Multiplex, high-throughput method to study cancer and immune cell mechanotransduction.

Studying cellular mechanoresponses during cancer metastasis is limited by sample variation or complex protocols that current techniques require. Metastasis is governed by mechanotransduction, whereby cells translate external stimuli, such as circulatory fluid shear stress (FSS), into biochemical cues. We present high-throughput, semi-automated methods to expose cells to FSS using the VIAFLO96 multichannel pipetting device custom-fitted with 22 G needles, increasing the maximum FSS 94-fold from the unmodified tips. Specifically, we develop protocols to semi-automatically stain live samples and to fix, permeabilize, and intracellularly process cells for flow cytometry analysis. Our first model system confirmed that the pro-apoptotic effects of TRAIL therapeutics in prostate cancer cells can be enhanced via FSS-induced Piezo1 activation. Our second system implements this multiplex methodology to show that FSS exposure (290 dyn cm-2) increases activation of murine bone marrow-derived dendritic cells. These methodologies greatly improve the mechanobiology workflow, offering a high-throughput, multiplex approach.

High-throughput tagging of endogenous loci for rapid characterization of protein function.

To facilitate the interrogation of protein function at scale, we have developed high-throughput insertion of tags across the genome (HITAG). HITAG enables users to rapidly produce libraries of cells, each with a different protein of interest C-terminally tagged. HITAG is based on a modified strategy for performing Cas9-based targeted insertions, coupled with an improved approach for selecting properly tagged lines. Analysis of the resulting clones generated by HITAG reveals high tagging specificity, with most successful tagging events being indel free. Using HITAG, we fuse mCherry to a set of 167 stress granule-associated proteins and elucidate the features that drive a subset of proteins to strongly accumulate within these transient RNA-protein granules.

Behavioral Assays Dissecting NMDA Receptor Function in Zebrafish.

Zebrafish are a powerful system to study brain development and to dissect the activity of complex circuits. One advantage is that they display complex behaviors, including prey capture, learning, responses to photic and acoustic stimuli, and social interaction (Dreosti et al., Front Neural Circuits 9:39, 2015; Bruckner et al., PLoS Biol 20:e3001838, 2022; Zoodsma et al., Mol Autism 13:38, 2022) that can be probed to assess brain function. Many of these behaviors are easily assayed at early larval stages, offering a noninvasive and high-throughput readout of nervous system function. Additionally, larval zebrafish readily uptake small molecules dissolved in water making them ideal for behavioral-based drug screens. Together, larval zebrafish and their behavioral repertoire offer a means to rapidly dissect brain circuitry and can serve as a template for high-throughput small molecule screens.NMDA receptor subunits are highly conserved in zebrafish compared to mammals (Zoodsma et al., Mol Autism 13:38, 2022; Cox et al., Dev Dyn 234:756-766, 2005; Zoodsma et al., J Neurosci 40:3631-3645, 2020). High amino acid and domain structure homology between humans and zebrafish underlie conserved functional similarities. Here we describe a set of behavioral assays that are useful to study the NMDA receptor activity in brain function.

Using Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy.

High-throughput microscopy has enabled screening of cell phenotypes at unprecedented scale. Systematic identification of cell phenotype changes (such as cell morphology and protein localization changes) is a major analysis goal. Because cell phenotypes are high-dimensional, unbiased approaches to detect and visualize the changes in phenotypes are still needed. Here, we suggest that changes in cellular phenotype can be visualized in reduced dimensionality representations of the image feature space. We describe a freely available analysis pipeline to visualize changes in protein localization in feature spaces obtained from deep learning. As an example, we use the pipeline to identify changes in subcellular localization after the yeast GFP collection was treated with hydroxyurea.

Magnetic Microtweezers for High-Throughput Bioseparation in Sub-Nanoliter Droplets.

Multiomics studies at single-cell level require small volume manipulation, high throughput analysis, and multiplexed detection, characteristics that droplet microfluidics can tackle. However, the initial step of molecule bioseparation remains challenging. Here, we describe a unique magnetic device to trap and extract magnetic particles in sub-nanoliter droplets, for compartmentalisation of detection steps. Relying on electrodeposition of NiFe structures and microfluidic manipulation, the extraction of 1 µm diameter magnetic particles was achieved at high throughput (20 droplets per second) with an efficiency close to 100% in 450 pL droplets. The first demonstration of its adaptability to single-cell analysis is demonstrated with the extraction of mRNA. Using a purified nucleic acid solution, this unique magnetic configuration was able to reach a RNA extraction rate of 72%. This is the first demonstration of a physical separation in droplets at high throughput at single-cell scale.

Current progress in high-throughput screening for drug repurposing.

High-throughput screening (HTS) is a simple, rapid and cost-effective solution to determine active candidates from large library of compounds. HTS is gaining attention from Pharmaceuticals and Biotechnology companies for accelerating their drug discovery programs. Conventional drug discovery program is time consuming and expensive. In contrast drug repurposing approach is cost-effective and increases speed of drug discovery as toxicity profile is already known. The present chapter highlight HTS technology including microplate, microfluidics, lab-on-chip, organ-on-chip for drug repurposing. The current chapter also highlights the application of HTS for bacterial infections and cancer.

Construction and application of 3-fucosyllactose whole-cell biosensor for high-throughput screening of overproducers.

Biosensor-based high-throughput screening is efficient for improving industrial microorganisms. There is a severe shortage of human milk oligosaccharides (HMOs) biosensors. This study established a 3-fucosyllactose (3-FL, a kind of HMOs) whole-cell biosensor by coupling cell growth with production. To construct and optimize the biosensor, an Escherichia coli 3-FL producer was engineered by deleting the manA, yihS and manX genes, directing the mannose flux solely to 3-FL synthesis. Then, an α-L-fucosidase was introduced to hydrolyze 3-FL to fucose which was used as the only carbon source for cell growth. Using the biosensor, the 3-FL production of a screened mutant was improved by 25 % to 42.05 ± 1.28 g/L. The productivity reached 1.17 g/L/h, the highest level reported by now. The csrB mutant obtained should be a new clue for the 3-FL overproduction mechanism. In summary, this study provided a novel approach to construct HMOs biosensors for strain improvement.

Recent advances in computational and experimental protein-ligand affinity determination techniques.

INTRODUCTION: Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved. AREAS COVERED: In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design. EXPERT OPINION: The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.

Using DNA-encoded libraries of fragments for hit discovery of challenging therapeutic targets.

INTRODUCTION: The effectiveness of Fragment-based drug design (FBDD) for targeting challenging therapeutic targets has been hindered by two factors: the small library size and the complexity of the fragment-to-hit optimization process. The DNA-encoded library (DEL) technology offers a compelling and robust high-throughput selection approach to potentially address these limitations. AREA COVERED: In this review, the authors propose the viewpoint that the DEL technology matches perfectly with the concept of FBDD to facilitate hit discovery. They begin by analyzing the technical limitations of FBDD from a medicinal chemistry perspective and explain why DEL may offer potential solutions to these limitations. Subsequently, they elaborate in detail on how the integration of DEL with FBDD works. In addition, they present case studies involving both de novo hit discovery and full ligand discovery, especially for challenging therapeutic targets harboring broad drug-target interfaces. EXPERT OPINION: The future of DEL-based fragment discovery may be promoted by both technical advances and application scopes. From the technical aspect, expanding the chemical diversity of DEL will be essential to achieve success in fragment-based drug discovery. From the application scope side, DEL-based fragment discovery holds promise for tackling a series of challenging targets.

Metabolism and cytotoxicity studies of the two hallucinogens 1cP-LSD and 4-AcO-DET in human liver and zebrafish larvae models using LC-HRMS/MS and a high-content screening assay.

The continuous emergence of new psychoactive substances (NPS) attracted a great deal of attention within recent years. Lately, the two hallucinogenic NPS 1cP-LSD and 4-AcO-DET have appeared on the global market. Knowledge about their metabolism to identify potential metabolic targets for analysis and their cytotoxic properties is lacking. The aim of this work was thus to study their in vitro and in vivo metabolism in pooled human liver S9 fraction (pHLS9) and in zebrafish larvae (ZL) by means of liquid chromatography-high-resolution tandem mass spectrometry. Monooxygenases involved in the initial metabolic steps were elucidated using recombinant human isozymes. Investigations on their cytotoxicity were performed on the human hepatoma cell line HepG2 using a multiparametric, fluorescence-based high-content screening assay. This included measurement of CYP-enzyme mediated effects by means of the unspecific CYP inhibitor 1-aminbenzotriazole (ABT). Several phase I metabolites of both compounds and two phase II metabolites of 4-AcO-DET were produced in vitro and in vivo. After microinjection of 1cP-LSD into the caudal vein of ZL, three out of seven metabolites formed in pHLS9 were also detected in ZL. Twelve 4-AcO-DET metabolites were identified in ZL after exposure via immersion bath and five of them were found in pHLS9 incubations. Notably, unique metabolites of 4-AcO-DET were only produced by ZL, whereas 1cP-LSD specific metabolites were found both in ZL and in pHLS9. No toxic effects were observed for 1cP-LSD and 4-AcO-DET in HepG2 cells, however, two parameters were altered in incubations containing 4-AcO-DET together with ABT compared with incubations without ABT but in concentrations far above expected in vivo concentration. Further investigations should be done with other hepatic cell lines expressing higher levels of CYP enzymes.

Development, High-Throughput Profiling, and Biopanning of a Large Phage Display Single-Domain Antibody Library.

Immunoglobulin G-based monoclonal antibodies (mAbs) have been effective in treating various diseases, but their large molecular size can limit their penetration of tissue and efficacy in multifactorial diseases, necessitating the exploration of alternative forms. In this study, we constructed a phage display library comprising single-domain antibodies (sdAbs; or "VHHs"), known for their small size and remarkable stability, using a total of 1.6 × 109 lymphocytes collected from 20 different alpacas, resulting in approximately 7.16 × 1010 colonies. To assess the quality of the constructed library, next-generation sequencing-based high-throughput profiling was performed, analyzing approximately 5.65 × 106 full-length VHH sequences, revealing 92% uniqueness and confirming the library's diverse composition. Systematic characterization of the library revealed multiple sdAbs with high affinity for three therapeutically relevant antigens. In conclusion, our alpaca sdAb phage display library provides a versatile resource for diagnostics and therapeutics. Furthermore, the library's vast natural VHH antibody repertoire offers insights for generating humanized synthetic sdAb libraries, further advancing sdAb-based therapeutics.

Machine Learning-Accelerated High-Throughput Computational Screening: Unveiling Bimetallic Nanoparticles with Peroxidase-Like Activity.

Bimetallic nanoparticles (NPs) with peroxidase-like (POD-like) activity play a crucial role in biosensing, disease treatment, environmental management, and other fields. However, their development is impeded by a vast range of tunable properties in components and structures, making the establishment of structure-effect relationships and the discovery of active materials challenging. Addressing this, we established robust scaling relationships by meticulously analyzing the catalytic reaction networks of pure metal NPs, which laid the volcano-shaped correlation between the activity and O* adsorption energy. Utilizing these relationships, we introduced an innovative and versatile descriptor of the NPs, which was then integrated into a machine learning-accelerated high-throughput computational workflow, significantly boosting the predictive accuracy for the POD-like activity of bimetallic NPs. Our methodological approach enabled the successful prediction of activities for 1260 bimetallic NPs, leading to the identification of several highly effective catalysts. Furthermore, we distilled several strategies for designing efficient bimetallic NPs based on our screening results.

Bringing Artificial Intelligence (AI) into Environmental Toxicology Studies: A Perspective of AI-Enabled Zebrafish High-Throughput Screening.

The booming development of artificial intelligence (AI) has brought excitement to many research fields that could benefit from its big data analysis capability for causative relationship establishment and knowledge generation. In toxicology studies using zebrafish, the microscopic images and videos that illustrate the developmental stages, phenotypic morphologies, and animal behaviors possess great potential to facilitate rapid hazard assessment and dissection of the toxicity mechanism of environmental pollutants. However, the traditional manual observation approach is both labor-intensive and time-consuming. In this Perspective, we aim to summarize the current AI-enabled image and video analysis tools to realize the full potential of AI. For image analysis, AI-based tools allow fast and objective determination of morphological features and extraction of quantitative information from images of various sorts. The advantages of providing accurate and reproducible results while avoiding human intervention play a critical role in speeding up the screening process. For video analysis, AI-based tools enable the tracking of dynamic changes in both microscopic cellular events and macroscopic animal behaviors. The subtle changes revealed by video analysis could serve as sensitive indicators of adverse outcomes. With AI-based toxicity analysis in its infancy, exciting developments and applications are expected to appear in the years to come.

Ultrapotent influenza hemagglutinin fusion inhibitors developed through SuFEx-enabled high-throughput medicinal chemistry.

Seasonal and pandemic-associated influenza strains cause highly contagious viral respiratory infections that can lead to severe illness and excess mortality. Here, we report on the optimization of our small-molecule inhibitor F0045(S) targeting the influenza hemagglutinin (HA) stem with our Sulfur-Fluoride Exchange (SuFEx) click chemistry-based high-throughput medicinal chemistry (HTMC) strategy. A combination of SuFEx- and amide-based lead molecule diversification and structure-guided design led to identification and validation of ultrapotent influenza fusion inhibitors with subnanomolar EC50 cellular antiviral activity against several influenza A group 1 strains. X-ray structures of six of these compounds with HA indicate that the appended moieties occupy additional pockets on the HA surface and increase the binding interaction, where the accumulation of several polar interactions also contributes to the improved affinity. The compounds here represent the most potent HA small-molecule inhibitors to date. Our divergent HTMC platform is therefore a powerful, rapid, and cost-effective approach to develop bioactive chemical probes and drug-like candidates against viral targets.

New methods for drug synergy prediction: A mini-review.

In this mini-review, we explore the new prediction methods for drug combination synergy relying on high-throughput combinatorial screens. The fast progress of the field is witnessed in the more than thirty original machine learning methods published since 2021, a clear majority of them based on deep learning techniques. We aim to put these articles under a unifying lens by highlighting the core technologies, the data sources, the input data types and synergy scores used in the methods, as well as the prediction scenarios and evaluation protocols that the articles deal with. Our finding is that the best methods accurately solve the synergy prediction scenarios involving known drugs or cell lines while the scenarios involving new drugs or cell lines still fall short of an accurate prediction level.

Using Infrared Thermography for High-Throughput Plant Phenotyping.

Infrared thermography offers a rapid, noninvasive method for measuring plant temperature, which provides a proxy for stomatal conductance and plant water status and can therefore be used as an index for plant stress. Thermal imaging can provide an efficient method for high-throughput screening of large numbers of plants. This chapter provides guidelines for using thermal imaging equipment and illustrative methodologies, coupled with essential considerations, to access plant physiological processes.

High throughput screening aids clinical decision-making in refractory acute myeloid leukaemia.

BACKGROUND: Despite advances in therapeutics for adverse-risk acute myeloid leukaemia (AML), overall survival remains poor, especially in refractory disease. Comprehensive tumour profiling and pre-clinical drug testing can identify effective personalised therapies. CASE: We describe a case of ETV6-MECOM fusion-positive refractory AML, where molecular analysis and in vitro high throughput drug screening identified a tolerable, novel targeted therapy and provided rationale for avoiding what could have been a toxic treatment regimen. Ruxolitinib combined with hydroxyurea led to disease control and enhanced quality-of-life in a patient unsuitable for intensified chemotherapy or allogeneic stem cell transplantation. CONCLUSION: This case report demonstrates the feasibility and role of combination pre-clinical high throughput screening to aid decision making in high-risk leukaemia. It also demonstrates the role a JAK1/2 inhibitor can have in the palliative setting in select patients with AML.

HEIDI: an experiment-management platform enabling high-throughput fragment and compound screening.

The Swiss Light Source facilitates fragment-based drug-discovery campaigns for academic and industrial users through the Fast Fragment and Compound Screening (FFCS) software suite. This framework is further enriched by the option to utilize the Smart Digital User (SDU) software for automated data collection across the PXI, PXII and PXIII beamlines. In this work, the newly developed HEIDI webpage (https://heidi.psi.ch) is introduced: a platform crafted using state-of-the-art software architecture and web technologies for sample management of rotational data experiments. The HEIDI webpage features a data-review tab for enhanced result visualization and provides programmatic access through a representational state transfer application programming interface (REST API). The migration of the local FFCS MongoDB instance to the cloud is highlighted and detailed. This transition ensures secure, encrypted and consistently accessible data through a robust and reliable REST API tailored for the FFCS software suite. Collectively, these advancements not only significantly elevate the user experience, but also pave the way for future expansions and improvements in the capabilities of the system.

AptaShield: A Universal Signal-Transduction System for Fast and High-Throughput Optical Molecular Biosensing.

Biosensing technologies are often described to provide facile, sensitive, and minimally to noninvasive detection of molecular analytes across diverse scientific, environmental, and clinical diagnostic disciplines. However, commercialization has been very limited mostly due to the difficulty of biosensor reconfiguration for different analyte(s) and limited high-throughput capabilities. The immobilization of different biomolecular probes (e.g., antibodies, peptides, and aptamers) requires the sensor surface chemistry to be tailored to provide optimal probe coupling, orientation, and passivation and prevent nonspecific interactions. To overcome these challenges, here we report the development of a solution-phase biosensor consisting of an engineered aptamer, the AptaShield, capable of universally binding to any antigen recognition site (Fab') of fluorescently labeled immunoglobulins (IgG) produced in rabbits. The resulting AptaShield biosensor relies on a low affinity dynamic equilibrium between the fluorescently tagged aptamer and IgG to generate a specific Förster resonance energy transfer (FRET) signal. As the analyte binds to the IgG, the AptaShield DNA aptamer-IgG complex dissociates, leading to an analyte concentration-dependent decrease of the FRET signal. The biosensor demonstrates high selectivity, specificity, and reproducibility for analyte quantification in different biological fluids (e.g., urine and blood serum) in a one-step and low sample volume (0.5-6.25 µL) format. The AptaShield provides a universal signal transduction mechanism as it can be coupled to different rabbit antibodies without the need for aptamer modification, therefore representing a robust high-throughput solution-phase technology suitable for point-of-care applications, overcoming the current limitations of gold standard enzyme-linked immunosorbent assays (ELISA) for molecular profiling.

Interlaboratory comparison of high-throughput protein biomarker assay quantifications for radiation exposure classification.

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada. The Center for Radiological Research (CRR) at CU served as the central laboratory and reference instrument, where samples were prepared in triplicate, labeled with two radiation responsive leukocyte biomarkers (BAX and phosphor-p53 (Ser37)), and distributed for simultaneous interrogation by each IFC. Initial tests showed that significantly different baseline biomarker measurements were generated on each instrument when using the same acquisition settings, suggesting that harmonization of signal intensities is necessary. Subsequent tests harmonized biomarker measurements after irradiation by modulating laser intensity using two reference materials: unstained samples and standardized rainbow beads. Both methods generated measurements on each instrument without significant differences between the new and references instruments, allowing for the use of one master template to quantify biomarker expression across multiple instruments. Deming regression analyses of 0-5 Gy dose-response curves showed overall good correlation of BAX and p53 values across new and reference instruments. While Bland-Altman analyses indicated low to moderate instrument biases, ROC Curve analyses ultimately show successful discrimination between exposed and unexposed samples on each instrument (AUC values > 0.85).