Widespread Receptor Driven Modulation in Peripheral Olfactory Coding, bioRxiv, 2019-09-09
AbstractWe utilized swept confocally aligned planar excitation (SCAPE) microscopy to measure odor-driven activity simultaneously in many (>10,000) olfactory sensory neurons distributed over large areas of intact mouse olfactory epithelium. This approach allowed us to investigate the responses to mixtures or blends of odors and their components, a more realistic stimulus than monomolecular odors. In up to 38% of responding cells, responses to a mixture of odors were different - absent, smaller or larger - than what would be expected from the sum of the individual components. Further investigation revealed instances of both antagonism and allosteric enhancement in the primary olfactory sensory neurons. All 10 of the odor compounds tested were found to act as both agonists and antagonists at different receptors. We present a hypothetical scheme for how modulation at the peripheral receptors increases the capability of the olfactory system to recognize patterns of complex odor mixtures. The widespread modulation of primary sensory receptors argues against a simple combinatorial code and should motivate a search for alternative coding strategies.
biorxiv neuroscience 0-100-users 2019Improved metagenomic analysis with Kraken 2, bioRxiv, 2019-09-08
Although Kraken’s k-mer-based approach provides fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed five-fold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.
biorxiv bioinformatics 200-500-users 2019immuneSIM tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking, bioRxiv, 2019-09-07
AbstractSummaryB- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full length variable region immune receptor sequences. ImmuneSIM enables the tuning of the immune receptor features (i) species and chain type (BCR, TCR, single, paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation, and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis, and machine learning methods for motif detection.AvailabilityThe package is available via <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsgithub.comGreiffLabimmuneSIM>httpsgithub.comGreiffLabimmuneSIM<jatsext-link> and will also be available at CRAN (submitted). The documentation is hosted at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsimmuneSIM.readthedocs.io>httpsimmuneSIM.readthedocs.io<jatsext-link>.Contactvictor.greiff@medisin.uio.no, sai.reddy@ethz.ch
biorxiv bioinformatics 100-200-users 2019Single-cell RNA-sequencing reveals profibrotic roles of distinct epithelial and mesenchymal lineages in pulmonary fibrosis, bioRxiv, 2019-09-07
AbstractPulmonary fibrosis is a form of chronic lung disease characterized by pathologic epithelial remodeling and accumulation of extracellular matrix. In order to comprehensively define the cell types, mechanisms and mediators driving fibrotic remodeling in lungs with pulmonary fibrosis, we performed single-cell RNA-sequencing of single-cell suspensions from 10 non-fibrotic control and 20 PF lungs. Analysis of 114,396 cells identified 31 distinct cell types. We report a remarkable shift in epithelial cell phenotypes occurs in the peripheral lung in PF, and identify several previously unrecognized epithelial cell phenotypes including a KRT5−KRT17+, pathologic ECM-producing epithelial cell population that was highly enriched in PF lungs. Multiple fibroblast subtypes were observed to contribute to ECM expansion in a spatially-discrete manner. Together these data provide high-resolution insights into the complexity and plasticity of the distal lung epithelium in human disease, and indicate a diversity of epithelial and mesenchymal cells contribute to pathologic lung fibrosis.One Sentence SummarySingle-cell RNA-sequencing provides new insights into pathologic epithelial and mesenchymal remodeling in the human lung.
biorxiv genomics 100-200-users 2019Deep learning for brains? Different linear and nonlinear scaling in UK Biobank brain images vs. machine-learning datasets, bioRxiv, 2019-09-06
AbstractIn recent years, deep learning has unlocked unprecedented success in various domains, especially in image, text, and speech processing. These breakthroughs may hold promise for neuroscience and especially for brain-imaging investigators who start to analyze thousands of participants. However, deep learning is only beneficial if the data have nonlinear relationships and if they are exploitable at currently available sample sizes. We systematically profiled the performance of deep models, kernel models, and linear models as a function of sample size on UK Biobank brain images against established machine learning references. On MNIST and Zalando Fashion, prediction accuracy consistently improved when escalating from linear models to shallow-nonlinear models, and further improved when switching to deep-nonlinear models. The more observations were available for model training, the greater the performance gain we saw. In contrast, using structural or functional brain scans, simple linear models performed on par with more complex, highly parameterized models in agesex prediction across increasing sample sizes. In fact, linear models kept improving as the sample size approached ∼10,000 participants. Our results indicate that the increase in performance of linear models with additional data does not saturate at the limit of current feasibility. Yet, nonlinearities of common brain scans remain largely inaccessible to both kernel and deep learning methods at any examined scale.
biorxiv bioinformatics 100-200-users 2019Single Cell RNA-seq reveals ectopic and aberrant lung resident cell populations in Idiopathic Pulmonary Fibrosis, bioRxiv, 2019-09-06
AbstractWe provide a single cell atlas of Idiopathic Pulmonary Fibrosis (IPF), a fatal interstitial lung disease, focusing on resident lung cell populations. By profiling 312,928 cells from 32 IPF, 29 healthy control and 18 chronic obstructive pulmonary disease (COPD) lungs, we demonstrate that IPF is characterized by changes in discrete subpopulations of cells in the three major parenchymal compartments the epithelium, endothelium and stroma. Among epithelial cells, we identify a novel population of IPF enriched aberrant basaloid cells that co-express basal epithelial markers, mesenchymal markers, senescence markers, developmental transcription factors and are located at the edge of myofibroblast foci in the IPF lung. Among vascular endothelial cells in the in IPF lung parenchyma we identify an expanded cell population transcriptomically identical to vascular endothelial cells normally restricted to the bronchial circulation. We confirm the presence of both populations by immunohistochemistry and independent datasets. Among stromal cells we identify fibroblasts and myofibroblasts in both control and IPF lungs and leverage manifold-based algorithms diffusion maps and diffusion pseudotime to infer the origins of the activated IPF myofibroblast. Our work provides a comprehensive catalogue of the aberrant cellular transcriptional programs in IPF, demonstrates a new framework for analyzing complex disease with scRNAseq, and provides the largest lung disease single-cell atlas to date.
biorxiv genomics 0-100-users 2019