Development of a planar waveguide microarray for the monitoring and early detection of five harmful algal toxins in water and cultures.

A novel multiplex microarray has been developed for the detection of five groups of harmful algal and cyanobacterial toxins found in marine, brackish, and freshwater environments including domoic acid (DA), okadaic acid (OA, and analogues), saxitoxin (STX, and analogues), cylindrospermopsin (CYN) and microcystins (MC, and analogues). The sensitivity and specificity were determined and feasibility to be used as a screening tool investigated. Results for algal/cyanobacterial cultures (n = 12) and seawater samples (n = 33) were compared to conventional analytical methods, such as high performance liquid chromatography (HPLC) and liquid chromatography tandem mass spectrometry (LC-MS/MS). Detection limits for the 15 min assay were 0.37, 0.44, 0.05, 0.08, and 0.40 ng/mL for DA, OA, STX, CYN, and MC, respectively. The correlation of data obtained from the microarray compared to conventional analysis for the 12 cultures was r(2) = 0.83. Analysis of seawater samples showed that 82, 82, 70, 82, and 12% of samples were positive (>IC20) compared to 67, 55, 36, 0, and 0% for DA, OA, STX, CYN, and MC, respectively, for conventional analytical methods. The discrepancies in results can be attributed to the enhanced sensitivity and cross-reactivity profiles of the antibodies in the MBio microarray. The feasibility of the microarray as a rapid, easy to use, and highly sensitive screening tool has been illustrated for the five-plex detection of biotoxins. The research demonstrates an early warning screening assay to support national monitoring agencies by providing a faster and more accurate means of identifying and quantifying harmful toxins in water samples.

Evolving to the optoelectronic mouse for phycotoxin analysis in shellfish.

Despite ethical and technical concerns, the in vivo method, or more commonly referred to mouse bioassay (MBA), is employed globally as a reference method for phycotoxin analysis in shellfish. This is particularly the case for paralytic shellfish poisoning (PSP) and emerging toxin monitoring. A high-performance liquid chromatography method (HPLC-FLD) has been developed for PSP toxin analysis, but due to difficulties and limitations in the method, this procedure has not been fully implemented as a replacement. Detection of the diarrhetic shellfish poisoning (DSP) toxins has moved towards LC-mass spectrometry (MS) analysis, whereas the analysis of the amnesic shellfish poisoning (ASP) toxin domoic acid is performed by HPLC. Although alternative methods of detection to the MBA have been described, each procedure is specific for a particular toxin and its analogues, with each group of toxins requiring separate analysis utilising different extraction procedures and analytical equipment. In addition, consideration towards the detection of unregulated and emerging toxins on the replacement of the MBA must be given. The ideal scenario for the monitoring of phycotoxins in shellfish and seafood would be to evolve to multiple toxin detection on a single bioanalytical sensing platform, i.e. 'an artificial mouse'. Immunologically based techniques and in particular surface plasmon resonance technology have been shown as a highly promising bioanalytical tool offering rapid, real-time detection requiring minimal quantities of toxin standards. A Biacore Q and a prototype multiplex SPR biosensor have been evaluated for their ability to be fit for purpose for the simultaneous detection of key regulated phycotoxin groups and the emerging toxin palytoxin. Deemed more applicable due to the separate flow channels, the prototype performance for domoic acid, okadaic acid, saxitoxin, and palytoxin calibration curves in shellfish achieved detection limits (IC20) of 4,000, 36, 144 and 46 µg/kg of mussel, respectively. A one-step extraction procedure demonstrated recoveries greater than 80% for all toxins. For validation of the method at the 95% confidence limit, the decision limits (CCα) determined from an extracted matrix curve were calculated to be 450, 36 and 24 µg/kg, and the detection capability (CCß) as a screening method is ≤10 mg/kg, ≤160 µg/kg and ≤400 µg/kg for domoic acid, okadaic acid and saxitoxin, respectively.

A novel patches-selection method for the classification of point-of-care biosensing lateral flow assays with cardiac biomarkers.

Cardiovascular Disease (CVD) is amongst the leading cause of death globally, which calls for rapid detection and treatment. Biosensing devices are used for the diagnosis of cardiovascular disease at the point-of-care (POC), with lateral flow assays (LFAs) being particularly useful. However, due to their low sensitivity, most LFAs have been shown to have difficulties detecting low analytic concentrations. Breakthroughs in artificial intelligence (AI) and image processing reduced this detection constraint and improved disease diagnosis. This paper presents a novel patches-selection approach for generating LFA images from the test line and control line of LFA images, analyzing the image features, and utilizing them to reliably predict and classify LFA images by deploying classification algorithms, specifically Convolutional Neural Networks (CNNs). The generated images were supplied as input data to the CNN model, a strong model for extracting crucial information from images, to classify the target images and provide risk stratification levels to medical professionals. With this approach, the classification model produced about 98% accuracy, and as per the literature review, this approach has not been investigated previously. These promising results show the proposed method may be useful for identifying a wide variety of diseases and conditions, including cardiovascular problems.

High-Sensitive Detection and Quantitative Analysis of Thyroid-Stimulating Hormone Using Gold-Nanoshell-Based Lateral Flow Immunoassay Device.

Au nanoparticles (AuNPs) have been used as signal reporters in colorimetric lateral flow immunoassays (LFAs) for decades. However, it remains a major challenge to significantly improve the detection sensitivity of traditional LFAs due to the low brightness of AuNPs. As an alternative approach, we overcome this problem by utilizing 150 nm gold nanoshells (AuNSs) that were engineered by coating low-density silica nanoparticles with a thin layer of gold. AuNSs are dark green, have 14 times larger surface area, and are approximately 35 times brighter compared to AuNPs. In this study, we used detection of thyroid-stimulating hormone (TSH) in a proof-of-concept assay. The limit of detection (LOD) with AuNS-based LFA was 0.16 µIU/mL, which is 26 times more sensitive than the conventional colorimetric LFA that utilizes AuNP as a label. The dynamic range of the calibration curve was 0.16−9.5 µIU/mL, making it possible to diagnose both hyperthyroidism (<0.5 µIU/mL) and hypothyroidism (>5 µIU/mL) using AuNS-based LFA. Thus, the developed device has a strong potential for early screening and diagnosis of diseases related to the thyroid hormone.

A Novel Method for Quantitative Analysis of C-Reactive Protein Lateral Flow Immunoassays Images via CMOS Sensor and Recurrent Neural Networks.

Objective: To design and implement an easy-to-use, Point-of-Care (PoC) lateral flow immunoassays (LFA) reader and data analysis system, which provides a more in-depth quantitative analysis for LFA images than conventional approaches thereby supporting efficient decision making for potential early risk assessment of cardiovascular disease (CVD). Methods and procedures: A novel end-to-end system was developed including a portable device with CMOS camera integrated with optimized illumination and optics to capture the LFA images produced using high-sensitivity C-Reactive Protein (hsCRP) (concentration level < 5 mg/L). The images were transmitted via WiFi to a back-end server system for image analysis and classification. Unlike common image classification approaches which are based on averaging image intensity from a region-of-interest (ROI), a novel approach was developed which considered the signal along the sample's flow direction as a time series and, consequently, no need for ROI detection. Long Short-Term Memory (LSTM) networks were deployed for multilevel classification. The features based on Dynamic Time Warping (DTW) and histogram bin counts (HBC) were explored for classification. Results: For the classification of hsCRP, the LSTM outperformed the traditional machine learning classifiers with or without DTW and HBC features performed the best (with mean accuracy of 94%) compared to other features. Application of the proposed method to human plasma also suggests that HBC features from LFA time series performed better than the mean from ROI and raw LFA data. Conclusion: As a proof of concept, the results demonstrate the capability of the proposed framework for quantitative analysis of LFA images and suggest the potential for early risk assessment of CVD. Clinical impact: The hsCRP levels < 5 mg/L were aligned with clinically actionable categories for early risk assessment of CVD. The outcomes demonstrated the real-world applicability of the proposed system for quantitative analysis of LFA images, which is potentially useful for more LFA applications beyond presented in this study.

Evaluation of the IgG antibody response to SARS CoV-2 infection and performance of a lateral flow immunoassay: cross-sectional and longitudinal analysis over 11 months.

OBJECTIVE: To evaluate the dynamics and longevity of the humoral immune response to SARS-CoV-2 infection and assess the performance of professional use of the UK-RTC AbC-19 Rapid Test lateral flow immunoassay (LFIA) for the target condition of SARS-CoV-2 spike protein IgG antibodies. DESIGN: Nationwide serological study. SETTING: Northern Ireland, UK, May 2020-February 2021. PARTICIPANTS: Plasma samples were collected from a diverse cohort of individuals from the general public (n=279), Northern Ireland healthcare workers (n=195), pre-pandemic blood donations and research studies (n=223) and through a convalescent plasma programme (n=183). Plasma donors (n=101) were followed with sequential samples over 11 months post-symptom onset. MAIN OUTCOME MEASURES: SARS-CoV-2 antibody levels in plasma samples using Roche Elecsys Anti-SARS-CoV-2 IgG/IgA/IgM, Abbott SARS-CoV-2 IgG and EuroImmun IgG SARS-CoV-2 ELISA immunoassays over time. UK-RTC AbC-19 LFIA sensitivity and specificity, estimated using a three-reference standard system to establish a characterised panel of 330 positive and 488 negative SARS-CoV-2 IgG samples. RESULTS: We detected persistence of SARS-CoV-2 IgG antibodies for up to 10 months post-infection, across a minimum of two laboratory immunoassays. On the known positive cohort, the UK-RTC AbC-19 LFIA showed a sensitivity of 97.58% (95.28% to 98.95%) and on known negatives, showed specificity of 99.59% (98.53 % to 99.95%). CONCLUSIONS: Through comprehensive analysis of a cohort of pre-pandemic and pandemic individuals, we show detectable levels of IgG antibodies, lasting over 46 weeks when assessed by EuroImmun ELISA, providing insight to antibody levels at later time points post-infection. We show good laboratory validation performance metrics for the AbC-19 rapid test for SARS-CoV-2 spike protein IgG antibody detection in a laboratory-based setting.

Development of a nanoarray capable of the rapid and simultaneous detection of zearalenone, T2-toxin and fumonisin.

Fusarium mycotoxins such as trichothecenes, zearalenone and fumonisins occur on a worldwide basis in cereal grains, animal feeds and forages. Practical solutions for multiple mycotoxin determination in samples are required by industry and regulators for cost effective screening purposes. The feasibility of developing a novel multiplex nanoarray for the simultaneous and semi-quantitative detection of three regulated mycotoxins: zearalenone (ZEA), T2-toxin (T2) and fumonisin B1 (FUM) was examined. Additionally, the assay was also able to detect HT2 toxin and fumonisin B2 and B3 due to the cross reactivity profiles of the antibodies used. Individual mycotoxin conjugates specific to the three mycotoxins were nano-spotted onto wells of a microtitre plate. Optimisation of assay parameters and antibodies was undertaken with both individual and multiplex calibration curves generated. A competitive assay format was employed enabling a calibration curve for concentration analysis and duplicate results for up to 40 samples in 70min for the three target mycotoxins. The characteristics and performance of the nanoarray were evaluated including sensitivity and specificity for each target. Additionally, intra and inter spotting precision, cross reactivity, matrix effects and sample analysis in maize and wheat (n=8) was performed. Sensitivity, determined as the concentration causing 50% inhibition, was 70.1, 2.8 and 90.9ppb in PBS, 172.4, 3.2 and 129.3ppb in methanol, 197.4, 0.7 and 216.7ppb in wheat and 43.6, 0.5 and 25.9ppb in maize for ZEA, T2 and FUM respectively. Intra spotting precision was 6%, 11% and 10% for PBS and 5%, 11% and 12% for methanol for ZEA, T2 and FUM respectively. Inter spotting precision was 4%, 14% and 6% for PBS and 3%, 9% and 16% for methanol for ZEA, T2 and FUM respectively. The feasibility of the nanoarray as an easy to use sensitive screening tool in the 96 well format has been demonstrated for the multiplex detection of three regulated mycotoxins. Improvements in automated image and data analysis software for novice end users are required to improve the overall rapidity of analysis.

Feasibility of a novel multispot nanoarray for antibiotic screening in honey.

Practical solutions for multiple antibiotic determination in food are required by the food industry and regulators for cost-effective screening purposes. This study describes the feasibility in development and preliminary performance of a novel multispot nanoarray for antibiotic screening in honey. Using a multiplex approach, the metabolites of the four main nitrofuran antibiotics, including morpholinomethyl-2-oxazolidone (AMOZ), 3-amino-2-oxazolidinone (AOZ), semicarbazide (SEM), 1-aminohydantoin (AHD) and chloramphenicol (CAP), were simultaneously detected. Antibodies specific to the five antibiotics were nano-spotted onto microtitre plate wells and a direct competitive assay format was employed. The assay characteristics and performance were evaluated for feasibility as a screening tool for antibiotic determination in honey to replace traditional ELISAs. Optimisation of the spotting and assay parameters was undertaken with both individual and multiplex calibration curves generated in PBS and a honey matrix. The limits of detection as determined by the 20% inhibitory concentrations (IC20) were determined as 0.19, 0.83, 0.09, 15.2 and 35.9 ng ml-1 in PBS, 0.34, 0.87, 0.17, 42.1 and 90.7 ng ml-1 in honey (fortified at the start of the extraction), and 0.23, 0.98, 0.24, 24.8 and 58.9 ng ml-1 in honey (fortified at the end of the extraction) for AMOZ, AOZ, CAP, SEM and AHD respectively. This work has demonstrated the potential of multiplex analysis for antibiotics with results available for 40 samples within a 90-min period for antibiotics sharing a common sample preparation. Although both the SEM and AHD assay do not show the required sensitivity with the antibodies available for use to meet regulatory limits, with further improvements in these particular antibodies this multiplex format has the potential to show a reduction in cost with reduced labour time in combination with the high-throughput screening of samples. This is the first 96-well spotted microtitre plate nanoarray for the semi-quantitative and simultaneous analysis of antibiotics.

A validated UPLC-MS/MS method for the surveillance of ten aquatic biotoxins in European brackish and freshwater systems.

Over the past few decades, there has been an increased frequency and duration of cyanobacterial Harmful Algal Blooms (HABs) in freshwater systems globally. These can produce secondary metabolites called cyanotoxins, many of which are hepatotoxins, raising concerns about repeated exposure through ingestion of contaminated drinking water or food or through recreational activities such as bathing/swimming. An ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) multi-toxin method has been developed and validated for freshwater cyanotoxins; microcystins-LR, -YR, -RR, -LA, -LY and -LF, nodularin, cylindrospermopsin, anatoxin-a and the marine diatom toxin domoic acid. Separation was achieved in around 9min and dual SPE was incorporated providing detection limits of between 0.3 and 5.6ng/L of original sample. Intra- and inter-day precision analysis showed relative standard deviations (RSD) of 1.2-9.6% and 1.3-12.0% respectively. The method was applied to the analysis of aquatic samples (n=206) from six European countries. The main class detected were the hepatotoxins; microcystin-YR (n=22), cylindrospermopsin (n=25), microcystin-RR (n=17), microcystin-LR (n=12), microcystin-LY (n=1), microcystin-LF (n=1) and nodularin (n=5). For microcystins, the levels detected ranged from 0.001 to 1.51µg/L, with two samples showing combined levels above the guideline set by the WHO of 1µg/L for microcystin-LR. Several samples presented with multiple toxins indicating the potential for synergistic effects and possibly enhanced toxicity. This is the first published pan European survey of freshwater bodies for multiple biotoxins, including two identified for the first time; cylindrospermopsin in Ireland and nodularin in Germany, presenting further incentives for improved monitoring and development of strategies to mitigate human exposure.

Distribution, occurrence and biotoxin composition of the main shellfish toxin producing microalgae within European waters: A comparison of methods of analysis.

Harmful algal blooms (HABs) are a natural global phenomena emerging in severity and extent. Incidents have many economic, ecological and human health impacts. Monitoring and providing early warning of toxic HABs are critical for protecting public health. Current monitoring programmes include measuring the number of toxic phytoplankton cells in the water and biotoxin levels in shellfish tissue. As these efforts are demanding and labour intensive, methods which improve the efficiency are essential. This study compares the utilisation of a multitoxin surface plasmon resonance (multitoxin SPR) biosensor with enzyme-linked immunosorbent assay (ELISA) and analytical methods such as high performance liquid chromatography with fluorescence detection (HPLC-FLD) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) for toxic HAB monitoring efforts in Europe. Seawater samples (n=256) from European waters, collected 2009-2011, were analysed for biotoxins: saxitoxin and analogues, okadaic acid and dinophysistoxins 1/2 (DTX1/DTX2) and domoic acid responsible for paralytic shellfish poisoning (PSP), diarrheic shellfish poisoning (DSP) and amnesic shellfish poisoning (ASP), respectively. Biotoxins were detected mainly in samples from Spain and Ireland. France and Norway appeared to have the lowest number of toxic samples. Both the multitoxin SPR biosensor and the RNA microarray were more sensitive at detecting toxic HABs than standard light microscopy phytoplankton monitoring. Correlations between each of the detection methods were performed with the overall agreement, based on statistical 2×2 comparison tables, between each testing platform ranging between 32% and 74% for all three toxin families illustrating that one individual testing method may not be an ideal solution. An efficient early warning monitoring system for the detection of toxic HABs could therefore be achieved by combining both the multitoxin SPR biosensor and RNA microarray.

Multiplex biotoxin surface plasmon resonance method for marine biotoxins in algal and seawater samples.

A multiplex surface plasmon resonance (SPR) biosensor method for the detection of paralytic shellfish poisoning (PSP) toxins, okadaic acid (and analogues) and domoic acid was developed. This method was compared to enzyme-linked immunosorbent assay (ELISA) methods. Seawater samples (n=256) from around Europe were collected by the consortia of an EU project MIcroarrays for the Detection of Toxic Algae (MIDTAL) and evaluated using each method. A simple sample preparation procedure was developed which involved lysing and releasing the toxins from the algal cells with glass beads followed by centrifugation and filtering the extract before testing for marine biotoxins by both multi-SPR and ELISA. Method detection limits based on IC20 values for PSP, okadaic acid and domoic acid toxins were 0.82, 0.36 and 1.66 ng/ml, respectively, for the prototype multiplex SPR biosensor. Evaluation by SPR for seawater samples has shown that 47, 59 and 61 % of total seawater samples tested positive (result greater than the IC20) for PSP, okadaic acid (and analogues) and domoic acid toxins, respectively. Toxic samples were received mainly from Spain and Ireland. This work has demonstrated the potential of multiplex analysis for marine biotoxins in algal and seawater samples with results available for 24 samples within a 7 h period for three groups of key marine biotoxins. Multiplex immunological methods could therefore be used as early warning monitoring tools for a variety of marine biotoxins in seawater samples.