Integrated Model of Metabolism and Autoimmune Response in β-Cell Death and Progression to Type 1 Diabetes

Progression to type 1 diabetes is characterized by complex interactions of environmental, metabolic and immune system factors, involving both degenerative pathways leading to loss of pancreatic β-cells as well as protective pathways. The interplay between the degenerative and protective pathways may hold the key to disease outcomes, but no models have so far captured the two together. Here we propose a mathematical framework, an ordinary differential equation (ODE) model, which integrates metabolism and the immune system in early stages of disease process. We hypothesize that depending on the degree of regulation, autoimmunity may also play a protective role in the initial response to stressors. We assume that β-cell destruction follows two paths of loss: degenerative and autoimmune-induced loss. The two paths are mutually competing, leading to termination of the degenerative loss and further to elimination of the stress signal and the autoimmune response, and ultimately stopping the β-cell loss. The model describes well our observations from clinical and non-clinical studies and allows exploration of how the rate of β-cell loss depends on the amplitude and duration of autoimmune response.     

Key for European species of the Cheilosia proxima group (Diptera,Syrphidae) with a description of a new species

A new hoverfly species, Cheilosia barbafacies Vujić & Radenković sp. n. (Diptera, Syrphidae), is described and distinguished from the closely related species Cheilosia pascuorum Becker, 1894, based on material collected from the mountains of the Balkan Peninsula. Diagnostic characteristics and an identification key for the members of the proxima group of Cheilosia s. str., including the new taxon, are provided.     

Characterization of the Variability of Epstein-Barr Virus Genes in Nasopharyngeal Biopsies: Potential Predictors for Carcinoma Progression

Epstein-Barr virus (EBV) infection is a significant factor in the pathogenesis of nasopharyngeal carcinoma, especially in the undifferentiated carcinoma of nasopharyngeal type (UCNT, World Health Organization type III), which is the dominant histopathological type in high-risk areas. The major EBV oncogene is latent membrane protein 1 (LMP1). LMP1 gene shows variability with different tumorigenic and immunogenic potentials. EBV nuclear antigen 1 (EBNA1) regulates progression of EBV-related tumors; however, the influence of EBNA1 sequence variability on tumor pathogenesis is controversial. The aims of this study were to characterize polymorphisms of EBV genes in non-endemic nasopharyngeal carcinoma biopsies and to investigate potential sequence patterns that correlate with the clinical presentation of nasopharyngeal carcinoma. In total, 116 tumor biopsies of undifferentiated carcinoma of nasopharyngeal type (UCNT), collected from 2008 to 2014, were evaluated in this study. The genes EBNA2, LMP1, and EBNA1 were amplified using nested-PCR. EBNA2 genotyping was performed by visualization of PCR products using gel electrophoresis. Investigation of LMP1 and EBNA1 included sequence, phylogenetic, and statistical analyses. The presence of EBV DNA was significantly distributed between TNM stages. LMP1 variability showed six variants, with the detection of the first China1 and North Carolina variants in European nasopharyngeal carcinoma biopsies. Newly discovered variants Srb1 and Srb2 were UCNT-specific LMP1 polymorphisms. The B95-8 and North Carolina variants are possible predictors for favorable TNM stages. In contrast, deletions in LMP1 are possible risk factors for the most disfavorable TNM stage, independent of EBNA2 or EBNA1 variability. A newly discovered EBNA1 subvariant, P-thr-sv-5, could be a potential diagnostic marker, as it represented a UCNT-specific EBNA1 subvariant. A particular combination of EBNA2, LMP1, and EBNA1 polymorphisms, type 1/Med/P-thr was identified as a possible risk factor for TNM stage IVB or progression to the N3 stage.     

Optimized Null Model for Protein Structure Networks

Much attention has recently been given to the statistical significance of topological features observed in biological networks. Here, we consider residue interaction graphs (RIGs) as network representations of protein structures with residues as nodes and inter-residue interactions as edges. Degree-preserving randomized models have been widely used for this purpose in biomolecular networks. However, such a single summary statistic of a network may not be detailed enough to capture the complex topological characteristics of protein structures and their network counterparts. Here, we investigate a variety of topological properties of RIGs to find a well fitting network null model for them. The RIGs are derived from a structurally diverse protein data set at various distance cut-offs and for different groups of interacting atoms. We compare the network structure of RIGs to several random graph models. We show that 3-dimensional geometric random graphs, that model spatial relationships between objects, provide the best fit to RIGs. We investigate the relationship between the strength of the fit and various protein structural features. We show that the fit depends on protein size, structural class, and thermostability, but not on quaternary structure. We apply our model to the identification of significantly over-represented structural building blocks, i.e., network motifs, in protein structure networks. As expected, choosing geometric graphs as a null model results in the most specific identification of motifs. Our geometric random graph model may facilitate further graph-based studies of protein conformation space and have important implications for protein structure comparison and prediction. The choice of a well-fitting null model is crucial for finding structural motifs that play an important role in protein folding, stability and function. To our knowledge, this is the first study that addresses the challenge of finding an optimized null model for RIGs, by comparing various RIG definitions against a series of network models.     

Complete genome sequence of Hirschia baltica type strain (IFAM 1418(T))

The family Hyphomonadaceae within the Alphaproteobacteria is largely comprised of bacteria isolated from marine environments with striking morphologies and an unusual mode of cell growth. Here, we report the complete genome sequence Hirschia baltica, which is only the second a member of the Hyphomonadaceae with a published genome sequence. H. baltica is of special interest because it has a dimorphic life cycle and is a stalked, budding bacterium. The 3,455,622 bp long chromosome and 84,492 bp plasmid with a total of 3,222 protein-coding and 44 RNA genes were sequenced as part of the DOE Joint Genome Institute Program CSP 2008.     

Bag3-Induced Autophagy Is Associated with Degradation of JCV Oncoprotein, T-Ag

JC virus, JCV, is a human neurotropic polyomavirus whose replication in glial cells causes the fatal demyelinating disease progressive multifocal leukoencephalopathy (PML). In addition, JCV possesses oncogenic activity and expression of its transforming protein, large T-antigen (T-Ag), in several experimental animals induces tumors of neural origin. Further, the presence of JCV DNA and T-Ag have been repeatedly observed in several human malignant tissues including primitive neuroectodermal tumors and glioblastomas. Earlier studies have demonstrated that Bag3, a member of the Bcl-2-associated athanogene (Bag) family of proteins, which is implicated in autophagy and apoptosis, is downregulated upon JCV infection of glial cells and that JCV T-Ag is responsible for suppressing the activity of the BAG3 promoter. Here, we investigated the possible impact of Bag3 on T-Ag expression in JCV-infected human primary glial cells as well as in cells derived from T-Ag-induced medulloblastoma in transgenic animals. Results from these studies revealed that overexpression of Bag3 drastically decreases the level of T-Ag expression by inducing the autophagic degradation of the viral protein. Interestingly, this event leads to the inhibition of JCV infection of glial cells, suggesting that the reduced levels of T-antigen seen upon the overexpression of Bag3 has a biological impact on the viral lytic cycle. Results from protein-protein interaction studies showed that T-Ag and Bag3 physically interact with each other through the zinc-finger of T-Ag and the proline rich domains of Bag3, and this interaction is important for the autophagic degradation of T-Ag. Our observations open a new avenue of research for better understanding of virus-host interaction by investigating the interplay between T-Ag and Bag3, and their impact on the development of JCV-associated diseases.     

Complete genome sequence of Ilyobacter polytropus type strain (CuHbu1)

Ilyobacter polytropus Stieb and Schink 1984 is the type species of the genus Ilyobacter, which belongs to the fusobacterial family Fusobacteriaceae. The species is of interest because its members are able to ferment quite a number of sugars and organic acids. I. polytropus has a broad versatility in using various fermentation pathways. Also, its members do not degrade poly-β-hydroxybutyrate but only the monomeric 3-hydroxybutyrate. This is the first completed genome sequence of a member of the genus Ilyobacter and the second sequence from the family Fusobacteriaceae. The 3,132,314 bp long genome with its 2,934 protein-coding and 108 RNA genes consists of two chromosomes (2 and 1 Mbp long) and one plasmid, and is a part of the Genomic Encyclopedia of Bacteria and Archaea project.     

Genome sequence of Brevibacillus laterosporus LMG 15441, a pathogen of invertebrates

Here we announce the genome sequence of the bacterium Brevibacillus laterosporus LMG 15441, which is a pathogen of invertebrates. The genome consists of one chromosome and two circular plasmids. Sequence analysis revealed a large potential to produce polyketides, nonribosomal peptides, and toxins.