Proposal for minimum information guidelines to report and reproduce results of particle tracking and motion analysis [preprint]

The proposed Minimum Information About Particle Tracking Experiments (MIAPTE) reporting guidelines described here aim to deliver a set of rules representing the minimal information required to report and support interpretation and assessment of data arising from intracellular multiple particle tracking (MPT) experiments. Examples of such experiments are those tracking viral particles as they move from the site of entry to the site of replication within an infected cell, or those following vesicular dynamics during secretion, endocytosis, or exocytosis. By promoting development of community standards, we hope that MIAPTE will contribute to making MPT data FAIR (Findable Accessible Interoperable and Reusable). Ultimately, the goal of MIAPTE is to promote and maximize data access, discovery, preservation, re-use, and repurposing through efficient annotation, and ultimately to enable reproducibility of particle tracking experiments. This document introduces MIAPTE v0.2, which updates the version that was posted to Fairsharing.org in October 2016. MIAPTE v0.2 is presented with the specific intent of soliciting comments from the particle tracking community with the purpose of extending and improving the model. The MIAPTE guidelines are intended for different categories of users: 1) Scientists with the desire to make new results available in a way that can be interpreted unequivocally by both humans and machines. For this class of users, MIAPTE provides data descriptors to define data entry terms and the analysis workflow in a unified manner. 2) Scientists wishing to evaluate, replicate and re-analyze results published by others. For this class of users MIAPTE provides descriptors that define the analysis procedures in a manner that facilitates its reproduction. 3) Developers who want to take advantage of the schema of MIAPTE to produce MIAPTE compatible tools. MIAPTE consists of a list of controlled vocabulary (CV) terms that describe elements and properties for the minimal description of particle tracking experiments, with a focus on viral and vesicular traffic within cells. As part of this submission we provide entity relationship (ER) diagrams that show the relationship between terms. Finally, we also provide documents containing the MIAPTE-compliant XML schema describing the data model used by Open Microscopy Environment inteGrated Analysis (OMEGA), our novel particle tracking data analysis and management tool, which is reported in a separate manuscript. MIAPTE is structured in two sub-sections: 1) Section 1 contains elements, attributes and data structures describing the results of particle tracking, namely: particles, links, trajectories and trajectory segments. 2) Section 2 contains elements that provide details about the algorithmic procedure utilized to produce and analyze trajectories as well as the results of trajectory analysis. In addition MIAPTE includes those OME-XML elements that are required to capture the acquisition parameters and the structure of images to be subjected to particle tracking

Micro-Meta App: an interactive tool for collecting microscopy metadata based on community specifications

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

OMEGA: a software tool for the management, analysis, and dissemination of intracellular trafficking data that incorporates motion type classification and quality control [preprint]

MOTIVATION: Particle tracking coupled with time-lapse microscopy is critical for understanding the dynamics of intracellular processes of clinical importance. Spurred on by advances in the spatiotemporal resolution of microscopy and automated computational methods, this field is increasingly amenable to multi-dimensional high-throughput data collection schemes (Snijder et al, 2012). Typically, complex particle tracking datasets generated by individual laboratories are produced with incompatible methodologies that preclude comparison to each other. There is therefore an unmet need for data management systems that facilitate data standardization, meta-analysis, and structured data dissemination. The integration of analysis, visualization, and quality control capabilities into such systems would eliminate the need for manual transfer of data to diverse downstream analysis tools. At the same time, it would lay the foundation for shared trajectory data, particle tracking, and motion analysis standards. RESULTS: Here, we present Open Microscopy Environment inteGrated Analysis (OMEGA), a cross-platform data management, analysis, and visualization system, for particle tracking data, with particular emphasis on results from viral and vesicular trafficking experiments. OMEGA provides easy to use graphical interfaces to implement integrated particle tracking and motion analysis workflows while keeping track of error propagation and data provenance. Specifically, OMEGA: 1) imports image data and metadata from data management tools such as Open Microscopy Environment Remote Objects (OMERO; Allan et al., 2012); 2) tracks intracellular particles moving across time series of image planes; 3) facilitates parameter optimization and trajectory results inspection and validation; 4) performs downstream trajectory analysis and motion type classification; 5) estimates the uncertainty associated with motion analysis; and, 6) facilitates storage and dissemination of analysis results, and analysis definition metadata, on the basis of our newly proposed Minimum Information About Particle Tracking Experiments (MIAPTE; Rigano & Strambio-De-Castillia, 2016; 2017) guidelines in combination with the OME-XML data model (Goldberg et al, 2005)

Transgenic chloroplasts are efficient sites for high-yield production of the vaccinia virus envelope protein A27L in plant cells.

Orthopoxviruses (OPVs) have recently received increasing attention because of their potential use in bioterrorism and the occurrence of zoonotic OPV outbreaks, highlighting the need for the development of safe and cost-effective vaccines against smallpox and related viruses. In this respect, the production of subunit protein-based vaccines in transgenic plants is an attractive approach. For this purpose, the A27L immunogenic protein of vaccinia virus was expressed in tobacco using stable transformation of the nuclear or plastid genome. The vaccinia virus protein was expressed in the stroma of transplastomic plants in soluble form and accumulated to about 18% of total soluble protein (equivalent to approximately 1.7 mg/g fresh weight). This level of A27L accumulation was 500-fold higher than that in nuclear transformed plants, and did not decline during leaf development. Transplastomic plants showed a partial reduction in growth and were chlorotic, but reached maturity and set fertile seeds. Analysis by immunofluorescence microscopy indicated altered chlorophyll distribution. Chloroplast-synthesized A27L formed oligomers, suggesting correct folding and quaternary structure, and was recognized by serum from a patient recently infected by a zoonotic OPV. Taken together, these results demonstrate that chloroplasts are an attractive production vehicle for the expression of OPV subunit vaccines

OmegaProject/Omega: Omega public beta release 0.47

This public beta release of OMEGA is described in details in the following preprint manuscript: OMEGA: a software tool for the management, analysis, and dissemination of intracellular trafficking data that incorporates motion type classification and quality control Alessandro Rigano, Vanni Galli, Jasmine M. Clark, Lara E. Pereira, Loris Grossi, Jeremy Luban, Raffaello Giulietti, Tiziano Leidi, Eric Hunter, Mario Valle, Ivo F. Sbalzarini, Caterina Strambio-De-Castillia bioRxiv 251850; doi: https://doi.org/10.1101/251850, which can be found at: https://www.biorxiv.org/content/early/2018/02/27/251850

Design of a Large Deployable Reflector Opening System

Large Deployable Reflectors (LDR) are receiving considerable attention from aerospace government companies and researchers. In this paper, the design of the opening system of a LDR is presented. Starting from an elementary cell, a first ideal kinematic model is discussed. Then, a more complex “design model” including feasible design solutions for joints and links is developed. The final design avoids collisions between links while maintaining the original kinematic features

An algorithm-centric Monte Carlo method to empirically quantify motion type estimation uncertainty in single-particle tracking [preprint]

Quantitative analysis of microscopy images is ideally suited for understanding the functional biological correlates of individual molecular species identified by one of the several available “omics” techniques. Due to advances in fluorescent labeling, microscopy engineering and image processing, it is now possible to routinely observe and quantitatively analyze at high temporal and spatial resolution the real-time behavior of thousands of individual cellular structures as they perform their functional task inside living systems. Despite the central role of microscopic imaging in modern biology, unbiased inference, valid interpretation, scientific reproducibility and results dissemination are hampered by the still prevalent need for subjective interpretation of image data and by the limited attention given to the quantitative assessment and reporting of the error associated with each measurement or calculation, and on its effect on downstream analysis steps (i.e., error propagation). One of the mainstays of bioimage analysis is represented by single-particle tracking (SPT)1–5, which coupled with the mathematical analysis of trajectories and with the interpretative modelling of motion modalities, is of key importance for the quantitative understanding of the heterogeneous intracellular dynamic behavior of fluorescently-labeled individual cellular structures, vesicles, virions and single-molecules. Despite substantial advances, the evaluation of analytical error propagation through SPT and motion analysis pipelines is absent from most available tools 6. This severely hinders the critical evaluation, comparison, reproducibility and integration of results emerging from different laboratories, at different times, under different experimental conditions and using different model systems. Here we describe a novel, algorithmic-centric, Monte Carlo method to assess the effect of experimental parameters such as signal to noise ratio (SNR), particle detection error, trajectory length, and the diffusivity characteristics of the moving particle on the uncertainty associated with motion type classification The method is easily extensible to a wide variety of SPT algorithms, is made widely available via its implementation in our Open Microscopy Environment inteGrated Analysis (OMEGA) software tool for the management and analysis of tracking data 7, and forms an integral part of our Minimum Information About Particle Tracking Experiments (MIAPTE) data model 8

Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model [preprint]

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 Nucleome Initiative (4DN) (1, 2) Imaging Standards Working Group (IWG), working in conjunction with the BioImaging North America (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 European Light Microscopy Initiative (ELMI), Global BioImaging (GBI), and European Molecular Biology Laboratory (EMBL) - European Bioinformatics Institute (EBI). Consequently, close ties were established between our endeavour and the undertakings of the recently established QUAlity Assessment and REProducibility for Instruments and Images in Light Microscopy global community initiative (9). As a result this flexible 4DN-BINA-OME (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

Micro-Meta App - React implementation

Micro-Meta App is an intuitive Graphical User Interface (GUI)-based open-source software that helps scientists to interactively build graphical representations of microscope hardware by dragging-and-dropping individual components onto the workspace and entering the relevant attribute values based on the 4D Nucleome (4DN) - BioImaging North America (BINA) Microscopy Metadata guidelines that scale experimental complexity. From this, Micro-Meta App automatically generates structured Microscope files that can be saved locally, consumed by existing data portals, shared with other scientists, and used repeatedly whenever the same microscope is used to produce image data. Thus, when the image acquisition settings utilized to produce a given image dataset need to be recorded, the user selects the desired image data alongside the relevant Microscope file. Then, Micro-Meta App imports the relevant metadata from the header of image data files to be annotated and interactively guides the user through the collection of all missing attributes. Finally, the App generates a Settings-file, which coupled with the Microscope-file contains comprehensive descriptions of the conditions utilized to produce individual microscopy datasets.If you use this software please cite both the software using the metadata indicated below, and the papers as indicated in the scope of each referenc

Gestational Diabetes—Placental Expression of Human Equilibrative Nucleoside Transporter 1 (hENT1): Is Delayed Villous Maturation an Adaptive Pattern?

Gestational diabetes mellitus (GDM) is a metabolic disease that can affect placental villous maturation and villous vascularity. The main effects of GDM on placental growth are a delay of villous maturation (DVM) and decreased formation of vasculo-syncytial membranes (VSM). Human equilibrative nucleoside transporter-1 (hENT1) is an adenosine transporter expressed in the human umbilical vein endothelial cells (HUVEC) and human placental microvascular endothelium cells (hPMEC). Its role is crucial in maintaining physiological fetal adenosine levels during pregnancy, and its reduction has been described in GDM. Twenty-four placentas from pregnancies with a confirmed diagnosis of GDMd and twenty-four matched non-GDM placentas (controls) were retrospectively analyzed to investigate the immunohistochemical expression of hENT1 in HUVEC and hPMEC. The study included the quantitative evaluation of VSM/mm2 in placental tissue and the immunohistochemical quantitative evaluation of Ki-67, PHH3, and p57 in villous trophoblast. hENT1 expression was higher in all the vascular districts of the control cases compared to the GDMd placentas (p 2 were lower in the GDMd cases, while the Ki-67, PHH3, and p57 were higher when compared to the control cases. To our knowledge, this is the first report of hENT1 expression in the human placentas of GDM patients. The absence/low expression of hENT1 in all the GDMd patients may indicate a potential role in microvascular adaptative mechanisms. The trophoblasts’ proliferative/antiapoptotic pattern (high Ki-67, high PHH3, and high p57 count) may explain the statistically significant lower number of VSM/mm2 found in the GDMd cases