Sequential Delivery of Host-Induced Virulence Effectors by Appressoria and Intracellular Hyphae of the Phytopathogen Colletotrichum higginsianum

Phytopathogens secrete effector proteins to manipulate their hosts for effective colonization. Hemibiotrophic fungi must maintain host viability during initial biotrophic growth and elicit host death for subsequent necrotrophic growth. To identify effectors mediating these opposing processes, we deeply sequenced the transcriptome of Colletotrichum higginsianum infecting Arabidopsis. Most effector genes are host-induced and expressed in consecutive waves associated with pathogenic transitions, indicating distinct effector suites are deployed at each stage. Using fluorescent protein tagging and transmission electron microscopy-immunogold labelling, we found effectors localised to stage-specific compartments at the host-pathogen interface. In particular, we show effectors are focally secreted from appressorial penetration pores before host invasion, revealing new levels of functional complexity for this fungal organ. Furthermore, we demonstrate that antagonistic effectors either induce or suppress plant cell death. Based on these results we conclude that hemibiotrophy in Colletotrichum is orchestrated through the coordinated expression of antagonistic effectors supporting either cell viability or cell death

Modulation of γ-Secretase Activity by Multiple Enzyme-Substrate Interactions: Implications in Pathogenesis of Alzheimer's Disease

BACKGROUND: We describe molecular processes that can facilitate pathogenesis of Alzheimer's disease (AD) by analyzing the catalytic cycle of a membrane-imbedded protease γ-secretase, from the initial interaction with its C99 substrate to the final release of toxic Aβ peptides. RESULTS: The C-terminal AICD fragment is cleaved first in a pre-steady-state burst. The lowest Aβ42/Aβ40 ratio is observed in pre-steady-state when Aβ40 is the dominant product. Aβ42 is produced after Aβ40, and therefore Aβ42 is not a precursor for Aβ40. The longer more hydrophobic Aβ products gradually accumulate with multiple catalytic turnovers as a result of interrupted catalytic cycles. Saturation of γ-secretase with its C99 substrate leads to 30% decrease in Aβ40 with concomitant increase in the longer Aβ products and Aβ42/Aβ40 ratio. To different degree the same changes in Aβ products can be observed with two mutations that lead to an early onset of AD, ΔE9 and G384A. Four different lines of evidence show that γ-secretase can bind and cleave multiple substrate molecules in one catalytic turnover. Consequently depending on its concentration, NotchΔE substrate can activate or inhibit γ-secretase activity on C99 substrate. Multiple C99 molecules bound to γ-secretase can affect processive cleavages of the nascent Aβ catalytic intermediates and facilitate their premature release as the toxic membrane-imbedded Aβ-bundles. CONCLUSIONS: Gradual saturation of γ-secretase with its substrate can be the pathogenic process in different alleged causes of AD. Thus, competitive inhibitors of γ-secretase offer the best chance for a successful therapy, while the noncompetitive inhibitors could even facilitate development of the disease by inducing enzyme saturation at otherwise sub-saturating substrate. Membrane-imbedded Aβ-bundles generated by γ-secretase could be neurotoxic and thus crucial for our understanding of the amyloid hypothesis and AD pathogenesis

The structure and function of Alzheimer's gamma secretase enzyme complex

The production and accumulation of the beta amyloid protein (Aβ) is a key event in the cascade of oxidative and inflammatory processes that characterizes Alzheimer’s disease (AD). A multi-subunit enzyme complex, referred to as gamma (γ) secretase, plays a pivotal role in the generation of Aβ from its parent molecule, the amyloid precursor protein (APP). Four core components (presenilin, nicastrin, aph-1, and pen-2) interact in a high-molecular-weight complex to perform intramembrane proteolysis on a number of membrane-bound proteins, including APP and Notch. Inhibitors and modulators of this enzyme have been assessed for their therapeutic benefit in AD. However, although these agents reduce Aβ levels, the majority have been shown to have severe side effects in pre-clinical animal studies, most likely due to the enzymes role in processing other proteins involved in normal cellular function. Current research is directed at understanding this enzyme and, in particular, at elucidating the roles that each of the core proteins plays in its function. In addition, a number of interacting proteins that are not components of γ-secretase also appear to play important roles in modulating enzyme activity. This review will discuss the structural and functional complexity of the γ-secretase enzyme and the effects of inhibiting its activity

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Alignment of the ALICE Inner Tracking System with cosmic-ray tracks

37 pages, 15 figures, revised version, accepted by JINSTALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 micron in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10^5 charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.Peer reviewe