Protein acetylation in archaea, bacteria, and eukaryotes

Proteins can be acetylated at the alpha-amino group of the N-terminal amino acid (methionine or the penultimate amino acid after methionine removal) or at the epsilon-amino group of internal lysines. In eukaryotes the majority of proteins are N-terminally acetylated, while this is extremely rare in bacteria. A variety of studies about N-terminal acetylation in archaea have been reported recently, and it was revealed that a considerable fraction of proteins is N-terminally acetylated in haloarchaea and Sulfolobus, while this does not seem to apply for methanogenic archaea. Many eukaryotic proteins are modified by differential internal acetylation, which is important for a variety of processes. Until very recently, only two bacterial proteins were known to be acetylation targets, but now 125 acetylation sites are known for E. coli. Knowledge about internal acetylation in archaea is extremely limited; only two target proteins are known, only one of which--Alba--was used to study differential acetylation. However, indications accumulate that the degree of internal acetylation of archaeal proteins might be underestimated, and differential acetylation has been shown to be essential for the viability of haloarchaea. Focused proteomic approaches are needed to get an overview of the extent of internal protein acetylation in archaea

A Comparison of some recent Task-based Parallel Programming Models

The need for parallel programming models that are simple to use and at the same time efficient for current ant future parallel platforms has led to recent attention to task-based models such as Cilk++, Intel TBB and the task concept in OpenMP version 3.0. The choice of model and implementation can have a major impact on the final performance and in order to understand some of the trade-offs we have made a quantitative study comparing four implementations of OpenMP (gcc, Intel icc, Sun studio and the research compiler Mercurium/nanos mcc), Cilk++ and Wool, a high-performance task-based library developed at SICS. Abstract. We use microbenchmarks to characterize costs for task-creation and stealing and the Barcelona OpenMP Tasks Suite for characterizing application performance. By far Wool and Cilk++ have the lowest overhead in both spawning and stealing tasks. This is reflected in application performance when many tasks with small granularity are spawned where Cilk++ and, in particular, has the highest performance. For coarse granularity applications, the OpenMP implementations have quite similar performance as the more light-weight Cilk++ and Wool except for one application where mcc is superior thanks to a superior task scheduler. Abstract. The OpenMP implemenations are generally not yet ready for use when the task granularity becomes very small. There is no inherent reason for this, so we expect future implementations of OpenMP to focus on this issue

Performance Characterization of In-Memory Data Analytics on a Modern Cloud Server

In last decade, data analytics have rapidly progressed from traditional disk-based processing to modern in-memory processing. However, little effort has been devoted at enhancing performance at micro-architecture level. This paper characterizes the performance of in-memory data analytics using Apache Spark framework. We use a single node NUMA machine and identify the bottlenecks hampering the scalability of workloads. We also quantify the inefficiencies at micro-architecture level for various data analysis workloads. Through empirical evaluation, we show that spark workloads do not scale linearly beyond twelve threads, due to work time inflation and thread level load imbalance. Further, at the micro-architecture level, we observe memory bound latency to be the major cause of work time inflation.Comment: Accepted to The 5th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2015

Air freight in the Stockholm region with focus on Eskilstuna Airport

Purpose: The purpose of this article is to analyse the conditions for commencing air freight operations at the regional Eskilstuna Airport in Sweden, which require investments in airport infrastructure of at least SEK 140 –180 million. Design/ methodology: The qualitative data collection for the study was carried out through open-ended interviews with representatives of airport management, staff, representatives of residents, and actors and stakeholders in the field. In addition, much written material was collected from different authorities. Document analysis was used to systematically evaluate and review the collected documents. Content analysis was applied to organize collected data into categories. Based on the reports, decisions, environmental scanning and interviews, the data have been coded and categorized in tables via thematic analysis. Findings: The major findings of the study are that Eskilstuna Airport lacks cargo facilities and has limited apron space, and that there is strong competition from four other airports in the Stockholm region. The prospects for permanent air freight operations at Eskilstuna Airport are therefore not favourable in the current situation. However, if the development of Eskilstuna Logistics Park and the concept of inter modal highway-rail transportation are successful, they could serve as a major driving force for the development of air cargo. Furthermore, with sustainable development as a guiding principle, there is great potential to develop an airport with a high standard of environmental profile. Originality/ value: My findings are of great value to managers of airports and cargo airlines, as they highlight some of the competition aspects associated with engaging in air cargo at regional airports. The study fills a gap in existing research whose main focus is environmental issues concerning airports in general.Peer Reviewe

Recombinant amyloid beta-peptide production by coexpression with an affibody ligand.

BACKGROUND: Oligomeric and fibrillar aggregates of the amyloid beta-peptide (Abeta) have been implicated in the pathogenesis of Alzheimer's disease (AD). The characterization of Abeta assemblies is essential for the elucidation of the mechanisms of Abeta neurotoxicity, but requires large quantities of pure peptide. Here we describe a novel approach to the recombinant production of Abeta. The method is based on the coexpression of the affibody protein ZAbeta3, a selected affinity ligand derived from the Z domain three-helix bundle scaffold. ZAbeta3 binds to the amyloidogenic central and C-terminal part of Abeta with nanomolar affinity and consequently inhibits aggregation. RESULTS: Coexpression of ZAbeta3 affords the overexpression of both major Abeta isoforms, Abeta(1-40) and Abeta(1-42), yielding 4 or 3 mg, respectively, of pure 15N-labeled peptide per liter of culture. The method does not rely on a protein-fusion or -tag and thus does not require a cleavage reaction. The purified peptides were characterized by NMR, circular dichroism, SDS-PAGE and size exclusion chromatography, and their aggregation propensities were assessed by thioflavin T fluorescence and electron microscopy. The data coincide with those reported previously for monomeric, largely unstructured Abeta. ZAbeta3 coexpression moreover permits the recombinant production of Abeta(1-42) carrying the Arctic (E22G) mutation, which causes early onset familial AD. Abeta(1-42)E22G is obtained in predominantly monomeric form and suitable, e.g., for NMR studies. CONCLUSION: The coexpression of an engineered aggregation-inhibiting binding protein offers a novel route to the recombinant production of amyloidogenic Abeta peptides that can be advantageously employed to study the molecular basis of AD. The presented expression system is the first for which expression and purification of the aggregation-prone Arctic variant (E22G) of Abeta(1-42) is reported.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Ranking factors involved in diabetes remission after bariatric surgery using machine-learning integrating clinical and genomic biomarkers

AbstractAs weight-loss surgery is an effective treatment for the glycaemic control of type 2 diabetes in obese patients, yet not all patients benefit, it is valuable to find predictive factors for this diabetic remission. This will help elucidating possible mechanistic insights and form the basis for prioritising obese patients with dysregulated diabetes for surgery where diabetes remission is of interest. In this study, we combine both clinical and genomic factors using heuristic methods, informed by prior biological knowledge in order to rank factors that would have a role in predicting diabetes remission, and indeed in identifying patients who may have low likelihood in responding to bariatric surgery for improved glycaemic control. Genetic variants from the Illumina CardioMetaboChip were prioritised through single-association tests and then seeded a larger selection from protein–protein interaction networks. Artificial neural networks allowing nonlinear correlations were trained to discriminate patients with and without surgery-induced diabetes remission, and the importance of each clinical and genetic parameter was evaluated. The approach highlighted insulin treatment, baseline HbA1c levels, use of insulin-sensitising agents and baseline serum insulin levels, as the most informative variables with a decent internal validation performance (74% accuracy, area under the curve (AUC) 0.81). Adding information for the eight top-ranked single nucleotide polymorphisms (SNPs) significantly boosted classification performance to 84% accuracy (AUC 0.92). The eight SNPs mapped to eight genes — ABCA1, ARHGEF12, CTNNBL1, GLI3, PROK2, RYBP, SMUG1 and STXBP5 — three of which are known to have a role in insulin secretion, insulin sensitivity or obesity, but have not been indicated for diabetes remission after bariatric surgery before.</jats:p

Residual beta-Cell Function 3-6 Years After Onset of Type 1 Diabetes Reduces Risk of Severe Hypoglycemia in Children and Adolescents

OBJECTIVETo determine the prevalence of residual -cell function (RBF) in children after 3-6 years of type 1 diabetes, and to examine the association between RBF and incidence of severe hypoglycemia, glycemic control, and insulin requirements.RESEARCH DESIGN AND METHODSA total of 342 children (173 boys) 4.8-18.9 years of age with type 1 diabetes for 3-6 years were included. RBF was assessed by testing meal-stimulated C-peptide concentrations. Information regarding severe hypoglycemia within the past year, current HbA(1c), and daily insulin requirements was retrieved from the medical records and through patient interviews.RESULTSNinety-two children (27%) had RBF &gt;0.04 nmol/L. Patients with RBF 0.04 nmol/L (odds ratio, 2.59; 95% CI, 1.10-7.08; P &lt;0.03). HbA(1c) was significantly higher in patients with RBF 0.04 nmol/L (mean, 8.49 0.08% [69.3 +/- 0.9 mmol/mol] vs. 7.92 +/- 0.13% [63.1 +/- 1.4 mmol/mol]; P &lt;0.01), and insulin requirements were significantly lower in patients with RBF &gt;0.2 nmol/L (mean +/- SE: 1.07 +/- 0.02 vs. 0.93 +/- 0.07 units/kg/day; P &lt;0.04).CONCLUSIONSWe demonstrated considerable phenotypic diversity in RBF among children after 3-6 years of type 1 diabetes. Children with RBF are at lower risk for severe hypoglycemia, have better diabetes regulation, and have lower insulin requirements compared with children without RBF. There appears to be a lower limit for stimulated RBF of approximate to 0.04 nmol/L that confers a beneficial effect on hypoglycemia and metabolic control