439 research outputs found
Editorial : Autophagy : from big data to physiological significance
Autophagy is a fundamental catabolic process where cytoplasmic components are sequestered into double-membrane vesicles called autophagosomes, which then fuse with lysosomes and their content is degraded. Our knowledge about autophagy sharply increased during the last decade. This significant progress helped us to understand better the molecular mechanisms of autophagy and to elucidate its role in health and disease. This special issue contains a collection of three original research papers and 12 review articles covering a broad range of topics highlighting how big data and screening approaches can help toward uncovering the molecular mechanisms of autophagy
Selective Autophagy in Drosophila
Autophagy is an evolutionarily conserved process of cellular self-eating and is a major pathway for degradation of cytoplasmic material by the lysosomal machinery. Autophagy functions as a cellular response in nutrient starvation, but it is also associated with the removal of protein aggregates and damaged organelles and therefore plays an important role in the quality control of proteins and organelles. Although it was initially believed that autophagy occurs randomly in the cell, during the last years, there is growing evidence that sequestration and degradation of cytoplasmic material by autophagy can be selective. Given the important role of autophagy and selective autophagy in several disease-related processes such as neurodegeneration, infections, and tumorigenesis, it is important to understand the molecular mechanisms of selective autophagy, especially at the organismal level. Drosophila is an excellent genetically modifiable model organism exhibiting high conservation in the autophagic machinery. However, the regulation and mechanisms of selective autophagy in Drosophila have been largely unexplored. In this paper, I will present an overview of the current knowledge about selective autophagy in Drosophila
Forecasting Mortality Rate Using a Neural Network with Fuzzy Inference System
Various methods have been developed to improve mortality forecasts. The authors proposed a neuro-fuzzy model to forecast the mortality. The forecasting of mortality is curried out by an ANFIS model which uses a first order Sugeno-type FIS. The model predicts the yearly mortality in a one step ahead prediction scheme. The method of trial and error was used in order to decide the type of membership function that describe better the model and provides the minimum error. The output of the models is the next year�s mortality. The results were presented and compared based on three different kinds of errors: RMSE, MAE, and MAPE. The ANFIS model gives good results for the case of two gbell membership functions and 500 epochs. Finally, the ANFIS model gives better results than the AR and ARMA model.ANFIS, Forecasting, Mortality, Modeling.
Time Flies: Autophagy During Ageing in Drosophila
The process of ageing compromises the age-associated decrease in fertility, gradual loss of function, and increased vulnerability to disease, which progressively diminishes the capability of an organism to survive [1-3]. Unsurprisingly, in the past years it has been of great interest to understand which factors influence this inevitable and complex process. As a result a wide array of molecular and cellular damages has been identified and shown to accumulate during ageing. The lifelong accumulation of such damages will eventually result in frailty and disease [4]. The variety of identified age-dependent damages has given rise to different theories for molecular ageing mechanisms. These mechanisms include decreased cellular capacity to deal with DNA damage, and decline in cellular division capacity, which is linked to the progressive shortening of telomeres upon each cell cycle. Also an increased accumulation of damaged mitochondria and the involved increase in reactive oxygen species (ROS) production and decline in ATP synthesis has been shown to occur over time (reviewed in [5]). One of the phenotypic hallmarks of aged cells is the intracellular accumulation of damaged proteins and therefore protein turnover/protein degradation has attracted attention over the last years [2].
At the same time, forward genetics have allowed to investigate single gene alterations and their influence on lifespan of whole organisms. Even though the ageing process is without doubt influenced by stochastic and environmental factors, single gene mutations were shown to extend lifespan in worms, flies, and mice, suggesting the existence of a central process of ageing [6, 7]. Many of the genetic manipulations that alter longevity affect metabolism, nutrient sensing and stress response pathways. As all these pathways are connected to autophagy (an important player also in protein turnover), the question about the role of autophagy in ageing has come more and more to the fore. In this chapter we will focus on how research conducted in the excellent genetic model system Drosophila melanogaster has contributed to understand more about the interplay of autophagy and ageing
iLIR : a web resource for prediction of Atg8-family interacting proteins
Macroautophagy was initially considered to be a nonselective process for bulk breakdown of cytosolic material. However, recent evidence points toward a selective mode of autophagy mediated by the so-called selective autophagy receptors (SARs). SARs act by recognizing and sorting diverse cargo substrates (e.g., proteins, organelles, pathogens) to the autophagic machinery. Known SARs are characterized by a short linear sequence motif (LIR-, LRS-, or AIM-motif) responsible for the interaction between SARs and proteins of the Atg8 family. Interestingly, many LIR-containing proteins (LIRCPs) are also involved in autophagosome formation and maturation and a few of them in regulating signaling pathways. Despite recent research efforts to experimentally identify LIRCPs, only a few dozen of this class of—often unrelated—proteins have been characterized so far using tedious cell biological, biochemical, and crystallographic approaches. The availability of an ever-increasing number of complete eukaryotic genomes provides a grand challenge for characterizing novel LIRCPs throughout the eukaryotes. Along these lines, we developed iLIR, a freely available web resource, which provides in silico tools for assisting the identification of novel LIRCPs. Given an amino acid sequence as input, iLIR searches for instances of short sequences compliant with a refined sensitive regular expression pattern of the extended LIR motif (xLIR-motif) and retrieves characterized protein domains from the SMART database for the query. Additionally, iLIR scores xLIRs against a custom position-specific scoring matrix (PSSM) and identifies potentially disordered subsequences with protein interaction potential overlapping with detected xLIR-motifs. Here we demonstrate that proteins satisfying these criteria make good LIRCP candidates for further experimental verification. Domain architecture is displayed in an informative graphic, and detailed results are also available in tabular form. We anticipate that iLIR will assist with elucidating the full complement of LIRCPs in eukaryotes
iLIR@viral : a web resource for LIR motif-containing proteins in viruses
Autophagy has been shown to mediate the lysosomal degradation of pathogenic bacteria and viruses (xenophagy), and to contribute to the activation of innate and adaptative immune responses. Autophagy can serve as an antiviral defense mechanism but also as a proviral process during infection. ATG8-family proteins play a central role in the autophagy process due to their ability to interact with components of the autophagy machinery as well as selective autophagy receptors and adaptor proteins. Such interactions are usually mediated through LC3-interacting region (LIR) motifs. So far, only one viral protein has been experimentally shown to have a functional LIR motif, leaving open a vast field for investigation. Here, we have developed the iLIR@viral database (http://ilir.uk/virus/) as a freely accessible web resource listing all the putative canonical LIR motifs identified in viral proteins. Additionally, we used a curated text-mining analysis of the literature to identify novel putative LIR motif-containing protein (LICRPs) in viruses. We anticipate that iLIR@viral will assist with elucidating the full complement of LIRCPs in viruses
3D freeform surfaces from planar sketches using neural networks
A novel intelligent approach into 3D freeform surface reconstruction from planar sketches is proposed. A multilayer perceptron (MLP) neural network is employed to induce 3D freeform surfaces from planar freehand curves. Planar curves were used to represent the boundaries of a freeform surface patch. The curves were varied iteratively and sampled to produce training data to train and test the neural network. The obtained results demonstrate that the network successfully learned the inverse-projection map and correctly inferred the respective surfaces from fresh curves
The selectivity and specificity of autophagy in drosophila
Autophagy is a process of cellular self-degradation and is a major pathway for elimination of cytoplasmic material by the lysosomes. Autophagy is responsible for the degradation of damaged organelles and protein aggregates and therefore plays a significant role in cellular homeostasis. Despite the initial belief that autophagy is a nonselective bulk process, there is growing evidence during the last years that sequestration and degradation of cellular material by autophagy can be accomplished in a selective and specific manner. Given the role of autophagy and selective autophagy in several disease related processes such as tumorigenesis, neurodegeneration and infections, it is very important to dissect the molecular mechanisms of selective autophagy, in the context of the system and the organism. An excellent genetically tractable model organism to study autophagy is Drosophila, which appears to have a highly conserved autophagic machinery compared with mammals. However, the mechanisms of selective autophagy in Drosophila have been largely unexplored. The aim of this review is to summarize recent discoveries about the selectivity of autophagy in Drosophila
Selective autophagic degradation of the IKK complex in Drosophila is mediated by Kenny/IKKy to control inflammation
Implication of autophagy in the downregulation of immune signalling pathways through the degradation of their components constitutes an emerging field of investigation. Our work showed that the selective interaction of Drosophila Kenny/IKK with the autophagic machinery is required for the degradation of the IKK complex. This regulatory mechanism is essential for the downregulation of the IMD immune pathway in response to commensal microbiota to prevent inflammatio
Impact of autophagy impairment on experience- and diet-related synaptic plasticity
The beneficial effects of diet and exercise on brain function are traditionally attributed to the enhancement of autophagy, which plays a key role in neuroprotection via the degradation of potentially harmful intracellular structures. The molecular machinery of autophagy has also been suggested to influence synaptic signaling via interaction with trafficking and endocytosis of synaptic vesicles and proteins. Still, the role of autophagy in the regulation of synaptic plasticity remains elusive, especially in the mammalian brain. We explored the impact of autophagy on synaptic transmission and homeostatic and acute synaptic plasticity using transgenic mice with induced deletion of the Beclin1 protein. We observed down-regulation of glutamatergic and up-regulation of GABAergic synaptic currents and impairment of long-term plasticity in the neocortex and hippocampus of Beclin1-deficient mice. Beclin1 deficiency also significantly reduced the effects of environmental enrichment, caloric restriction and its pharmacological mimetics (metformin and resveratrol) on synaptic transmission and plasticity. Taken together, our data strongly support the importance of autophagy in the regulation of excitatory and inhibitory synaptic transmission and synaptic plasticity in the neocortex and hippocampus. Our results also strongly suggest that the positive modulatory actions of metformin and resveratrol in acute and homeostatic synaptic plasticity, and therefore their beneficial effects on brain function, occur via the modulation of autophagy
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