Projection Neuron Circuits Resolved Using Correlative Array Tomography

Assessment of three-dimensional morphological structure and synaptic connectivity is essential for a comprehensive understanding of neural processes controlling behavior. Different microscopy approaches have been proposed based on light microcopy (LM), electron microscopy (EM), or a combination of both. Correlative array tomography (CAT) is a technique in which arrays of ultrathin serial sections are repeatedly stained with fluorescent antibodies against synaptic molecules and neurotransmitters and imaged with LM and EM (Micheva and Smith, 2007). The utility of this correlative approach is limited by the ability to preserve fluorescence and antigenicity on the one hand, and EM tissue ultrastructure on the other. We demonstrate tissue staining and fixation protocols and a workflow that yield an excellent compromise between these multimodal imaging constraints. We adapt CAT for the study of projection neurons between different vocal brain regions in the songbird. We inject fluorescent tracers of different colors into afferent and efferent areas of HVC in zebra finches. Fluorescence of some tracers is lost during tissue preparation but recovered using anti-dye antibodies. Synapses are identified in EM imagery based on their morphology and ultrastructure and classified into projection neuron type based on fluorescence signal. Our adaptation of array tomography, involving the use of fluorescent tracers and heavy-metal rich staining and embedding protocols for high membrane contrast in EM will be useful for research aimed at statistically describing connectivity between different projection neuron types and for elucidating how sensory signals are routed in the brain and transformed into a meaningful motor output

Correlative Microscopy of Densely Labeled Projection Neurons Using Neural Tracers

Three-dimensional morphological information about neural microcircuits is of high interest in neuroscience, but acquiring this information remains challenging. A promising new correlative technique for brain imaging is array tomography (Micheva and Smith, 2007), in which series of ultrathin brain sections are treated with fluorescent antibodies against neurotransmitters and synaptic proteins. Treated sections are repeatedly imaged in the fluorescence light microscope (FLM) and then in the electron microscope (EM). We explore a similar correlative imaging technique in which we differentially label distinct populations of projection neurons, the key routers of electrical signals in the brain. In songbirds, projection neurons can easily be labeled using neural tracers, because the vocal control areas are segregated into separate nuclei. We inject tracers into areas afferent and efferent to the main premotor area for vocal production, HVC, to retrogradely and anterogradely label different classes of projection neurons. We optimize tissue preparation protocols to achieve high fluorescence contrast in the FLM and good ultrastructure in the EM (using osmium tetroxide). Although tracer fluorescence is lost during EM preparation, we localize the tracer molecules after fixation and embedding by using fluorescent antibodies against them. We detect signals mainly in somata and dendrites, allowing us to classify synapses within a single ultrathin section as belonging to a particular type of projection neuron. The use of our method will be to provide statistical information about connectivity among different neuron classes, and to elucidate how signals in the brain are processed and routed among different areas

Hoxa2 Selects Barrelette Neuron Identity and Connectivity in the Mouse Somatosensory Brainstem

Mouse whiskers are somatotopically mapped in brainstem trigeminal nuclei as neuronal modules known as barrelettes. Whisker-related afferents form barrelettes in ventral principal sensory (vPrV) nucleus, whereas mandibular input targets dorsal PrV (dPrV). How barrelette neuron identity and circuitry is established is poorly understood. We found that ectopic Hoxa2 expression in dPrV neurons is sufficient to attract whisker-related afferents, induce asymmetrical dendrite arbors, and allow ectopic barrelette map formation. Moreover, the thalamic area forming whisker-related barreloids is prenatally targeted by both vPrV and dPrV axons followed by perinatal large-scale pruning of dPrV axons and refinement of vPrV barrelette input. Ectopic Hoxa2 expression allows topographically directed targeting and refinement of dPrV axons with vPrV axons into a single whisker-related barreloid map. Thus, a single HOX transcription factor is sufficient to switch dPrV into a vPrV barrelette neuron program and coordinate input-output topographic connectivity of a dermatome-specific circuit module.publishe

EDAM-bioimaging: the ontology of bioimage informatics operations, topics, data, and formats (update 2020)

EDAM is a well-established ontology of operations, topics, types of data, and data formats that are used in bioinformatics and its neighbouring fields [1,2] . EDAM-bioimaging is an extension of EDAM dedicated to bioimage analysis, bioimage informatics, and bioimaging. It is being developed in collaboration between the ELIXIR research infrastructure and the NEUBIAS and COMULIS COST Actions, in close contact with the Euro-BioImaging research infrastructure and the Global BioImaging network. EDAM-bioimaging contains an inter-related hierarchy of concepts including bioimage analysis and related operations, bioimaging topics and technologies, and bioimage data and their formats. The modelled concepts enable interoperable descriptions of software, publications, data, workflows, and training materials, fostering open science and "reproducible" bioimage analysis. New developments in EDAM-bioimaging at the time of publication [3] include among others: A concise but relatively comprehensive ontology of Machine learning, Artificial intelligence, and Clustering (to the level relevant in particular in bioimaging, biosciences, and also scientific data analysis in general) Added and refined topics and synonyms within Sample preparation and Tomography, and finalised coverage of imaging techniques (all of these to the high-level extent that influences choices of downstream analysis, i.e. the scope of EDAM) EDAM-bioimaging continues being under active development, with a growing and diversifying community of contributors. It is used in BIII.eu, the registry of bioimage analysis tools, workflows, and training materials, and emerging also in descriptions of Debian Med packages available in Debian and Bio-Linux, and tools in bio.tools. Development of EDAM-bioimaging has been carried out in a successful open community manner, in a fruitful collaboration between numerous bioimaging experts and ontology developers. The last stable release at the time of poster publication is version alpha06 [3], and the live development version can be viewed and commented on WebProtégé (free registration required). New contributors are warmly welcome! [1] Ison, J., Kalaš, M., Jonassen, I., Bolser, D., Uludag, M., McWilliam, H., Malone, J., Lopez, R., Pettifer, S. and Rice, P. (2013). EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats. Bioinformatics, 29(10): 1325-1332. DOI: 10.1093/bioinformatics/btt113 Open Access [2] Kalaš, M., Ménager, H., Schwämmle, V., Ison, J. and EDAM Contributors (2017). EDAM – the ontology of bioinformatics operations, types of data, topics, and data formats (2017 update) [version 1; not peer reviewed]. F1000Research, 6(ISCB Comm J):1181 (Poster) DOI: 10.7490/f1000research.1114459.1 Open Access [3] Matúš Kalaš, Laure Plantard, Martin Jones, Nataša Sladoje, Marie-Charlotte Domart, Matthia Karreman, Arrate Muñoz-Barrutia, Raf Van de Plas, Ivana Vrhovac Madunić, Dean Karaica, Laura Nicolás Sáenz, Estibaliz Gómez de Marisca, Daniel Sage, Robert Haase Joakim Lindblad, and all contributors to previous versions (2020). edamontology/edam-bioimaging: alpha06 (Version alpha06). Zenodo. DOI: 10.5281/zenodo.3695725 Open Acces