Development of the Theta-Comparative-Cell-Scoring (TCCS) Method to Quantify Diverse Phenotypic Responses between Distinct Cell Types

In this article, we have developed novel data visualization tools and a Theta comparative cell scoring (TCCS) method, which supports high-throughput in vitro pharmacogenomic studies across diverse cellular phenotypes measured by multiparametric high-content analysis. The TCCS method provides a univariate descriptor of divergent compound-induced phenotypic responses between distinct cell types, which can be used for correlation with genetic, epigenetic, and proteomic datasets to support the identification of biomarkers and further elucidate drug mechanism-of-action. Application of these methods to compound profiling across high-content assays incorporating well-characterized cells representing known molecular subtypes of disease supports the development of personalized healthcare strategies without prior knowledge of a drug target. We present proof-of-principle data quantifying distinct phenotypic response between eight breast cancer cells representing four disease subclasses. Application of the TCCS method together with new advances in next-generation sequencing, induced pluripotent stem cell technology, gene editing, and high-content phenotypic screening are well placed to advance the identification of predictive biomarkers and personalized medicine approaches across a broader range of disease types and therapeutic classes

Image informatics approaches to advance cancer drug discovery

High content image-based screening assays utilise cell based models to extract and quantify morphological phenotypes induced by small molecules. The rich datasets produced can be used to identify lead compounds in drug discovery efforts, infer compound mechanism of action, or aid biological understanding with the use of tool compounds. Here I present my work developing and applying high-content image based screens of small molecules across a panel of eight genetically and morphologically distinct breast cancer cell lines. I implemented machine learning models to predict compound mechanism of action from morphological data and assessed how well these models transfer to unseen cell lines, comparing the use of numeric morphological features extracted using computer vision techniques against more modern convolutional neural networks acting on raw image data. The application of cell line panels have been widely used in pharmacogenomics in order to compare the sensitivity between genetically distinct cell lines to drug treatments and identify molecular biomarkers that predict response. I applied dimensional reduction techniques and distance metrics to develop a measure of differential morphological response between cell lines to small molecule treatment, which controls for the inherent morphological differences between untreated cell lines. These methods were then applied to a screen of 13,000 lead-like small molecules across the eight cell lines to identify compounds which produced distinct phenotypic responses between cell lines. Putative hits from a subset of approved compounds were then validated in a three-dimensional tumour spheroid assay to determine the functional effect of these compounds in more complex models, as well as proteomics to determine the responsible pathways. Using data generated from the compound screen, I carried out work towards integrating knowledge of chemical structures with morphological data to infer mechanistic information of the unannotated compounds, and assess structure activity relationships from cell-based imaging data

The fungal alkaloid Okaramine-B activates an L-glutamate-gated chloride channel from Ixodes scapularis, a tick vector of Lyme disease

This work was supported by Merial Ltd., The Japan Society for the Promotion of Sciences (KAKENHI, Grant number: 17H01472) and The UK Medical Research Council.A novel L-glutamate-gated anion channel (IscaGluCl1) has been cloned from the black-legged tick, Ixodes scapularis, which transmits multiple pathogens including the agents of Lyme disease and human granulocytic anaplasmosis. When mRNA encoding IscaGluCl1 was expressed in Xenopus laevis oocytes, we detected robust 50–400 nA currents in response to 100 μM L-glutamate. Responses to L-glutamate were concentration-dependent (pEC50 3.64 ± 0.11). Ibotenate was a partial agonist on IscaGluCl1. We detected no response to 100 μM aspartate, quisqualate, kainate, AMPA or NMDA. Ivermectin at 1 μM activated IscaGluCl1, whereas picrotoxinin (pIC50 6.20 ± 0.04) and the phenylpyrazole fipronil (pIC50 6.90 ± 0.04) showed concentration-dependent block of the L-glutamate response. The indole alkaloid okaramine B, isolated from fermentation products of Penicillium simplicissimum (strain AK40) grown on okara pulp, activated IscaGluCl1 in a concentration-dependent manner (pEC50 5.43 ± 0.43) and may serve as a candidate lead compound for the development of new acaricides.Publisher PDFPeer reviewe

Neutralising immunity to omicron sublineages BQ.1.1, XBB, and XBB.1.5 in healthy adults is boosted by bivalent BA.1-containing mRNA vaccination and previous Omicron infection

The global COVID-19 landscape is increasingly complex; emerging new variants rapidly cause waves of infection in people with variably induced immunity. Most individuals now have so-called hybrid immunity from both infection and vaccination. However, sequential infecting variants, induction of immunity, and subsequent waning are interlinked, and immune protection against new variants is unclear

Strong peak immunogenicity but rapid antibody waning following third vaccine dose in older residents of care homes

Third-dose coronavirus disease 2019 vaccines are being deployed widely but their efficacy has not been assessed adequately in vulnerable older people who exhibit suboptimal responses after primary vaccination series. This observational study, which was carried out by the VIVALDI study based in England, looked at spike-specific immune responses in 341 staff and residents in long-term care facilities who received an mRNA vaccine following dual primary series vaccination with BNT162b2 or ChAdOx1. Third-dose vaccination strongly increased antibody responses with preferential relative enhancement in older people and was required to elicit neutralization of Omicron. Cellular immune responses were also enhanced with strong cross-reactive recognition of Omicron. However, antibody titers fell 21–78% within 100 d after vaccine and 27% of participants developed a breakthrough Omicron infection. These findings reveal strong immunogenicity of a third vaccine in one of the most vulnerable population groups and endorse an approach for widespread delivery across this population. Ongoing assessment will be required to determine the stability of immune protection

Data-analysis strategies for image-based cell profiling

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.Peer reviewe