Detection of Tetrodotoxins in Puffer Fish by a Self-Assembled Monolayer-Based Immunoassay and Comparison with Surface Plasmon Resonance, LC-MS/MS, and Mouse Bioassay

The increasing occurrence of puffer fish containing tetrodotoxin (TTX) in the Mediterranean could represent a major food safety risk for European consumers and threaten the fishing industry. The work presented herein describes the development of a new enzyme linked immunosorbent assay (mELISA) based on the immobilization of TTX through dithiol monolayers self-assembled on maleimide plates, which provides an ordered and oriented antigen immobilization and favors the antigen-antibody affinity interaction. The mELISA was found to have a limit of detection (LOD) of TTX of 0.23 mg/kg of puffer fish matrix. The mELISA and a surface plasmon resonance (SPR) immunosensor previously developed were employed to establish the cross-reactivity factors (CRFs) of 5,6,11-trideoxy-TTX, 5,11-deoxy-TTX, 11-nor-TTX-6-ol, and 5,6,11-trideoxy-4-anhydro-TTX, as well as to determine TTX equivalent contents in puffer fish samples. Results obtained by both immunochemical tools were correlated (R(2) = 0.977). The puffer fish samples were also analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), and the corresponding CRFs were applied to the individual TTX contents. Results provided by the immunochemical tools, when compared with those obtained by LC-MS/MS, showed a good degree of correlation (R(2) = 0.991 and 0.979 for mELISA and SPR, respectively). The mouse bioassay (MBA) slightly overestimated the CRF adjusted TTX content of samples when compared with the data obtained from the other techniques. The mELISA has been demonstrated to be fit for the purpose for screening samples in monitoring programs and in research activities.

Separation Science and Technology - Theory

I have completed 80% of a teaching text book (text and graphics) on Separation Science and Technology - Theory. The book's content is what I've learned over many years of practice and teaching with an emphasis on clarifying and explaining the nuances within the theories associated with various practical approaches to chemical and biochemical separations.

The book is divided into self-contained Chapters with many worked examples and practice questions. It very much aligns with my teaching on CHM3005D, CHM2010, CHM2007 and is ideal for PMY8105 and the new proposed MSci in Analytical Chemistry Programme. The book brings together diverse material in single space and will be a valuable pedagogical resource for the teaching of this key discipline within QUB and elsewhere.

Industrial scale microwave processing of tomato juice using a novel continuous microwave system

This study evaluated the effect of an industrial scale continuous flow microwave volumetric heating system in comparison to conventional commercial scale pasteurisation for the processing of tomato juice in terms of physicochemical properties, microbial characteristics and antioxidant capacity. The effect against oxidative stress in Caco-2 cells, after in vitro digestion was also investigated. Physicochemical and colour characteristics of juices were very similar between technologies and during storage. Both conventional and microwave pasteurisation inactivated microorganisms and kept them in low levels throughout storage. ABTS⁺ values, but not ORAC, were higher for the microwave pasteurised juice at day 0 however no significant differences between juices were observed during storage. Juice processed with the microwave system showed an increased cytoprotective effect against H₂O₂ induced oxidation in Caco-2 cells. Organoleptic analysis revealed that the two tomato juices were very similar. The continuous microwave volumetric heating system appears to be a viable alternative to conventional pasteurisation.

Specific Noncompetitive Immunoassay for HT-2 Mycotoxin Detection

Here we demonstrate a novel homogeneous one-step immunoassay, utilizing a pair of recombinant antibody antigen-binding fragments (Fab), that is specific for HT-2 toxin and has a positive readout. Advantages over the conventional competitive immunoassay formats such as enzyme-linked immunosorbent assay (ELISA) are the specificity, speed, and simplicity of the assay. Recombinant antibody HT2-10 Fab recognizing both HT-2 and T-2 toxins was developed from a phage display antibody library containing 6 × 10(7) different antibody clones. Specificity of the immunoassay was introduced by an anti-immune complex (IC) antibody binding the primary antibody-HT-2 toxin complex. When the noncompetitive immune complex assay was compared to the traditional competitive assay, an over 10-fold improvement in sensitivity was observed. Although the HT2-10 antibody has 100% cross-reactivity for HT-2 and T-2 toxins, the immune complex assay is highly specific for HT-2 alone. The assay performance with real samples was evaluated using naturally contaminated wheat reference material. The half-maximal effective concentration (EC50) value of the time-resolved fluorescence resonance energy transfer (TR-FRET) assay was 9.6 ng/mL, and the limit of detection (LOD) was 0.38 ng/mL (19 μg/kg). The labeled antibodies can be predried to the assay vials, e.g., microtiter plate wells, and readout is ready in 10 min after the sample application.

Infrared and Raman screening of seized novel psychoactive substances: A large scale study of >200 samples

The potential of IR absorption and Raman spectroscopy for rapid identification of novel psychoactive substances (NPS) has been tested using a set of 221 unsorted seized samples suspected of containing NPS. Both IR and Raman spectra showed large variation between the different sub-classifications of NPS and smaller, but still distinguishable, differences between closely related compounds within the same class. In initial tests, screening the samples using spectral searching against a limited reference library allowed only 41% of the samples to be fully identified. The limiting factor in the identification was the large number of active compounds in the seized samples for which no reference vibrational data were available in the libraries rather than poor spectral quality. Therefore, when 33 of these compounds were independently identified by NMR and mass spectrometry and their spectra used to extend the libraries, the percentage of samples identified by IR and Raman screening alone increased to 76%, with only 7% of samples having no identifiable constituents. This study, which is the largest of its type ever carried out, therefore demonstrates that this approach of detecting non-matching samples and then identifying them using standard analytical methods has considerable potential in NPS screening since it allows rapid identification of the constituents of the majority of street quality samples. Only one complete feedback cycle was carried out in this study but there is clearly the potential to carry out continuous identification/updating when this system is used in operational settings.

Generating Data Augmented Spectroscopic Data For Performance Enhancement

The application of chemometrics in food science has revolutionized the field by allowing the creation of models able to automate a broad range of applications such as food authenticity and food fraud detection. In order to create effective and general models able to address the complexity of real life problems, a vast amount of varied training samples are required. Training dataset has to cover all possible types of sample and instrument variability. However, acquiring a varied amount of samples is a time consuming and costly process, in which collecting samples representative of the real world variation is not always possible, specially in some application fields. To address this problem, a novel framework for the application of data augmentation techniques to spectroscopic data has been designed and implemented. This is a carefully designed pipeline of four complementary and independent blocks which can be finely tuned depending on the desired variance for enhancing model's robustness: a) blending spectra, b) changing baseline, c) shifting along x axis, and d) adding random noise.
This novel data augmentation solution has been tested in order to obtain highly efficient generalised classification model based on spectroscopic data. Fourier transform mid-infrared (FT-IR) spectroscopic data of eleven pure vegetable oils (106 admixtures) for the rapid identification of vegetable oil species in mixtures of oils have been used as a case study to demonstrate the influence of this pioneering approach in chemometrics, obtaining a 10% improvement in classification which is crucial in some applications of food adulteration.