Dieses Sachbuch berichtet über die Entschlüsselung der inneren Uhren, den sogenannten circadianen Rhythmen, und wie diese in Organismen auf molekularer Ebene zustande kommen. Die Autoren gewähren faszinierende Einblicke wie Sport, Schlaf oder gar Sex von diesen Rhythmen beeinflusst werden.

High-throughput experiments are characterized by the generation of large amounts of imaging data in short time which requires fast, automated and reliable methods for processing and analysis. Most of the gold standard meth­ods for quantitative and semi-quantitative analysis of fluorescent images are relying on human decision-making. The existing automated analysis methods require very strict maintenance of constancy in all experimental condi­tions from animal care and material acquisition to image acquisition. In the high-throughput experiments, how­ever, even the smallest biases introduced by human involvement and the tiniest fluctuations of experimental con­ditions may be multiplied to unacceptable magnitudes. Thus, any image processing and analysis algorithm, part of such an experiment, must reduce human-produced biases and be robust to variability in experimental condi­tions. We propose a processing sequence suitable for the analysis of images produced by wide-field epifluores­cence RNA-FISH and FIHC experiments which is easily adjustable to the conditions of different experiments. The algorithm involves the following steps: (i) Optimal image acquisition of multichannel z-stack images; (ii) Shad­ing correction of the multidimensional images; (iii) Single manifold extraction of an accurate high-contrast de­blurred 2D-projection; (iv) Correction of exposure with emphasis on background normalization in the final im­age. With this algorithm, we produced images for automated classification of cells expressing different markers. After the initial processing a machine learning algorithm segments the DAPI stained channel and perinuclear re­gions of interest are produced. Next, the marker channels overlap with the perinuclear RoIs was used to classify each cell into positive or negative for the corresponding marker. The proposed sequence of image processing and analysis steps is performed with an easily procurable open source software (Fiji/ImageJ and Ilastik) which allows full automation thanks to its scripting capabilities.

NG2-glia in the adult brain are known to proliferate and differentiate into mature and myelinating oligodendrocytes throughout lifetime. However, the role of these newly generated oligodendrocytes in the adult brain still remains little understood. Here we took advantage of the Sox10-iCreERT2 x CAG-eGFP x Esco2fl/fl mouse line in which we can specifically ablate proliferating NG2-glia in adult animals. Surprisingly, we observed that the generation of new oligodendrocytes in the adult brain was severely affected, although the number of NG2-glia remained stable due to the enhanced proliferation of non-recombined cells. This lack of oligodendrogenesis led to the elongation of the nodes of Ranvier as well as the associated paranodes, which could be locally rescued by myelinating oligodendrocytes differentiated from transplanted NG2-glia deriving from wildtype mice. Repetitive measurements of conduction velocity in the corpus callosum of awake animals revealed a progressive deceleration specifically in the mice lacking adult oligodendrogenesis that resulted in progressive motor deficits. In summary, here we demonstrated for the first time that axon function is not only controlled by the reliable organization of myelin, but also requires a dynamic and continuous generation of new oligodendrocytes in the adult brain. GLIA 2016;64:2201-2218.

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We discuss technical means by which the complexity of gene and protein signalling cascades can be projected onto the complex structure of the mammalian brain. We argue that this requires both robotics and novel computational tools to register images of gene expression, annotate expression patterns and quantify gene expression. When sufficiently enriched and detailed, such gene expression/neuroanatomical atlases are hypothesis‐generating tools and contain in themselves much of the information needed to investigate function in normal and genetically or otherwise modified brains. To be successful and useful, data‐rich and comprehensive gene expression/neuroanatomical atlases have to be web accessible and structured in a way that allows the application of data exploration and mining tools.

Adenylate cyclases (Adcys) are components of several developmentally, neurophysiologically, and pharmacologically relevant signaling pathways. A prominent feature of Adcys is their ability to integrate multiple signaling pathways into a single second messenger pathway, the production of cAMP. Nine isoforms of membrane‐bound Adcys are known, each encoded by a distinct gene. These isoforms differ in their response to regulatory upstream pathways as well as in their distribution in the brain and elsewhere. Use of various detection methods and animal species has, however, hampered a direct comparison of expression patterns, so the potential contribution of single isoforms to Adcy activity in different brain regions remains unclear. We have determined the expression patterns of all nine Adcy genes in the embryonic, postnatal day 7, and adult mouse brain by nonradioactive robotic in situ hybridization (ISH). Here we describe the salient features of these patterns. Regional colocalization of Adcy transcripts encoding isoforms with different regulatory properties was detected in the cortex, subregions of the hippocampus, olfactory bulb, thalamus, and striatum. Hence, our expression data support models for modulation of cAMP signaling by combinatorial action of multiple Adcy isoforms. However, in several instances, the expression domains of genes encoding isoforms with similar regulatory properties spatially exclude each other, which is most evident in not previously described expression domains of the embryonic midbrain roof. This is suggestive of functional specialization. J. Comp. Neurol. 496:684–697, 2006. © 2006 Wiley‐Liss, Inc.

Associating specific gene activity with functional locations in the brain results in a greater understanding of the role of the gene. To perform such an association for the over 20,000 genes in the mammalian genome, reliable automated methods that characterize the distribution of gene expression in relation to a standard anatomical model are required. In this work, we propose a new automatic method that results in the segmentation of gene expression images into distinct anatomical regions in which the expression can be quantified and compared with other images. Our method utilizes shape models from training images, texture differentiation at region boundaries, and features of anatomical landmarks, to deform a subdivision mesh-based atlas to fit gene expression images. The subdivision mesh provides a common coordinate system for internal brain data through which gene expression patterns can be compared across images. The automated large-scale annotation will help scientists interpret gene expression patterns at cellular resolution more efficiently.

A recently developed robotic platform termed “Genepaint” can carry out large‐scale nonradioactive in situ hybridization (ISH) on tissue sections. We report a series of experiments that validate this novel platform. Signal‐to‐noise ratio and mRNA detection limits were comparable to traditional ISH procedures, and hybridization was transcript‐specific, even in cases in which probes could have hybridized to several transcripts of a multigene family. We established an atlas of expression patterns of fibroblast growth factors ( Fgfs ) and their receptors ( Fgfrs ) for the embryonic day 14.5 mouse embryo. This atlas provides a comprehensive overview of previously known as well as novel sites of expression for this important family of signaling molecules. The Fgf / Fgfr atlas was integrated into the transcriptome database ( www.genepaint.org ), where individual Fgf and Fgfr expression patterns can be interactively viewed at cellular resolution and where sites of expressions can be retrieved using an anatomy‐based search. Developmental Dynamics 234:371–386, 2005. © 2005 Wiley‐Liss, Inc.

The orphan nuclear receptor Ear2 (Nr2f6) is transiently expressed in the rostral part of the rhombic lip in which the locus coeruleus (LC) arises. LC development, regulated by a signaling cascade (Mash1 --> Phox2b --> Phox2a), is disrupted in Ear2-/- embryos as revealed by an approximately threefold reduction in the number of Phox2a- and Phox2b-expressing LC progenitor cells. Mash1 expression in the rhombic lip, however, is unaffected, placing Ear2 in between Mash1 and Phox2a/b. Dopamine-beta-hydroxylase and tyrosine hydroxylase staining demonstrate that >70% of LC neurons are absent in the adult with agenesis affecting primarily the dorsal division of the LC. Normally, this division projects noradrenergic efferents to the cortex that appear to be diminished in Ear2-/- since the cortical concentration of noradrenaline is four times lower in these mice. The rostral region of the cortex is known to contain a circadian pacemaker regulating adaptability to light- and restricted food-driven entrainment. In situ hybridization establishes that the circadian expression pattern of the clock gene Period1 is abolished in the Ear2-/- forebrain. Behavioral experiments reveal that Ear2 mutants have a delayed entrainment to shifted light-dark cycles and adapt less efficiently to daytime feeding schedules. We propose that neurons in the dorsal division of LC contribute to the regulation of the forebrain clock, at least in part, through targeted release of noradrenaline into the cortical area.

Acquiring information about the expression of a gene in different cell populations and tissues can provide key insight into the function of the gene. A high-throughput in situ hybridization (ISH) method was recently developed for rapid and reproducible acquisition of gene expression patterns in serial tissue sections at cellular resolution. Characterizing and analysing expression patterns on thousands of sections requires efficient methods for locating cells and estimating the level of expression in each cell. Such cellular quantification is an essential step in both annotating and quantitatively comparing high-throughput ISH results. Here we describe a novel automated and efficient methodology for performing this quantification on postnatal mouse brain.