A large-scale genetic validation study coupled with in vitro analyses reveal a role for vitamin Dsignaling in the pathogenesis and response to treatment of hepatitis C virus infection

Background and Aims: Vitamin D is an important modulatorof numerous cellular processes. Some of us recently observedan association of the 1a-hydroxylase promoter polymorphismCYP27B1-1260 rs10877012 with sustained virologic response (SVR)in a relatively small number of German patients with chronichepatitis C. In the present study, we aimed to validate thisassociation in a large and well characterized patient cohort, theSwiss Hepatitis C Cohort Study (SCCS). In addition, we examinedthe effect of vitamin D on the hepatitis C virus (HCV) life cyclein vitro.Methods: CYP27B1-1260 rs10877012 and IL28B rs12979860 singlenucleotide polymorphisms (SNPs) were genotyped in 1049 patientswith chronic hepatitis C from the SCCS, of whom 698 were treatedwith pegylated interferon-a (PEG-IFN-a) and ribavirin. In addition,112 patients with spontaneous clearance of HCV were examined.SNPs were correlated with variables reflecting the natural courseand treatment outcome of chronic hepatitis C. The effect of1,25-(OH)2D3 (calcitriol) on HCV replication and viral particleproduction was investigated in vitro using human hepatoma celllines (Huh-7.5) harbouring subgenomic replicons and cell culturederivedHCV.Results: The CYP27B1-1260 rs10877012 genotype was notassociated with SVR in patients with the good-response IL28Brs1279860 CC genotype. However, in patients with poor-responseIL28B rs1279860 genotype CT and TT, CYP27B1-1260 rs10877012was a significant independent predictor of SVR (15% difference inSVR between rs10877012 genotype AA vs. CC, p = 0.030, OR = 1.495,95% CI = 1.038-2.152). The CYPB27-1260 rs10877012 genotype wasneither associated with spontaneous clearance of HCV, nor withliver fibrosis progression rate, inflammatory activity of chronichepatitis C, or HCV viral load. Physiological doses of 1,25-(OH)2D3did not significantly affect HCVRNA replication or infectiousparticle production in vitro.Conclusions: The results of this large-scale genetic validationstudy reveal a role of vitamin D metabolism in the responseto treatment in chronic hepatitis C, but 1,25-(OH)2D3 does notexhibit a significant direct inhibitory antiviral effect. Thus, theability of vitamin D to modulate immunity against HCV shouldbe investigated.

Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.

MOTIVATION: Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked. RESULTS: More than 1 million hyper-variable internal transcribed spacer 1 (ITS1) sequences of fungal origin have been analyzed. The ITS1 sequences were first properly extracted from 454 reads using generalized profiles. Then, otupipe, cd-hit-454, ESPRIT-Tree and DBC454, a new algorithm presented here, were used to analyze the sequences. A numerical assay was developed to measure the reproducibility and robustness of these algorithms. DBC454 was the most robust, closely followed by ESPRIT-Tree. DBC454 features density-based hierarchical clustering, which complements the other methods by providing insights into the structure of the data. AVAILABILITY: An executable is freely available for non-commercial users at ftp://ftp.vital-it.ch/tools/dbc454. It is designed to run under MPI on a cluster of 64-bit Linux machines running Red Hat 4.x, or on a multi-core OSX system. CONTACT: dbc454@vital-it.ch or nicolas.guex@isb-sib.ch.

Large scale purification of presynaptic plasma membranes from Torpedo marmorata electric organ

The presynaptic plasma membrane (PSPM) of cholinergic nerve terminals was purified from Torpedo electric organ using a large-scale procedure. Up to 500 g of frozen electric organ were fractioned in a single run, leading to the isolation of greater than 100 mg of PSPM proteins. The purity of the fraction is similar to that of the synaptosomal plasma membrane obtained after subfractionation of Torpedo synaptosomes as judged by its membrane-bound acetylcholinesterase activity, the number of Glycera convoluta neurotoxin binding sites, and the binding of two monoclonal antibodies directed against PSPM. The specificity of these antibodies for the PSPM is demonstrated by immunofluorescence microscopy.

Addressing trypsin bias in large scale (phospho)proteome analysis by size exclusion chromatography and secondary digestion of large post-trypsin peptides.

In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways.

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

The co-evolution of social institutions, demography, and large-scale human cooperation.

Human cooperation is typically coordinated by institutions, which determine the outcome structure of the social interactions individuals engage in. Explaining the Neolithic transition from small- to large-scale societies involves understanding how these institutions co-evolve with demography. We study this using a demographically explicit model of institution formation in a patch-structured population. Each patch supports both social and asocial niches. Social individuals create an institution, at a cost to themselves, by negotiating how much of the costly public good provided by cooperators is invested into sanctioning defectors. The remainder of their public good is invested in technology that increases carrying capacity, such as irrigation systems. We show that social individuals can invade a population of asocials, and form institutions that support high levels of cooperation. We then demonstrate conditions where the co-evolution of cooperation, institutions, and demographic carrying capacity creates a transition from small- to large-scale social groups.

Large-scale clustering through functional embedding

We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an ?out-of-sample? problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.

Bioinformatics: making large-scale science happen

Bionformatics is a rapidly evolving research field dedicated toanalyzing and managing biological data with computational resources. This paperaims to overview some of the processes and applications currently implementedat CCiT-UB¿s Bioinformatics Unit, focusing mainly on the areas of Genomics,Transcriptomics and Proteomics