An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current <it>in silico </it>prediction methods suffer from gene-model errors introduced during genome annotation.</p> <p>Results</p> <p>A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring <it>Aspergillus </it>species was developed to create an improved list of potential signal peptide containing proteins encoded by the <it>Aspergillus niger </it>genome. As a complement to these <it>in silico </it>predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in <it>A. niger </it>were identified.</p> <p>Conclusions</p> <p>We were able to improve the <it>in silico </it>inventory of <it>A. niger </it>secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed <it>in silico </it>predictions.</p

Robust Multimodal Image Registration Using Deep Recurrent Reinforcement Learning

The crucial components of a conventional image registration method are the choice of the right feature representations and similarity measures. These two components, although elaborately designed, are somewhat handcrafted using human knowledge. To this end, these two components are tackled in an end-to-end manner via reinforcement learning in this work. Specifically, an artificial agent, which is composed of a combined policy and value network, is trained to adjust the moving image toward the right direction. We train this network using an asynchronous reinforcement learning algorithm, where a customized reward function is also leveraged to encourage robust image registration. This trained network is further incorporated with a lookahead inference to improve the registration capability. The advantage of this algorithm is fully demonstrated by our superior performance on clinical MR and CT image pairs to other state-of-the-art medical image registration methods

GAN-based multiple adjacent brain MRI slice reconstruction for unsupervised alzheimer’s disease diagnosis

Unsupervised learning can discover various unseen diseases, relying on large-scale unannotated medical images of healthy subjects. Towards this, unsupervised methods reconstruct a single medical image to detect outliers either in the learned feature space or from high reconstruction loss. However, without considering continuity between multiple adjacent slices, they cannot directly discriminate diseases composed of the accumulation of subtle anatomical anomalies, such as Alzheimer's Disease (AD). Moreover, no study has shown how unsupervised anomaly detection is associated with disease stages. Therefore, we propose a two-step method using Generative Adversarial Network-based multiple adjacent brain MRI slice reconstruction to detect AD at various stages: (Reconstruction) Wasserstein loss with Gradient Penalty + L1 loss---trained on 3 healthy slices to reconstruct the next 3 ones---reconstructs unseen healthy/AD cases; (Diagnosis) Average/Maximum loss (e.g., L2 loss) per scan discriminates them, comparing the reconstructed/ground truth images. The results show that we can reliably detect AD at a very early stage with Area Under the Curve (AUC) 0.780 while also detecting AD at a late stage much more accurately with AUC 0.917; since our method is fully unsupervised, it should also discover and alert any anomalies including rare disease.Comment: 10 pages, 4 figures, Accepted to Lecture Notes in Bioinformatics (LNBI) as a volume in the Springer serie

Comparative bioavailability of a newly developed Irbesartan 300 mg containing preparation

Introduction: Irbesartan (CAS registry: 138402-11-6) is a potent, orally active, selective antagonist of the angiotensin II receptors (type AT1) indicated for the treatment of arterial hypertension and chronic heart failure. Aim: The objective of the present study was to demonstrate the bioequivalence of an oral test preparation (Irbesartan 300 mg film-coated tablets Tchaikapharma High Quality Medicines Inc., Bulgaria) and a reference (Aprovel 300 mg film-coated tablets, Sanofi Clir SNC, France), by comparing the rate and extent of absorption of both products upon a single oral administration of the tablets under fasting conditions in healthy volunteers. Methodology: The study was carried out as a single-center, open-label, randomised, twoperiod, single dose, crossover oral bioequivalence study in 40 healthy male and female subjects under fasting conditions. During each study period blood samples for analysis of irbesartan were taken prior to dosing and at 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.5, 3, 3.5, 4, 5, 6, 8, 12, 24, 36, 48 and 72 hours after dosing. The separated plasma was analyzed in the bioanalytical division of Anapharm Europe with a validated method using reversed phase high performance liquid chromatography coupled to a tandem mass spectrometry detector (RP-LC/MS/MS). Results: The point estimates with 90% confidence intervals of the geometric mean ratios of test and reference (T/R) in the study were found to be 102.39% (95.55% - 109.71%) for Cmax and 98.56 % (92.72 % - 104.76 %) for AUC0-72. Thus, the corresponding ratios of Cmax and AUC0-72 met the predetermined criteria for bioequivalence (90% confidence intervals of the geometric mean ratios of test and reference within the 80.00% - 125.00%). Both products were generally very well tolerated. Conclusions: Irbesartan 300 mg film-coated tablets, Tchaikapharma High Quality Medicines Inc., Bulgaria) and Aprovel 300 mg film-coated tablets (Sanofi Clir SNC, France), are bioequivalent with regard to the rate and extent of absorption

Slx8 removes Pli1-dependent protein-SUMO conjugates including SUMOylated Topoisomerase I to promote genome stability

Peer reviewedPublisher PD

Identification of Genes Affecting the Toxicity of Anti-Cancer Drug Bortezomib by Genome-Wide Screening in S. pombe

Bortezomib/PS-341/Velcade, a proteasome inhibitor, is widely used to treat multiple myeloma. While several mechanisms of the cytotoxicity of the drug were proposed, the actual mechanism remains elusive. We aimed to identify genes affecting the cytotoxicity of Bortezomib in the fission yeast S.pombe as the drug inhibits this organism's cell division cycle like proteasome mutants. Among the 2815 genes screened (covering 56% of total ORFs), 19 genes, whose deletions induce strong synthetic lethality with Bortezomib, were identified. The products of the 19 genes included four ubiquitin enzymes and one nuclear proteasome factor, and 13 of them are conserved in humans. Our results will provide useful information for understanding the actions of Bortezomib within cells

Cdk1 and SUMO Regulate Swe1 Stability

The Swe1/Wee1 kinase phosphorylates and inhibits Cdk1-Clb2 and is a major mitotic switch. Swe1 levels are controlled by ubiquitin mediated degradation, which is regulated by interactions with various mitotic kinases. We have recently reported that Swe1 levels are capable of sensing the progress of the cell cycle by measuring the levels of Cdk1-Clb2, Cdc5 and Hsl1. We report here a novel mechanism that regulates the levels of Swe1. We show that S.cerevisiae Swe1 is modified by Smt3/SUMO on residue K594 in a Cdk1 dependant manner. A degradation of the swe1K594R mutant that cannot be modified by Smt3 is considerably delayed in comparison to wild type Swe1. Swe1K594R cells express elevated levels of Swe1 protein and demonstrate higher levels of Swe1 activity as manifested by Cdk1-Y19 phosphorylation. Interestingly this mutant is not targeted, like wild type Swe1, to the bud neck where Swe1 degradation takes place. We show that Swe1 is SUMOylated by the Siz1 SUMO ligase, and consequently siz1Δ cells express elevated levels of Swe1 protein and activity. Finally we show that swe1K594R cells are sensitive to osmotic stress, which is in line with their compromised regulation of Swe1 degradation

QTL for phytosterol and sinapate ester content in Brassica napus L. collocate with the two erucic acid genes

Improving oil and protein quality for food and feed purposes is an important goal in rapeseed (Brassica napus L.) breeding programs. Rapeseed contains phytosterols, used to enrich food products, and sinapate esters, which are limiting the utilization of rapeseed proteins in the feed industry. Increasing the phytosterol content of oil and lowering sinapate ester content of meal could increase the value of the oilseed rape crop. The objective of the present study was to identify quantitative trait loci (QTL) for phytosterol and sinapate ester content in a winter rapeseed population of 148 doubled haploid lines, previously found to have a large variation for these two traits. This population also segregated for the two erucic acid genes. A close negative correlation was found between erucic acid and phytosterol content (Spearman’s rank correlation, rs = −0.80**). For total phytosterol content, three QTL were detected, explaining 60% of the genetic variance. The two QTL with the strongest additive effects were mapped on linkage groups N8 and N13 within the confidence intervals of the two erucic acid genes. For sinapate ester content four QTL were detected, explaining 53% of the genetic variance. Again, a close negative correlation was found between erucic acid and sinapate ester content (rs = −0.66**) and the QTL with the strongest additive effects mapped on linkage groups N8 and N13 within the confidence intervals of the two erucic acid genes. The results suggests, that there is a pleiotropic effect of the two erucic acid genes on phytosterol and sinapate ester content; the effect of the alleles for low erucic acid content is to increase phytosterol and sinapate ester content. Possible reasons for this are discussed based on known biosynthetic pathways

Summary of the ISEV workshop on extracellular vesicles as disease biomarkers, held in Birmingham, UK, during December 2017

This report summarises the presentations and activities of the ISEV Workshop on extracellular vesicle biomarkers held in Birmingham, UK during December 2017. Among the key messages was broad agreement about the importance of biospecimen science. Much greater attention needs to be paid towards the provenance of collected samples. The workshop also highlighted clear gaps in our knowledge about pre-analytical factors that alter extracellular vesicles (EVs). The future utility of certified standards for credentialing of instruments and software, to analyse EV and for tracking the influence of isolation steps on the structure and content of EVs were also discussed. Several example studies were presented, demonstrating the potential utility for EVs in disease diagnosis, prognosis, longitudinal serial testing and stratification of patients. The conclusion of the workshop was that more effort focused on pre-analytical issues and benchmarking of isolation methods is needed to strengthen collaborations and advance more effective biomarkers

Diagnostic and prognostic value of long noncoding RNAs as biomarkers in urothelial carcinoma

Many long noncoding RNAs (lncRNAs) are deregulated in cancer and contribute to oncogenesis. In urothelial carcinoma (UC), several lncRNAs have been reported to be overexpressed and proposed as biomarkers. As most reports have not been confirmed independently in large tissue sets, we aimed to validate the diagnostic and prognostic value of lncRNA upregulation in independent cohorts of UC patients. Thus, expression of seven lncRNA candidates (GAS5, H19, linc-UBC1, MALAT1, ncRAN, TUG1, UCA1) was measured by RT-qPCR in cell lines and tissues and correlated to clinicopathological parameters including follow-up data (set 1: N n = 10; T n = 106). Additionally, publicly available TCGA data was investigated for differential expression in UC tissues (set 2: N n = 19; T n = 252,) and correlation to overall survival (OS). All proposed candidates tended to be upregulated in tumour tissues, with the exception of MALAT1, which was rather diminished in cancer tissues of both data sets. However, strong overexpression was generally limited to individual tumour tissues and statistically significant overexpression was only observed for UCA1, TUG1, ncRAN and linc-UBC1 in tissue set 2, but for no candidate in set 1. Altered expression of individual lncRNAs was associated with overall survival, but not consistently between both patient cohorts. Interestingly, lower expression of TUG1 in a subset of UC patients with muscle-invasive tumours was significantly correlated with worse OS in both cohorts. Further analysis revealed that tumours with low TUG1 expression are characterized by a basal-squamous-like subtype signature accounting for the association with poor outcome. In conclusion, our study demonstrates that overexpression of the candidate lncRNAs is found in many UC cases, but does not occur consistently and strongly enough to provide reliable diagnostic or prognostic value as an individual biomarker. Subtype-dependent expression patterns of lncRNAs like TUG1 could become useful to stratify patients by molecular subtype, thus aiding personalized treatments