PEATmoss (Physcomitrella Expression Atlas Tool): a unified gene expression atlas for the model plant Physcomitrella patens

Physcomitrella patens is a bryophyte model plant that is often used to study plant evolution and development. Its resources are of great importance for comparative genomics and evo‐devo approaches. However, expression data from Physcomitrella patens were so far generated using different gene annotation versions and three different platforms: CombiMatrix and NimbleGen expression microarrays and RNA sequencing. The currently available P. patens expression data are distributed across three tools with different visualization methods to access the data. Here, we introduce an interactive expression atlas, Physcomitrella Expression Atlas Tool (PEATmoss), that unifies publicly available expression data for P. patens and provides multiple visualization methods to query the data in a single web‐based tool. Moreover, PEATmoss includes 35 expression experiments not previously available in any other expression atlas. To facilitate gene expression queries across different gene annotation versions, and to access P. patens annotations and related resources, a lookup database and web tool linked to PEATmoss was implemented. PEATmoss can be accessed at https://peatmoss.online.uni-marburg.de     

Mechanisms governing avian phylosymbiosis: Genetic dissimilarity based on neutral and MHC regions exhibits little relationship with gut microbiome distributions of Galápagos mockingbirds

The gut microbiome of animals, which serves important functions but can also contain potential pathogens, is to varying degrees under host genetic control. This can generate signals of phylosymbiosis, whereby gut microbiome composition matches host phylogenetic structure. However, the genetic mechanisms that generate phylosymbiosis and the scale at which they act remain unclear. Two non‐mutually exclusive hypotheses are that phylosymbiosis is driven by immunogenetic regions such as the major histocompatibility complex (MHC) controlling microbial composition, or by spatial structuring of neutral host genetic diversity via founder effects, genetic drift, or isolation by distance. Alternatively, associations between microbes and host phylogeny may be generated by their spatial autocorrelation across landscapes, rather than the direct effects of host genetics. In this study, we collected MHC, microsatellite, and gut microbiome data from separate individuals belonging to the Galápagos mockingbird species complex, which consists of four allopatrically distributed species. We applied multiple regression with distance matrices and Bayesian inference to test for correlations between average genetic and microbiome similarity across nine islands for which all three levels of data were available. Clustering of individuals by species was strongest when measured with microsatellite markers and weakest for gut microbiome distributions, with intermediate clustering of MHC allele frequencies. We found that while correlations between island‐averaged gut microbiome composition and both microsatellite and MHC dissimilarity existed across species, these relationships were greatly weakened when accounting for geographic distance. Overall, our study finds little support for large‐scale control of gut microbiome composition by neutral or adaptive genetic regions across closely related bird phylogenies, although this does not preclude the possibility that host genetics shapes gut microbiome at the individual level.     

PEtab—Interoperable specification of parameter estimation problems in systems biology

Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been—so far—no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies.     

The cell death protease Kex1p is essential for hypochlorite-induced apoptosis in yeast

Following microbial pathogen invasion, the human immune system of activated phagocytes generates and releases the potent oxidant hypochlorous acid (HOCl), which contributes to the killing of menacing microorganisms. Though tightly controlled, HOCl generation by the myeloperoxidase-hydrogen peroxide-chloride system of neutrophils/monocytes may occur in excess and lead to tissue damage. It is thus of marked importance to delineate the molecular pathways underlying HOCl cytotoxicity in both microbial and human cells. Here, we show that HOCl induces the generation of reactive oxygen species (ROS), apoptotic cell death and the formation of specific HOCl-modified epitopes in the budding yeast Saccharomyces cerevisiae. Interestingly, HOCl cytotoxicity can be prevented by treatment with ROS scavengers, suggesting oxidative stress to mediate the lethal effect. The executing pathway involves the pro-apoptotic protease Kex1p, since its absence diminishes HOCl-induced production of ROS, apoptosis and protein modification. By characterizing HOCl-induced cell death in yeast and identifying a corresponding central executor, these results pave the way for the use of Saccharomyces cerevisiae in HOCl research, not least given that it combines both being a microorganism as well as a model for programmed cell death in higher eukaryotes.     

Membrane protein shaving with thermolysin can be used to evaluate topology predictors

Topology analysis of membrane proteins can be obtained by enzymatic shaving in combination with MS identification of peptides. Ideally, such analysis could provide quite detailed information about the membrane spanning regions. Here, we examine the ability of some shaving enzymes to provide large‐scale analysis of membrane proteome topologies. To compare different shaving enzymes, we first analyzed the detected peptides from two over‐expressed proteins. Second, we analyzed the peptides from non‐over‐expressed Escherichia coli membrane proteins with known structure to evaluate the shaving methods. Finally, the identified peptides were used to test the accuracy of a number of topology predictors. At the end we suggest that the usage of thermolysin, an enzyme working at the natural pH of the cell for membrane shaving, is superior because: (i) we detect a similar number of peptides and proteins using thermolysin and trypsin; (ii) thermolysin shaving can be run at a natural pH and (iii) the incubation time is quite short. (iv) Fewer detected peptides from thermolysin shaving originate from the transmembrane regions. Using thermolysin shaving we can also provide a clear separation between the best and the less accurate topology predictors, indicating that using data from shaving can provide valuable information when developing new topology predictors.     

Transcriptional Cofactor TBLR1 Controls Lipid Mobilization in White Adipose Tissue

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Highlights? TBLR1 controls cAMP-dependent lipolysis in adipocytes ? Adipocyte-specific deletion of TBLR1 in mice impairs fasting-induced lipolysis ? Lack of TBLR1 in adipocytes aggravates diet-induced obesity and metabolic dysfunction ? TBLR1 mRNA levels in WAT are elevated under lipolytic conditions in mice and humans     

Seminal roots of wild and cultivated barley differentially respond to osmotic stress in gene expression,suberization, and hydraulic conductivity

Wild barley, Hordeum vulgare spp. spontaneum, has a wider genetic diversity than its cultivated progeny, Hordeum vulgare spp. vulgare. Osmotic stress leads to a series of different responses in wild barley seminal roots, ranging from no changes in suberization to enhanced endodermal suberization of certain zones and the formation of a suberized exodermis, which was not observed in the modern cultivars studied so far. Further, as a response to osmotic stress, the hydraulic conductivity of roots was not affected in wild barley, but it was 2.5-fold reduced in cultivated barley. In both subspecies, osmotic adjustment by increasing proline concentration and decreasing osmotic potential in roots was observed. RNA-sequencing indicated that the regulation of suberin biosynthesis and water transport via aquaporins were different between wild and cultivated barley. These results indicate that wild barley uses different strategies to cope with osmotic stress compared with cultivated barley. Thus, it seems that wild barley is better adapted to cope with osmotic stress by maintaining a significantly higher hydraulic conductivity of roots during water deficit.