SummaryNeural 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

Neural circuit mapping is generating datasets of 10,000s 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 1052 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.

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. In the insect olfactory system, second order projection neurons target both the mushroom body, required for learning, and the lateral horn (LH), proposed to mediate innate olfactory behavior. Mushroom body neurons form a sparse olfactory population code, which is not stereotyped across animals. In contrast, odor coding in the LH remains poorly understood. We combine genetic driver lines, anatomical and functional criteria to show that the Drosophila LH has ~1400 neurons and >165 cell types. Genetically labeled LHNs have stereotyped odor responses across animals and on average respond to three times more odors than single projection neurons. LHNs are better odor categorizers than projection neurons, likely due to stereotyped pooling of related inputs. Our results reveal some of the principles by which a higher processing area can extract innate behavioral significance from sensory stimuli.

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 <monospace>natverse</monospace>. The <monospace>natverse</monospace> allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the <monospace>natverse</monospace> enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The <monospace>natverse</monospace> 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 <monospace>natverse</monospace> 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.

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 15 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 20 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.

Herpesviruses are large and complex viruses that have a long history of coevolution with their host species. One important factor in the virus–host interaction is the alteration of intracellular morphology during viral replication with critical implications for viral assembly. However, the details of this remodeling event are not well understood, in part because insufficient tools are available to deconstruct this highly heterogeneous process. To provide an accurate and reliable method of investigating the spatiotemporal dynamics of virus-induced changes to cellular architecture, we constructed a dual-fluorescent reporter virus that enabled us to classify four distinct stages in the infection cycle of herpes simplex virus-1 at the single cell level. This timestamping method can accurately track the infection cycle across a wide range of multiplicities of infection. We used high-resolution fluorescence microscopy analysis of cellular structures in live and fixed cells in concert with our reporter virus to generate a detailed and chronological overview of the spatial and temporal reorganization during viral replication. The highly orchestrated and striking relocation of many organelles around the compartments of secondary envelopment during transition from early to late gene expression suggests that the reshaping of these compartments is essential for virus assembly. We furthermore find that accumulation of HSV-1 capsids in the cytoplasm is accompanied by fragmentation of the Golgi apparatus with potential impact on the late steps of viral assembly. We anticipate that in the future similar tools can be systematically applied for the systems-level analysis of intracellular morphology during replication of other viruses.

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 template 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.

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.