ABSTRACT
SARS-like coronaviruses, including SARS-CoV and SARS-CoV-2, encode spike proteins that bind human ACE2 protein on the cell surface to enter target cells and cause infection. The efficiency of virus entry depends on ACE2 sequence and expression levels in target cells. A small fraction of humans encodes variants of ACE2, thus altering the biochemical properties at the protein interaction interface. All humans possess cells with vastly differing amounts of ACE2 on the cell surface, ranging from cell types with high expression in the gut and lungs to lower expression in the liver and pancreas. Mastering our understanding of spike-ACE2 interaction and infection requires experiments precisely perturbing both variables. Thus, we developed a synthetic cell engineering approach compatible with high throughput assays for pseudo-typed virus infection. Our assay system is capable of assessing both variables individually and in combination. We adapted an engineered HEK293T DNA recombinase landing pad cell line capable of expressing transgenic ACE2 sequences at highly precise levels. Infection with lentiviruses pseudotyped with the spikes of SARS-like coronaviruses revealed that high ACE2 abundance could mask the effects of impaired binding thereby making it challenging to know the role of affinity altering mutations during infection. We limited the ACE2 abundance on the cell surface by expressing transgenic ACE2 behind a suboptimal Kozak sequence, thereby altering its protein translation rate. This allowed us to understand how ACE2 sequence could impact its interaction with coronavirus spike proteins as two human ACE2 variants at the binding interface, K31D and D355N, exhibited reduced infection. Our experiments suggested that we need to better understand how ACE2 expression determines the susceptibility of cells for SARS-like coronavirus binding and infection. We thus created an ACE2 Kozak library consisting of ~4,096 Kozak variants, each conferring a different ACE2 protein translation rate thus resulting in a range of ACE2 steady-state abundances. Combining fluorescence-activated cell sorting and high-throughput DNA sequencing (FACS-seq) revealed the library to span two orders of magnitude of ACE2 abundance. Challenging this library of cells with spike pseudotyped lentiviruses revealed how ACE2 abundance correlated with infection rate. The library-based experiments yielded a dynamic range wider than traditional single sample infection assay, likely more representative of infection dynamics in vivo. Now that we have characterized the impacts of ACE2 abundance on infectivity in engineered cells, our next goal is to expand the comparison to physiologically relevant cells with endogenously expressed proteins. Modulating protein abundance levels will be key to creating maximally informative functional assays for any protein in cell-based assays, and we have laid the groundwork for being able to simultaneously test the impacts of protein abundance and sequence in combination for proteins involved in diverse cellular processes. This research was supported by a National Institute of Health (NIH) grant GM142886 (KAM).Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.
ABSTRACT
The application of machine learning in the medical field is still limited. The main reason behind the lack of use is the unavailability of an easy-to-use machine learning system that targets non-technical users. The objective of this paper is to propose an automated machine learning system to aid non-technical users. The proposed system provides the user with simple choices to provide suggestions to the system. The system uses the combination of the user's choices and performance evaluation to select the most suited model from available options. In this study, we employed the system on a Parkinson's disease dataset. The templates for support vector machine and random forest algorithms are provided to the system. Support vector machines and random forests were able to produce 80% and 75% accuracy, respectively. The system used performance parameters of the system and user choices to select the most suited models for each test case. The support vector machine was selected as the most suited model in three test cases, while random forest was selected as the most suited for one test case. The test cases also showed that the weighted time parameter impacted the results heavily.Copyright © 2022 The Author(s)
ABSTRACT
COVID-19 has been found to affect the expression profile of several mRNAs and miRNAs, leading to dysregulation of a number of signaling pathways, particularly those related to inflammatory responses. In the current study, a systematic biology procedure was used for the analysis of high-throughput expression data from blood specimens of COVID-19 and healthy individuals. Differentially expressed miRNAs in blood specimens of COVID-19 vs. healthy specimens were then identified to construct and analyze miRNA-mRNA networks and predict key miRNAs and genes in inflammatory pathways. Our results showed that 171 miRNAs were expressed as outliers in box plot and located in the critical areas according to our statistical analysis. Among them, 8 miRNAs, namely miR-1275, miR-4429, miR-4489, miR-6721-5p, miR-5010-5p, miR-7110-5p, miR-6804-5p and miR-6881-3p were found to affect expression of key genes in NF-KB, JAK/STAT and MAPK signaling pathways implicated in COVID-19 pathogenesis. In addition, our results predicted that 25 genes involved in above-mentioned inflammatory pathways were targeted not only by these 8 miRNAs but also by other obtained miRNAs (163 miRNAs). The results of the current in silico study represent candidate targets for further studies in COVID-19.Copyright © 2023 Elsevier B.V.
ABSTRACT
The emergence of the novel severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) Coronavirus resulted in a global pandemic due to its nature of rapid transmission and variable severities that facilitated its spread worldwide. Correspondingly, owing to advances in molecular technologies, information on this virus is generated at an unprecedented pace. Since the onset of the pandemic, multiple highthroughput "omics" analyses - including transcriptomics and proteomics of different viral infection models - have been made readily available to the research and wider community. The availability and ability to rapidly generate these data facilitate the deciphering of virus–host interactions during SARS-CoV-2 infection - thus enhancing understanding of the viral transmission, host susceptibility, pathogenesis, viral evolution, and disease complications. Such information is vital for eventual applications towards biomarker and treatment discovery against Coronavirus disease 2019 (COVID-19), and can serve as useful models for future pandemic responses. © 2023 by World Scientific Publishing Co. Pte. Ltd.
ABSTRACT
Ethnopharmacological relevance: Scutellaria baicalensis Georgi. contains varieties of function compounds, and it has been used as traditional drug for centuries. Baicalein is the highest amount of flavonoid found in Scutellaria baicalensis Georgi., which exerts various pharmacological activities and might be a promising drug to treat COVID-19. Aim of the study: The present work aims to investigate the metabolism of baicalein in humans after oral administration, and study the pharmacokinetics of BA and its seven metabolites in plasma and urine. Materials and methods: The metabolism profiling and the identification of baicalein metabolites were performed on HPLC-Q-TOF. Then a column-switching method named MPX™-2 system was applied for the high-throughput quantificationof BA and seven metabolites. Results: Seven metabolites were identified using HPLC-Q-TOF, including sulfate, glucuronide, glucoside, and methyl-conjugated metabolites. Pharmacokinetic study found that BA was extensively metabolized in vivo, and only 5.65% of the drug remained intact in the circulatory system after single dosing. Baicalein-7-O-sulfate and baicalein-6-O-glucuronide-7-O-glucuronide were the most abundant metabolites. About 7.2% of the drug was excreted through urine and mostly was metabolites. Conclusion: Seven conjugated metabolites were identified in our assay. A high-throughput HPLC-MS/MS method using column switch was established for quantifying BA and its metabolites. The method has good sensitivity and reproducibility, and successfully applied for the clinical pharmacokinetic study of baicalein and identified metabolites. We expect that our results will provide a metabolic and pharmacokinetic foundation for the potential application of baicalein in medicine. © 2022
ABSTRACT
Background: The prevalence of vaccinated, previously infected, and individuals at risk of SARS-CoV-2 infection is important for epidemiologic studies and public health interventions. Asymptomatic infections and reluctance to disclose vaccination status hinder accurate assessments of the current state of the epidemic. Since COVID-19 vaccines generate immune responses to spike (S1), but not nucleocapsid (N), it is possible to differentiate between vaccinated, infected, and unexposed individuals by comparing antibody reactivity to each antigen. The MSD V-Plex SARS-CoV-2 IgG assay can potentially differentiate each state in one test by simultaneously evaluating IgG reactivity to the S1, receptor binding domain (RBD), and N proteins. Methods: The MSD assay was validated with three sample sets: known vaccination with no previous infection (n=158);known infected and not vaccinated (n=157);and samples collected prior to the COVID-19 pandemic in 2016 (n=144). Of the previously infected individuals, 15 (9.6%) were hospitalized;sample collection occurred a median of 48 days after a PCR-positive result. Using an algorithm, samples with positive results on both S1 and RBD but negative on N were classified as vaccinated. Samples with a positive result on all three proteins were considered to be infected with the possibility of subsequent vaccination. Any other result was classified as unexposed. Sensitivity and specificity for each state were calculated. Results: Reactivity to each antigen is shown in the figure. 100% (95% confidence interval [CI] 97.7-100), 92% (95% CI 86.3-95.5), and 0.7% (95% CI 0.02-3.8) of vaccinated, infected, and unexposed samples were positive for S1. 100% (95% CI 97.7-100.0%), 91% (95% CI 85.5-95.0%), and 0.7% (95% CI 0.02-3.8%) of vaccinated, infected and unexposed samples were positive for RBD. 0% (95% CI 0-2.3), 86% (95% CI 79.6-91.0), and 2.1% (95% CI 0.4-6.0) of vaccinated, infected and unexposed samples were positive for N. Algorithm sensitivity and specificity for classification of vaccinated samples were 100% (95% CI 97.7-100) and 96.7 (95% CI 94-98.4). For the classification of samples from previously infected individuals, sensitivity and specificity were 83.4% (95% CI 76.7-88.9) and 100% (95% CI 98.8-100). Conclusion: This study establishes the sensitivity and specificity for a high-throughput assay ideal for SARS-CoV-2 seroprevalence studies. Future research should focus on applying this assay in health care settings to guide practice and policy to mitigate the pandemic.
ABSTRACT
Introduction: The emergence of the SARS-CoV-2 virus, the cause of the COVID-19 pandemic, in late 2019 put every country on high alert and led to major changes in global diagnostic testing capability in infectious disease. From the outset it was apparent that local health authorities were under-prepared and under-staffed to cope with the rapid onset and spread of the disease. Demand for SAR-CoV-2 testing soared, highlighting the limitations of capacity in existing infectious disease laboratories along with requests from governments to support growing testing need. We partnered with US and UK Governments to establish, supply, staff and operate three large-scale, high-throughput SARS-CoV-2 testing facilities. These were ultimately established in Valencia, CA, offering testing of up to 150k samples per day, and in Loughborough and Newport, UK, offering a combined testing of up to 70k samples per day. The biggest challenge faced globally was the unprecedented scale of testing required and the timeframe to deliver a reliable and sensitive high-throughput assay. The benefits of industry and government partnerships become evident along with having a dedicated supply chain to feed the reagent and consumable needs for high-throughput testing as well as a highly accurate test with a fast turnaround time. Experts from multiple divisions, including R&D, Genomics, Enterprise, and regional centres were bought into the project, resulting in the establishment of SARS-CoV-2 testing within the three facilities in approximately eight weeks. Clinical testing experts in high-throughput, newborn screening, and rare disease testing, built molecular testing pipelines for the facilities based around the use of real-time polymerase chain reaction (RT-PCR) assays and sequencing. Laboratories were setup to meet the requirements set by various regulatory and accreditation agencies such as Clinical Laboratory Improvement Amendments, College of American Pathologies, the UK National Health Service validation group and ISO15189. Methods: Underpinning the testing was the massive IT and bioinformatics effort to enable reporting of the testing outcomes to the relevant authorities. We were able to deploy a novel LIMS system that is used throughout the laboratories to maintain sample chain of custody from arrival at the facility to reporting of results and incorporating interpretive software to support clinical interpretation of the resulting RT-PCR data. The LIMS systems are constantly undergoing improvement to support interpretation and troubleshooting. Local experts in clinical interpretation and reporting were onboarded to augment data analysis and ensure high-quality and reliable reporting whilst ensuring that clinical governance remains at the centre of all activities. Results: Before any SARS-CoV-2 testing was able to commence, several significant challenges were overcome by combining the expertise of our global teams with the local knowledge and support of the respective Governments. Experts in logistics and program management were able to convert three empty facilities with no pre-existing laboratory infrastructure into fully functional clinical testing laboratories within eight weeks. Our assay manufacturing capacity was majorly expanded to accommodate the requirements of SARS-CoV-2 testing, with all three facilities operating on automated platforms and utilizing chemistry with a dedicated secure supply chain. The final major challenge was rapid onboarding and training of staff for the facilities, and a year out, the two active facilities are currently employing over 600 individuals. Conclusion: To date the three facilities have performed over 12 million SARS-CoV-2 RT-PCR assays and SARS-CoV-2 testing will continue into 2022. The number of cases is again growing globally, and with the emergence of new variants and continual uncertainty about the impact on existing vaccines, there is an ongoing requirement for this scale of testing. From the experience of the SARS-CoV-2 global pandemic, the benefits of industry and government collaboration or the public has become much clearer, including greater access to large-scale testing options, significant reductions in time-to-testing and reporting and the rapid deployment of modern, cutting edge technology in diagnostic and monitoring programmes and eventually reduced costs to health services from mass-production. Ultimately the longevity of the individual testing facilities is unclear, but the future of large-scale clinical testing has changed forever and the legacy of this is the clear benefit to everybody when industry and governments work together to provide the public high quality and reliable testing operations.