Early manifestations of replicative aging in the yeast Saccharomyces cerevisiae

The yeast Saccharomyces cerevisiae is successfully used as a model organism to find genes responsible for lifespan control of higher organisms. As functional decline of higher eukaryotes can start as early as one quarter of the average lifespan, we asked whether S. cerevisiae can be used to model this manifestation of aging. While the average replicative lifespan of S. cerevisiae mother cells ranges between 15 and 30 division cycles, we found that resistances to certain stresses start to decrease much earlier. Looking into the mechanism, we found that knockouts of genes responsible for mitochondriato-nucleus (retrograde) signaling, RTG1 or RTG3, significantly decrease the resistance of cells that generated more than four daughters, but not of the younger ones. We also found that even young mother cells frequently contain mitochondria with heterogeneous transmembrane potential and that the percentage of such cells correlates with replicative age. Together, these facts suggest that retrograde signaling starts to malfunction in relatively young cells, leading to accumulation of heterogeneous mitochondria within one cell. The latter may further contribute to a decline in stress resistances

MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways

<p>MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many published sources provide information about miRs and their targets. However, bioinformatic tools elucidating higher level impact of the established total miR profiles, are still largely missing. Recently, we developed a method termed OncoFinder enabling quantification of the activities of intracellular molecular pathways basing on gene expression data. Here we propose a new technique, MiRImpact, which enables to link miR expression data with its estimated outcome on the regulation of molecular pathways, like signaling, metabolic, cytoskeleton rearrangement, and DNA repair pathways. MiRImpact uses OncoFinder rationale for pathway activity calculations, with the major distinctions that (i) it deals with the concentrations of miRs - known regulators of gene products participating in molecular pathways, and (ii) miRs are considered as negative regulators of target molecules, if other is not specified. MiRImpact operates with 2 types of databases: for molecular targets of miRs and for gene products participating in molecular pathways. We applied MiRImpact to compare regulation of human bladder cancer-specific signaling pathways at the levels of mRNA and miR expression. We took 2 most complete alternative databases of experimentally validated miR targets – miRTarBase and DianaTarBase, and an OncoFinder database featuring 2725 gene products and 271 signaling pathways. We showed that the impact of miRs is orthogonal to pathway regulation at the mRNA level, which stresses the importance of studying posttranscriptional regulation of gene expression. We also report characteristic set of miR and mRNA regulation features linked with bladder cancer.</p

Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers

Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived “healthy” normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min – 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact “differential” expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice

Measurement of pseudorapidity distributions of charged particles in proton-proton collisions at sqrt(s) = 8 TeV by the CMS and TOTEM experiments

Pseudorapidity ( $\eta$ ) distributions of charged particles produced in proton–proton collisions at a centre-of-mass energy of 8 $~\text {TeV}$ are measured in the ranges $|\eta | < 2.2$ and $5.3 < |\eta | < 6.4$ covered by the CMS and TOTEM detectors, respectively. The data correspond to an integrated luminosity of $\mathcal {L} = 45 \mu {\mathrm {b}}^{-1}$ . Measurements are presented for three event categories. The most inclusive category is sensitive to 91–96 % of the total inelastic proton–proton cross section. The other two categories are disjoint subsets of the inclusive sample that are either enhanced or depleted in single diffractive dissociation events. The data are compared to models used to describe high-energy hadronic interactions. None of the models considered provide a consistent description of the measured distributions