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The germination of Bacillus spores is triggered by certain amino acids and sugar molecules which permeate the outermost layers of the spore to interact with receptor complexes that reside in the inner membrane. Previous studies have shown that mutations in the hexacistronic gerP locus reduce the rate of spore germination, with experimental evidence indicating that the defect stems from reduced permeability of the spore coat to germinant molecules. Here, we use the ellipsoid localization microscopy technique to reveal that all six Bacillus cereus GerP proteins share proximity with cortex-lytic enzymes within the inner coat. We also reveal that the GerPA protein alone can localize in the absence of all other GerP proteins and that it has an essential role for the localization of all other GerP proteins within the spore. Its essential role is also demonstrated to be dependent on SafA, but not CotE, for localization, which is consistent with an inner coat location. GerP-null spores are shown also to have reduced permeability to fluorescently labeled dextran molecules compared to wild-type spores. Overall, the results support the hypothesis that the GerP proteins have a structural role within the spore associated with coat permeability.IMPORTANCE The bacterial spore coat comprises a multilayered proteinaceous structure that influences the distribution, survival, and germination properties of spores in the environment. The results from the current study are significant since they increase our understanding of coat assembly and architecture while adding detail to existing models of germination. We demonstrate also that the ellipsoid localization microscopy (ELM) image analysis technique can be used as a novel tool to provide direct quantitative measurements of spore coat permeability. Progress in all of these areas should ultimately facilitate improved methods of spore control in a range of industrial, health care, and environmental sectors.

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. For example, in insects, second order olfactory projection neurons target both the mushroom body, which is required for learning, and the lateral horn (LH), which has been proposed to mediate innate olfactory behavior. Mushroom body neurons encode odors in a sparse population code, which does not appear stereotyped across animals. In contrast the functional principles of odor coding in the LH remain poorly understood. We have carried out a comprehensive anatomical analysis of the Drosophila LH, counting ~1400 neurons; combining genetic driver lines, anatomical and functional criteria, we identify 165 LHN cell types. We then show that genetically labeled LHNs have stereotyped odor responses across animals for 33 of these cell types. LHN tuning can be ultra-sparse (1/40 odors tested), but on average single LHNs respond to three times more odors than single projection neurons. This difference can be rationalized by our observation that LHNs are better odor categorizers, likely due to pooling of input projection neurons responding to different odors of the same category. Our results reveal some of the principles by which a higher sensory processing area can extract innate behavioral significance from sensory stimuli.

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 feature's 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.

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.

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, Highlights • NBLAST is a fast and sensitive algorithm to measure pairwise neuronal similarity • NBLAST can distinguish neuronal types at the finest level without training • Automated clustering of 16,129 Drosophila neurons identifies 1,052 classes • Online search tool for databases of single neurons or genetic driver lines, Thousands of single-neuron images are being generated by efforts to map circuits and define neuronal types. Costa et al. validate a new neuronal similarity algorithm, NBLAST, demonstrating that it can distinguish neuronal types and organize huge datasets.

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.

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