DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders

This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencoder (CDAE) for generating an invariant, compact representation of in situ hybridization (ISH) images. While most existing methods for bio-imaging analysis were not developed to handle images with highly complex anatomical structures, the results presented in this paper show that functional representation extracted by CDAE can help learn features of functional gene ontology categories for their classification in a highly accurate manner. Using this CDAE representation, our method outperforms the previous state-of-the-art classification rate, by improving the average AUC from 0.92 to 0.98, i.e., achieving 75% reduction in error. The method operates on input images that were downsampled significantly with respect to the original ones to make it computationally feasible

Output from VIP cells of the mammalian central clock regulates daily physiological rhythms

The suprachiasmatic nucleus (SCN) circadian clock is critical for optimising daily cycles in mammalian physiology and behaviour. The roles of the various SCN cell types in communicating timing information to downstream physiological systems remain incompletely understood, however. In particular, while vasoactive intestinal polypeptide (VIP) signalling is essential for SCN function and whole animal circadian rhythmicity, the specific contributions of VIP cell output to physiological control remains uncertain. Here we reveal a key role for SCN VIP cells in central clock output. Using multielectrode recording and optogenetic manipulations, we show that VIP neurons provide coordinated daily waves of GABAergic input to target cells across the paraventricular hypothalamus and ventral thalamus, supressing their activity during the mid to late day. Using chemogenetic manipulation, we further demonstrate specific roles for this circuitry in the daily control of heart rate and corticosterone secretion, collectively establishing SCN VIP cells as influential regulators of physiological timing

Unique reporter-based sensor platforms to monitor signalling in cells

Introduction: In recent years much progress has been made in the development of tools for systems biology to study the levels of mRNA and protein, and their interactions within cells. However, few multiplexed methodologies are available to study cell signalling directly at the transcription factor level. <p/>Methods: Here we describe a sensitive, plasmid-based RNA reporter methodology to study transcription factor activation in mammalian cells, and apply this technology to profiling 60 transcription factors in parallel. The methodology uses two robust and easily accessible detection platforms; quantitative real-time PCR for quantitative analysis and DNA microarrays for parallel, higher throughput analysis. <p/>Findings: We test the specificity of the detection platforms with ten inducers and independently validate the transcription factor activation. <p/>Conclusions: We report a methodology for the multiplexed study of transcription factor activation in mammalian cells that is direct and not theoretically limited by the number of available reporters

Scalable In Situ Hybridization on Tissue Arrays for Validation of Novel Cancer and Tissue-Specific Biomarkers

Tissue localization of gene expression is increasingly important for accurate interpretation of large scale datasets from expression and mutational analyses. To this end, we have (1) developed a robust and scalable procedure for generation of mRNA hybridization probes, providing >95% first-pass success rate in probe generation to any human target gene and (2) adopted an automated staining procedure for analyses of formalin-fixed paraffin-embedded tissues and tissue microarrays. The in situ mRNA and protein expression patterns for genes with known as well as unknown tissue expression patterns were analyzed in normal and malignant tissues to assess procedure specificity and whether in situ hybridization can be used for validating novel antibodies. We demonstrate concordance between in situ transcript and protein expression patterns of the well-known pathology biomarkers KRT17, CHGA, MKI67, PECAM1 and VIL1, and provide independent validation for novel antibodies to the biomarkers BRD1, EZH2, JUP and SATB2. The present study provides a foundation for comprehensive in situ gene set or transcriptome analyses of human normal and tumor tissues

Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo

Cortical fast-spiking parvalbumin interneurons enwrapped in the perineuronal net express the metallopeptidases Adamts8, Adamts15 and Neprilysin.

The in situ hybridization Allen Mouse Brain Atlas was mined for proteases expressed in the somatosensory cerebral cortex. Among the 480 genes coding for protease/peptidases, only four were found enriched in cortical interneurons: Reln coding for reelin; Adamts8 and Adamts15 belonging to the class of metzincin proteases involved in reshaping the perineuronal net (PNN) and Mme encoding for Neprilysin, the enzyme degrading amyloid β-peptides. The pattern of expression of metalloproteases (MPs) was analyzed by single-cell reverse transcriptase multiplex PCR after patch clamp and was compared with the expression of 10 canonical interneurons markers and 12 additional genes from the Allen Atlas. Clustering of these genes by K-means algorithm displays five distinct clusters. Among these five clusters, two fast-spiking interneuron clusters expressing the calcium-binding protein Pvalb were identified, one co-expressing Pvalb with Sst (PV-Sst) and another co-expressing Pvalb with three metallopeptidases Adamts8, Adamts15 and Mme (PV-MP). By using Wisteria floribunda agglutinin, a specific marker for PNN, PV-MP interneurons were found surrounded by PNN, whereas the ones expressing Sst, PV-Sst, were not

An anatomic gene expression atlas of the adult mouse brain

Studying gene expression provides a powerful means of understanding structure-function relationships in the nervous system. The availability of genome-scale in situ hybridization datasets enables new possibilities for understanding brain organization based on gene expression patterns. The Anatomic Gene Expression Atlas (AGEA) is a new relational atlas revealing the genetic architecture of the adult C57Bl/6J mouse brain based on spatial correlations across expression data for thousands of genes in the Allen Brain Atlas (ABA). The AGEA includes three discovery tools for examining neuroanatomical relationships and boundaries: (1) three-dimensional expression-based correlation maps, (2) a hierarchical transcriptome-based parcellation of the brain and (3) a facility to retrieve from the ABA specific genes showing enriched expression in local correlated domains. The utility of this atlas is illustrated by analysis of genetic organization in the thalamus, striatum and cerebral cortex. The AGEA is a publicly accessible online computational tool integrated with the ABA (http://mouse.brain-map.org/agea)

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page