Safe food through better labelling; a robust method for the rapid determination of caprine and bovine milk allergens.

Accidental milk cross-contamination is one of the most common causes for costly food recalls. Yet, quantifying trace-levels of allergen is time-consuming and current methods are not adapted for routine analyses making quality control for trace-level allergen content impractical. This perpetuates voluntary "may-contain" statements that are unhelpful for people suffering from food allergies. Here, we developed a rapid LC-MS method enabling milk allergen quantification by comparing all tryptic-peptides of major milk allergens. The bovine-specific αS-2 casein peptide and allergen-epitope NAVPITPTLNR provided excellent performance in sensitivity (LOD 1 mg.kg-1; LOQ 2 mg.kg-1) across various dairy products, good recovery rates in baked croissants (77% with a 10% inter-day RSD) and a linear range of 2-2,000 mg.kg-1. The method can be used for routine determination of trace-contamination with bovine milk allergen and the adulteration of high-value caprine dairy products with lower-value bovine milk products, protecting consumer trust and the growing population suffering from food allergies.

Smartphone-based immunochemical sensor exploiting peroxidase-like activity of ligand-capped gold nanostars: A proof-of-concept detection of Mycobacterium bovis.

Bacterial pathogens represent a safety concern in the food industry, and this is amplified by the lack of sensing devices that can be applied on-site by non-trained personnel. In this study, peroxidase-mimicking activity of gold nanostars was exploited to develop a user-friendly colourimetric sensor. A smartphone was exploited as an image reader and analyser, empowered with a novel App developed in-house. The mobile App was evaluated and compared with a commercial smartphone App for its capability to quantify generated colourimetric signals. A major obstacle found with sensors relying on gold nanozymes is the fact that modification of the surface of gold nanoparticles with biorecognition elements generally lead to a suppression of their nanozyme activity. This drawback was overcome by introducing an autocatalytic growth step, which successfully restored the peroxidase-mimicking activity through generation of new gold nanoseeds acting as catalytic centres. A proof-of-concept using this sensing mechanism was developed targeting Mycobacterium bovis, a zoonotic pathogen primarily found in cattle but that can be transmitted to humans by consumption of contaminated food and cause tuberculosis disease. The resulting smartphone-based immunological sensor has shown promising results with a linear response between 104 - 106 CFU/mL, enabling detection of M. bovis at concentrations as low as 7.2·103 CFU/mL in buffer conditions. It is anticipated that the concept of the developed approach will have applicability in many fields relying on smartphone-based biosensing.

Taking control of microplastics data: A comparison of control and blank data correction methods.

Although significant headway has been achieved regarding method harmonisation for the analysis of microplastics, analysis and interpretation of control data has largely been overlooked. There is currently no consensus on the best method to utilise data generated from controls, and consequently many methods are arbitrarily employed. This study identified 6 commonly implemented strategies: a) No correction; b) Subtraction; c) Mean Subtraction; d) Spectral Similarity; e) Limits of detection/ limits of quantification (LOD/LOQ) or f) Statistical analysis, of which many variations are possible. Here, the 6 core methods and 45 variant methods (n = 51) thereof were used to correct a dummy dataset using control data. Most of the methods tested were too inflexible to account for the inherent variation present in microplastic data. Only 7 of the 51 methods tested (six LOD/LOQ methods and one statistical method) showed promise, removing between 96.3 % and 100 % of the contamination data from the dummy set. The remaining 44 methods resulted in deficient corrections for background contamination due to the heterogeneity of microplastics. These methods should be avoided in the future to avoid skewed results, especially in low abundance samples. Overall, LOD/LOQ methods or statistical analysis comparing means are recommended for future use in microplastic studies.

Secure Food-Allergen Determination by Combining Smartphone-Based Raw Image Analyses and Liquid Chromatography-Mass Spectrometry for the Quantification of Proteins Contained in Lateral Flow Assays.

The current food safety testing system, based on laboratory-based quantification, is difficult to scale up in line with the growth in the export market and does not enable traceability through the nodes of the food supply system. Screening assays, for example, lateral flow assays (LFAs), can improve traceability but often lack the required reliability to guarantee compliance. Here, we present an alternative pipeline for secure on-site compliance testing, using allergens as a case study. The pipeline features smartphone-driven LFA quantification and an liquid chromatography-mass spectrometry (LC-MS) method enabling direct quantification of the allergens contained in the LFA. The system enables swift and objective screening and provides a control measure to verify LFA assay reliability. For the smartphone assay, 8-bit RGB and grayscale colorimetric channels were compared with 16-bit raw intensity values. The latter outperformed RGB and grayscale channels in sensitivity, repeatability, and precision, while ratiometric ambient light correction resulted in excellent robustness for light-intensity variation. Calibration curves for peanut determination using two commercial LFAs featured excellent analytical parameters (R2 = 0.97-0.99; RSD 7-1%; LOD 3-7 ppm). Gluten determination with a third commercial LFA was equally established. A prediction error of 13 ± 11% was achieved for the best performing assay. Good performance-calibration curves (R2 = 0.93-0.99) and CVs (<15%)- were observed for the analyte quantification from the LFA by LC-MS. The LOD for the LC-MS assay was 0.5 ppm, well below the LODs reported for the LFAs. This method creates a digital, fast, and secure food safety compliance testing paradigm that can benefit the industry and consumer alike.

The General Growth Tendency: A tool to improve publication trend reporting by removing record inflation bias and enabling quantitative trend analysis.

The trend of the number of publications on a research field is often used to quantify research interest and effort, but this measure is biased by general publication record inflation. This study introduces a novel metric as an unbiased and quantitative tool for trend analysis and bibliometrics. The metric was used to reanalyze reported publication trends and perform in-depth trend analyses on patent groups and a broad range of field in the life-sciences. The analyses confirmed that inflation bias frequently results in the incorrect identification of field-specific increased growth. It was shown that the metric enables a more detailed, quantitative and robust trend analysis of peer reviewed publications and patents. Some examples of the metric's uses are quantifying inflation-corrected growth in research regarding microplastics (51% ± 10%) between 2012 and 2018 and detecting inflation-corrected growth increase for transcriptomics and metabolomics compared to genomics and proteomics (Tukey post hoc p<0.0001). The developed trend-analysis tool removes inflation bias from bibliometric trend analyses. The metric improves evidence-driven decision-making regarding research effort investment and funding allocation.

Targeted proteomics for rapid and robust peanut allergen quantification.

This study improves LC-MS-based trace level peanut allergen quantification in processed food by refining method robustness, total analysis time and method sensitivity. Extraction buffer (six compared) and peptide choice were optimised and found to profoundly affect method robustness. A rapid extraction and in-solution digestion method was developed omitting subsequent reduction, alkylation and sample clean-up steps effectively reducing total analysis time from the previously reported ∼5.5-20 h to ∼2.5 h. For the three best performing peptides, accurate quantification (CVs < 15%) with matrix-matched calibration curves (R2 = 0.99-0.97) was achieved for peanut muffin and ice-cream with excellent linearity (0.25-1000 mg kg-1). The best performing peptide enabled excellent recovery rates in ice-cream (106.0 ± 15.1%) and peanut muffin (72.7 ± 13.4%). Sensitivity (LOD = 0.25-0.5 mg kg-1; LOQ = 0.5-1.0 mg kg-1) was 2- to 20-fold improved compared to previous methods depending on the peptide. These methodological improvements contribute to robust peanut detection in food and can be translated to additional food-borne allergens.

Biomarkers and biosensors for the diagnosis of noncompliant pH, dark cutting beef predisposition, and welfare in cattle.

Meat quality can be affected by stress, exhaustion, feed composition, and other physical and environmental conditions. These stressors can alter the pH in postmortem muscle, leading to high pH and low-quality dark cutting (DC) beef, resulting in considerable economic loss. Moreover, the dark cutting prediction may equally provide a measure for animal welfare since it is directly related to animal stress. There are two needs to advance on-site detection of dark cutters: (1) a clear indication that biomarker (signature compounds) levels in cattle correlate with stress and DC outcome; and (2) measuring these biomarkers rapidly and accurately on-farm or the abattoir, depending on the objectives. This critical review assesses which small molecules and proteins have been identified as potential biomarkers of stress and dark cutting in cattle. We discuss the potential of promising small molecule biomarkers, including catecholamine/cortisol metabolites, lactate, succinate, inosine, glucose, and ß-hydroxybutyrate, and we identify a clear research gap for proteomic biomarker discovery in live cattle. We also explore the potential of chemical-sensing and biosensing technologies, including direct electrochemical detection improved through nanotechnology (e.g., carbon and gold nanostructures), surface-enhanced Raman spectroscopy in combination with chemometrics, and commercial hand-held devices for small molecule detection. No current strategy exists to rapidly detect predictive meat quality biomarkers due to the need to further validate biomarkers and the fact that different biosensor types are needed to optimally detect different molecules. Nonetheless, several biomarker/biosensor combinations reported herein show excellent potential to enable the measurement of DC potential in live cattle.

ASSURED Point-of-Need Food Safety Screening: A Critical Assessment of Portable Food Analyzers.

Standard methods for chemical food safety testing in official laboratories rely largely on liquid or gas chromatography coupled with mass spectrometry. Although these methods are considered the gold standard for quantitative confirmatory analysis, they require sampling, transferring the samples to a central laboratory to be tested by highly trained personnel, and the use of expensive equipment. Therefore, there is an increasing demand for portable and handheld devices to provide rapid, efficient, and on-site screening of food contaminants. Recent technological advancements in the field include smartphone-based, microfluidic chip-based, and paper-based devices integrated with electrochemical and optical biosensing platforms. Furthermore, the potential application of portable mass spectrometers in food testing might bring the confirmatory analysis from the laboratory to the field in the future. Although such systems open new promising possibilities for portable food testing, few of these devices are commercially available. To understand why barriers remain, portable food analyzers reported in the literature over the last ten years were reviewed. To this end, the analytical performance of these devices and the extent they match the World Health Organization benchmark for diagnostic tests, i.e., the Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end-users (ASSURED) criteria, was evaluated critically. A five-star scoring system was used to assess their potential to be implemented as food safety testing systems. The main findings highlight the need for concentrated efforts towards combining the best features of different technologies, to bridge technological gaps and meet commercialization requirements.

Highly sensitive electrochemical detection of the marine toxins okadaic acid and domoic acid with carbon black modified screen printed electrodes.

A novel electrochemical immunosensor for the detection of the important marine biotoxins domoic acid (DA) and okadaic acid (OA) was developed. The sensors used carbon black modified screen-printed electrodes (CB-SPE) obtained using a high-throughput method. The electrochemical performance and stability of CB modified SPEs and bare carbon SPEs (c-SPEs) were compared using cyclic voltammetry and electrochemical impedance spectroscopy. CB-SPEs showed improved long-term (at least six months) stability and electro-catalytic properties compared with c-SPEs. The CB-SPEs were bio-functionalized with DA or OA protein-conjugates and used to develop two indirect competitive immunosensors using differential pulse voltammetry (DPV). The DPV signals obtained for the OA and DA immunosensors fitted well to four-parameter dose-response curves (R2 > 0.98) and showed excellent LODs (LOD = 1.7 ng mL-1 for DA in buffer; LOD = 1.9 ng mL-1 for DA in mussel extract; LOD = 0.15 ng mL-1 for OA in buffer; LOD = 0.18 ng mL-1 for OA in mussel extract). No significant interference of the naturally co-occurring marine toxins saxitoxin, tetrodotoxin and OA was detected for the DA immunosensor. Similarly, for the OA immunosensor saxitoxin, tetrodotoxin and DA did not cross-react and very limited interference was observed for the dinophysis toxins DTX-1, DTX-2 and DTX-3 (OA congeners). Moreover, both immunosensors remained stable after at least 25 days of storage at 4 °C. This work demonstrates the potential of affordable, mass-produced nanomaterial-modified SPEs for marine toxin detection in shellfish.

A plasmonic biosensor array exploiting plasmon coupling between gold nanorods and spheres for domoic acid detection via two methods.

An immunoassay was developed that utilized plasmonic coupling between immobilised gold nanorods and colloid gold nanospheres to detect the marine toxin domoic acid (DA). The aspect ratio of the nanorods was optimised and the effects of variation in acidity, silver to gold ratio, cetyltrimethylammonium bromide (CTAB) concentration and seed addition in the growth solution on the yield, size variance and LSPR peak position was investigated. Excellent nanorods (size variation < 15%; aspect ratio 3.5-5; yield 0.26-0.35 nM mL-1) were obtained for the LSPR range 785-867 nm using strong acidic conditions (12 µl HCl (37%)), silver to gold ratio of 1:5, 0.05-0.1 M CTAB and 20-30 µl seed addition to 10 mL of growth solution. One set of nanorods (54.9 X 15.7 nm; LSPR 785 nm) were immobilised onto a silica support and bio-functionalised with DA hapten. Colloid nanospheres (15 nm; LSPR 519 nm) were bio-functionalised with an anti-domoic-acid monoclonal antibody. The functionalised nanoparticles were used to detect DA by plasmon coupling by quantifying the average LSPR shift of individual plasmon couples with hyperspectral imaging or quantifying the pixels count caused by the particle aggregation visible under darkfield microscopy. The first method led to a LSPR blue-shift of ~55 nm caused by the immunoreaction. The second, simpler method, enabled very clear qualitative detection (p < 0.0005) of domoic acid when 10 µM domoic acid was added. Both methods show potential though the novelty and simplicity of the second platform allowing rapid (~30 min) detection with high-throughput possibilities using a simple set-up is of most interest.

A Randomized Combined Channel Approach for the Quantification of Color- and Intensity-Based Assays with Smartphones.

Quantification of colorimetric assays with smartphones is being increasingly reported. However, a complete characterization of the performance of existing color spaces and single-color channels for optimum color/intensity change quantification is absent. Moreover, it has not been ascertained if it is necessary to utilize existing color spaces to reach optimal assay quantification. In this study, a randomized channel approach was adapted utilizing all single channels from RGB, HSV, and CieLab color space and all nonrepeating random combinations of two and three channels of these color spaces. Assays based on color or intensity change using pH strips and gold or carbon black nanoparticle-containing paper strips were optimized using this approach. Several novel channel combinations showed great promise, in terms of prediction error and interphone variation reduction, outperforming RGB, HSV, and CieLab color spaces. These novel combinations were used in a custom-developed smartphone application that performed automated background subtraction and polynomial regression for the quantification of a lateral flow assay for the detection of goat milk adulteration with cow milk and for pH prediction in soil. For the lateral flow assay the channel combination BSA was found optimum (mean average error = 36% ± 6%; R2 = 0.97). For the soil pH assay the channel combination RLC was found optimum (mean average error = 1.31% ± 0.02%; R2 = 0.997). The study has shown that nonclassical channel combinations for colorimetric quantification of specific assays are very promising and should be considered for smartphone-based analysis.

The benefits of carbon black, gold and magnetic nanomaterials for point-of-harvest electrochemical quantification of domoic acid.

Gold nanostars (GNST), gold nanospheres (GNP) and carbon black (CB) are chosen as alternative nanomaterials to modify carbon screen-printed electrodes (c-SPEs). The resulting three kinds of modified c-SPEs (GNP-SPE, CB-SPE and GNSP-SPE) were electrochemically and microscopically characterized and compared with standardized c-SPEs after pretreatment with phosphate buffer by pre-anodization (pre-SPE). The results show outstanding electrochemical performance of the carbon black-modified SPEs which show low transient current, low capacitance and good porosity. A competitive chronoamperometric immunoassay for the shellfish toxin domoic acid (DA) is described. The performances of the CB-SPE, GNP-SPE and pre-SPE were compared. Hapten-functionalized magnetic beads were used to avoid individual c-SPE functionalization with antibody while enhancing the signal by creating optimum surface proximity for electron transfer reactions. This comparison shows that the CB-SPE biosensor operated best at a potential near - 50 mV (vs. Ag/AgCl) and enables DA to be determined with a detection limit that is tenfold lower compared to pre-SPE (4 vs. 0.4 ng mL-1). These results show very good agreement with HPLC data when analysing contaminated scallops, and the LOD is 0.7 mg DA kg-1 of shellfish. Graphical abstractSchematic representation of the magnetic bead-based immunoassay for the quantification of domoic acid (DA) in shellfish with nanomaterial-modified screen-printed electrodes. CB, carbon black; GNP, gold nanospheres; GNST, gold nanostars; MB, magnetic beads; DA-mAb, anti-DA monoclonal mouse antibody; HRP-pAb, horseradish conjugated polyclonal goat anti-mouse antibody; DA-BSA, bovine serum albumin conjugated DA; HQ, hydroquinone; BQ, benzoquinone.