James Manton

NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases

Summary Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish. Video Abstract

Combining genome-scale Drosophila 3D neuroanatomical data by bridging template brains

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation, clustering and graph theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison of morphology and connectivity across many neurons after imaging or co-registration within a common space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.The stereotyped structure of mammalian and invertebrate brains is a crucial determinant of their circuit organization. Thus large scale efforts to map circuit organization using 3D image data are underway in a number of model systems, including flies and mice. Many of these studies use registration of sample images to a standard template brain to enable co-visualization and spatial querying. However, studies often use distinct template brains, resulting in large islands of data which cannot be directly compared. To enable this comparison, we have constructed bridging registrations between template brains accounting for the vast majority of Drosophila melanogaster 3D neuroanatomical data. Furthermore, we solve the related problem of mapping data between the left and right brain hemispheres via the construction of mirroring registrations. Finally, we extend our approach across species to demonstrate its potential use in evolutionary studies of neural circuit structure and provide bridging registrations that link a new set of template brains generated for four Drosophila species that are divergent over 40 million years of evolution. We describe our strategy, document the freely available anatomical data and open source com- puter tools that we have generated and provide numerous examples of their use. This effort has unified data from over 30,000 publicly available images, with resources including the 3D atlas embodying the new standard Drosophila anatomical nomenclature and the largest single neuron databank yet available in any species. Over 20,000 registered images have been contributed to the Virtual Fly Brain project and can be viewed online at www.virtualflybrain.org.

triSPIM: light sheet microscopy with isotropic super-resolution.

We propose a three-objective light sheet microscopy geometry which, through a combination of skewed lattice light sheet excitation through two objectives and the computational fusion of images taken from two separate lens pairings, would allow for isotropic super-resolution in mesoscopic samples. We also show that simultaneous coherent excitation through two excitation objectives could further substantially increase resolution. Simulations demonstrate that our design could achieve a resolution of 120 nm for EGFP imaging while minimizing photodamage.

Functional and Anatomical Specificity in a Higher Olfactory Centre

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. For example, second order olfactory neurons make divergent projections onto functionally distinct brain areas relevant to different behaviors. In insects, one area, the mushroom body has been intensively studied for its role in olfactory learning while the lateral horn is proposed to mediate innate olfactory behavior. Some lateral horn neurons (LHNs) show selective responses to sex pheromones but its functional principles remain poorly understood. We have carried out a comprehensive anatomical analysis of the Drosophila lateral horn and identified genetic driver lines targeting many LHNs. We find that the lateral horn contains >1300 neurons and by combining genetic, anatomical and functional criteria, we identify >150 cell types. In particular we show that genetically labeled LHNs show stereotyped odor responses from one animal to the next. Although LHN tuning can be ultra-sparse (1/40 odors tested), as a population they respond to three times more odors than their inputs; this coding change can be rationalized by our observation that LHNs are better odor categorizers. Our results reveal some of the principles by which a higher sensory processing area can extract innate behavioral significance from sensory stimuli.

Ellipsoid Localization Microscopy Infers the Size and Order of Protein Layers in Bacillus Spore Coats

Multilayered protein coats are crucial to the dormancy, robustness, and germination of bacterial spores. In Bacillus subtilis spores, the coat contains over 70 distinct proteins. Identifying which proteins reside in each layer may provide insight into their distinct functions. We present image analysis methods that determine the order and geometry of concentric protein layers by fitting a model description for a spheroidal fluorescent shell image to optical micrographs of spores incorporating fluorescent fusion proteins. The radius of a spherical protein shell can be determined with <10 nm error by fitting an equation to widefield fluorescence micrographs. Ellipsoidal shell axes can be fitted with comparable precision. The layer orders inferred for B. subtilis and B. megaterium are consistent with measurements in the literature. The aspect ratio of elongated spores and the tendency of some proteins to localize near their poles can be quantified, enabling measurement of structural anisotropy.

Development of an open technology sensor suite for assisted living: a student-led research project.

Many countries have a rapidly ageing population, placing strain on health services and creating a growing market for assistive technology for older people. We have, through a student-led, 12-week project for 10 students from a variety of science and engineering backgrounds, developed an integrated sensor system to enable older people, or those at risk, to live independently in their own homes for longer, while providing reassurance for their family and carers. We provide details on the design procedure and performance of our sensor system and the management and execution of a short-term, student-led research project. Detailed information on the design and use of our devices, including a door sensor, power monitor, fall detector, general in-house sensor unit and easy-to-use location-aware communications device, is given, with our open designs being contrasted with closed proprietary systems. A case study is presented for the use of our devices in a real-world context, along with a comparison with commercially available systems. We discuss how the system could lead to improvements in the quality of life of older users and increase the effectiveness of their associated care network. We reflect on how recent developments in open source technology and rapid prototyping increase the scope and potential for the development of powerful sensor systems and, finally, conclude with a student perspective on this team effort and highlight learning outcomes, arguing that open technologies will revolutionize the way in which technology will be deployed in academic research in the future.

Research data supporting: Proteins encoded by the gerP operon are localised to the inner coat in Bacillus cereus spores and are dependent on GerPA for assembly

Image data, image analysis software, and numerical results in support of a paper on protein location in B. cereus spores

ELM: super-resolution analysis of wide-field images of fluorescent shell structures.

It is often necessary to precisely quantify the size of specimens in biological studies. When measuring feature size in fluorescence microscopy, significant biases can arise due to blurring of its edges if the feature is smaller than the diffraction limit of resolution. This problem is avoided if an equation describing the features entire image is fitted to its image data. In this paper we present open-source software, ELM, which uses this approach to measure the size of spheroidal or cylindrical fluorescent shells with a precision of around 10 nm. This has been used to measure coat protein locations in bacterial spores and cell wall diameter in vegetative bacilli, and may also be valuable in microbiological studies of algae, fungi and viruses. ELM is available for download at https://github.com/quantitativeimaging/ELM.