Amyloid-β acts as a regulator of neurotransmitter release disrupting the interaction between synaptophysin and VAMP2.

BACKGROUND: It is becoming increasingly evident that deficits in the cortex and hippocampus at early stages of dementia in Alzheimer's disease (AD) are associated with synaptic damage caused by oligomers of the toxic amyloid-β peptide (Aβ42). However, the underlying molecular and cellular mechanisms behind these deficits are not fully understood. Here we provide evidence of a mechanism by which Aβ42 affects synaptic transmission regulating neurotransmitter release. METHODOLOGY/FINDINGS: We first showed that application of 50 nM Aβ42 in cultured neurones is followed by its internalisation and translocation to synaptic contacts. Interestingly, our results demonstrate that with time, Aβ42 can be detected at the presynaptic terminals where it interacts with Synaptophysin. Furthermore, data from dissociated hippocampal neurons as well as biochemical data provide evidence that Aβ42 disrupts the complex formed between Synaptophysin and VAMP2 increasing the amount of primed vesicles and exocytosis. Finally, electrophysiology recordings in brain slices confirmed that Aβ42 affects baseline transmission. CONCLUSIONS/SIGNIFICANCE: Our observations provide a necessary and timely insight into cellular mechanisms that underlie the initial pathological events that lead to synaptic dysfunction in Alzheimer's disease. Our results demonstrate a new mechanism by which Aβ42 affects synaptic activity

Combined tissue and fluid proteomics with Tandem Mass Tags to identify low-abundance protein biomarkers of disease in peripheral body fluid: An Alzheimer's Disease case study

RATIONALE: Ideal biomarkers are present in readily accessible samples including plasma and cerebrospinal fluid (CSF), and are directly derived from diseased tissue, therefore likely to be of relatively low abundance. Traditional unbiased proteomic approaches for biomarker discovery have struggled to detect low-abundance markers due to the high dynamic range of proteins, the predominance of hyper-abundant proteins, and the use of data-dependent acquisition mass spectrometry (MS). To overcome these limitations and improve biomarker discovery in peripheral fluids, we have developed TMTcalibrator™; a novel MS workflow combining isobarically labelled diseased tissue digests in parallel with an appropriate set of labelled body fluids to increase the chance of identifying low-abundance, tissue-derived biomarkers. METHODS: A disease relevant cell line was labelled with TMT® in a range of concentrations generating a multi-point calibration curve. Peripheral biofluid samples were labelled with the remaining tags and quantitative analysis was performed using an Orbitrap Fusion Tribrid mass spectrometer with a Top10 CID-HCD MS3 synchronous precursor selection (SPS) method. SPS allowed direct analysis of non-depleted, unfractionated CSF samples with complete profiling of six individual samples requiring only 15 hours of MS time, equivalent to 1.5 h per sample. RESULTS: Using the TMTcalibrator™ workflow allowed the identification of several markers of microglia activation that are differentially quantified in the CSF of patients with Alzheimer's disease (AD). We report peptides from 41 proteins that have not previously been detected in the CSF, that appear to be regulated by at least 60% in AD. CONCLUSIONS: This study has demonstrated the benefits of the new TMTcalibrator™ workflow and the results suggest this is a suitable and efficient method of detecting low-abundance peptides within biological fluids. The use of TMTcalibrator™ in further biomarker discovery studies should be considered to overcome some of the limitations commonly associated with more conventional approaches

3D global multi-species Hall-MHD simulation of the Cassini T9 flyby

The wake region of Titan is an important component of Titan's interaction with its surrounding plasma and therefore a thorough understanding of its formation and structure is of primary interest. The Cassini spacecraft passed through the distant downstream region of Titan on 18: 59: 30 UT Dec. 26, 2005, which is referred to as the T9 flyby and provided a great opportunity to test our understanding of the highly dynamic wake region. In this paper we compare the observational data (from the magnetometer, plasma analyzer and Langmuir probe) with numerical results using a 7-species Hall MHD Titan model. There is a good agreement between the observed and modeled parameters, given the uncertainties in plasma measurements and the approximations inherent in the Hall MHD model. Our simulation results also show that Hall MHD model results fit the observations better than the non-Hall MHD model for the flyby, consistent with the importance of kinetic effects in the Titan interaction. Based on the model results, we also identify various regions near Titan where Hall MHD models are applicable

Awe and Wonder in Scientific Practice: Implications for the Relationship Between Science and Religion

This paper examines the role of awe and wonder in scientific practice. Drawing on evidence from psychological research and the writings of scientists and science communicators, I argue that awe and wonder play a crucial role in scientific discovery. They focus our attention on the natural world, encourage open-mindedness, diminish the self (particularly feelings of self-importance), help to accord value to the objects that are being studied, and provide a mode of understanding in the absence of full knowledge. I will flesh out implications of the role of awe and wonder in scientific discovery for debates on the relationship between science and religion. Abraham Heschel argued that awe and wonder are religious emotions because they reduce our feelings of self-importance, and thereby help to cultivate the proper reverent attitude towards God. Yet metaphysical naturalists such as Richard Dawkins insist that awe and wonder need not lead to any theistic commitments for scientists. The awe some scientists experience can be regarded as a form of non-theistic spirituality, which is neither a reductive naturalism nor theism. I will attempt to resolve the tension between these views by identifying some common ground

Microbiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products

We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end. The number of reads generated permitted saturating or near-saturating analysis of samples of the vaginal microbiome. The large number of reads al- lowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an ob- servation that has significant implications for sequence clustering of similar high-throughput data. We show that the short reads are sufficient to assign organisms to the genus or species level in most cases. We suggest that this method will be useful for the deep sequencing of any short nucleotide region that is taxonomically informative; these include the V3, V5 regions of the bac- terial 16S rRNA genes and the eukaryotic V9 region that is gaining popularity for sampling protist diversity.Comment: 28 pages, 13 figure

Who Watches the Watchmen? An Appraisal of Benchmarks for Multiple Sequence Alignment

Multiple sequence alignment (MSA) is a fundamental and ubiquitous technique in bioinformatics used to infer related residues among biological sequences. Thus alignment accuracy is crucial to a vast range of analyses, often in ways difficult to assess in those analyses. To compare the performance of different aligners and help detect systematic errors in alignments, a number of benchmarking strategies have been pursued. Here we present an overview of the main strategies--based on simulation, consistency, protein structure, and phylogeny--and discuss their different advantages and associated risks. We outline a set of desirable characteristics for effective benchmarking, and evaluate each strategy in light of them. We conclude that there is currently no universally applicable means of benchmarking MSA, and that developers and users of alignment tools should base their choice of benchmark depending on the context of application--with a keen awareness of the assumptions underlying each benchmarking strategy.Comment: Revie

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy