For quality, interpretation, reproducibility and sharing value, microscopy images should be accompanied by detailed descriptions of the conditions that were used to produce them. Micro-Meta App is an intuitive, highly interoperable, open-source software tool that was developed in the context of the 4D Nucleome (4DN) consortium and is designed to facilitate the extraction and collection of relevant microscopy metadata as specified by the recent 4DN-BINA-OME tiered-system of Microscopy Metadata specifications. In addition to substantially lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training purposes.

A common viral replication strategy is characterized by the assembly of intracellular compartments that concentrate factors needed for viral replication and simultaneously conceal the viral genome from host-defense mechanisms. Recently, various membrane-less virus-induced compartments and cellular organelles have been shown to represent biomolecular condensates (BMCs) that assemble through liquid-liquid phase separation (LLPS). In the present work, we analyze biophysical properties of intranuclear replication compartments (RCs) induced during human adenovirus (HAdV) infection. The viral ssDNA-binding protein (DBP) is a major component of RCs that contains intrinsically disordered and low complexity proline-rich regions, features shared with proteins that drive phase transitions. Using fluorescence recovery after photobleaching (FRAP) and time-lapse studies in living HAdV-infected cells, we show that DBP-positive RCs display properties of liquid BMCs, which can fuse and divide, and eventually form an intranuclear mesh with less fluid-like features. Moreover, the transient expression of DBP recapitulates the assembly and liquid-like properties of RCs in HAdV-infected cells. These results are of relevance as they indicate that DBP may be a scaffold protein for the assembly of HAdV-RCs and should contribute to future studies on the role of BMCs in virus-host cell interactions.

Hypophysiotropic thyrotropin-releasing hormone (TRH) neurons function as metabolic sensors that regulate the thyroid axis and energy homeostasis. Less is known about the role of other hypothalamic TRH neurons. As central administration of TRH decreases food intake and increases histamine in the tuberomammillary nuclei (TMN), and TMN histamine neurons are densely innervated by TRH fibers from an unknown origin, we mapped the location of TRH neurons that project to the TMN. The retrograde tracer, cholera toxin B subunit (CTB), was injected into the TMN E1–E2, E4–E5 subdivisions of adult Sprague–Dawley male rats. TMN projecting neurons were observed in the septum, preoptic area, bed nucleus of the stria terminalis (BNST), perifornical area, anterior paraventricular nucleus, peduncular and tuberal lateral hypothalamus (TuLH), suprachiasmatic nucleus and medial amygdala. However, CTB/pro-TRH178-199 double-labeled cells were only found in the TuLH. The specificity of the retrograde tract-tracing result was confirmed by administering the anterograde tracer, Phaseolus vulgaris leuco-agglutinin (PHAL) into the TuLH. Double-labeled PHAL-pro-TRH boutons were identified in all subdivisions of the TMN. TMN neurons double-labeled for histidine decarboxylase (Hdc)/PHAL, Hdc/Trh receptor (Trhr), and Hdc/Trh. Further confirmation of a TuLH-TRH neuronal projection to the TMN was established in a transgenic mouse that expresses Cre recombinase in TRH-producing cells following microinjection of a Cre recombinase-dependent AAV that expresses mCherry into the TuLH. We conclude that, in rodents, the TRH innervation of TMN originates in part from TRH neurons in the TuLH, and that this TRH population may contribute to regulate energy homeostasis through histamine Trhr-positive neurons of the TMN.

1 - Digital light microscopy provides powerful tools for quantitatively probing the real-time dynamics of subcellular structures. While the power of modern microscopy techniques is undeniable, rigorous record-keeping and quality control are required to ensure that imaging data may be properly interpreted ( quality ), reproduced ( reproducibility ), and used to extract reliable information and scientific knowledge which can be shared for further analysis ( value ). Keeping notes on microscopy experiments and quality control procedures ought to be straightforward, as the microscope is a machine whose components are defined and the performance measurable. Nevertheless, to this date, no universally adopted community-driven specifications exist that delineate the required information about the microscope hardware and acquisition settings (i.e., microscopy “data provenance” metadata) and the minimally accepted calibration metrics (i.e., microscopy quality control metadata) that should be automatically recorded by both commercial microscope manufacturers and customized microscope developers. In the absence of agreed guidelines, it is inherently difficult for scientists to create comprehensive records of imaging experiments and ensure the quality of resulting image data or for manufacturers to incorporate standardized reporting and performance metrics. To add to the confusion, microscopy experiments vary greatly in aim and complexity, ranging from purely descriptive work to complex, quantitative and even sub-resolution studies that require more detailed reporting and quality control measures. To solve this problem, the 4D N ucleome Initiative (4DN) ( 1, 2 ) Imaging Standards Working Group (IWG), working in conjunction with the B io I maging N orth A merica (BINA) Quality Control and Data Management Working Group (QC-DM-WG) ( 3 ), here propose light Microscopy Metadata specifications that scale with experimental intent and with the complexity of the instrumentation and analytical requirements. They consist of a revision of the Core of the Open Microscopy Environment (OME) Data Model, which forms the basis for the widely adopted Bio-Formats library ( 4 – 6 ), accompanied by a suite of three extensions, each with three tiers, allowing the classification of imaging experiments into levels of increasing imaging and analytical complexity ( 7, 8 ). Hence these specifications not only provide an OME-based comprehensive set of metadata elements that should be recorded, but they also specify which subset of the full list should be recorded for a given experimental tier. In order to evaluate the extent of community interest, an extensive outreach effort was conducted to present the proposed metadata specifications to members of several core-facilities and international bioimaging initiatives including the E uropean L ight M icroscopy I nitiative (ELMI), G lobal B io I maging (GBI), and E uropean M olecular B iology L aboratory (EMBL) - E uropean B ioinformatics I nstitute (EBI). Consequently, close ties were established between our endeavour and the undertakings of the recently established QUA lity Assessment and REP roducibility for Instruments and Images in Li ght Mi croscopy global community initiative ( 9 ). As a result this flexible 4D N - B INA- O ME (NBO namespace) framework ( 7, 8 ) represents a turning point towards achieving community-driven Microscopy Metadata standards that will increase data fidelity, improve repeatability and reproducibility, ease future analysis and facilitate the verifiable comparison of different datasets, experimental setups, and assays, and it demonstrates the method for future extensions. Such universally accepted microscopy standards would serve a similar purpose as the Encode guidelines successfully adopted by the genomic community ( 10, 11 ). The intention of this proposal is therefore to encourage participation, critiques and contributions from the entire imaging community and all stakeholders, including research and imaging scientists, facility personnel, instrument manufacturers, software developers, standards organizations, scientific publishers, and funders.

For the information content of microscopy images to be appropriately interpreted, reproduced, and meet FAIR (Findable Accessible Interoperable and Reusable) principles, they should be accompanied by detailed descriptions of microscope hardware, image acquisition settings, image pixel and dimensional structure, and instrument performance. Nonetheless, the thorough documentation of imaging experiments is significantly impaired by the lack of community-sanctioned easy-to-use software tools to facilitate the extraction and collection of relevant microscopy metadata. Here we present Micro-Meta App , an intuitive open-source software designed to tackle these issues that was developed in the context of nascent global bioimaging community organizations, including B io I maging N orth A merica (BINA) and QUA lity Assessment and REP roducibility in Li ght Mi croscopy (QUAREP-LiMi), whose goal is to improve reproducibility, data quality and sharing value for imaging experiments. The App provides a user-friendly interface for building comprehensive descriptions of the conditions utilized to produce individual microscopy datasets as specified by the recently proposed 4DN-BINA-OME tiered-system of Microscopy Metadata model. To achieve this goal the App provides a visual guide for a microscope-user to: 1) interactively build diagrammatic representations of hardware configurations of given microscopes that can be easily reused and shared with colleagues needing to document similar instruments. 2) Automatically extracts relevant metadata from image files and facilitates the collection of missing image acquisition settings and calibration metrics associated with a given experiment. 3) Output all collected Microscopy Metadata to interoperable files that can be used for documenting imaging experiments and shared with the community. In addition to significantly lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training users that have limited knowledge of the intricacies of light microscopy experiments. To ensure wide-adoption by microscope-users with different needs Micro-Meta App closely interoperates with MethodsJ2 and OMERO.mde , two complementary tools described in parallel manuscripts.