Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics

Learning Pathway Recommendation based on a Pedagogical Ontology and its Implementation in Moodle

When learners may select among different alternatives, or are guided to do so by an adaptive learning environment (ALE), it is generally meaningful to discuss the concept of different learning pathways. Pedagogically, these learning pathways may either be defined macroscopically, e.g. in terms of desired learning outcomes or competencies, or microscopically in terms of a didactical model for individual knowledge objects. In this contribution we consider such learning pathways from a pedagogical point of view and then establish a mathematical model for their traversal by a learner and for the analysis of his behavior. This model is implemented in a novel ALE provided by the EU FP7 project INTUITEL, introduced in its Moodle version as concrete example

The SZT2 Interactome Unravels New Functions of the KICSTOR Complex

Seizure threshold 2 (SZT2) is a component of the KICSTOR complex which, under catabolic conditions, functions as a negative regulator in the amino acid-sensing branch of mTORC1. Mutations in this gene cause a severe neurodevelopmental and epileptic encephalopathy whose main symptoms include epilepsy, intellectual disability, and macrocephaly. As SZT2 remains one of the least characterized regulators of mTORC1, in this work we performed a systematic interactome analysis under catabolic and anabolic conditions. Besides numerous mTORC1 and AMPK signaling components, we identified clusters of proteins related to autophagy, ciliogenesis regulation, neurogenesis, and neurodegenerative processes. Moreover, analysis of SZT2 ablated cells revealed increased mTORC1 signaling activation that could be reversed by Rapamycin or Torin treatments. Strikingly, SZT2 KO cells also exhibited higher levels of autophagic components, independent of the physiological conditions tested. These results are consistent with our interactome data, in which we detected an enriched pool of selective autophagy receptors/regulators. Moreover, preliminary analyses indicated that SZT2 alters ciliogenesis. Overall, the data presented form the basis to comprehensively investigate the physiological functions of SZT2 that could explain major molecular events in the pathophysiology of developmental and epileptic encephalopathy in patients with SZT2 mutations

Towards screening Barrett’s Oesophagus: current guidelines, imaging modalities and future developments

Barrett’s oesophagus is the only known precursor to oesophageal adenocarcinoma (OAC). Although guidelines on the screening and surveillance exist in Barrett’s oesophagus, the current strategies are inadequate. Oesophagogastroduodenoscopy (OGD) is the gold standard method in screening for Barrett’s oesophagus. This invasive method is expensive with associated risks negating its use as a current screening tool for Barrett’s oesophagus. This review explores current definitions, epidemiology, biomarkers, surveillance, and screening in Barrett’s oesophagus. Imaging modalities applicable to this condition are discussed, in addition to future developments. There is an urgent need for an alternative non-invasive method of screening and/or surveillance which could be highly beneficial towards reducing waiting times, alleviating patient fears and reducing future costs in current healthcare services. Vibrational spectroscopy has been shown to be promising in categorising Barrett’s oesophagus through to high-grade dysplasia (HGD) and OAC. These techniques need further validation through multicentre trials

Time-resolved optical investigation of tunneling of carriers through single AlxGa1-xAs barriers

An asymmetric double quantum well structure consisting of a wide and a narrow quantum well separated by AlsubxGasub1minusxAs barriers of various thicknesses is used to investigate resonant and nonresonant tunneling of electrons as well as holes through a single barrier. The carrier transfer times are obtained by tracing the luminescence decay of the two quantum wells with picosecond time resolution as a function of an applied electric field. For the first time, resonant and nonresonant electron and hole tunneling times in one single structure are reported. Our results are compared with those of other groups. Idealized theoretical models cannot explain the experimental values

Tomatidine, a novel antiviral compound towards dengue virus

Dengue is the most common arboviral disease worldwide with 96 million symptomatic cases annually. Despite its major impact on global human health and huge economic burden there is no antiviral drug available to treat the disease. The first tetravalent dengue virus vaccine was licensed in 2015 for individuals aged 9 to 45, however, most cases are reported in infants and young children. This, together with the limited efficacy of the vaccine to dengue virus (DENV) serotype 2, stresses the need to continue the search for compounds with anti-viral activity to DENV. In this report, we describe tomatidine as a novel compound with potent antiviral properties towards all DENV serotypes and the related Zika virus. The strongest effect was observed for DENV-2 with an EC50 and EC90 value of 0.82 and 1.61 mu M, respectively, following infection of Huh7 cells at multiplicity of infection of 1. The selectivity index is 97.7. Time-of-drug-addition experiments revealed that tomatidine inhibits virus particle production when added pre, during and up to 12 h post-infection. Subsequent experiments show that tomatidine predominantly acts at a step after virus-cell binding and membrane fusion but prior to the secretion of progeny virions. Tomatidine was found to control the expression of the cellular protein activating transcription factor 4 (ATF4), yet, this protein is not solely responsible for the observed antiviral effect. Here, we propose tomatidine as a candidate for the treatment of dengue given its potent antiviral activity

Learning pathway recommendation based on a pedagogical ontology and its implementation in Moodle

When learners may select among different alternatives, or are guided to do so by an adaptive learning environment (ALE), it is generally meaningful to discuss the concept of different learning pathways. Pedagogically, these learning pathways may either be defined macroscopically, e.g. in terms of desired learning outcomes or competencies, or microscopically in terms of a didactical model for individual knowledge objects. In this contribution we consider such learning pathways from a pedagogical point of view and then establish a mathematical model for their traversal by a learner and for the analysis of his behavior. This model is implemented in a novel ALE provided by the EU FP7 project INTUITEL, introduced in its Moodle version as concrete example

Phosphoproteomics Profiling Defines a Target Landscape of the Basophilic Protein Kinases AKT, S6K, and RSK in Skeletal Myotubes

Phosphorylation-dependent signal transduction plays an important role in regulating the functions and fate of skeletal muscle cells. Central players in the phospho-signaling network are the protein kinases AKT, S6K, and RSK as part of the PI3K-AKT-mTOR-S6K and RAF-MEK-ERK-RSK pathways. However, despite their functional importance, knowledge about their specific targets is incomplete because these kinases share the same basophilic substrate motif RxRxxp[ST]. To address this, we performed a multifaceted quantitative phosphoproteomics study of skeletal myotubes following kinase inhibition. Our data corroborate a cross talk between AKT and RAF, a negative feedback loop of RSK on ERK, and a putative connection between RSK and PI3K signaling. Altogether, we report a kinase target landscape containing 49 so far unknown target sites. AKT, S6K, and RSK phosphorylate numerous proteins involved in muscle development, integrity, and functions, and signaling converges on factors that are central for the skeletal muscle cytoskeleton. Whereas AKT controls insulin signaling and impinges on GTPase signaling, nuclear signaling is characteristic for RSK. Our data further support a role of RSK in glucose metabolism. Shared targets have functions in RNA maturation, stability, and translation, which suggests that these basophilic kinases establish an intricate signaling network to orchestrate and regulate processes involved in translation