions.