SNARE-mediated plant immune responses at the cell periphery

Pre-invasion resistance responses of Arabidopsis to the non-adapted barley powdery mildew fungus Blumeria graminis fsp hordei (B. g. hordei) require at least four PEN (penetration) genes. PEN1 to PEN4 encode a syntaxin, a ß-glycosyl hydrolase, an ABC transporter, and a γ-glutamylcysteine synthetase, respectively. Epistasis analysis suggests that the PEN1 syntaxin acts in a pathway that is different from a second pathway comprising PEN2, PEN3, and PEN4. Syntaxins are members of the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein super family mediating intracellular vesicle trafficking processes in eukaryotic cells. In animals and yeast, syntaxins direct vesicle trafficking by forming ternary SNARE complexes with a SNAP25 adapter protein and a vesicle-resident v-SNARE (VAMP).The isolation of four independent pen1 alleles, each supporting enhanced cellular entry of B. g. hordei condidiospores, provided for the first time genetic evidence for the possible existence of a vesicle-based and secretory disease resistance mechanism at the cell periphery mediated by a single syntaxin family member. My work aimed to investigate PEN1 structure-function relationships using transgenic Arabidopsis plants that express engineered PEN1 variants at native levels in a pen1-1 null mutant background. Single amino acid substitutions that have previously been reported to affect the activity of syntaxins in Rattus norvegicus, Caenorhabditis elegans, and Drosophila melanogaster were introduced into the PEN1 sequence to generate a first set of PEN1 variants. Functional analysis of the respective Arabidopsis transgenic lines revealed that amino acid residues in and adjacent to the conserved SNARE domain are required for full PEN1 activity in disease resistance to B. g. hordei, thereby supporting the idea that PEN1 functions in this biological process like an authentic syntaxin that involve SNARE-SNARE domain interactions. Additional PEN1 variants involved N-terminal serine substitutions that were previously found to be phosphorylated in cultured Arabidopsis cells upon elicitation with the bacterial-derived flg22 peptide, which is recognized by the plasma membrane-resident FLS2 immune receptor. Phosphorylation of N-terminal residues upon flg22 elicitation has also been reported in the closely related family member, syntaxin SYP122. Transgenic lines expressing PEN1 phospho-mimic variants show wild-type-like PEN1 activity, but elevated B. g. hordei entry rates of lines expressing phospho-knockout derivatives suggest that N-terminal phosphorylation events modulate PEN1 activity during disease resistance responses. Unlike PEN1, a marked pathogen-inducible increase in protein levels of SYP122 was found only at late time points upon B. g. hordei challenge, raising the possibility that the apparent functional diversification of the closely related family members might be due to their differential accumulation patterns. However, constitutive overexpression of SYP122 could not complement the pen1 mutant phenotype although PEN1 overexpressing lines restored disease resistance to B. g. hordei. This suggests that in disease resistance to B. g. hordei the functional diversification between PEN1 and SYP122 is complete. Functional GFP-tagged PEN1 has previously been shown to accumulate beneath attempted powdery mildew entry sites. I found that the candidate interacting SNARE proteins SNAP33 and VAMP722 co-localized with PEN1 at such sites. Interestingly, non-functional PEN1 variants also accumulate at fungal entry sites, indicating that the focal accumulation is not a marker of PEN1 activity. I discuss a model in which PEN1 accumulation at fungal entry sites and PEN1 activity in disease resistance are separate biological processes

Übersicht über Systemidentifikation mit dem Fokus der Inversen Modellierung

The intention behind this literature review is to obtain knowledge about the current status in the field of system identification with special focus put on the inverse modelling step. There the parameters for a model are to be determined by taking data obtained from the true system into account. The application in mind is located in geophysics, especially oil reservoir engineering, so special focus is put on methods which are relevant for system identification problems that arise in that context. Nonetheless the review should be interesting for everybody who works on system identification problems.--- Die Intention des Literaturreviews ist eine Übersicht über den Bereich der Systemidentifikation, im speziellen den Bereich der inversen Modellierung, zu erhalten. In diesem Schritt werden Parameter für ein Modell durch Konditionierung auf gemessene Daten eines realen Systems bestimmt. Das Anwendungsgebiet ist im Bereich der Geophysik, im speziellen Erdöl-Reservoirs, angesiedelt. Daher werden besonders die dort genutzten Methoden betrachtet

Stochastische spektrale Methoden zur linearen Bayes'schen Inferenz

Simulation-based control of dynamic systems is of key importance for many areas of science and industry. To ensure the predictive capabilities, simulation models used for predicting control responses have to be calibrated to available observations. Bayesian approaches to make inference from data on unobservable quantities are used because of their consistent, inherent treatment of diverse sources of uncertainties. Spectral approaches to uncertainty quantification have become popular over the last years. However, their combination with Bayesian inference usually employs expensive probabilistic sampling methods. In this work, a family of linear Bayesian approaches is presented which directly results in a representation of the posterior. A specific implementation is discussed which overcomes some of the difficulties that remained unsolved in related approaches. All implementation details are given, and the applicability is demonstrated on some linear and non-linear numerical examples.Die simulationsbasierte Steuerung von dynamischen Systemen stellt eine Schlüsseltechnologie für weite Bereiche von Forschung und Industrie dar. Um die Vorhersagefähigkeiten von Simulationsmodellen sicherzustellen müssen diese auf die verfügbaren Daten kalibriert werden. Bayes'sche Ansätze für die Erzeugung von Rückschlüssen aus Daten auf unbeobachtbare Modellgrößen sind aufgrund ihrer inhärenten Möglichkeiten, Unsicherheiten in den Rückschlussprozess einzubetten, beliebt. Spektrale Methoden für die Quantifizierung von Unsicherheiten sind über die letzten Jahre populär geworden. Allerdings bedingt ihre Kombination mit Bayes'schen Rückschlussmethoden typischerweise den Einsatz von aufwändigen probabilistischen Abtastverfahren. In dieser Arbeit wird eine Familie von linearen Bayes'schen Vorgehensweisen präsentiert, welche direkt die spektrale à posteriori Repräsentation der unsicheren Zielgröße erzeugen. Eine spezifische Implementierung wird vorgestellt, welche einige der Schwierigkeiten der bisher existierenden Ansätze umgeht. Alle Implementierungsdetails hierzu werden beschrieben, und die Anwendbarkeit anhand von verschiedenen linearen und nicht-linearen numerischen Beispielen belegt

Overview of System Identification with Focus on Inverse Modeling: Literature Review

The intention behind this literature review is to obtain knowledge about the current status in the field of system identification with special focus put on the inverse modelling step. There the parameters for a model are to be determined by taking data obtained from the true system into account. The application in mind is located in geophysics, especially oil reservoir engineering, so special focus is put on methods which are relevant for system identification problems that arise in that context. Nonetheless the review should be interesting for everybody who works on system identification problems.--- Die Intention des Literaturreviews ist eine Übersicht über den Bereich der Systemidentifikation, im speziellen den Bereich der inversen Modellierung, zu erhalten. In diesem Schritt werden Parameter für ein Modell durch Konditionierung auf gemessene Daten eines realen Systems bestimmt. Das Anwendungsgebiet ist im Bereich der Geophysik, im speziellen Erdöl-Reservoirs, angesiedelt. Daher werden besonders die dort genutzten Methoden betrachtet

ESCRT machinery mediates selective microautophagy of endoplasmic reticulum in yeast

ER-phagy, the selective autophagy of endoplasmic reticulum (ER), safeguards organelle homeostasis by eliminating misfolded proteins and regulating ER size. ER-phagy can occur by macroautophagic and microautophagic mechanisms. While dedicated machinery for macro-ER-phagy has been discovered, the molecules and mechanisms mediating micro-ER-phagy remain unknown. Here, we first show that micro-ER-phagy in yeast involves the conversion of stacked cisternal ER into multilamellar ER whorls during microautophagic uptake into lysosomes. Second, we identify the conserved Nem1-Spo7 phosphatase complex and the ESCRT machinery as key components for micro-ER-phagy. Third, we demonstrate that macro- and micro-ER-phagy are parallel pathways with distinct molecular requirements. Finally, we provide evidence that the ESCRT machinery directly functions in scission of the lysosomal membrane to complete the microautophagic uptake of ER. These findings establish a framework for a mechanistic understanding of micro-ER-phagy and, thus, a comprehensive appreciation of the role of autophagy in ER homeostasis

Inverse Problems in a Bayesian Setting

In a Bayesian setting, inverse problems and uncertainty quantification (UQ) --- the propagation of uncertainty through a computational (forward) model --- are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.Comment: arXiv admin note: substantial text overlap with arXiv:1312.504

Radiation mitigation of the intestinal acute radiation injury in mice by 1-[(4-nitrophenyl)sulfonyl]-4-phenylpiperazine.

The objective of the study was to identify the mechanism of action for a radiation mitigator of the gastrointestinal (GI) acute radiation syndrome (ARS), identified in an unbiased high-throughput screen. We used mice irradiated with a lethal dose of radiation and treated with daily injections of the radiation mitigator 1-[(4-nitrophenyl)sulfonyl]-4-phenylpiperazine to study its effects on key pathways involved in intestinal stem cell (ISC) maintenance. RNASeq, quantitative reverse transcriptase-polymerase chain reaction, and immunohistochemistry were performed to identify pathways engaged after drug treatment. Target validation was performed with competition assays, reporter cells, and in silico docking. 1-[(4-Nitrophenyl)sulfonyl]-4-phenylpiperazine activates Hedgehog signaling by binding to the transmembrane domain of Smoothened, thereby expanding the ISC pool, increasing the number of regenerating crypts and preventing the GI-ARS. We conclude that Smoothened is a target for radiation mitigation in the small intestine that could be explored for use in radiation accidents as well as to mitigate normal tissue toxicity during and after radiotherapy of the abdomen