Cellular & Molecular Imaging

The European Reference Genome Atlas (ERGA) initiative is a pan-European scientific response to current threats to biodiversity. Reference genomes provide the most complete insight into the genetic basis that forms each species and represent a powerful resource in understanding how biodiversity functions. This is a collection of the samples included in the study, provided by COPO at Earlham Institute.

Our calendar goes into a second round! After having a first edition of the NFDI4BIOIMAGE calendar in 2024, we were eager to assemble an improved version for 2025. This time, we invited also other consortia of the National Research Data Infrastructure (NFDI) to contribute with the aim to extend our calendar to a consortium spanning edition. In this year’s calendar we present very different types of images, taken by mobile phones, cameras, drones, and microscopes, representing the work of our colleagues from the various consortia of NFDI. As you may know, biological images often include additional information in the form of technical metadata, detailing the conditions under which the image was captured. Ideally, this technical data is paired with biological metadata, which explains the specimen depicted and how it was prepared. This year, we also requested that authors submit their images with complete accompanying metadata – a "full package". In bioimaging, the use of metadata standards, specifically the Recommended Metadata for Biological Images (REMBI) guideline (https://doi.org/10.1038/s41592-021-01166-8), has become increasingly common. Many of the submissions for this calendar adhere to REMBI guidelines with comprehensive metadata annotations alongside the bioimage data, as you can observe on the right accompanying our cover image. However, for images captured with other tools, such as mobile phones or drones – images not typically classified as biological – the required metadata differs to accurately convey what is shown and why the image was created. Through this calendar, we step outside the bioimaging sphere to explore how metadata for other types of images might be structured. We hope you will find it as exciting as we do to see all the different contributions and the plethora of information that will teach you more about the respective images. NFDI4BIOMAGE – who we are and what we are aiming for The NFDI4BIOIMAGE consortium started its work in March 2023 as one of the third round applicants within the NFDI, funded by the Federal Ministry for Education and Research (BMBF) and the Länder. Our consortium is working on solutions for bioimage data management along the bioimage life cycle. Bioimaging is an indispensable tool within life and medical sciences. But bioimaging data is also a very divers type of data that is present in numerous proprietary file types, is usually of large size and covers many different imaging modalities. Due to this heterogeneity, storage and interaction with bioimaging data is not trivial and is handled very differently within the research community. Our aim is to find solutions for appropriate bioimage storage, data handling, data analysis, data publication, and to provide overarching standards and support for bioimage data management for the scientific community. Our final goal is to enable researchers to make their bioimaging data Findable, Accessible, Interoperable, and Reusable (FAIR). If you need help or advise on how to handle your bioimaging data, NFDI4BIOIMAGE Data Stewards are here to provide support. Beginning of 2024 we have set up a Help Desk to get in contact with our Data Steward team. You can use the help request form (https://nfdi4bioimage.de/help-desk/) or write an e-mail to helpdesk@nfdi4bioimage.de. For further information you can also get in contact with our project office via e-mail (office@nfdi4bioimage.de) or visit our webpage https://nfdi4bioimage.de.

De-identified H&E whole-slide images (WSIs) of human prostate needle biopsies collected in Erbil, Iraq (mid-2013 to mid-2024). The cohort comprises 1,017 WSIs from 339 glass slides of185 patients (154 with two slides; 31 with one), each glass slide rescanned on three brightfield scanners (Grundium/SVS, Hamamatsu/NDPI, Leica/SVS) to enable cross-scanner benchmarking and robustness studies. Slides are fully anonymized and linked across rescans by a stable slide_id; no re-identification key exists. Slide-level Gleason and ISUP grades from three independent pathologists are provided: rater-1 graded all 339 slides, rater-2 graded 337, and rater-3 graded 59, supporting validation against human reference and weakly supervised training. This dataset, among the first high-quality WSI resources from an under-digitized setting like Iraq, aims to advance the development and evaluation of generalizable computational pathology models.

Chlamydomonas smithii exhibits remarkable morphological plasticity (pleomorphism) in response to environmental conditions. This dataset captures the diverse cell shapes and subcellular structures observed when C. smithii cultures are maintained under nutrient-depleted conditions over extended periods (40-43 days). We examined cells grown on multiple media types (Marine Broth, Erdschreiber's Medium, Kuhl's Medium, TAP, and water) supplemented with 1.5% agar, resuspended in liquid growth media, and applied various fluorescent stains (FM4-64 membrane stain, MitoTracker Orange, PKmito Orange) to visualize subcellular compartments. The dataset includes brightfield, RGB, and fluorescence z-stack images capturing the wide range of pleomorphic forms that emerge during prolonged culture, including multi-lobed cells, enlarged vacuoles, and altered chloroplast morphologies.

While commensal bacteria generally respect natural barriers of the human body, pathogens are able to breach epithelia, invade deeper tissue layers and cause life-threatening infections. Pseudomonas aeruginosa, an opportunistic human pathogen, is a leading cause of severe hospital-acquired pneumonia, with mortality rates up to 50% in mechanically ventilated patients1–3. Effective colonization and breaching of lung mucosa are hallmarks of P. aeruginosa pathogenesis4. Although virulence factors and behavioral strategies of P. aeruginosa have been described5,6, it has remained unclear how this pathogen disseminates on functional mucosal surfaces, how it avoids mucociliary clearance and how it invades the tissue barrier. Using fully differentiated human lung epithelia, we demonstrate that P. aeruginosa efficiently spreads on the apical tissue surface before it breaches epithelia by preferentially invading mucus secreting goblet cells. Internalization leads to host cell death and expulsion and the formation of ruptures of the epithelial barrier. Rupture sites are rapidly colonized by extracellular bacteria through active chemotaxis, leading to increasing tissue damage and successful pathogen translocation to the unprotected basolateral side of the epithelium. We show that cell invasion is promoted by two Type-6 toxin secretion systems (T6SS), while Type-3 (T3SS) mediates cell death of infected goblet cells. T3SS mutants invade goblet cells normally, but internalized bacteria fail to trigger goblet cell expulsion and instead show unrestrained intracellular replication. While the effective shedding of infected host cells reveals potent tissue protection mechanisms, the discovery of an intracellular lifestyle of P. aeruginosa in pseudostratified human lung epithelia provides new entry points into investigating the intersection of antibiotic and immune mechanisms during lung infections. By demonstrating that P. aeruginosa uses a combination of specific virulence factors and collective behavior to invade goblet cells and breach the lung tissue barrier from within, these studies reveal novel mechanisms underlying lung infection dynamics under physiological conditions.

Supplementary electron microscopy files for the manuscript

Corresponding scanned images from Figure 5D of the Smith et al. EMBO J submission "Differentiation signals induce APOBEC3A expression via GRHL3 in squamous epithelia and squamous cell carcinoma", August 2024.

In 2015, we launched the mesoSPIM initiative (www.mesospim.org), an open-source project for making light-sheet microscopy of large cleared tissues more accessible. Meanwhile, the demand for imaging larger samples at higher speed and resolution has increased, requiring major improvements in the capabilities of light-sheet microscopy. Here, we introduce the next-generation mesoSPIM ("Benchtop") with significantly increased field of view, improved resolution, higher throughput, more affordable cost and simpler assembly compared to the original version. We developed a new method for testing objectives, enabling us to select detection objectives optimal for light-sheet imaging with large-sensor sCMOS cameras. The new mesoSPIM achieves high spatial resolution (1.5 µm laterally, 3.3 µm axially) across the entire field of view, a magnification up to 20x, and supports sample sizes ranging from sub-mm up to several centimetres, while being compatible with multiple clearing techniques. The new microscope serves a broad range of applications in neuroscience, developmental biology, and even physics.

Representative Raw data releated to the paper "Virtual reality empowered deep learning analysis of brain cells" by Kaltenecker, Al-Maskari and Negwer et al. Additional scans are available upon reasonable request.

Here, we reconstituted bronchial epithelia from adult and child donors and show that SARS-CoV-2 infections spread fast, resulting in the formation and synchronized release of large clusters of infected cells and syncytia into the apical lumen, contributing to virus dissemination. Some epithelia, for the most part from children, revealed an intrinsic resistance to infection and virus spread. This infection control correlates with faster type III interferon secretion and can be transferred to permissive epithelia through exogenous interferon application. Child epithelia also showed a muted inflammatory response compared with adult, suggesting a specific and age-adapted epithelial response to SARS-CoV-2 infection that may explain why children are less susceptible to severe COVID-19.