High-throughput Screening Research Articles

Aptamer-based assay for high-throughput substrate profiling of RNA decapping enzymes.

Recent years have led to the identification of a number of enzymes responsible for RNA decapping. This has provided a basis for further research to identify their role, dependency and substrate specificity. However, the multiplicity of these enzymes and the complexity of their functions require advanced tools to study them. Here, we report a high-throughput fluorescence intensity assay based on RNA aptamers designed as substrates for decapping enzymes. Using a library of differently capped RNA probes we generated a decapping susceptibility heat map, which confirms previously reported substrate specificities of seven tested hydrolases and uncovers novel. We have also demonstrated the utility of our assay for evaluating inhibitors of viral decapping enzymes and performed kinetic studies of the decapping process. The assay may accelerate the characterization of new decapping enzymes, enable high-throughput screening of inhibitors and facilitate the development of molecular tools for a better understanding of RNA degradation pathways.

Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines.

In the rapidly evolving field of drug discovery, high-throughput screening (HTS) is essential for identifying bioactive compounds. This study introduces a novel application of data valuation, a concept for evaluating the importance of data points based on their impact, to enhance drug discovery pipelines. Our approach improves active learning for compound library screening, robustly identifies true and false positives in HTS data, and identifies important inactive samples in an imbalanced HTS training, all while accounting for computational efficiency. We demonstrate that importance-based methods enable more effective batch screening, reducing the need for extensive HTS. Machine learning models accurately differentiate true biological activity from assay artifacts, streamlining the drug discovery process. Additionally, importance undersampling aids in HTS data set balancing, improving machine learning performance without omitting crucial inactive samples. These advancements could significantly enhance the efficiency and accuracy of drug development.

An Automated Digital Microfluidic System Based on Inkjet Printing

Cellular interactions, such as intercellular communication and signal transduction, can be enhanced within three-dimensional cell spheroids, contributing significantly to cellular viability and proliferation. This is crucial for advancements in cancer research, drug testing, and personalized medicine. The dimensions of the cell spheroids play a pivotal role in their functionality, affecting cell proliferation and differentiation, intercellular interactions, gene expression, protein synthesis, drug penetration, and metabolism. Consequently, different spheroid sizes may be required for various drug sensitivity experiments. However, conventional 3D cell spheroid cultures suffer from challenges such as size inconsistency, poor uniformity, and low throughput. To address these issues, we have developed an automated, intelligent system based on inkjet printing. This system allows for precise control of droplet volume by adjusting algorithms, thereby enabling the formation of spheroids of varying sizes. For spheroids of a single size, the printing pattern can be modified to achieve a coefficient of variation within 10% through a bidirectional compensation method. Furthermore, the system is equipped with an automatic pipetting module, which facilitates the high-throughput preparation of cell spheroids. We have implemented a 3 × 3 spheroid array in a 24-well plate, printing a total of 216 spheroids in just 11 min. Last, we attempted to print mouse small intestinal organoids and cultured them for 7 days, followed by immunofluorescent staining experiments. The results indicate that our equipment is capable of supporting the culture of organoids, which is of great significance for high-throughput drug screening and personalized medicine.

Solanum pimpinellifolium exhibits complex genetic resistance to Pseudomonas syringae pv. tomato.

Pseudomonas syringae pv. tomato (Pst) is the causal agent of bacterial speck disease in tomatoes. The Pto/Prf gene cluster from Solanum pimpinellifolium was introgressed into several modern tomato cultivars and provided protection against Pst race 0 strains for many decades. However, virulent Pst race 1 strains that evade Pto-mediated immunity now predominate in tomato-growing regions worldwide. Here we report the identification of resistance to a Pst race 1 strain (Pst19) in the wild tomato accession S. pimpinellifolium LA1589 (hereafter LA1589), using our rapid high-throughput seedling screen. LA1589 supports less bacterial growth than cultivars, and does not exhibit a hypersensitive response to Pst19. We tested an existing set of 87 Inbred Backcross Lines (IBLs) derived from a cross between susceptible Solanum lycopersicum E-6203 and Solanum pimpinellifolium LA1589 for resistance to Pst19. Using single-marker analysis, we identified three genomic regions associated with resistance. Bacterial growth assays on IBLs confirmed that these regions contribute to resistance in planta. We also mapped candidate genes associated with resistance in a cross between the Solanum lycopersicum var. lycopersicum cultivar Heinz BG-1706 and S. pimpinellifolium LA1589. By comparing candidates from the two mapping approaches, we were able to identify 3 QTL and 5 candidate genes in LA1589 for a role in resistance to Pst19. This work will assist in molecular marker-assisted breeding to protect tomato from bacterial speck disease.

Enhancing the Predictive Power of Machine Learning Models through a Chemical Space Complementary DEL Screening Strategy.

DNA-encoded library (DEL) technology is an effective method for small molecule drug discovery, enabling high-throughput screening against target proteins. While DEL screening produces extensive data, it can reveal complex patterns not easily recognized by human analysis. Lead compounds from DEL screens often have higher molecular weights, posing challenges for drug development. This study refines traditional DELs by integrating alternative techniques like photocross-linking screening to enhance chemical diversity. Combining these methods improved predictive performance for small molecule identification models. Using this approach, we predicted active small molecules for BRD4 and p300, achieving hit rates of 26.7 and 35.7%. Notably, the identified compounds exhibit smaller molecular weights and better modification potential compared to traditional DEL molecules. This research demonstrates the synergy between DEL and AI technologies, enhancing drug discovery.

Identification of human pregnane X receptor antagonists utilizing a high-throughput screening platform.

Pregnane X receptor (PXR) is a xenobiotic-sensing nuclear receptor with a well-established role in regulating drug metabolism and clearance. Recent studies have shown that PXR is involved in cell proliferation, apoptosis, immune response, and energy homeostasis. It is important to identify compounds that may modulate PXR activity to prevent drug-drug interactions, distinguish chemicals which could potentially generate toxicity, and identify compounds for further development towards therapeutic usage. In this study, we have screened the National Center for Advancing Translational Sciences (NCATS) Pharmacologically Active Chemical Toolbox (NPACT) library, which consists of 5,099 unique pharmacologically active synthetic and naturally derived small molecules to identify PXR antagonists. Ninety-four compounds were identified as potential PXR antagonists through a primary screen and 66 were confirmed in a confirmation study. Of these compounds, twenty potential PXR antagonists, including gamma-secretase modulator 2 (GSM2) and fusidic acid, were selected for further study based on their efficacy, potency, and novelty. Their PXR inhibition abilities were assessed by examining their effects on cytrochrome P450 (CYP) 3A4 mRNA expression using metabolically competent HepaRG cells. Additionally, a pharmacological inhibition assay using various concentrations of rifampicin as a stimulator was performed in HepG2-CYP3A4-hPXR cells to confirm the activity of the 20 selected compounds against PXR. Finally, HepaRG cells were used to confirm PXR antagonism by verification of a concentration-dependent decrease of CYP3A4 when co-treated with the known PXR agonist, rifampicin. Additionally, the potent actives were further investigated using molecular docking to find the potential interactions of the novel ligands with the active sites of hPXR. To our knowledge from the current study, GSM2 and fusidic acid have been identified as novel PXR antagonists, which provides useful information for further investigation regarding possible drug-drug interactions, as well as the detection of potential therapeutic effects or other toxic consequences.

Diatomic Active Sites Embedded Graphyne as Electrocatalysts for Ammonia Synthesis.

Ammonia (NH3) is a vital chemical compound in industry and agriculture, and the electrochemical nitrogen reduction reaction (eNRR) is considered a promising approach for NH3 synthesis. However, the development of eNRR faces the challenge of high overpotential and low Faradaic efficiency. In this work, graphyne (GY) is anchored by 3d, 4d, and 5d dual transition metal atoms to form diatomic catalysts (DACs) and is roundly investigated as an electrocatalyst for eNRR via density functional theory calculations. Due to the protrusion of anchored metal atoms, the active sites of GY are better exposed compared to other substrates, exhibiting higher activity. Through four-step hierarchical high-throughput screening (ΔG*N2 < 0 eV, ΔG*N2→*N2H < 0.4 eV, ΔG*NH2→*NH3 < 0.4 eV, and ΔG*N2 < ΔG*H), the number of selected catalysts in each step is 325, 240, 145, and 20, respectively. Considering a series of factors, including stability, initial potential, and selectivity, 13 kinds of eligible catalysts are identified. Optimal eNRR paths studies show that the best catalyst Mn2@GY features no onset potential. For the three catalysts (Mn2@GY, Ir2@GY, and RhOs@GY), the onset potentials of the most favorable eNRR pathways are -0.07, -0.12, and -0.17 V, respectively. The excellent catalytic activity can be credited to the effective charge transfer and orbital interaction between the active site and adsorbed N2. Our work demonstrates the significance of DACs for ammonia synthesis and provides a paradigm for the study of DACs even for other important reactions.

Structure-Guided Discovery of Selective USP7 Inhibitors with In Vivo Activity.

Inhibition of ubiquitin-specific protease 7, USP7, has been proposed as a mechanism to affect many disease processes, primarily those implicated in oncology. The bound crystal structure of a published high-throughput screening hit with low-micromolar affinity for USP7 identified three regions of the compound for structure-guided optimization. Replacing one side of the compound with different aromatic moieties gave little improvement in affinity, and the central piperidine could not be improved. However, the binding site for the other side of the compound was poorly defined in the crystal structure, which suggested a wide variety of synthetically accessible options for optimization. These were assessed by screening reaction mixtures that introduced different substituents to this other side. Subsequent optimization led to a compound with low-nanomolar affinity for USP7, which showed target engagement in tumors, was tolerated in mice, and showed efficacy in xenograft models.

High-Throughput Discovery of Synthetic Siderophores for Trojan Horse Antibiotics.

To cause infection, bacterial pathogens must overcome host immune factors and barriers to nutrient acquisition. Reproducing these aspects of host physiology in vitro has shown great promise for antibacterial drug discovery. When used as a bacterial growth medium, human serum replicates several aspects of the host environment, including innate immunity and iron limitation. We previously reported that a high-throughput chemical screen using serum as the growth medium enabled the discovery of novel growth inhibitors overlooked by conventional screens. Here, we report that a subset of compounds from this high-throughput serum screen display an unexpected growth enhancing phenotype and are enriched for synthetic siderophores. We selected 35 compounds of diverse chemical structure and quantified their ability to enhance bacterial growth in human serum. We show that many of these compounds chelate iron, suggesting they were acting as siderophores and providing iron to the bacteria. For two different pharmacophores represented among these synthetic siderophores, conjugation to the β-lactam antibiotic ampicillin imparted iron-dependent enhancement in antibacterial activity. Conjugation of the most potent growth-enhancing synthetic siderophore with the monobactam aztreonam produced MLEB-22043, a broad-spectrum antibiotic with significantly improved activity against Klebsiella pneumoniae, Escherichia coli, Acinetobacter baumannii, and Pseudomonas aeruginosa. This synthetic siderophore-monobactam conjugate uses multiple TonB-dependent transporters for uptake into P. aeruginosa. Like aztreonam, MLEB-22043 demonstrated activity against metallo-β-lactamase expressing bacteria, and, when combined with the β-lactamase inhibitor avibactam, was active against clinical strains coexpressing the NDM-1 metallo-β-lactamase and serine β-lactamases. Our work shows that human serum is an effective bacterial growth medium for the high-throughput discovery of synthetic siderophores, enabling the development of novel Trojan Horse antibiotics.

Unveiling the Human Brain on a Chip: An Odyssey to Reconstitute Neuronal Ensembles and Explore Plausible Applications in Neuroscience.

The brain is an incredibly complex structure that consists of millions of neural networks. In developmental and cellular neuroscience, probing the highly complex dynamics of the brain remains a challenge. Furthermore, deciphering how several cues can influence neuronal growth and its interactions with different brain cell types (such as astrocytes and microglia) is also a formidable task. Traditional in vitro macroscopic cell culture techniques offer simple and straightforward methods. However, they often fall short of providing insights into the complex phenomena of neuronal network formation and the relevant microenvironments. To circumvent the drawbacks of conventional cell culture methods, recent advancements in the development of microfluidic device-based microplatforms have emerged as promising alternatives. Microfluidic devices enable precise spatiotemporal control over compartmentalized cell cultures. This feature facilitates researchers in reconstituting the intricacies of the neuronal cytoarchitecture within a regulated environment. Therefore, in this review, we focus primarily on modeling neuronal development in a microfluidic device and the various strategies that researchers have adopted to mimic neurogenesis on a chip. Additionally, we have presented an overview of the application of brain-on-chip models for the recapitulation of the blood-brain barrier and neurodegenerative diseases, followed by subsequent high-throughput drug screening. These lab-on-a-chip technologies have tremendous potential to mimic the brain on a chip, providing valuable insights into fundamental brain processes. The brain-on-chip models will also serve as innovative platforms for developing novel neurotherapeutics to address several neurological disorders.

CRISPR-GRIT: Guide RNAs with Integrated Repair Templates Enable Precise Multiplexed Genome Editing in the Diploid Fungal Pathogen Candida albicans.

Candida albicans, an opportunistic fungal pathogen, causes severe infections in immunocompromised individuals. Limited classes and overuse of current antifungals have led to the rapid emergence of antifungal resistance. Thus, there is an urgent need to understand fungal pathogen genetics to develop new antifungal strategies. Genetic manipulation of C. albicans is encumbered by its diploid chromosomes requiring editing both alleles to elucidate gene function. Although the recent development of CRISPR-Cas systems has facilitated genome editing in C. albicans, large-scale and multiplexed functional genomic studies are still hindered by the necessity of cotransforming repair templates for homozygous knockouts. Here, we present CRISPR-GRIT (Guide RNAs with Integrated Repair Templates), a repair template-integrated guide RNA design for expedited gene knockouts and multiplexed gene editing in C. albicans. We envision that this method can be used for high-throughput library screens and identification of synthetic lethal pairs in both C. albicans and other diploid organisms with strong homologous recombination machinery.

Computationally Driven Discovery and Characterization of SIRT3-Activating Compounds that Fully Recover Catalytic Activity under NAD+ Depletion

Many chronic, age-related disorders could be mitigated by enhancing the activity of enzymes that regulate biochemical signaling pathways, but all known modes of enzyme activation rely on allosteric binding sites, which have only been identified in less than 10% of proteins. Sirtuins (SIRT1-7) are nicotinamide adenine dinucleotide (NAD+)-dependent deacylases playing critical roles in lifespan and age-related diseases. The physiological importance of sirtuins and the reduction in their catalytic activity with the age-related decline in NAD+ levels have stimulated intense interest in designing sirtuin-activating compounds; however, except for substrate-specific allosteric SIRT1 activators, methodologies for rational design of sirtuin-activating compounds are lacking. Here, we introduce methods for the activation of such enzymes that do not rely on allosteric binding sites, and we demonstrate their successful application to the discovery of first-in-class activators of sirtuin enzymes. We establish how all-atom simulations of an enzyme’s active site under the potential of a small molecule modulator can be used to identify molecular properties that achieve desired changes in local enzyme conformational degrees of freedom conducive to the enhancement of catalytic activity. We apply computational high-throughput screening based on this biophysical model for activation of sirtuin enzymes to the major mitochondrial sirtuin SIRT3, which plays a critical role in age-related disorders but does not have a known allosteric site; we thereby identify first-in-class, nonallosteric activators of this enzyme. These compounds are the first reported steady-state activators of the major mitochondrial sirtuin enzyme, and they operate according to a mode of action not shared by any existing drug. Two such compounds can almost double the catalytic efficiency of SIRT3 with respect to NAD+, thus compensating for the loss in SIRT3 activity that occurs due to the age-related decline in NAD+, and they may be developed for therapeutic applications to combat multiple types of age-related disorders. These discoveries establish a foundation for the development of a new class of drugs that function through the activation of enzymes by modulation of local conformational ensembles. Published by the American Physical Society 2024

Identification and functional characterization of lncRNAs involved in human monocyte-to-macrophage differentiation

ABSTRACT Although long noncoding RNAs (lncRNAs) constitute the majority of the human transcriptome, the functional roles of most remain elusive. While protein-coding genes in macrophage biology have been extensively studied, the contribution of lncRNAs in this context is poorly understood. Given the vast number of lncRNAs (>20,000), identifying candidates for functional characterization poses a significant challenge. Here, we present two complementary approaches to pinpoint and investigate lncRNAs involved in monocyte-to-macrophage differentiation: RNA-seq for functional inference and a high-throughput functional screen. These strategies enabled us to identify four lncRNA regulators of monocyte differentiation: lincRNA-JADE1, lincRNA-ANXA3, GATA2-AS1, and PPP2R5C-AS1. Preliminary insights suggest these lncRNAs may act in cis through neighbouring protein-coding genes, although their precise mechanisms remain to be elucidated. We further discuss the strengths and weaknesses of these methodologies, along with validation pipelines crucial for establishing lncRNA functionality.

High-Throughput Algorithmic Optimization of In Vitro Transcription for SARS-CoV-2 mRNA Vaccine Production.

The in vitro transcription (IVT) of messenger ribonucleic acid (mRNA) from the linearized deoxyribonucleic acid (DNA) template of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant (B.1.617.2) was optimized for total mRNA yield and purity (by percent intact mRNA) utilizing machine learning in conjunction with automated, high-throughput liquid handling technology. An iterative Bayesian optimization approach successfully optimized 11 critical process parameters in 42 reactions across 5 experimental rounds. Once the optimized conditions were achieved, an automated, high-throughput screen was conducted to evaluate commercially available T7 RNA polymerases for rate and quality of mRNA production. Final conditions showed a 12% yield improvement and a 50% reduction in reaction time, while simultaneously significantly decreasing (up to 44% reduction) the use of expensive reagents. This novel platform offers a powerful new approach for optimizing IVT reactions for mRNA production.

Three-dimensional silk fibroin scaffolded co-culture of human neuroblastoma and innate immune cells

Neuroblastoma (NB) is the most common pediatric extracranial solid tumor. It accounts for 50 % of cancers diagnosed in infants less than 1 year old, and 10 % of all pediatric cancer deaths in the United States. High-risk patients have a less than 50 % 5-year survival rate with current treatment strategies. The complex tumor microenvironment of NB makes the development of treatment strategies for high-risk patients challenging. There is increasing evidence that intratumoral immune suppression plays an important role in the progression and invasion of NB tumors. Few three-dimensional (3D) cancer models include components of the innate immune system. This work develops a preclinical 3D NB-immune co-culture model using SK-N-AS NB cells, NK-92 natural killer cells, and THP-1 derived macrophages, co-cultured on porous 3D silk scaffolds to provide tumor architecture. Conditioned media and indirect co-culturing showed changes in SK-N-AS gene expression associated with immunoregulatory signaling, and changes in NK-92 gene expression that are associated with reduced cytotoxicity. This motivated the development of a 3D direct co-culture system in which NB cells were seeded prior to immune cells to allow incorporation and deposition of extracellular matrix within the construct. Immune cells were then incorporated into the model to achieve direct co-culture with SK-N-AS cells. Changes in THP-1 macrophage polarization toward a more M2-like phenotype were observed in 3D direct co-culture, as well as altered NK-92 cell protein secretion and cytotoxic activity. Preliminary testing of immunotherapeutics within the model was conducted on both NB-macrophage and NB-NK co-cultures, but the model demonstrated limited response to immunotherapeutics. This work lays the foundation for building high-throughput therapeutic screening models for the improved treatment NB and other solid tumors.

High-resolution acoustic ejection mass spectrometry for high-throughput library screening

An approach is described for high-throughput quality assessment of drug candidate libraries using high-resolution acoustic ejection mass spectrometry (AEMS). Sample introduction from 1536-well plates is demonstrated for this application using 2.5 nL acoustically dispensed sample droplets into an Open Port Interface (OPI) with pneumatically assisted electrospray ionization at a rate of one second per sample. Both positive and negative ionization are shown to be essential to extend the compound coverage of this protease inhibitor-focused library. Specialized software for efficiently interpreting this data in 1536-well format is presented. A new high-throughput method for quantifying the concentration of the components (HTQuant) is proposed that neither requires adding an internal standard to each well nor further encumbers the high-throughput workflow. This approach for quantitation requires highly reproducible peak areas, which is shown to be consistent within 4.4 % CV for a 1536-well plate analysis. An approach for troubleshooting the workflow based on the background ion current signal is also presented. The AEMS data is compared to the industry standard LC/PDA/ELSD/MS approach and shows similar coverage but at 180-fold greater throughput. Despite the same ionization process, both methods confirmed the presence of a small percentage of compounds in wells that the other did not. The data for this relatively small, focused library is compared to a larger, more chemically diverse library to indicate that this approach can be more generally applied beyond this single case study. This capability is particularly timely considering the growing implementation of artificial intelligence strategies that require the input of large amounts of high-quality data to formulate predictions relevant to the drug discovery process. The molecular structures of the 872-compound library analyzed here are included to begin the process of correlating molecular structures with ionization efficiency and other parameters as an initial step in this direction.

CRISPR associated enzymes are mislocalized to the cytoplasm in iPSC-derived neurons resulting in KRAB-specific degradation.

The use of CRISPR-associated enzymes in iPSC-derived neurons for precise gene targeting and high-throughput gene perturbation screens offers great potential but presents unique challenges compared to dividing cell lines. CRISPRi screens in iPSC-derived neurons and glia have already been successful in relating gene function to neurological phenotypes; however, loss of dCas9-KRAB expression after differentiation has been observed by many labs and has been largely ascribed to transgene silencing after differentiation. Here, we investigated the expression levels of different CRISPR enzymes in iPSC and Ngn2-derived neurons using piggybac delivery. We found that the commonly used dCas9-KRAB (using the KOX1 domain) displayed dramatic reduction in protein expression levels following neuronal differentiation, yet surprisingly, nCas9 constructs retained comparable protein expression between iPSCs and neurons. We further found that CRISPR constructs, primarily relying on the SV40 Nuclear Localization Signal (NLS), fail to efficiently localize to the nuclei of neurons, despite having robust nuclear levels in iPSCs, leading to KRAB-specific cytoplasmic degradation. By adding a neuronal-specific NLS, we were able to correct neuronal nuclear localization and protein expression, confirming the contribution of mislocalization to the instability of dCas9-KRAB in neurons. As the lack of nuclear localization can have a profound impact on editing and gene perturbation efficiency, we suggest further investigation across both cultured and in-vivo postmitotic cell models.

Use of Proximity Ligation Assay to Study Lymphoid Malignancies.

The advent of high-throughput and unbiased proteogenomic screens promises to rapidly advance our understanding of the molecular mechanisms underpinning pathogenesis of lymphoid malignancies. The wealth of data generated from these studies requires methods to rapidly confirm and extend findings into cell line models and primary patient samples. The proximity ligation assay (PLA) is a method that can visualize protein-protein interactions in situ. PLA can capture transient interactions and characterize constituents of stable biomolecular condensates, both of which pose technical difficulties for traditional biochemical and fluorescence imaging techniques.

High-throughput screening of halide solid-state electrolytes for all-solid-state Li-ion batteries through structural descriptor

All-solid-state Li-ion batteries (ASSLIBs) have attracted great attention due to their intrinsic safety and high potential energy density. To realize ASSLIBs, the development of solid-state electrolytes (SSEs) with favorable electrochemical stability and high Li-ion conductivity is of utmost significance. Compared to trial-and-error searches, theoretical computation-based methods are recognized as a powerful tool for accelerating the exploration of SSEs. However, the development of appropriate descriptors is often the first hurdle toward implementing accurate and meaningful screening process. Here we quantified the structural properties pertaining to low Li-ion migration barriers and performed a high-throughput screening of 3119 Li-containing halides obtained from the Materials Project (MP) database to search for promising SSEs. After excluding previously reported SSEs, three candidate materials, Li4ZrF8, Li3ErBr6, and Li2ZnI4 with crystal structure exhibiting 3D diffusion pathway were obtained. Subsequent theoretical calculations of these materials were performed to evaluate their thermodynamic stability, chemical/electrochemical stability, and ionic conductivity. The three halide materials appeared to be promising SSE candidates due to their robust thermodynamical stability against cathodes, and high ionic conductivity. This research provides a new insight and a systematic quantitative understanding of the relationship between the structural properties and Li-ion migration barriers, which can motivate future computational studies on new fast-ion conductors and accelerate the discovery of high ionic conductivity SSEs for the use in ASSLIBs.

Versatile Dual Reporter to Identify Ribosome Pausing Motifs Alleviated by Translation Elongation Factor P.

Protein synthesis is influenced by the chemical and structural properties of the amino acids incorporated into the polypeptide chain. Motifs containing consecutive prolines can slow the translation speed and cause ribosome stalling. Translation elongation factor P (EF-P) facilitates peptide bond formation in these motifs, thereby alleviating stalled ribosomes and restoring the regular translational speed. Ribosome pausing at various polyproline motifs has been intensively studied using a range of sophisticated techniques, including ribosome profiling, proteomics, and in vivo screening, with reporters incorporated into the chromosome. However, the full spectrum of motifs that cause translational pausing in Escherichia coli has not yet been identified. Here, we describe a plasmid-based dual reporter for rapid assessment of pausing motifs. This reporter contains two coupled genes encoding mScarlet-I and chloramphenicol acetyltransferase to screen motif libraries based on both bacterial fluorescence and survival. In combination with a diprolyl motif library, we used this reporter to reveal motifs of different pausing strengths in an E. coli strain lacking efp. Subsequently, we used the reporter for a high-throughput screen of four motif libraries, with and without prolines at different positions, sorted by fluorescence-associated cell sorting (FACS) and identify new motifs that influence the translational efficiency of the fluorophore. Our study provides an in vivo platform for rapid screening of amino acid motifs that affect translational efficiencies.