EU-LIFE charter of independent life science research institutes.

The diverse range of organizations contributing to the global research ecosystem is believed to enhance the overall quality and resilience of its output. Mid-sized autonomous research institutes, distinct from universities, play a crucial role in this landscape. They often lead the way in new research fields and experimental methods, including those in social and organizational domains, which are vital for driving innovation. The EU-LIFE alliance was established with the goal of fostering excellence by developing and disseminating best practices among European biomedical research institutes. As directors of the 15 EU-LIFE institutes, we have spent a decade comparing and refining our processes. Now, we are eager to share the insights we've gained. To this end, we have crafted this Charter, outlining 10 principles we deem essential for research institutes to flourish and achieve ground-breaking discoveries. These principles, detailed in the Charter, encompass excellence, independence, training, internationality and inclusivity, mission focus, technological advancement, administrative innovation, cooperation, societal impact, and public engagement. Our aim is to inspire the establishment of new institutes that adhere to these principles and to raise awareness about their significance. We are convinced that they should be viewed a crucial component of any national and international innovation strategies.

EmbedSeg: Embedding-based Instance Segmentation for Biomedical Microscopy Data.

Automatic detection and segmentation of biological objects in 2D and 3D image data is central for countless biomedical research questions to be answered. While many existing computational methods are used to reduce manual labeling time, there is still a huge demand for further quality improvements of automated solutions. In the natural image domain, spatial embedding-based instance segmentation methods are known to yield high-quality results, but their utility to biomedical data is largely unexplored. Here we introduce EmbedSeg, an embedding-based instance segmentation method designed to segment instances of desired objects visible in 2D or 3D biomedical image data. We apply our method to four 2D and seven 3D benchmark datasets, showing that we either match or outperform existing state-of-the-art methods. While the 2D datasets and three of the 3D datasets are well known, we have created the required training data for four new 3D datasets, which we make publicly available online. Next to performance, also usability is important for a method to be useful. Hence, EmbedSeg is fully open source (https://github.com/juglab/EmbedSeg), offering (i) tutorial notebooks to train EmbedSeg models and use them to segment object instances in new data, and (ii) a napari plugin that can also be used for training and segmentation without requiring any programming experience. We believe that this renders EmbedSeg accessible to virtually everyone who requires high-quality instance segmentations in 2D or 3D biomedical image data.

Time to Upgrade: A New OpenSPIM Guide to Build and Operate Advanced OpenSPIM Configurations.

OpenSPIM is an Open Access platform for Selective Plane Illumination Microscopy (SPIM) and allows hundreds of laboratories around the world to generate and process light-sheet data in a cost-effective way due to open-source hardware and software. While setting up a basic OpenSPIM configuration can be achieved expeditiously, correctly assembling and operating more complex OpenSPIM configurations can be challenging for routine standard OpenSPIM users. Detailed instructions on how to equip an OpenSPIM with two illumination sides and two detection axes (X-OpenSPIM) are provided, and a solution is also provided on how the temperature can be controlled in the sample chamber. Additionally, it is demonstrated how to operate it by implementing an ArduinoUNO microcontroller and introducing µOpenSPIM, a new software plugin for OpenSPIM, to facilitate image acquisition. The new software works on any OpenSPIM configuration comes with drift correction functionality, on-the-fly image processing, and gives users more options in the way time-lapse movies are initially set up and saved. Step-by-step guides are also provided within the Supporting Information and on the website on how to align the lasers, configure the hardware, and acquire images using µOpenSPIM. With this, current OpenSPIM users are empowered in various ways, and newcomers striving to use more advanced OpenSPIM systems are helped.

The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis.

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.

Regionalized tissue fluidization is required for epithelial gap closure during insect gastrulation.

Many animal embryos pull and close an epithelial sheet around the ellipsoidal egg surface during a gastrulation process known as epiboly. The ovoidal geometry dictates that the epithelial sheet first expands and subsequently compacts. Moreover, the spreading epithelium is mechanically stressed and this stress needs to be released. Here we show that during extraembryonic tissue (serosa) epiboly in the insect Tribolium castaneum, the non-proliferative serosa becomes regionalized into a solid-like dorsal region with larger non-rearranging cells, and a more fluid-like ventral region surrounding the leading edge with smaller cells undergoing intercalations. Our results suggest that a heterogeneous actomyosin cable contributes to the fluidization of the leading edge by driving sequential eviction and intercalation of individual cells away from the serosa margin. Since this developmental solution utilized during epiboly resembles the mechanism of wound healing, we propose actomyosin cable-driven local tissue fluidization as a conserved morphogenetic module for closure of epithelial gaps.

Publisher Correction: Tissue clearing and its applications in neuroscience.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Ordered patterning of the sensory system is susceptible to stochastic features of gene expression.

Sensory neuron numbers and positions are precisely organized to accurately map environmental signals in the brain. This precision emerges from biochemical processes within and between cells that are inherently stochastic. We investigated impact of stochastic gene expression on pattern formation, focusing on senseless (sens), a key determinant of sensory fate in Drosophila. Perturbing microRNA regulation or genomic location of sens produced distinct noise signatures. Noise was greatly enhanced when both sens alleles were present in homologous loci such that each allele was regulated in trans by the other allele. This led to disordered patterning. In contrast, loss of microRNA repression of sens increased protein abundance but not sensory pattern disorder. This suggests that gene expression stochasticity is a critical feature that must be constrained during development to allow rapid yet accurate cell fate resolution.

Imaging plant germline differentiation within Arabidopsis flowers by light sheet microscopy.

In higher plants, germline differentiation occurs during a relatively short period within developing flowers. Understanding of the mechanisms that govern germline differentiation lags behind other plant developmental processes. This is largely because the germline is restricted to relatively few cells buried deep within floral tissues, which makes them difficult to study. To overcome this limitation, we have developed a methodology for live imaging of the germ cell lineage within floral organs of Arabidopsis using light sheet fluorescence microscopy. We have established reporter lines, cultivation conditions, and imaging protocols for high-resolution microscopy of developing flowers continuously for up to several days. We used multiview imagining to reconstruct a three-dimensional model of a flower at subcellular resolution. We demonstrate the power of this approach by capturing male and female meiosis, asymmetric pollen division, movement of meiotic chromosomes, and unusual restitution mitosis in tapetum cells. This method will enable new avenues of research into plant sexual reproduction.

Tissue clearing and its applications in neuroscience.

State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.

Yorkie controls tube length and apical barrier integrity during airway development.

Epithelial organ size and shape depend on cell shape changes, cell-matrix communication, and apical membrane growth. The Drosophila melanogaster embryonic tracheal network is an excellent model to study these processes. Here, we show that the transcriptional coactivator of the Hippo pathway, Yorkie (YAP/TAZ in vertebrates), plays distinct roles in the developing Drosophila airways. Yorkie exerts a cytoplasmic function by binding Drosophila Twinstar, the orthologue of the vertebrate actin-severing protein Cofilin, to regulate F-actin levels and apical cell membrane size, which are required for proper tracheal tube elongation. Second, Yorkie controls water tightness of tracheal tubes by transcriptional regulation of the δ-aminolevulinate synthase gene (Alas). We conclude that Yorkie has a dual role in tracheal development to ensure proper tracheal growth and functionality.

Analysis of Actomyosin Dynamics at Local Cellular and Tissue Scales Using Time-lapse Movies of Cultured Drosophila Egg Chambers.

Drosophila immature eggs are called egg chambers, and their structure resembles primitive organs that undergo morphological changes from a round to an ellipsoid shape during development. This developmental process is called oogenesis and is crucial to generating functional mature eggs to secure the next fly generation. For these reasons, egg chambers have served as an ideal and relevant model to understand animal organ development. Several in vitro culturing protocols have been developed, but there are several disadvantages to these protocols. One involves the application of various covers that exert an artificial pressure on the imaged egg chambers in order to immobilize them and to increase the imaged acquisition plane of the circumferential surface of the analyzed egg chambers. Such an approach may negatively influence the behavior of the thin actomyosin machinery that generates the power to rotate egg chambers around their longer axis. Thus, to overcome this limitation, we culture Drosophila egg chambers freely in the media in order to reliably analyze actomyosin machinery along the circumference of egg chambers. In the first part of the protocol, we provide a manual detailing how to analyze the actomyosin machinery in a limited acquisition plane at the local cellular scale (up to 15 cells). In the second part of the protocol, we provide users with a new Fiji-based plugin that allows the simple extraction of a defined thin layer of the egg chambers' circumferential surface. The following protocol then describes how to analyze actomyosin signals at the tissue scale (>50 cells). Finally, we pinpoint the limitations of these approaches at both the local cellular and tissue scales and discuss its potential future development and possible applications.

Gene Regulation: Analog to Digital Conversion of Transcription Factor Gradients.

Transcription factor gradients trigger differential transcriptional responses based on concentration. But how, in some cases, do target genes maintain uniform transcription across portions of the gradient? Lessons from Drosophila demonstrate that organization of transcription into 'hubs' can lead to local increases in transcription factor concentration.

Publisher Correction: Attachment of the blastoderm to the vitelline envelope affects gastrulation of insects.

In this Letter, the sentence starting: 'For instance, Tribolium and Drosophila inflated are direct targets of the mesoderm…' has been corrected online; see accompanying Amendment.

Attachment of the blastoderm to the vitelline envelope affects gastrulation of insects.

During gastrulation, physical forces reshape the simple embryonic tissue to form the complex body plans of multicellular organisms1. These forces often cause large-scale asymmetric movements of the embryonic tissue2,3. In many embryos, the gastrulating tissue is surrounded by a rigid protective shell4. Although it is well-recognized that gastrulation movements depend on forces that are generated by tissue-intrinsic contractility5,6, it is not known whether interactions between the tissue and the protective shell provide additional forces that affect gastrulation. Here we show that a particular part of the blastoderm tissue of the red flour beetle (Tribolium castaneum) tightly adheres in a temporally coordinated manner to the vitelline envelope that surrounds the embryo. This attachment generates an additional force that counteracts tissue-intrinsic contractile forces to create asymmetric tissue movements. This localized attachment depends on an αPS2 integrin (inflated), and the knockdown of this integrin leads to a gastrulation phenotype that is consistent with complete loss of attachment. Furthermore, analysis of another integrin (the αPS3 integrin, scab) in the fruit fly (Drosophila melanogaster) suggests that gastrulation in this organism also relies on adhesion between the blastoderm and the vitelline envelope. Our findings reveal a conserved mechanism through which the spatiotemporal pattern of tissue adhesion to the vitelline envelope provides controllable, counteracting forces that shape gastrulation movements in insects.

SPIM workflow manager for HPC.

SUMMARY: Here we introduce a Fiji plugin utilizing the HPC-as-a-Service concept, significantly mitigating the challenges life scientists face when delegating complex data-intensive processing workflows to HPC clusters. We demonstrate on a common Selective Plane Illumination Microscopy image processing task that execution of a Fiji workflow on a remote supercomputer leads to improved turnaround time despite the data transfer overhead. The plugin allows the end users to conveniently transfer image data to remote HPC resources, manage pipeline jobs and visualize processed results directly from the Fiji graphical user interface. AVAILABILITY AND IMPLEMENTATION: The code is distributed free and open source under the MIT license. Source code: https://github.com/fiji-hpc/hpc-workflow-manager/, documentation: https://imagej.net/SPIM_Workflow_Manager_For_HPC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.