Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.

The free radical theory of aging is based on the idea that reactive oxygen species (ROS) may lead to the accumulation of age-related protein oxidation. Because the majority of cellular ROS is generated at the respiratory electron transport chain, this study focuses on the mitochondrial proteome of the aging model Podospora anserina as target for ROS-induced damage. To ensure the detection of even low abundant modified peptides, separation by long gradient nLC-ESI-MS/MS and an appropriate statistical workflow for iTRAQ quantification was developed. Artificial protein oxidation was minimized by establishing gel-free sample preparation in the presence of reducing and iron-chelating agents. This first large scale, oxidative modification-centric study for P. anserina allowed the comprehensive quantification of 22 different oxidative amino acid modifications, and notably the quantitative comparison of oxidized and nonoxidized protein species. In total 2341 proteins were quantified. For 746 both protein species (unmodified and oxidatively modified) were detected and the modification sites determined. The data revealed that methionine residues are preferably oxidized. Further prominent identified modifications in decreasing order of occurrence were carbonylation as well as formation of N-formylkynurenine and pyrrolidinone. Interestingly, for the majority of proteins a positive correlation of changes in protein amount and oxidative damage were noticed, and a general decrease in protein amounts at late age. However, it was discovered that few proteins changed in oxidative damage in accordance with former reports. Our data suggest that P. anserina is efficiently capable to counteract ROS-induced protein damage during aging as long as protein de novo synthesis is functioning, ultimately leading to an overall constant relationship between damaged and undamaged protein species. These findings contradict a massive increase in protein oxidation during aging and rather

Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wildtype transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.

Summary: We introduce Path2PPI, a new R package to identify protein–protein interaction (PPI) networks for fully sequenced organisms for which nearly none PPI are known. Path2PPI predicts PPI networks based on sets of proteins from well-established model organisms, providing an intuitive visualization and usability. It can be used to combine and transfer information of a certain pathway or biological process from several reference organisms to one target organism.Availability and implementation: Path2PPI is an open-source tool implemented in R. It can be obtained from the Bioconductor project: http://bioconductor.org/packages/Path2PPI/Contact: ina.koch@bioinformatik.uni-frankfurt.deSupplementary information: Supplementary data are available at Bioinformatics online.

BackgroundAutophagy is a conserved molecular pathway involved in the degradation and recycling of cellular components. It is active either as response to starvation or molecular damage. Evidence is emerging that autophagy plays a key role in the degradation of damaged cellular components and thereby affects aging and lifespan control. In earlier studies, it was found that autophagy in the aging model Podospora anserina acts as a longevity assurance mechanism. However, only little is known about the individual components controlling autophagy in this aging model. Here, we report a biochemical and bioinformatics study to detect the protein-protein interaction (PPI) network of P. anserina combining experimental and theoretical methods.ResultsWe constructed the PPI network of autophagy in P. anserina based on the corresponding networks of yeast and human. We integrated PaATG8 interaction partners identified in an own yeast two-hybrid analysis using ATG8 of P. anserina as bait. Additionally, we included age-dependent transcriptome data. The resulting network consists of 89 proteins involved in 186 interactions. We applied bioinformatics approaches to analyze the network topology and to prove that the network is not random, but exhibits biologically meaningful properties. We identified hub proteins which play an essential role in the network as well as seven putative sub-pathways, and interactions which are likely to be evolutionary conserved amongst species. We confirmed that autophagy-associated genes are significantly often up-regulated and co-expressed during aging of P. anserina.ConclusionsWith the present study, we provide a comprehensive biological network of the autophagy pathway in P. anserina comprising PPI and gene expression data. It is based on computational prediction as well as experimental data. We identified sub-pathways, important hub proteins, and evolutionary conserved interactions. The network clearly illustrates the relation of autophagy to aging processes and enables further specific studies to understand autophagy and aging in P. anserina as well as in other systems.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1603-2) contains supplementary material, which is available to authorized users.