Train the Trainers in Bioimage Analysis: A Community Initiative

The Royal Microscopical Society Data Analysis in IMaging (RMS DAIM), with the support of the Crick and Partners Networking Fund, has organised a "Train the Trainers in Bioimage Analysis" workshop in June 2025 at University College London. The Train the Trainers initiative aimed to establish and disseminate guidelines on how to organise courses and train researchers in bioimage analysis. Attendees of the Train the Trainer session became part of a network that provides local expertise and creates efficient channels for the dissemination of knowledge and good practices in bioimage analysis. The event was free, and travel and accommodation support was available for attendees outside the London area (max €100 pp). Participants were selected based on their expertise and role as trainers in bioimaging facilities or research groups. The target audience included researchers with knowledge of bioimage analysis principles who wished to improve their skills in providing training. Here, we present our experience in organising such an event, our take-home messages and feedback from the attendees. Poster presented as part of the Crick BioImage Analysis Symposium 2025.Permission has been given by authors to upload to Crick Figshare. Copyright remains with the original authors.</p

Evaluating Cellpose SAM as a segmentation algorithm for downstream cell morphology analysis

• It is known that exposing cells to chemicals can alter their morphology, for example Dimethyl Sulfoxide (DMSO) or Okadaic acid induceapoptosis, a programmed cell death characterised in part by cell membrane shrinkage and cytoplasm condensation [1].• To investigate the phenotypical changes of individual cells within a monolayer, the cell membranes need to be segmented.• Our aim was to optimise Cellpose SAM as a segmentation tool and to evaluate whether the morphological changes associated with cell death impact segmentation performance.• This was achieved by segmenting images of cell monolayers before and after treating them with an apoptosis inducing agent, henceforth known as ‘untreated’ and ‘treated’ images, respectively.Poster presented as part of the Crick BioImage Analysis Symposium 2025.Permission has been given by authors to upload to Crick Figshare. Copyright remains with the original authors.</p

CLEMnet: Recognizing biological features in large-scale electron microscopy from fluorescence training data

Poster presented as part of the Crick BioImage Analysis Symposium 2025.Permission has been given by authors to upload to Crick Figshare. Copyright remains with the original authors.</p

Microscopy Nodes: 3D data visualization in Blender

Poster presented as part of the Crick BioImage Analysis Symposium 2025.Permission has been given by authors to upload to Crick Figshare. Copyright remains with the original authors.</p

Single Molecule Localisation Microscopyand Image Analysis to investigatethe sarcomere at the nanoscale

The sarcomereThe sarcomere is the base contractile unit of muscle. With a length of ~2μm, interesting sub-sarcomeric structure is at the nanoscale and super-resolution (SR) microscopy is needed to image it and understand it. Electron Microscopy is limited in the denser regions made up of very similar domains; hence SR fluorescence microscopy provides nanoscale resolution imaging with high molecular specificity labelling. SMLM is at the forefront of SR-fluorescence microscopy, and is therefore an important tool for resolving substructure at the nanoscale.Poster presented as part of the Crick BioImage Analysis Symposium 2025.Permission has been given by authors to upload to Crick Figshare. Copyright remains with the original authors.</p

Expedited SARS‐CoV‐2 main protease inhibitor discovery through modular ‘direct‐to‐biology’ screening

Reactive fragment (RF) screening has emerged as an efficient method for ligand discovery across the proteome, irrespective of a target's perceived tractability. To date, however, the efficiency of subsequent optimisation campaigns has largely been low‐throughput, constrained by the need for synthesis and purification of target compounds. We report an efficient platform for ‘direct‐to‐biology’ (D2B) screening of cysteine‐targeting chloroacetamide RFs, wherein synthesis is performed in 384‐well plates allowing direct assessment in downstream biological assays without purification. Here, the developed platform was used to optimise inhibitors of SARS‐CoV‐2 main protease (MPro), an established drug target for the treatment of COVID‐19. An initial RF hit was developed into a series of potent inhibitors, and further exploration using D2B screening enabled a ‘switch’ to a reversible inhibitor series. This example of ligand discovery for MPro illustrates the acceleration that D2B chemistry can offer for optimising RFs towards covalent inhibitor candidates, as well as providing future impetus to explore the evolution of RFs into non‐covalent ligands

Context-dependent effects of CDKN2A and other 9p21 gene losses during the evolution of esophageal cancer.

CDKN2A is a tumor suppressor located in chromosome 9p21 and frequently lost in Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC). How CDKN2A and other 9p21 gene co-deletions affect EAC evolution remains understudied. We explored the effects of 9p21 loss in EACs and cancer progressor and non-progressor BEs with matched genomic, transcriptomic and clinical data. Despite its cancer driver role, CDKN2A loss in BE prevents EAC initiation by counterselecting subsequent TP53 alterations. 9p21 gene co-deletions predict poor patient survival in EAC but not BE through context-dependent effects on cell cycle, oxidative phosphorylation and interferon response. Immune quantifications using bulk transcriptome, RNAscope and high-dimensional tissue imaging showed that IFNE loss reduces immune infiltration in BE, but not EAC. Mechanistically, CDKN2A loss suppresses the maintenance of squamous epithelium, contributing to a more aggressive phenotype. Our study demonstrates context-dependent roles of cancer genes during disease evolution, with consequences for cancer detection and patient management

Prospective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma.

Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. We prospectively validate the survival association of a clonal expression biomarker, Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors, and in stage I disease. We expand our mechanistic understanding, discovering that clonal transcriptional signals are detectable before tissue invasion, act as a molecular fingerprint for lethal metastatic clones and predict chemotherapy sensitivity. Lastly, we find that ORACLE summarizes the prognostic information encoded by genetic evolutionary measures, including chromosomal instability, as a concise 23-transcript assay

Characterizing the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

Proliferation is a key hallmark of cancer, but whether it differs between evolutionarily distinct clones co-existing within a tumor is unknown. We introduce the Single-cell Proliferation Rate Inference in Non-homogeneous Tumors through Evolutionary Routes (SPRINTER) algorithm that uses single-cell whole-genome DNA sequencing data to enable accurate identification and clone assignment of S- and G2-phase cells, as assessed by generating accurate ground truth data. Applied to a newly generated longitudinal, primary-metastasis-matched dataset of 14,994 non-small cell lung cancer cells, SPRINTER revealed widespread clone proliferation heterogeneity, orthogonally supported by Ki-67 staining, nuclei imaging and clinical imaging. We further demonstrated that high-proliferation clones have increased metastatic seeding potential, increased circulating tumor DNA shedding and clone-specific altered replication timing in proliferation- or metastasis-related genes associated with expression changes. Applied to previously generated datasets of 61,914 breast and ovarian cancer cells, SPRINTER revealed increased single-cell rates of different genomic variants and enrichment of proliferation-related gene amplifications in high-proliferation clones

A scaleable inducible knockout system for studying essential gene function in the malaria parasite.

The malaria parasite needs nearly half of its genes to propagate normally within red blood cells. Inducible ways to interfere with gene expression like the DiCre-lox system are necessary to study the function of these essential genes. However, existing DiCre-lox strategies are not well-suited to be deployed at scale to study several genes simultaneously. To overcome this, we have developed SHIFTiKO (frameshift-based trackable inducible knockout), a novel scaleable strategy that uses short, easy-to-construct, barcoded repair templates to insert loxP sites around short regions in target genes. Induced DiCre-mediated excision of the flanked region causes a frameshift mutation resulting in genetic ablation of gene function. Dual DNA barcodes inserted into each mutant enables verification of successful modification and induced excision at each locus and collective phenotyping of the mutants, not only across multiple replication cycles to assess growth fitness but also within a single cycle to identify specific phenotypic impairments. As a proof of concept, we have applied SHIFTiKO to screen the functions of malarial rhomboid proteases, successfully identifying their blood stage-specific essentiality. SHIFTiKO thus offers a powerful platform to conduct inducible phenotypic screens to study essential gene function at scale in the malaria parasite