ACE configurator for ELISpot: optimizing combinatorial design of pooled ELISpot assays with an epitope similarity model

The enzyme-linked immunosorbent spot (ELISpot) assay is a powerful in vitro immunoassay that enables cost-effective quantification of antigen-specific T-cell reactivity. It is used widely in the context of cancer and infectious diseases to validate the immunogenicity of predicted epitopes. While technological advances have kept pace with the demand for increased throughput, efforts to increase scale are bottlenecked by current assay design and deconvolution methods, which have remained largely unchanged. Current methods for designing pooled ELISpot experiments offer limited flexibility of assay parameters, lack support for high-throughput scenarios and do not consider peptide identity during pool assignment. We introduce the ACE Configurator for ELISpot (ACE) to address these gaps. ACE generates optimized peptide-pool assignments from highly customizable user inputs and handles the deconvolution of positive peptides using assay readouts. In this study, we present a novel sequence-aware pooling strategy, powered by a fine-tuned ESM-2 model that groups immunologically similar peptides, reducing the number of false positives and subsequent confirmatory assays compared to existing combinatorial approaches. To validate ACE's performance on real-world datasets, we conducted a comprehensive benchmark study, contextualizing design choices with their impact on prediction quality. Our results demonstrate ACE's capacity to further increase precision of identified immunogenic peptides, directly optimizing experimental efficiency. ACE is freely available as an executable with a graphical user interface and command-line interfaces at https://github.com/pirl-unc/ace.

Cross-Platform Bayesian Optimization System for Autonomous Biological Assay Development

Current high-throughput screening assay optimization is often a manual and time-consuming process, even when utilizing design-of-experiment approaches. A cross-platform, Cloud-based Bayesian optimization-based algorithm was developed as part of the National Center for Advancing Translational Sciences (NCATS) ASPIRE (A Specialized Platform for Innovative Research Exploration) Initiative to accelerate preclinical drug discovery. A cell-free assay for papain enzymatic activity was used as proof of concept for biological assay development and system operationalization. Compared with a brute-force approach that sequentially tested all 294 assay conditions to find the global optimum, the Bayesian optimization algorithm could find suitable conditions for optimal assay performance by testing 21 assay conditions on average, with up to 20 conditions being tested simultaneously, as confirmed by repeated simulation. The algorithm could achieve a sevenfold reduction in costs for lab supplies and high-throughput experimentation runtime, all while being controlled from a remote site through a secure connection. Based on this proof of concept, this technology is expected to be applied to more complex biological assays and automated chemistry reaction screening at NCATS, and should be transferable to other institutions.

Effective optimization of SARS-CoV-2 laboratory testing variables in an era of supply chain constraints

RT-PCR-based assays for the detection of SARS-CoV-2 have played an essential role in the current COVID-19 pandemic. However, the sample collection and test reagents are in short supply, primarily due to supply chain issues. Thus, to eliminate testing constraints, we have optimized three key process variables: RNA extraction and RT-PCR reactions, different sample types and media to facilitate SARS-CoV-2 testing. By performing various validation and bridging studies, we have shown that various sample types such as nasopharyngeal swab, bronchioalveolar lavage and saliva, collected using conventional nasopharyngeal swabs, ESwab or 3D-printed swabs and, preserved in viral transport media, universal transport media, 0.9% sodium chloride or Amies media are compatible with RT-PCR assay for COVID-19. Besides, the reduction of PCR reagents by up to fourfold also produces reliable results.

Protocol Improvement for RNA Extraction From Compromised Frozen Specimens Generated in Austere Conditions: A Path Forward to Transcriptomics-Pathology Systems Integration

At the heart of the phenome-to-genome approach is high throughput assays, which are liable to produce false results. This risk can be mitigated by minimizing the sample bias, specifically, recycling the same tissue specimen for both phenotypic and genotypic investigations. Therefore, our aim is to suggest a methodology of obtaining robust results from frozen specimens of compromised quality, particularly if the sample is produced in conditions with limited resources. For example, generating samples at the International Space Station (ISS) is challenging because the time and laboratory footprint allotted to a project can get expensive. In an effort to be economical with available resources, snap-frozen euthanized mice are the straightforward solution; however, this method increases the risk of temperature abuse during the thawing process at the beginning of the tissue collection. We found that prolonged immersion of snap frozen mouse carcass in 10% neutral buffered formalin at 4°C yielded minimal microscopic signs of ice crystallization and delivered tissues with histomorphology that is optimal for hematoxylin and eosin (H&E) staining and fixation on glass slides. We further optimized a method to sequester the tissue specimen from the H&E slides using an incubator shaker. Using this method, we were able to recover an optimal amount of RNA that could be used for downstream transcriptomics assays. Overall, we demonstrated a protocol that enables us to maximize scientific values from tissues collected in austere condition. Furthermore, our protocol can suggest an improvement in the spatial resolution of transcriptomic assays.

A General Guide for the Optimization of Enzyme Assay Conditions Using the Design of Experiments Approach

Many factors must be considered during the optimization of an enzyme assay. These include the choice of buffer and its composition, the type of enzyme and its concentration, as well as the type of substrate and concentrations, the reaction conditions, and the appropriate assay technology. The process of an enzyme assay optimization, in our experience, can take more than 12 weeks using the traditional one-factor-at-a-time approach. In contrast, the design of experiments (DoE) approaches have the potential to speed up the assay optimization process and provide a more detailed evaluation of tested variables. However, not all researchers are aware of DoE approaches or believe that it is easy to employ a DoE approach for the optimization of an assay. In order to facilitate enzyme assay developers to use DoE methodologies, we present in detail the steps required to identify in less than 3 days (1) the factors that significantly affect the activity of an enzyme and (2) the optimal assay conditions using a fractional factorial approach and response surface methodology. This is exemplified with the optimization of assay conditions for the human rhinovirus-3C protease, and the methodology used could be employed as a basic guide for the speedy identification of the optimum assay conditions for any enzyme.

Evolution of proteomic biomarker for chronic liver disease: Promise into reality

Liver is the vital organ for synthesis of proteins whose concentration in blood reflects liver dysfunction. Variations in protein domain can generate clinically significant biomarkers. Biomarker pipeline includes discovery of candidates, qualification, verification, assay optimization, and validation. Advances in proteomic approach can discover protein biomarker candidates based on “up-or-down” regulation or fold change in expression which is correlated with disease state. Despite numerous biomarker candidates been discovered, only few are useful in clinical practice which indicates the need for well-established validation regimen. Hence, the main purpose of this review is to understand the protein biomarker development and pitfalls. Companion diagnostics provide insights into potential cost-effective diagnosis for chronic liver disease.

Flavones as Quorum Sensing Inhibitors Identified by a Newly Optimized Screening Platform Using Chromobacterium violaceum as Reporter Bacteria

Quorum sensing (QS) is the process by which bacteria produce and detect signal molecules to coordinate their collective behavior. This intercellular communication is a relevant target for anti-biofilm therapies. Here we have optimized a screening-applicable assay to search for new quorum sensing inhibitors from natural compound libraries. In this system, QS is correlated with the production of violacein, which is directly controlled by the LuxI/LuxR system in Chromobacterium violaceum ATCC 31532. The parallel use of C. violaceum Tn5-mutant CV026, which depends on auto-inducer addition, allows simultaneous discrimination of compounds that act as quenchers of the AHL signal (quorum quenchers). The incorporation of a redox stain into the platform allowed further distinction between QS inhibitors, quorum quenchers and antibacterial compounds. A pilot screening was performed with 465 natural and synthetic flavonoids. All the most active compounds were flavones and they displayed potencies (IC₅₀) in the range of 3.69 to 23.35 μM. These leads were particularly promising as they inhibited the transition from microcolonies into mature biofilms from Escherichia coli and Pseudomonas aeruginosa strains. This approach can be very effective in identifying new antimicrobials posing lesser risks of resistance.

Sensitive Detection of Cardiac Biomarkers Using a Magnetic Microbead Immunoassay

To achieve improved sensitivity in cardiac biomarker detection, a batch incubation magnetic microbead immunoassay was developed and tested on three separate human protein targets: myoglobin, heart-type fatty acid binding protein, and cardiac troponin I. A sandwich immunoassay was performed in a simple micro-centrifuge tube allowing full dispersal of the solid capture surface during incubations. Following magnetic bead capture and wash steps, samples were analyzed in the presence of a manipulated magnetic field utilizing a modified microscope slide and fluorescent inverted microscope to collect video data files. Analysis of the video data allowed for the quantitation of myoglobin, heart-type fatty acid binding protein and cardiac troponin I to levels of 360 aM, 67 fM, and 42 fM, respectively. Compared to the previous detection limit of 50 pM for myoglobin, this offers a five-fold improvement in sensitivity. This improvement in sensitivity and incorporation of additional markers, along with the small sample volumes required, suggest the potential of this platform for incorporation as a detection method in a total sample analysis device enabling multiplexed detection for the analysis of clinical samples.

Simultaneous assay of activated platelet count and platelet-activating capacity by P-selectin detection using K2-EDTA-treated whole blood for antiplatelet agents

INTRODUCTION

It is well recognized that examinations of activated platelets (aPLTs) and platelet-activating capacity are very important to observe and prevent embolic diseases (events) such as ischemic stroke and myocardial infarction. Previously, we reported an appropriate measurement technique of aPLT for clinical assay. In this paper, we investigated stable conditions for measurement of activating capacity of platelets.

METHODS

Blood samples were taken from healthy volunteers using anticoagulants of 2K-EDTA, sodium citrate and heparin, and platelets were stimulated with adenosine diphosphate (ADP) or collagen. We demonstrated platelet-activating capacity by detection of scattering light, absorbance, microscopic observation, and P-selectin (CD62P) expression. We also performed basic experiments in seven healthy volunteers to test the clinical application of these assays with monitoring aspirin therapy.

RESULTS

We judged that samples of whole blood with 2K-EDTA were suitable for CD62P expression assay as functional assessments of platelet activity, because platelets treated with anticoagulants such as sodium citrate and heparin were extremely damaged after stimulation, and it was difficult to measure the CD62P expression by flow cytometry. For optimal results, samples should be tested within 1 h after the drawing of blood and stimulated with ADP or collagen for 10 min. The CD62P-positive platelet value of blood from volunteers who had taken aspirin was decreased, and platelet activation was inhibited as well.

CONCLUSION

The simultaneous assay of aPLT and platelet-activating capacity by CD62P detection using whole blood treated with the K2-EDTA anticoagulant was useful for the monitoring of antiplatelet drugs.

Empirically optimized flow cytometric immunoassay validates ambient analyte theory

Ekins' ambient analyte theory predicts, counterintuitively, that an immunoassay's limit of detection can be improved by reducing the amount of capture antibody. In addition, it also anticipates that results should be insensitive to the volume of sample as well as the amount of capture antibody added. The objective of this study was to empirically validate all of the performance characteristics predicted by Ekins' theory. Flow cytometric analysis was used to detect binding between a fluorescent ligand and capture microparticles because it can directly measure fractional occupancy, the primary response variable in ambient analyte theory. After experimentally determining ambient analyte conditions, comparisons were carried out between ambient and nonambient assays in terms of their signal strengths, limits of detection, and sensitivity to variations in reaction volume and number of particles. The critical number of binding sites required for an assay to be in the ambient analyte region was estimated to be 0.1 VK(d). As predicted, such assays exhibited superior signal/noise levels and limits of detection and were not affected by variations in sample volume and number of binding sites. When the signal detected measures fractional occupancy, ambient analyte theory is an excellent guide to developing assays with superior performance characteristics.

The development, optimization and validation of an assay for high throughput antiviral drug screening against Dengue virus

Dengue virus (DENV) is listed as one of the NIAID Category A priority pathogens. Dengue disease is endemic in most tropical countries, with an estimated 2.5 billion people living in areas at risk of DENV infection. Due to the lack of vaccines and antiviral drugs, it is now a huge public health burden around the world. In order to screen large compound libraries for the identification of novel antivirals targeting DENV, it is essential to develop a high throughput screening (HTS) amenable assay. Here, we present the development, optimization and validation of a cytopathic effect-based assay against Dengue virus serotype-2 (DENV-2). The assay conditions, including cell culturing conditions, DMSO tolerance and the multiplicity of infection, were optimized in both 96- and 384-well plates. Assay robustness and reproducibility were determined under the optimized conditions in 96-well plate, including Z'-value of 0.71, signal-to-background ratio of 6.88, coefficient of variation of 6.3% in mock-infected cells and 12.3% in DENV-2 infected cells. This assay was further miniaturized into a 384-well plate format with similar assay robustness and reproducibility comparing with these in the 96-well plate format. This assay was then validated using the LOPAC(1280) compound library, demonstrating its repeatability with comparable assay robustness and reproducibility. This fully developed and validated HTS amenable assay could be used in future studies to screen large compound libraries for the identification of novel antivirals against dengue disease.