MALDI-TOF Mass Spectrometry-Based Assay for Measuring Covalent Target Engagement of KRAS G12C Inhibitors.

MALDI-TOF mass spectrometry enables high-throughput screening of covalent fragment libraries and SAR compound progressions of selective KRAS G12C inhibitors. Using the MALDI-TOF platform instead of the more traditional ESI-MS TOF/orbitrap instrumentation can radically shorten sample acquisition time, allowing up to 384 samples to be screened in 30 min. The typical throughput for a covalent library screen is 1152 samples per 8 h, including processing, calculation, and reporting steps. The throughput can be doubled without any significant assay modification.

High-Throughput Cell-Based Screening of Small Molecule KRAS Signaling Inhibitors Using a Homogeneous Time-Resolved Fluorescence (HTRF) Assay.

With recent advances proving that effective inhibition of KRAS is possible, there have been significant efforts made to develop inhibitors of specific mutant alleles. Here we describe a detailed protocol that employs homogeneous time-resolved fluorescence (HTRF) to identify compounds acting on KRAS signaling in malignant cell lines. This method allows for high-throughput, cell-based screens of large compound libraries for the development of RAS-targeted therapeutics.

High-Throughput µPAD with Cascade Signal Amplification through Dual Enzymes for arsM in Paddy Soil.

The arsM gene is a critical biomarker for the potential risk of arsenic exposure in paddy soil. However, on-site screening of arsM is limited by the lack of high-throughput point-of-use (POU) methods. Here, a multiplex CRISPR/Cas12a microfluidic paper-based analytical device (µPAD) was constructed for the high-throughput POU analysis of arsM, with cascade amplification driven by coupling crRNA-enhanced Cas12a and horseradish peroxidase (HRP)-modified probes. First, seven crRNAs were designed to recognize arsM, and their LODs and background signal intensities were evaluated. Next, a step-by-step iterative approach was utilized to develop and optimize coupling systems, which improved the sensitivity 32 times and eliminated background signal interference. Then, ssDNA reporters modified with HRP were introduced to further lower the LOD to 16 fM, and the assay results were visible to the naked eye. A multiplex channel microfluidic paper-based chip was developed for the reaction integration and simultaneous detection of 32 samples and generated a recovery rate between 87.70 and 114.05%, simplifying the pretreatment procedures and achieving high-throughput POU analysis. Finally, arsM in Wanshan paddy soil was screened on site, and the arsM abundance ranged from 1.05 × 106 to 6.49 × 107 copies/g; this result was not affected by the environmental indicators detected in the study. Thus, a coupling crRNA-based cascade amplification method for analyzing arsM was constructed, and a microfluidic device was developed that contains many more channels than previous paper chips, greatly improving the analytical performance in paddy soil samples and providing a promising tool for the on-site screening of arsM at large scales.

AI is a viable alternative to high throughput screening: a 318-target study.

High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery.

High-throughput visualization mutation screening technology to enhance the specificity of CadR based whole-cell cadmium biosensor.

As a heavy metal pollutant, Cd2+ often enters the human body through the food chain causing great harm to human health. Whole-cell biosensor is an emerging technology for rapid on-site detection of heavy metals with the advantages of inexpensive, fast to mass-produce, and strong in anti-interference resistance, but suffering from insatisfactory specificity. In this study, a strategy of Adjacent Site Saturation Mutation (ASSM) was designed to improve the specificity of transcription factor CadR, which acted as the recognition element and determined the specificity of whole cell Cd2+ biosensors. A specific saturated library was constructed using the strategy of adjacent mutation. After two rounds of high-throughput visual screening, a whole-cell biosensor with good response to Cd2+, and with significant weakened Hg2+ interference was obtained. The optimized whole-cell biosensor showed a linear dynamic concentration range from 500 nM to 100 µM, a detection limit of 0.079 µM, and has satisfactory specificity and anti-interference. The ASSM strategy proposed in this study can provide a new method for the application of synthetic biology in food safety detection, indicating the importance of whole-cell biosensors for the detection of heavy metals.

A High-Throughput Approach for Photosynthesis Studies in a Brassicaceae Panel.

The study of natural variations in photosynthesis in the Brassicaceae family offers the possibility of identifying mechanisms to enhance photosynthetic efficiency in crop plants. Indeed, this family, and particularly its tribe Brassiceae, has been shown to harbor species that have a higher-than-expected photosynthetic efficiency, possibly as a result of a complex evolutionary history. Over the past two decades, methods have been developed to measure photosynthetic efficiency based on chlorophyll fluorescence. Chlorophyll fluorescence measurements are performed with special cameras, such as the FluorCams, which can be included in robotic systems to create high-throughput phenotyping platforms. While these platforms have so far demonstrated high efficiency in measuring small model species like Arabidopsis thaliana, they have the drawback of limited adaptability to accommodate different plant sizes. As a result, the range of species that can be analyzed is restricted. This chapter presents our approach to analyze the photosynthetic parameters: ϕPSII and Fv/Fm for a panel of Brassicaceae species, including a high-photosynthesis species, Hirschfeldia incana, and the adaptations to the phenotyping platform that are required to accommodate this varied group of plants.

An Overview of High-Throughput Crop Phenotyping: Platform, Image Analysis, Data Mining, and Data Management.

In this chapter, we explore the application of high-throughput crop phenotyping facilities for phenotype data acquisition and the extraction of significant information from the collected data through image processing and data mining methods. Additionally, the construction and outlook of crop phenotype databases are introduced and the need for global cooperation and data sharing is emphasized. High-throughput crop phenotyping significantly improves accuracy and efficiency compared to traditional measurements, making significant contributions to overcoming bottlenecks in the phenotyping field and advancing crop genetics.

Cell Painting-based bioactivity prediction boosts high-throughput screening hit-rates and compound diversity.

Identifying active compounds for a target is a time- and resource-intensive task in early drug discovery. Accurate bioactivity prediction using morphological profiles could streamline the process, enabling smaller, more focused compound screens. We investigate the potential of deep learning on unrefined single-concentration activity readouts and Cell Painting data, to predict compound activity across 140 diverse assays. We observe an average ROC-AUC of 0.744 ± 0.108 with 62% of assays achieving ≥0.7, 30% ≥0.8, and 7% ≥0.9. In many cases, the high prediction performance can be achieved using only brightfield images instead of multichannel fluorescence images. A comprehensive analysis shows that Cell Painting-based bioactivity prediction is robust across assay types, technologies, and target classes, with cell-based assays and kinase targets being particularly well-suited for prediction. Experimental validation confirms the enrichment of active compounds. Our findings indicate that models trained on Cell Painting data, combined with a small set of single-concentration data points, can reliably predict the activity of a compound library across diverse targets and assays while maintaining high hit rates and scaffold diversity. This approach has the potential to reduce the size of screening campaigns, saving time and resources, and enabling primary screening with more complex assays.

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.

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.

Enhancing the Small-Scale Screenable Biological Space beyond Known Chemogenomics Libraries with Gray Chemical Matter─Compounds with Novel Mechanisms from High-Throughput Screening Profiles.

Phenotypic assays have become an established approach to drug discovery. Greater disease relevance is often achieved through cellular models with increased complexity and more detailed readouts, such as gene expression or advanced imaging. However, the intricate nature and cost of these assays impose limitations on their screening capacity, often restricting screens to well-characterized small compound sets such as chemogenomics libraries. Here, we outline a cheminformatics approach to identify a small set of compounds with likely novel mechanisms of action (MoAs), expanding the MoA search space for throughput limited phenotypic assays. Our approach is based on mining existing large-scale, phenotypic high-throughput screening (HTS) data. It enables the identification of chemotypes that exhibit selectivity across multiple cell-based assays, which are characterized by persistent and broad structure activity relationships (SAR). We validate the effectiveness of our approach in broad cellular profiling assays (Cell Painting, DRUG-seq, and Promotor Signature Profiling) and chemical proteomics experiments. These experiments revealed that the compounds behave similarly to known chemogenetic libraries, but with a notable bias toward novel protein targets. To foster collaboration and advance research in this area, we have curated a public set of such compounds based on the PubChem BioAssay dataset and made it available for use by the scientific community.

Exploring the mechanism of contact-dependent cell-cell communication on chemosensitivity based on single-cell high-throughput drug screening platform.

High-throughput drug screening (HTDS) has significantly reduced the time and cost of new drug development. Nonetheless, contact-dependent cell-cell communication (CDCCC) may impact the chemosensitivity of tumour cells. There is a pressing need for low-cost single-cell HTDS platforms, alongside a deep comprehension of the mechanisms by which CDCCC affects drug efficacy, to fully unveil the efficacy of anticancer drugs. In this study, we develop a microfluidic chip for single-cell HTDS and evaluate the molecular mechanisms impacted by CDCCC using quantitative mass spectrometry-based proteomics. The chip achieves high-quality drug mixing and single-cell capture, with single-cell drug screening results on the chip showing consistency with those on the 96-well plates under varying concentration gradients. Through quantitative proteomic analysis, we deduce that the absence of CDCCC in single tumour cells can enhance their chemoresistance potential, but simultaneously subject them to stronger proliferation inhibition. Additionally, pathway enrichment analysis suggests that CDCCC could impact several signalling pathways in tumour single cells that regulate vital biological processes such as tumour proliferation, adhesion, and invasion. These results offer valuable insights into the potential connection between CDCCC and the chemosensitivity of tumour cells. This research paves the way for the development of single-cell HTDC platforms and holds the promise of advancing tumour personalized treatment strategies.

C. elegans: a prominent platform for modeling and drug screening in neurological disorders.

INTRODUCTION: Human neurodevelopmental and neurodegenerative diseases (NDevDs and NDegDs, respectively) encompass a broad spectrum of disorders affecting the nervous system with an increasing incidence. In this context, the nematode C. elegans, has emerged as a benchmark model for biological research, especially in the field of neuroscience. AREAS COVERED: The authors highlight the numerous advantages of this tiny worm as a model for exploring nervous system pathologies and as a platform for drug discovery. There is a particular focus given to describing the existing models of C. elegans for the study of NDevDs and NDegDs. Specifically, the authors underscore their strong applicability in preclinical drug development. Furthermore, they place particular emphasis on detailing the common techniques employed to explore the nervous system in both healthy and diseased states. EXPERT OPINION: Drug discovery constitutes a long and expensive process. The incorporation of invertebrate models, such as C. elegans, stands as an exemplary strategy for mitigating costs and expediting timelines. The utilization of C. elegans as a platform to replicate nervous system pathologies and conduct high-throughput automated assays in the initial phases of drug discovery is pivotal for rendering therapeutic options more attainable and cost-effective.

Using automated patch clamp electrophysiology platforms in ion channel drug discovery: an industry perspective.

INTRODUCTION: Automated patch clamp (APC) is now well established as a mature technology for ion channel drug discovery in academia, biotech and pharma companies, and in contract research organizations (CRO), for a variety of applications including channelopathy research, compound screening, target validation and cardiac safety testing. AREAS COVERED: Ion channels are an important class of drugged and approved drug targets. The authors present a review of the current state of ion channel drug discovery along with new and exciting developments in ion channel research involving APC. This includes topics such as native and iPSC-derived cells in ion channel drug discovery, channelopathy research, organellar and biologics in ion channel drug discovery. EXPERT OPINION: It is our belief that APC will continue to play a critical role in ion channel drug discovery, not only in 'classical' hit screening, target validation and cardiac safety testing, but extending these applications to include high throughput organellar recordings and optogenetics. In this way, with advancements in APC capabilities and applications, together with high resolution cryo-EM structures, ion channel drug discovery will be re-invigorated, leading to a growing list of ion channel ligands in clinical development.

Expanding the flexibility of base editing for high-throughput genetic screens in bacteria.

Genome-wide screens have become powerful tools for elucidating genotype-to-phenotype relationships in bacteria. Of the varying techniques to achieve knockout and knockdown, CRISPR base editors are emerging as promising options. However, the limited number of available, efficient target sites hampers their use for high-throughput screening. Here, we make multiple advances to enable flexible base editing as part of high-throughput genetic screening in bacteria. We first co-opt the Streptococcus canis Cas9 that exhibits more flexible protospacer-adjacent motif recognition than the traditional Streptococcus pyogenes Cas9. We then expand beyond introducing premature stop codons by mutating start codons. Next, we derive guide design rules by applying machine learning to an essentiality screen conducted in Escherichia coli. Finally, we rescue poorly edited sites by combining base editing with Cas9-induced cleavage of unedited cells, thereby enriching for intended edits. The efficiency of this dual system was validated through a conditional essentiality screen based on growth in minimal media. Overall, expanding the scope of genome-wide knockout screens with base editors could further facilitate the investigation of new gene functions and interactions in bacteria.

Open microfluidics: droplet microarrays as next generation multiwell plates for high throughput screening.

Multiwell plates are prominent in the biological and chemical sciences; however, they face limitations in terms of throughput and deployment in emerging bioengineering fields. Droplet microarrays, as an open microfluidic technology, organise tiny droplets typically in the order of thousands, on an accessible plate. In this perspective, we summarise current approaches for generating droplets, fluid handling on them, and analysis within droplet microarrays. By enabling unique plate engineering opportunities, demonstrating the necessary experimental procedures required for manipulating and interacting with biological cells, and integrating with label-free analytical techniques, droplet microarrays can be deployed across a more extensive experimental domain than what is currently covered by multiwell plates. Droplet microarrays thus offer a solution to the bottlenecks associated with multiwell plates, particularly in the areas of biological cultivation and high-throughput compound screening.

A sensitive and scalable fluorescence anisotropy single stranded RNA targeting approach for monitoring riboswitch conformational states.

The capacity of riboswitches to undergo conformational changes in response to binding their native ligands is closely tied to their functional roles and is an attractive target for antimicrobial drug design. Here, we established a probe-based fluorescence anisotropy assay to monitor riboswitch conformational switching with high sensitivity and throughput. Using the Bacillus subtillis yitJ S-Box (SAM-I), Fusobacterium nucleatum impX RFN element of (FMN) and class-I cyclic-di-GMP from Vibrio cholerae riboswitches as model systems, we developed short fluorescent DNA probes that specifically recognize either ligand-free or -bound riboswitch conformational states. We showed that increasing concentrations of native ligands cause measurable and reproducible changes in fluorescence anisotropy that correlate with riboswitch conformational changes observed by native gel analysis. Furthermore, we applied our assay to several ligand analogues and confirmed that it can discriminate between ligands that bind, triggering the native conformational change, from those that bind without causing the conformational change. This new platform opens the possibility of high-throughput screening compound libraries to identify potential new antibiotics that specifically target functional conformational changes in riboswitches.

High-Throughput Screening Techniques for the Selection of Thermostable Enzymes.

The acquisition of a thermostable enzyme is an indispensable prerequisite for its successful implementation in industrial applications and the development of novel functionalities. Various protein engineering approaches, including rational design, semirational design, and directed evolution, have been employed to enhance thermostability. However, all of these approaches require sensitive and reliable high-throughput screening (HTS) technologies to efficiently and rapidly identify variants with improved properties. While numerous reviews focus on modification strategies for enhancing enzyme thermostability, there is a dearth of literature reviewing HTS methods specifically aimed at this objective. Herein, we present a comprehensive overview of various HTS methods utilized for modifying enzyme thermostability across different screening platforms. Additionally, we highlight significant recent examples that demonstrate the successful application of these methods. Furthermore, we address the technical challenges associated with HTS technologies used for screening thermostable enzyme variants and discuss valuable perspectives to promote further advancements in this field. This review serves as an authoritative reference source offering theoretical support for selecting appropriate screening strategies tailored to specific enzymes with the aim of improving their thermostability.

Nucleic acid hybridization-based detection of pathogenic RNA using microscale thermophoresis.

Infectious diseases are one of the world's leading causes of morbidity. Their rapid spread emphasizes the need for accurate and fast diagnostic methods for large-scale screening. Here, we describe a robust method for the detection of pathogens based on microscale thermophoresis (MST). The method involves the hybridization of a fluorescently labeled DNA probe to a target RNA and the assessment of thermophoretic migration of the resulting complex in solution within a 2 to 30-time window. We found that the thermophoretic migration of the nucleic acid-based probes is primarily determined by the fluorescent molecule used, rather than the nucleic acid sequence of the probe. Furthermore, a panel of uniformly labeled probes that bind to the same target RNA yields a more responsive detection pattern than a single probe, and moreover, can be used for the detection of specific pathogen variants. In addition, intercalating agents (ICA) can be used to alter migration directionality to improve detection sensitivity and resolving power by several orders of magnitude. We show that this approach can rapidly diagnose viral SARS-CoV2, influenza H1N1, artificial pathogen targets, and bacterial infections. Furthermore, it can be used for anti-microbial resistance testing within 2 h, demonstrating its diagnostic potential for early pathogen detection.

High-throughput screening for aroma production in food fermentations.

A microtiter plate (MTP) method was developed to screen 1064 unique microorganisms-substrate fermentations for production of 68 target aroma compounds. Based on the number of hits identified by GC-MS, 50 fermentations were repeated at 50-mL scale in flasks. Comparison of GC-MS data showed that scaling up from MTP to flask did not generally result in large differences between the volatile profiles, even with a wide variety of substrates (juice, food slurry and food side-streams) and microorganisms (yeast, bacteria and fungi) used. From the screening results, Lactobacillus plantarum fermentation of chilli pepper was further studied as a high amount of phenols, especially guaiacol and 4-ethylphenol, was produced after fermentation. From HPLC-MS and sensory analysis, capsaicin was shown to be a probable precursor for these phenols and a potential mechanism was proposed. The protocol described herein to screen aroma compounds from fermentation of agri-food products and side streams can support development of clean label flavourful food ingredients.