Structural Basis for Receptor-Mediated Selective Autophagy of Aminopeptidase I Aggregates

SummarySelective autophagy mediates the degradation of various cargoes, including protein aggregates and organelles, thereby contributing to cellular homeostasis. Cargo receptors ensure selectivity by tethering specific cargo to lipidated Atg8 at the isolation membrane. However, little is known about the structural requirements underlying receptor-mediated cargo recognition. Here, we report structural, biochemical, and cell biological analysis of the major selective cargo protein in budding yeast, aminopeptidase I (Ape1), and its complex with the receptor Atg19. The Ape1 propeptide has a trimeric coiled-coil structure, which tethers dodecameric Ape1 bodies together to form large aggregates. Atg19 disassembles the propeptide trimer and forms a 2:1 heterotrimer, which not only blankets the Ape1 aggregates but also regulates their size. These receptor activities may promote elongation of the isolation membrane along the aggregate surface, enabling sequestration of the cargo with high specificity

PosMed (Positional Medline): prioritizing genes with an artificial neural network comprising medical documents to accelerate positional cloning

PosMed (http://omicspace.riken.jp/) prioritizes candidate genes for positional cloning by employing our original database search engine GRASE, which uses an inferential process similar to an artificial neural network comprising documental neurons (or ‘documentrons’) that represent each document contained in databases such as MEDLINE and OMIM. Given a user-specified query, PosMed initially performs a full-text search of each documentron in the first-layer artificial neurons and then calculates the statistical significance of the connections between the hit documentrons and the second-layer artificial neurons representing each gene. When a chromosomal interval(s) is specified, PosMed explores the second-layer and third-layer artificial neurons representing genes within the chromosomal interval by evaluating the combined significance of the connections from the hit documentrons to the genes. PosMed is, therefore, a powerful tool that immediately ranks the candidate genes by connecting phenotypic keywords to the genes through connections representing not only gene–gene interactions but also other biological interactions (e.g. metabolite–gene, mutant mouse–gene, drug–gene, disease–gene and protein–protein interactions) and ortholog data. By utilizing orthologous connections, PosMed facilitates the ranking of human genes based on evidence found in other model species such as mouse. Currently, PosMed, an artificial superbrain that has learned a vast amount of biological knowledge ranging from genomes to phenomes (or ‘omic space’), supports the prioritization of positional candidate genes in humans, mouse, rat and Arabidopsis thaliana

Thin Film Growth and Device Fabrication of Iron-Based Superconductors

Iron-based superconductors have received much attention as a new family of high-temperature superconductors owing to their unique properties and distinct differences from cuprates and conventional superconductors. This paper reviews progress in thin film research on iron-based superconductors since their discovery for each of five material systems with an emphasis on growth, physical properties, device fabrication, and relevant bulk material properties.Comment: To appear in J. Phys. Soc. Jp

Improved tractography using asymmetric fibre orientation distributions

Diffusion MRI allows us to make inferences on the structural organisation of the brain by mapping water diffusion to white matter microstructure. However, such a mapping is generally ill-defined; for instance, diffusion measurements are antipodally symmetric (diffusion along x and –x are equal), whereas the distribution of fibre orientations within a voxel is generally not symmetric. Therefore, different sub-voxel patterns such as crossing, fanning, or sharp bending, cannot be distinguished by fitting a voxel-wise model to the signal. However, asymmetric fibre patterns can potentially be distinguished once spatial information from neighbouring voxels is taken into account. We propose a neighbourhood-constrained spherical deconvolution approach that is capable of inferring asymmetric fibre orientation distributions (A-fods). Importantly, we further design and implement a tractography algorithm that utilises the estimated A-fods, since the commonly used streamline tractography paradigm cannot directly take advantage of the new information. We assess performance using ultra-high resolution histology data where we can compare true orientation distributions against sub-voxel fibre patterns estimated from down-sampled data. Finally, we explore the benefits of A-fods-based tractography using in vivo data by evaluating agreement of tractography predictions with connectivity estimates made using different in-vivo modalities. The proposed approach can reliably estimate complex fibre patterns such as sharp bending and fanning, which voxel-wise approaches cannot estimate. Moreover, histology-based and in-vivo results show that the new framework allows more accurate tractography and reconstruction of maps quantifying (symmetric and asymmetric) fibre complexity

A High-Speed Congenic Strategy Using First-Wave Male Germ Cells

BACKGROUND: In laboratory mice and rats, congenic breeding is essential for analyzing the genes of interest on specific genetic backgrounds and for analyzing quantitative trait loci. However, in theory it takes about 3-4 years to achieve a strain carrying about 99% of the recipient genome at the tenth backcrossing (N10). Even with marker-assisted selection, the so-called 'speed congenic strategy', it takes more than a year at N4 or N5. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe a new high-speed congenic system using round spermatids retrieved from immature males (22-25 days of age). We applied the technique to three genetically modified strains of mice: transgenic (TG), knockin (KI) and N-ethyl-N-nitrosourea (ENU)-induced mutants. The donor mice had mixed genetic backgrounds of C57BL/6 (B6):DBA/2 or B6:129 strains. At each generation, males used for backcrossing were selected based on polymorphic marker analysis and their round spermatids were injected into B6 strain oocytes. Backcrossing was repeated until N4 or N5. For the TG and ENU-mutant strains, the N5 generation was achieved on days 188 and 190 and the proportion of B6-homozygous loci was 100% (74 markers) and 97.7% (172/176 markers), respectively. For the KI strain, N4 was achieved on day 151, all the 86 markers being B6-homozygous as early as on day 106 at N3. The carrier males at the final generation were all fertile and propagated the modified genes. Thus, three congenic strains were established through rapid generation turnover between 41 and 44 days. CONCLUSIONS/SIGNIFICANCE: This new high-speed breeding strategy enables us to produce congenic strains within about half a year. It should provide the fastest protocol for precise definition of the phenotypic effects of genes of interest on desired genetic backgrounds

Fusion in diffusion MRI for improved fibre orientation estimation: an application to the 3T and 7T data of the Human Connectome Project

Determining the acquisition parameters in diffusion magnetic resonance imaging (dMRI) is governed by a series of trade-offs. Images of lower resolution have less spatial specificity but higher signal to noise ratio (SNR). At the same time higher angular contrast, important for resolving complex fibre patterns, also yields lower SNR. Considering these trade-offs, the Human Connectome Project (HCP) acquires high quality dMRI data for the same subjects at different field strengths (3T and 7T), which are publically released. Due to differences in the signal behavior and in the underlying scanner hardware, the HCP 3T and 7T data have complementary features in k- and q-space. The 3T dMRI has higher angular contrast and resolution, while the 7T dMRI has higher spatial resolution. Given the availability of these datasets, we explore the idea of fusing them together with the aim of combining their benefits. We extend a previously proposed data-fusion framework and apply it to integrate both datasets from the same subject into a single joint analysis. We use a generative model for performing parametric spherical deconvolution and estimate fibre orientations by simultaneously using data acquired under different protocols. We illustrate unique features from each dataset and how they are retained after fusion. We further show that this allows us to complement benefits and improve brain connectivity analysis compared to analyzing each of the datasets individually

Prevalence of sexual dimorphism in mammalian phenotypic traits

The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans

The RIKEN integrated database of mammals

The RIKEN integrated database of mammals (http://scinets.org/db/mammal) is the official undertaking to integrate its mammalian databases produced from multiple large-scale programs that have been promoted by the institute. The database integrates not only RIKEN’s original databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists’ Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information

Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank