Cellular & Molecular Imaging

TrypTag genome-wide protein localisation project data. Widefield epifluorescence microscope images of protein subcellular localisation in the unicellular eukaryotic pathogen Trypanosoma brucei by endogenous tagging with mNeonGreen (mNG). This deposition includes the localisations, ontology and microscopy data used to build the TrypTag database. Data can also be browsed at TrypTag.org. If you use this data resource please cite Billington et al. 2023 Nature Microbiology (doi:10.1038/s41564-022-01295-6). We recommend including this citation in the results or methods if TrypTag was used as part of a discovery process. If directly using TrypTag images, please also indicate in the figure legend or similar which images are from TrypTag. If carrying out a large-scale data analysis, please also cite this BioStudies deposition. Data can be mined via the cellular localization imaging or cellular component GO term searches at the genome database TriTrypDB.org (part of VEuPathDB). If you do, please also cite the genome database. You may also find the following papers informative: Dean et al. 2016 Trends in Parasitology (doi:10.1016/j.pt.2016.10.009), which describes the original project aims and workflow. Halliday et al. 2019 Molecular and Biochemical Parasitology (doi:10.1016/j.molbiopara.2018.12.003), which describes the localisation ontology with example images and comparison to Leishmania.

Lepidoptera, i.e. butterflies and moths, are vital components of the global ecosystem. Project Psyche is a scientific research project established to sequence the genomes of all butterflies and moths of Europe; helping to conserve, protect and drive innovation.

The Darwin Tree of Life project has the goal to sequence the genomes of 70,000 species of eukaryotic organisms in Britain and Ireland. This is a collection of photographs of the samples included in the study, provided by the National History Museum (NHM).

Correlative 3D microCT-2D H&E Histology datasets associated with the publication 'Correlative three-dimensional X-ray histology (3D-XRH) as a tool for quantifying mammalian placental structure'

microCT, EM, and physiological modelling datasets of human and equid placental villi.

Correlative live cell imaging of landmark organelles — such as nuclei, nucleoli, cell membranes, nuclear envelope and lipid droplets — is critical for systems cell biology and drug discovery. However, achieving this with molecular labels is challenging. Virtual staining of multiple organelles and cell states from label-free images with deep neural networks is an emerging solution. This approach frees the light spectrum for imaging molecular sensors, photomanipulation, or other tasks. Current methods for virtual staining of landmark organelles often fail in the presence of nuisance variations in imaging, culture conditions, and cell types. We report training protocols and a flexible convolutional architecture, UNeXt2, that enable robust virtual staining of nuclei and membranes across diverse imaging parameters, cell states, and types. The strategies include self-supervised and supervised pre-training, improving robustness for multiple cell types — including human cell lines, zebrafish neuromasts, stem cells (iPSCs), and iPSC-derived neurons (iNeurons) — under a range of imaging conditions. We assess models using intensity, segmentation, and application-specific measurements obtained from virtually and experimentally stained nuclei and membranes. These models rescue missing labels, correct non-uniform expression, and mitigate photobleaching. We share three pre-trained models and a PyTorch-based pipeline (VisCy) for training, inference, and deployment.

This dataset comprises transmission electron microscopy (TEM) images of interscapular brown adipose tissue (iBAT) from female C57BL/6J mice. See the associated publications. Images are organised by animal (folders G1 83 and G1 90 = control diet; G2 79 = Western diet)

Macroscopic imaging and morphological assessment of mouse placentas at E12.5. Images are collected and analyzed to detect visible placental defects and developmental abnormalities.

Macroscopic imaging and morphological assessment of mouse placentas at E14.5-E15.5. Images are collected and analyzed to detect visible placental defects and developmental abnormalities.

All symptoms of malaria disease are associated with the asexual blood stages of development, involving cycles of red blood cell (RBC) invasion and egress by the Plasmodium spp. merozoite. Merozoite invasion is rapid and is actively powered by a parasite actomyosin motor. The current accepted model for actomyosin force generation envisages arrays of parasite myosins, pushing against short actin filaments connected to the external milieu that drive the merozoite forwards into the RBC. In Plasmodium falciparum, the most virulent human malaria species, Myosin A (PfMyoA) is critical for parasite replication. However, the precise function of PfMyoA in invasion, its regulation, the role of other myosins and overall energetics of invasion remain unclear. Here, we developed a conditional mutagenesis strategy combined with live video microscopy to probe PfMyoA function and that of the auxiliary motor PfMyoB in invasion. By imaging conditional mutants with increasing defects in force production, based on disruption to a key PfMyoA phospho-regulation site, the absence of the PfMyoA essential light chain, or complete motor absence, we define three distinct stages of incomplete RBC invasion. These three defects reveal three energetic barriers to successful entry: RBC deformation (pre-entry), mid-invasion initiation, and completion of internalisation, each requiring an active parasite motor. In defining distinct energetic barriers to invasion, these data illuminate the mechanical challenges faced in this remarkable process of protozoan parasitism, highlighting distinct myosin functions and identifying potential targets for preventing malaria pathogenesis.