Miro clusters regulate ER-mitochondria contact sites and link cristae organization to the mitochondrial transport machinery

Mitochondrial Rho (Miro) GTPases localize to the outer mitochondrial membrane and are essential machinery for the regulated trafficking of mitochondria to defined subcellular locations. However, their sub-mitochondrial localization and relationship with other critical mitochondrial complexes remains poorly understood. Here, using super-resolution fluorescence microscopy, we report that Miro proteins form nanometer-sized clusters along the mitochondrial outer membrane in association with the Mitochondrial Contact Site and Cristae Organizing System (MICOS). Using knockout mouse embryonic fibroblasts we show that Miro1 and Miro2 are required for normal mitochondrial cristae architecture and Endoplasmic Reticulum-Mitochondria Contacts Sites (ERMCS). Further, we show that Miro couples MICOS to TRAK motor protein adaptors to ensure the concerted transport of the two mitochondrial membranes and the correct distribution of cristae on the mitochondrial membrane. The Miro nanoscale organization, association with MICOS complex and regulation of ERMCS reveal new levels of control of the Miro GTPases on mitochondrial functionality

Comparison of two normative paediatric gait databases

The availability of age-matched normative data is an essential component of clinical gait analyses. Comparison of normative gait databases is difficult due to the high-dimensionality and temporal nature of the various gait waveforms. The purpose of this study was to provide a method of comparing the sagittal joint angle data between two normative databases. We compared a modern gait database to the historical San Diego database using statistical classifiers developed by Tingley et al. (2002). Gait data were recorded from 60 children aged 1–13 years. A six-camera Vicon 512 motion analysis system and two force plates were utilized to obtain temporal-spatial, kinematic, and kinetic parameters during walking. Differences between the two normative data sets were explored using the classifier index scores, and the mean and covariance structure of the joint angle data from each lab. Significant differences in sagittal angle data between the two databases were identified and attributed to technological advances and data processing techniques (data smoothing, sampling, and joint angle approximations). This work provides a simple method of database comparison using trainable statistical classifiers

A Functional Gene Array for Detection of Bacterial Virulence Elements

Emerging known and unknown pathogens create profound threats to public health. Platforms for rapid detection and characterization of microbial agents are critically needed to prevent and respond to disease outbreaks. Available detection technologies cannot provide broad functional information about known or novel organisms. As a step toward developing such a system, we have produced and tested a series of high-density functional gene arrays to detect elements of virulence and antibiotic resistance mechanisms. Our first generation array targets genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for gene family detection and discrimination. When tested with organisms at varying phylogenetic distances from the four target strains, the array detected orthologs for the majority of targeted gene families present in bacteria belonging to the same taxonomic family. In combination with whole-genome amplification, the array detects femtogram concentrations of purified DNA, either spiked in to an aerosol sample background, or in combinations from one or more of the four target organisms. This is the first report of a high density NimbleGen microarray system targeting microbial antibiotic resistance and virulence mechanisms. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples

Position dependent mismatch discrimination on DNA microarrays – experiments and model

<p>Abstract</p> <p>Background</p> <p>The propensity of oligonucleotide strands to form stable duplexes with complementary sequences is fundamental to a variety of biological and biotechnological processes as various as microRNA signalling, microarray hybridization and PCR. Yet our understanding of oligonucleotide hybridization, in particular in presence of surfaces, is rather limited. Here we use oligonucleotide microarrays made in-house by optically controlled DNA synthesis to produce probe sets comprising all possible single base mismatches and base bulges for each of 20 sequence motifs under study.</p> <p>Results</p> <p>We observe that mismatch discrimination is mostly determined by the defect position (relative to the duplex ends) as well as by the sequence context. We investigate the thermodynamics of the oligonucleotide duplexes on the basis of double-ended molecular zipper. Theoretical predictions of defect positional influence as well as long range sequence influence agree well with the experimental results.</p> <p>Conclusion</p> <p>Molecular zipping at thermodynamic equilibrium explains the binding affinity of mismatched DNA duplexes on microarrays well. The position dependent nearest neighbor model (PDNN) can be inferred from it. Quantitative understanding of microarray experiments from first principles is in reach.</p

Psoriasis Regression Analysis of MHC Loci Identifies Shared Genetic Variants with Vitiligo

Psoriasis is a common inflammatory skin disease with genetic components of both immune system and the epidermis. PSOR1 locus (6q21) has been strongly associated with psoriasis; however, it is difficult to identify additional independent association due to strong linkage disequilibrium in the MHC region. We performed stepwise regression analyses of more than 3,000 SNPs in the MHC region genotyped using Human 610-Quad (Illumina) in 1,139 cases with psoriasis and 1,132 controls of Han Chinese population to search for additional independent association. With four regression models obtained, two SNPs rs9468925 in HLA-C/HLA-B and rs2858881 in HLA-DQA2 were repeatedly selected in all models, suggesting that multiple loci outside PSOR1 locus were associated with psoriasis. More importantly we find that rs9468925 in HLA-C/HLA-B is associated with both psoriasis and vitiligo, providing first important evidence that two major skin diseases share a common genetic locus in the MHC, and a basis for elucidating the molecular mechanism of skin disorders

Mutations in Wnt2 Alter Presynaptic Motor Neuron Morphology and Presynaptic Protein Localization at the Drosophila Neuromuscular Junction

Wnt proteins are secreted proteins involved in a number of developmental processes including neural development and synaptogenesis. We sought to determine the role of the Drosophila Wnt7b ortholog, Wnt2, using the neuromuscular junction (NMJ). Mutations in wnt2 produce an increase in the number of presynaptic branches and a reduction in immunolabeling of the active zone proteins, Bruchpilot and synaptobrevin, at the NMJ. There was no change, however, in immunolabeling for the presynaptic proteins cysteine-string protein (CSP) and synaptotagmin, nor the postsynaptic proteins GluRIIA and DLG at the NMJ. Consistent with the presynaptic defects, wnt2 mutants exhibit approximately a 50% reduction in evoked excitatory junctional currents. Rescue, RNAi, and tissue-specific qRT-PCR experiments indicate that Wnt2 is expressed by the postsynaptic cell where it may serve as a retrograde signal that regulates presynaptic morphology and the localization of presynaptic proteins

The glial growth factors deficiency and synaptic destabilization hypothesis of schizophrenia

BACKGROUND: A systems approach to understanding the etiology of schizophrenia requires a theory which is able to integrate genetic as well as neurodevelopmental factors. PRESENTATION OF THE HYPOTHESIS: Based on a co-localization of loci approach and a large amount of circumstantial evidence, we here propose that a functional deficiency of glial growth factors and of growth factors produced by glial cells are among the distal causes in the genotype-to-phenotype chain leading to the development of schizophrenia. These factors include neuregulin, insulin-like growth factor I, insulin, epidermal growth factor, neurotrophic growth factors, erbB receptors, phosphatidylinositol-3 kinase, growth arrest specific genes, neuritin, tumor necrosis factor alpha, glutamate, NMDA and cholinergic receptors. A genetically and epigenetically determined low baseline of glial growth factor signaling and synaptic strength is expected to increase the vulnerability for additional reductions (e.g., by viruses such as HHV-6 and JC virus infecting glial cells). This should lead to a weakening of the positive feedback loop between the presynaptic neuron and its targets, and below a certain threshold to synaptic destabilization and schizophrenia. TESTING THE HYPOTHESIS: Supported by informed conjectures and empirical facts, the hypothesis makes an attractive case for a large number of further investigations. IMPLICATIONS OF THE HYPOTHESIS: The hypothesis suggests glial cells as the locus of the genes-environment interactions in schizophrenia, with glial asthenia as an important factor for the genetic liability to the disorder, and an increase of prolactin and/or insulin as possible working mechanisms of traditional and atypical neuroleptic treatments

Image-based promoter prediction: a promoter prediction method based on evolutionarily generated patterns

Abstract Prediction of promoter regions is crucial for studying gene function and regulation. The well-accepted position weight matrix method for this purpose relies on predefined motifs, which would hinder application across different species. Here, we introduce image-based promoter prediction (IBPP) as a method that creates an “image” from training promoter sequences using an evolutionary approach and predicts promoters by matching with the “image”. We used Escherichia coli σ70 promoter sequences to test the performance of IBPP and the combination of IBPP and a support vector machine algorithm (IBPP-SVM). The “images” generated with IBPP could effectively distinguish promoter from non-promoter sequences. Compared with IBPP, IBPP-SVM showed a substantial improvement in sensitivity. Furthermore, both methods showed good performance for sequences of up to 2,000 nt in length. The performances of IBPP and IBPP-SVM were largely affected by the threshold and dimension of vectors, respectively. The source code and documentation are freely available at https://github.com/hahatcdg/IBPP