Implementation of an open-source robotic platform for SARS-CoV-2 testing by real-time RT-PCR

Practical deployment of automation to expedite aqueous two-phase extraction

The feasibility of bioprocess development relies heavily on the successful application of primary recovery and purification techniques. Aqueous two-phase extraction (ATPE) disrupts the definition of "unit operation" by serving as an integrative and intensive technique that combines different objectives such as the removal of biomass and integrated recovery and purification of the product of interest. The relative simplicity of processing large samples renders this technique an attractive alternative for industrial bioprocessing applications. However, process development is hindered by the lack of easily predictable partition behaviours, the elucidation of which necessitates a large number of experiments to be conducted. Liquid handling devices can assist to address this problem; however, they are configured to operate using low viscosity fluids such as water and water-based solutions as opposed to highly viscous polymeric solutions, which are typically required in ATPE. In this work, an automated high throughput ATPE process development framework is presented by constructing phase diagrams and identifying the binodal curves for PEG6000, PEG3000, and PEG2000. Models were built to determine viscosity- and volume-independent transfer parameters. The framework provided an appropriate strategy to develop a very precise and accurate operation by exploiting the relationship between different liquid transfer parameters and process error. Process accuracy, measured by mean absolute error, and device precision, evaluated by the coefficient of variation, were both shown to be affected by the mechanical properties, particularly viscosity, of the fluids employed. For PEG6000, the mean absolute error improved by six-fold (from 4.82% to 0.75%) and the coefficient of variation improved by three-fold (from 0.027 to 0.008) upon optimisation of the liquid transfer parameters accounting for the viscosity effect on the PEG-salt buffer utilising ATPE operations. As demonstrated here, automated liquid handling devices can serve to streamline process development for APTE enabling wide adoption of this technique in large scale bioprocess applications.

Application of artificial intelligence (AI) to control COVID-19 pandemic: Current status and future prospects

The impact of the coronavirus disease 2019 (COVID-19) pandemic on the everyday livelihood of people has been monumental and unparalleled. Although the pandemic has vastly affected the global healthcare system, it has also been a platform to promote and develop pioneering applications based on autonomic artificial intelligence (AI) technology with therapeutic significance in combating the pandemic. Artificial intelligence has successfully demonstrated that it can reduce the probability of human-to-human infectivity of the virus through evaluation, analysis, and triangulation of existing data on the infectivity and spread of the virus. This review talks about the applications and significance of modern robotic and automated systems that may assist in spreading a pandemic. In addition, this study discusses intelligent wearable devices and how they could be helpful throughout the COVID-19 pandemic.

An open-source, automated, and cost-effective platform for COVID-19 diagnosis and rapid portable genomic surveillance using nanopore sequencing

The COVID-19 pandemic, caused by SARS-CoV-2, has emphasized the necessity for scalable diagnostic workflows using locally produced reagents and basic laboratory equipment with minimal dependence on global supply chains. We introduce an open-source automated platform for high-throughput RNA extraction and pathogen diagnosis, which uses reagents almost entirely produced in-house. This platform integrates our methods for self-manufacturing magnetic nanoparticles and qRT-PCR reagents-both of which have received regulatory approval for clinical use-with an in-house, open-source robotic extraction protocol. It also incorporates our "Nanopore Sequencing of Isothermal Rapid Viral Amplification for Near Real-time Analysis" (NIRVANA) technology, designed for tracking SARS-CoV-2 mutations and variants. The platform exhibits high reproducibility and consistency without cross-contamination, and its limit of detection, sensitivity, and specificity are comparable to commercial assays. Automated NIRVANA effectively identifies circulating SARS-CoV-2 variants. Our in-house, cost-effective reagents, automated diagnostic workflows, and portable genomic surveillance strategies provide a scalable and rapid solution for COVID-19 diagnosis and variant tracking, essential for current and future pandemic responses.

Customized Surface Design to Increase Throughput of Ambient Ionization Mass Spectrometry Lipidomics

Increased access to cheap and rapid mass spectrometry testing of biofluids is desirable for the analysis of disorders and diseases that may be linked to alterations in metabolite or lipid levels. The objective of this study is to establish an easily customized high-throughput workflow for the analysis of biological samples using desorption electrospray ionization-mass spectrometry (DESI-MS). The guiding principles of this workflow are the use of low-cost, open-source, and readily accessible materials with high-throughput and reproducibility. The design consists of 3 steps: (1) PARAFILM surface customization of size, shape, and depth of features on PARAFILM via 3D printed molds; (2) sample spotting via high-throughput robotics using the relatively inexpensive and open-source Opentrons platform to reduce variability and increase reliability of sample spotting; and (3) an open-source point-and-click graphical user interface (MSI.EAGLE) for data analysis via the R statistical language building on the Cardinal package. Here we describe this workflow and test optimal surface ionization characteristics by comparison of serum extracts spotted on PARAFILM and on PTFE (porous and nonporous). Untargeted analysis across three surfaces suggests that they are all suitable for ionization of a wide range of metabolites and lipids, with 3983 m/z features detected. Differential analysis of polar vs nonpolar serum extracts suggests that ∼80% of ions are desorbed preferentially from different surfaces. PARAFILM is less impacted by the interference of background ions derived from the surface. The developed system allows for a wide range of researchers to access custom surface design workflows and high-throughput analyses in a highly cost-effective manner.

Incorporation of automated buffer exchange empowers high-throughput protein and plasmid purification for downstream uses

The continued acceleration of time-to-market product development and rising demand for biotherapeutics have hastened the need for higher throughput within the biopharmaceutical industry. Automated liquid handlers (ALH) are increasingly popular due to flexible programming that enables processing of multiple samples with an array of functions. This flexibility is useful in streamlining research that requires chromatographic procedures to achieve product purity for downstream analysis. However, purification of biologics often requires additional off-deck buffer exchange steps due to undesirable elution conditions such as high acid or high salt content. Expanding the capability of ALHs to perform purification in sequence with buffer exchange would, therefore, increase workflow efficiency by eliminating the need for manual intervention, thus expediting sample preparation. Here we demonstrate two different automated purifications using pipet-based dispersive solid-phase extraction (dSPE). The first is an affinity purification of His-tagged proteins from bacterial lysate. The second is an anion-exchange purification of plasmid DNA. Both methods are followed by buffer exchange performed by an ALH. Percent recoveries for the three purified recombinant proteins ranged from 51 ± 1.2 to 86 ± 10%. The yields were inversely correlated to starting sample load and protein molecular weight. Yields for plasmid purification ranged between 11.4 ± 0.8 and 13.7 ± 0.9 µg, with the largest plasmid providing the highest yield. Both programs were rapid, with protein purification taking <80 min and plasmid purification <60 min. Our results demonstrate that high-quality, ready-to-use biologics can be obtained rapidly from a crude sample after two separate chromatographic processes without manual intervention.

Technical upgrade of an open-source liquid handler to support bacterial colony screening

The optimization of genetically engineered biological constructs is a key step to deliver high-impact biotechnological applications. The use of high-throughput DNA assembly methods allows the construction of enough genotypic variants to successfully cover the target design space. This, however, entails extra workload for researchers during the screening stage of candidate variants. Despite the existence of commercial colony pickers, their high price excludes small research laboratories and budget-adjusted institutions from accessing such extensive screening capability. In this work we present COPICK, a technical solution to automatize colony picking in an open-source liquid handler Opentrons OT-2. COPICK relies on a mounted camera to capture images of regular Petri dishes and detect microbial colonies for automated screening. COPICK's software can then automatically select the best colonies according to different criteria (size, color and fluorescence) and execute a protocol to pick them for further analysis. Benchmark tests performed for E. coli and P. putida colonies delivers a raw picking performance over pickable colonies of 82% with an accuracy of 73.4% at an estimated rate of 240 colonies/h. These results validate the utility of COPICK, and highlight the importance of ongoing technical improvements in open-source laboratory equipment to support smaller research teams.

An Open One-Step RT-qPCR for SARS-CoV-2 detection

The COVID-19 pandemic has resulted in millions of deaths globally, and while several diagnostic systems were proposed, real-time reverse transcription polymerase chain reaction (RT-PCR) remains the gold standard. However, diagnostic reagents, including enzymes used in RT-PCR, are subject to centralized production models and intellectual property restrictions, which present a challenge for less developed countries. With the aim of generating a standardized One-Step open RT-qPCR protocol to detect SARS-CoV-2 RNA in clinical samples, we purified and tested recombinant enzymes and a non-proprietary buffer. The protocol utilized M-MLV RT and Taq DNA pol enzymes to perform a Taqman probe-based assay. Synthetic RNA samples were used to validate the One-Step RT-qPCR components, and the kit showed comparable sensitivity to approved commercial kits. The One-Step RT-qPCR was then tested on clinical samples and demonstrated similar performance to commercial kits in terms of positive and negative calls. This study represents a proof of concept for an open approach to developing diagnostic kits for viral infections and diseases, which could provide a cost-effective and accessible solution for less developed countries.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

A high-throughput fully automatic biosensing platform for efficient COVID-19 detection

We propose a label-free biosensor based on a porous silicon resonant microcavity and localized surface plasmon resonance. The biosensor detects SARS-CoV-2 antigen based on engineered trimeric angiotensin converting enzyme-2 binding protein, which is conserved across different variants. Robotic arms run the detection process including sample loading, incubation, sensor surface rinsing, and optical measurements using a portable spectrometer. Both the biosensor and the optical measurement system are readily scalable to accommodate testing a wide range of sample numbers. The limit of detection is 100 TCID_50/ml. The detection time is 5 min, and the throughput of one single robotic site is up to 384 specimens in 30 min. The measurement interface requires little training, has standard operation, and therefore is suitable for widespread use in rapid and onsite COVID-19 screening or surveillance.

High—throughput and automated screening for COVID-19

The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.

Rational Design of CRISPR/Cas12a-RPA Based One-Pot COVID-19 Detection with Design of Experiments

Simple and effective molecular diagnostic methods have gained importance due to the devastating effects of the COVID-19 pandemic. Various isothermal one-pot COVID-19 detection methods have been proposed as favorable alternatives to standard RT-qPCR methods as they do not require sophisticated and/or expensive devices. However, as one-pot reactions are highly complex with a large number of variables, determining the optimum conditions to maximize sensitivity while minimizing diagnostic cost can be cumbersome. Here, statistical design of experiments (DoE) was employed to accelerate the development and optimization of a CRISPR/Cas12a-RPA-based one-pot detection method for the first time. Using a definitive screening design, factors with a significant effect on performance were elucidated and optimized, facilitating the detection of two copies/μL of full-length SARS-CoV-2 (COVID-19) genome using simple instrumentation. The screening revealed that the addition of a reverse transcription buffer and an RNase inhibitor, components generally omitted in one-pot reactions, improved performance significantly, and optimization of reverse transcription had a critical impact on the method’s sensitivity. This strategic method was also applied in a second approach involving a DNA sequence of the N gene from the COVID-19 genome. The slight differences in optimal conditions for the methods using RNA and DNA templates highlight the importance of reaction-specific optimization in ensuring robust and efficient diagnostic performance. The proposed detection method is automation-compatible, rendering it suitable for high-throughput testing. This study demonstrated the benefits of DoE for the optimization of complex one-pot molecular diagnostics methods to increase detection sensitivity.

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by a high rate of transmission and low mortality, the COVID-19 pandemic necessitated accurate and efficient diagnostic testing, particularly in closed populations such as residential universities. Initial availability of nucleic acid testing, like nasopharyngeal swabs, was limited due to supply chain pressure which also delayed reporting of test results. Saliva-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) testing has shown to be comparable in sensitivity and specificity to other testing methods, and saliva collection is less physically invasive to participants. Consequently, we developed a multiplex RT-qPCR diagnostic assay for population surveillance of Clemson University and the surrounding community. The assay utilized open-source liquid handling robots and thermocyclers instead of complex clinical automation systems to optimize workflow and system flexibility. Automation of saliva-based RT-qPCR enables rapid and accurate detection of a wide range of viral RNA concentrations for both large- and small-scale testing demands. The average turnaround for the automated system was < 9 h for 95% of samples and < 24 h for 99% of samples. The cost for a single test was $2.80 when all reagents were purchased in bulk quantities.

Lack of Prognostic Value of SARS-CoV2 RT-PCR Cycle Threshold in the Community

The immense impact of the COVID-19 pandemic on health systems has motivated the scientific community to search for clinical prognostic factors for SARS-CoV-2 infection. Low cycle threshold values (Ct) of diagnostic real-time RT-PCR assays in hospitalized patients have been associated with a poor prognosis in several studies, whereas other studies did not find this association. We explored whether SARS-CoV-2 Ct values at diagnosis were associated with a poor outcome (admission to hospital and death) in 604 community patients diagnosed at primary health centers. Although lower Ct values were found in patients who died of COVID-19, the Ct value was not significantly associated with a worse outcome in a multivariate analysis, while age remained an independent prognostic factor. We did not find evidence to support the role of Ct values as a prognostic factor of COVID-19 in community cases.