Cellular & Molecular Imaging

All images used to generate the figures of this manuscript

Transmission electron microscopy (TEM) of liver tissue from male Syrian golden hamsters (Mesocricetus auratus) used to examine how Opisthorchis viverrini infection modulates the severity of nonalcoholic fatty liver disease (NAFLD) induced by a high-fat/high-fructose (HFF) diet. The dataset comprises 45 TEM images across the four groups. Associated publication: Chaidee A, et al. Opisthorchis viverrini Infection Augments the Severity of Nonalcoholic Fatty Liver Disease in High-Fat/High-Fructose Diet-Fed Hamsters. Am J Trop Med Hyg. 2019;101(5):1161-1169.

The role of Queen Mandibular Pheromone (QMP) in nurse honey bee lipid metabolism, particularly its effects on lipogenesis in the fat body and hypopharyngeal gland (HPG) size, remains uncertain. I hypothesize that (1) QMP exposure increases lipogenesis in the fat bodies of nurse aged bees, (2) because of this increased lipogenesis HPG size will increase, and (3) bees with higher fat body lipogenesis will have larger HPGs. Lipogenesis was measured through a fatty acid synthase (FAS) assay and the HPGs were viewed under a Leica microscope and measured through ImageJ. This experiment was a 2-factorial study, using age as one factor (either 3-day-old nurses or 8-day-old nurses) and QMP presence or absence as another. The nurse-aged bees were treated with QMP strips or not in cages supplied with sucrose and a protein paste diet with no lipids. The four treatment groups were replicated 3 times.

Preventing parasite transmission from humans to mosquitoes is recognised to be critical for achieving elimination and eradication of malaria. Consequently developing new antimalarial drugs with transmission-blocking properties is a priority. Large screening campaigns have identified many new transmission-blocking molecules, however little is known about how they target transmissible Plasmodium falciparum stage V gametocytes, or how they affect their underlying cell biology. To respond to this knowledge gap, we have developed a machine learning image analysis pipeline to characterise and compare the cellular phenotypes generated by transmission-blocking molecules during male gametogenesis. Using this approach, we studied 40 molecules, categorising their activity based upon timing of action and visual effects on the organisation of tubulin and DNA in the cell. Our data both proposes new modes of action and corroborates existing modes of action of identified transmission-blocking molecules. Furthermore, the characterised molecules provide a new armoury of tool compounds to probe gametocyte cell biology and the generated imaging dataset provides a new reference for researchers to correlate molecular target or gene deletion to specific cellular phenotype. Our analysis pipeline is not optimised for a specific organism and could be applied to any fluorescence microscopy dataset containing cells delineated by bounding boxes, and so is extendible to any disease model.

Targeted protein degradation using conditional degron tags (CDTs) technologies is a powerful method for rapidly degrading a protein of interest (POI) upon the addition of a degrader drug. A prerequisite for the controlled degradation of an endogenous POI is the generation of homozygous knock-in cells that have the degron tag either integrated at the N- or C-terminus of their gene loci. However, obtaining those homozygous knock-in cells often requires selecting many single-cell clones, as human cells typically exhibit low homology-directed repair (HDR) activities. Additionally, tagging a degron to an endogenous protein may inadvertently impair the protein expression level, potentially affecting the protein function even before the drug is administered. Here, we develop a method for generating degron-tagged knock-in cells that allows us to skip the laborious single-cell cloning. The method was developed from our observation that most knock-in cells contain the degron tag only in one allele (heterozygous), while the other allele has a frame-shift insertion/deletion. This allowed us to bypass the need for single-cell cloning. We validated our method by knocking in degron tags at the N-terminus of cytoplasmic dynein1 subunits or Adaptor Protein 2 (AP2) subunit. Our experiments confirmed the rapid degradation of these proteins and their functional inhibition in bulk cell populations. To mitigate the reduced expression often associated with the degron tagging, we established a method to control expression levels by inserting a mini-promoter immediately upstream of the knock-in cassette. Our method simplifies the workflow for degron tag knock-in and enhances the versatility of these valuable technologies.

Tara Expeditions are global scientific voyages that probe morphological and molecular diversity, evolution and ecology of marine plankton to explore how they are impacted by changes in the Earth's climate. The first expeditions collected samples of marine plankton containing viruses, bacteria, archaea, protists and planktonic metazoans living in the photic layer of the world's oceans. These expeditions, the first taking place between 2009 and 2013, include Tara Oceans: a global view, and Tara Oceans Polar Circle, both of which followed the same sampling protocol. This dataset includes 1074 pictures of 284 planktonic taxa (mainly microalgae and other Ciliate and Radiolarian protists) collected from the vicinity of the Marquesas Islands in the Southern Pacific Ocean during the Tara Oceans expedition. Multiple samples particularly of the size fractions 5-20 and 20 180 um from four sites and two depths were processed with different methods and studied in detail using scanning electron microscopy.

Plasmodium parasites, the causative agents of malaria, undergo complex replication within vertebrate and insect hosts, presenting unique opportunities for therapeutic intervention. A key challenge during these replication events, i.e., schizogony in vertebrate red blood cells and sporogony in oocysts within mosquitos, is ensuring the faithful partitioning of nuclei and organelles into the numerous daughter cells that form at once from a single parent. While nuclear microtubule-organizing centers, or centriolar plaques (CPs), have been hypothesized to play a central role in this process, the molecular mediators linking the CPs and organelles remain incompletely defined. Here, we characterize two striated fiber assemblin (SFA) homologs, SFA1 and SFA2, in Plasmodium falciparum and Plasmodium berghei across two hosts. We show that these SFAs form a physical bridge between the CP and the nascent apical poles of daughter cells, facilitating high-fidelity progeny formation during schizogony and sporogony. Loss of SFA function disrupts merozoite and sporozoite formation, with profound consequences for transmission. These findings establish SFAs as essential organizers of parasite morphogenesis and highlight them as potential targets for antimalarial therapies. This submission includes the source microscopy image data for experiments performed in P. falciparum.

Light microscopy and scanning electron microscopy images of snow algae field samples containing Rosetta gen. nov., including type material.

Bacteria occupy heterogeneous environments, attaching and growing within pores in materials, living hosts, and matrices like soil. Systems that permit high-resolution visualization of dynamic bacterial processes within the physical confines of a realistic and tractable porous media environment are rare. Here we use microfluidics to replicate the grain shape and packing density of natural sands in a 2D platform to study the flow-induced spatial evolution of bacterial biofilms underground. We introduce a wildtype strain (Pantoea sp. YR343, n=3) or an EPS-defective strain (Pantoea sp. YR343 ΔUDP, n=3) to the porous media platform and then simulate a rainfall event using gravity-driven flow of bacterial growth media.

OME-NGFF converted study from idr0090. Drug resistance threatens the effective prevention and treatment of an ever-increasing range of human infections. This highlights an urgent need for new and improved drugs with novel mechanisms of action to avoid cross-resistance. Current cell-based drug screens are, however, restricted to binary live/dead readouts with no provision for mechanism of action prediction. Machine learning methods are increasingly being used to improve information extraction from imaging data. Such methods, however, work poorly with heterogeneous cellular phenotypes and generally require time-consuming human-led training. We have developed a semi-supervised machine learning approach, combining human- and machine-labelled training data from mixed human malaria parasite cultures. Designed for high-throughput and high-resolution screening, our semi-supervised approach is robust to natural parasite morphological heterogeneity and correctly orders parasite developmental stages. Our approach also reproducibly detects and clusters drug-induced morphological outliers by mechanism of action, demonstrating the potential power of machine learning for accelerating cell-based drug discovery.