Structural basis of complement membrane attack complex formation

In response to complement activation, the membrane attack complex (MAC) assembles from fluid-phase proteins to form pores in lipid bilayers. MAC directly lyses pathogens by a ‘multi-hit’ mechanism; however, sublytic MAC pores on host cells activate signalling pathways. Previous studies have described the structures of individual MAC components and subcomplexes; however, the molecular details of its assembly and mechanism of action remain unresolved. Here we report the electron cryo-microscopy structure of human MAC at subnanometre resolution. Structural analyses define the stoichiometry of the complete pore and identify a network of interaction interfaces that determine its assembly mechanism. MAC adopts a ‘split-washer’ configuration, in contrast to the predicted closed ring observed for perforin and cholesterol-dependent cytolysins. Assembly precursors partially penetrate the lipid bilayer, resulting in an irregular β-barrel pore. Our results demonstrate how differences in symmetric and asymmetric components of the MAC underpin a molecular basis for pore formation and suggest a mechanism of action that extends beyond membrane penetration

“Surgical” Abdomen in a Patient with Chronic Lymphocytic Leukemia: A Case of Acquired Angioedema

# The Author(s) 2011. This article is published with open access at Springerlink.com Introduction Acquired angioedema (AAE), an acquired deficiency of C1esterase inhibitor, is a medically treatable condition which can cause severe abdominal pain mimicking an acute surgical abdomen. This disorder is strongly associated with chronic lymphocytic leukemia (CLL) and other indolent lymphoplasmacytic disorders. Discussion We describe a patient with known CLL who developed incapacitating, recurrent severe abdominal pains, culminating in partial bowel resection. Signs, symptoms, laboratory and pathologic findings demonstrated AAE

Paris COP 21: Power that Speaks the Truth?

© 2016 Informa UK Limited, trading as Taylor & Francis Group In this paper, I set out some of the key aspects of the Paris COP 21 Climate Change Agreement. The Paris Agreement was initially reported as a major success. However, this was in so far as many thought any kind of agreement at all was unlikely, and because the Agreement includes Article 2: an aspiration to maintain average global temperature increases to significantly less than 2°C. I then ask the question: if the Paris Agreement is a success of sorts, has anything fundamental changed in order to translate the conditional success of achieving an agreement into an actual success that will realise the goals of the Agreement? I address this in terms of early assessment of trends and the Nationally Determined Contributions, how responsibility is positioned in the Agreement, and the political economy context, which has called forth the need for an agreement

Alzheimer’s disease-associated complement gene variants influence plasma complement protein levels

Background: Alzheimer’s disease (AD) has been associated with immune dysregulation in biomarker and genome-wide association studies (GWAS). GWAS hits include the genes encoding complement regulators clusterin (CLU) and complement receptor 1 (CR1), recognised as key players in AD pathology, and complement proteins have been proposed as biomarkers. Main body: To address whether changes in plasma complement protein levels in AD relate to AD-associated complement gene variants we first measured relevant plasma complement proteins (clusterin, C1q, C1s, CR1, factor H) in a large cohort comprising early onset AD (EOAD; n = 912), late onset AD (LOAD; n = 492) and control (n = 504) donors. Clusterin and C1q were significantly increased (p < 0.001) and sCR1 and factor H reduced (p < 0.01) in AD plasma versus controls. ROC analyses were performed to assess utility of the measured complement biomarkers, alone or in combination with amyloid beta, in predicting AD. C1q was the most predictive single complement biomarker (AUC 0.655 LOAD, 0.601 EOAD); combining C1q with other complement or neurodegeneration makers through stepAIC-informed models improved predictive values slightly. Effects of GWS SNPs (rs6656401, rs6691117 in CR1; rs11136000, rs9331888 in CLU; rs3919533 in C1S) on protein concentrations were assessed by comparing protein levels in carriers of the minor vs major allele. To identify new associations between SNPs and changes in plasma protein levels, we performed a GWAS combining genotyping data in the cohort with complement protein levels as endophenotype. SNPs in CR1 (rs6656401), C1S (rs3919533) and CFH (rs6664877) reached significance and influenced plasma levels of the corresponding protein, whereas SNPs in CLU did not influence clusterin levels. Conclusion: Complement dysregulation is evident in AD and may contribute to pathology. AD-associated SNPs in CR1, C1S and CFH impact plasma levels of the encoded proteins, suggesting a mechanism for impact on disease risk

Digital Quantum Simulation of the Statistical Mechanics of a Frustrated Magnet

Many interesting problems in physics, chemistry, and computer science are equivalent to problems of interacting spins. However, most of these problems require computational resources that are out of reach by classical computers. A promising solution to overcome this challenge is to exploit the laws of quantum mechanics to perform simulation. Several "analog" quantum simulations of interacting spin systems have been realized experimentally. However, relying on adiabatic techniques, these simulations are limited to preparing ground states only. Here we report the first experimental results on a "digital" quantum simulation on thermal states; we simulated a three-spin frustrated magnet, a building block of spin ice, with an NMR quantum information processor, and we are able to explore the phase diagram of the system at any simulated temperature and external field. These results serve as a guide for identifying the challenges for performing quantum simulation on physical systems at finite temperatures, and pave the way towards large scale experimental simulations of open quantum systems in condensed matter physics and chemistry.Comment: 7 pages for the main text plus 6 pages for the supplementary material

The Clinical Impact of Copy Number Variants in Inherited Bone Marrow Failure Syndromes

Inherited bone marrow failure syndromes (IBMFSs) comprise a genetically heterogeneous group of diseases with hematopoietic failure and a wide array of physical malformations. Copy number variants (CNVs) were reported in some IBMFSs. It is unclear what impact CNVs play in patients evaluated for a suspected diagnosis of IBMFS. Clinical and genetic data of 323 patients from the Canadian Inherited Marrow Failure Registry from 2001 to 2014, who had a documented genetic work-up, were analyzed. Cases with pathogenic CNVs (at least 1 kilobasepairs) were compared to cases with other mutations. Genotype-phenotype correlations were performed to assess the impact of CNVs. Pathogenic nucleotide-level mutations were found in 157 of 303 tested patients (51.8%). Genome-wide CNV analysis by single nucleotide polymorphism arrays or comparative genomic hybridization arrays revealed pathogenic CNVs in 11 of 67 patients tested (16.4%). In four of these patients, identification of CNV was crucial for establishing the correct diagnosis as their clinical presentation was ambiguous. Eight additional patients were identified to harbor pathogenic CNVs by other methods. Of the 19 patients with pathogenic CNVs, four had compound-heterozygosity of a CNV with a nucleotide-level mutation. Pathogenic CNVs were associated with more extensive non-hematological organ system involvement

Research priorities for neuroimmunology: identifying the key research questions to be addressed by 2030

Neuroimmunology in the broadest sense is the study of interactions between the nervous and the immune systems. These interactions play important roles in health from supporting neural development, homeostasis and plasticity to modifying behaviour. Neuroimmunology is increasingly recognised as a field with the potential to deliver a significant positive impact on human health and treatment for neurological and psychiatric disorders. Yet, translation to the clinic is hindered by fundamental knowledge gaps on the underlying mechanisms of action or the optimal timing of an intervention, and a lack of appropriate tools to visualise and modulate both systems. Here we propose ten key disease-agnostic research questions that, if addressed, could lead to significant progress within neuroimmunology in the short to medium term. We also discuss four cross-cutting themes to be considered when addressing each question: i) bi-directionality of neuroimmune interactions; ii) the biological context in which the questions are addressed (e.g. health vs disease vs across the lifespan); iii) tools and technologies required to fully answer the questions; and iv) translation into the clinic. We acknowledge that these ten questions cannot represent the full breadth of gaps in our understanding; rather they focus on areas which, if addressed, may have the most broad and immediate impacts. By defining these neuroimmunology priorities, we hope to unite existing and future research teams, who can make meaningful progress through a collaborative and cross-disciplinary effort

Mouse Gestation Length Is Genetically Determined

Background: Preterm birth is an enormous public health problem, affecting over 12 % of live births and costing over $26 billion in the United States alone. The causes are complex, but twin studies support the role of genetics in determining gestation length. Despite widespread use of the mouse in studies of the genetics of preterm birth, there have been few studies that actually address the precise natural gestation length of the mouse, and to what degree the timing of labor and birth is genetically determined. Methodology/Principal Findings: To further develop the mouse as a genetic model of preterm birth, we developed a highthroughput monitoring system and measured the gestation length in 15 inbred strains. Our results show an unexpectedly wide variation in overall gestation length between strains that approaches two full days, while intra-strain variation is quite low. Although litter size shows a strong inverse correlation with gestation length, genetic difference alone accounts for a significant portion of the variation. In addition, ovarian transplant experiments support a primary role of maternal genetics in the determination of gestation length. Preliminary analysis of gestation length in the C57BL/6J-Chr # A/J /NaJ chromosome substitution strain (B.A CSS) panel suggests complex genetic control of gestation length. Conclusions/Significance: Together, these data support the role of genetics in regulating gestation length and present th

Comparing biological networks via graph compression

<p>Abstract</p> <p>Background</p> <p>Comparison of various kinds of biological data is one of the main problems in bioinformatics and systems biology. Data compression methods have been applied to comparison of large sequence data and protein structure data. Since it is still difficult to compare global structures of large biological networks, it is reasonable to try to apply data compression methods to comparison of biological networks. In existing compression methods, the uniqueness of compression results is not guaranteed because there is some ambiguity in selection of overlapping edges.</p> <p>Results</p> <p>This paper proposes novel efficient methods, CompressEdge and CompressVertices, for comparing large biological networks. In the proposed methods, an original network structure is compressed by iteratively contracting identical edges and sets of connected edges. Then, the similarity of two networks is measured by a compression ratio of the concatenated networks. The proposed methods are applied to comparison of metabolic networks of several organisms, <it>H. sapiens, M. musculus, A. thaliana, D. melanogaster, C. elegans, E. coli, S. cerevisiae,</it> and <it>B. subtilis,</it> and are compared with an existing method. These results suggest that our methods can efficiently measure the similarities between metabolic networks.</p> <p>Conclusions</p> <p>Our proposed algorithms, which compress node-labeled networks, are useful for measuring the similarity of large biological networks.</p