Detection of hazardous food contaminants by transcriptomics fingerprinting

Unprecedented biotechnological advances in the past decade have delivered powerful transcriptomics methods that provide new opportunities for a risk-based and, hence, more effective control of food quality and safety. The fundamental hypothesis underlying the application of a transcriptomics or other

Development of a rapid low cost fluorescent biosensor for the detection of food contaminants

A prototype fluorescent based biosensor has been developed for the antibody based detection of food related contaminants. Its performance was characterised and showed a typical antibody binding signal of 200-2000 mV, a short term noise of 9.1 mV, and baseline slope of -0.016 mV/s over 4 h. Bulk signal detection repeatability (n=23) and reproducibility (n=3) were less than 2.4%CV. The biosensor detection unit was evaluated using two food related model systems proving its ability to monitor both binding using commercial products and inhibition through the development of an assay. This assay development potential was evaluated by observing the biosensor's performance whilst appraising several labelled antibody and glass slide configurations. The molecular interaction between biotin and an anti-biotin antibody was shown to be inhibited by 41% due to the presence of biotin in a sample. A food toxin (domoic acid) calibration curve was produced, with %CVs ranging from 2.7 to 7.8%, and a midpoint of approximately 17 ng/ml with further optimisation possible. The ultimate aim of this study was to demonstrate the working principles of this innovative biosensor as a potential portable tool with the opportunity of interchangeable assays. The biosensor design is applicable for the requirements of routine food contaminant analysis, with respect to performance, functionality and cost. (C) 2012 Elsevier B.V. All rights reserved.

An evaluation of the capability of a biolayer interferometry biosensor to detect low-molecular-weight food contaminants

The safety of our food is an essential requirement of society. One well-recognised threat is that of chemical contamination of our food, where low-molecular-weight compounds such as biotoxins, drug residues and pesticides are present. Low-cost, rapid screening procedures are sought to discriminate the suspect samples from the population, thus selecting only these to be forwarded for confirmatory analysis. Many biosensor assays have been developed as screening tools in food contaminant analysis, but these tend to be electrochemical, fluorescence or surface plasmon resonance based. An alternative approach is the use of biolayer interferometry, which has become established in drug discovery and life science studies but is only now emerging as a potential tool in the analysis of food contaminants. A biolayer interferometry biosensor was assessed using domoic acid as a model compound. Instrument repeatability was tested by simultaneously producing six calibration curves showing replicate repeatability (n = 2) ranging from 0.1 to 6.5 % CV with individual concentration measurements (n = 12) ranging from 4.3 to 9.3 % CV, giving a calibration curve midpoint of 7.5 ng/ml (2.3 % CV (n = 6)). Reproducibility was assessed by producing three calibration curves on different days, giving a midpoint of 7.5 ng/ml (3.4 %CV (n = 3)). It was further shown, using assay development techniques, that the calibration curve midpoint could be adjusted from 10.4 to 1.9 ng/ml by varying assay parameters before the simultaneous construction of three calibration curves in matrix and buffer. Sensitivity of the assay compared favourably with previously published biosensor data for domoic acid. © 2013 Springer-Verlag Berlin Heidelberg.

Challenging conventional risk assessment with respect to human exposure to multiple food contaminants in food: A case study using maize

Mycotoxins and heavy metals are ubiquitous in the environment and contaminate many foods. The widespread use of pesticides in crop production to control disease contributes further to the chemical contamination of foods. Thus multiple chemical contaminants threaten the safety of many food commodities; hence the present study used maize as a model crop to identify the severity in terms of human exposure when multiple contaminants are present. High Content Analysis (HCA) measuring multiple endpoints was used to determine cytotoxicity of complex mixtures of mycotoxins, heavy metals and pesticides. Endpoints included nuclear intensity (NI), nuclear area (NA), plasma membrane permeability (PMP), mitochondrial membrane potential (MMP) and mitochondrial mass (MM). At concentrations representing legal limits of each individual contaminant in maize (3. ng/ml ochratoxin A (OTA), 1. μg/ml fumonisin B1 (FB1), 2. ng/ml aflatoxin B1 (AFB1), 100. ng/ml cadmium (Cd), 150. ng/ml arsenic (As), 50. ng/ml chlorpyrifos (CP) and 5. μg/ml pirimiphos methyl (PM), the mixtures (tertiary mycotoxins plus Cd/As) and (tertiary mycotoxins plus Cd/As/CP/PM) were cytotoxic for NA and MM endpoints with a difference of up to 13.6% (. p≤. 0.0001) and 12% (. p≤. 0.0001) respectively from control values. The most cytotoxic mixture was (tertiary mycotoxins plus Cd/As/CP/PM) across all 4 endpoints (NA, NI, MM and MMP) with increases up to 61.3%, 23.0%, 61.4% and 36.3% (. p≤. 0.0001) respectively. Synergy was evident for two endpoints (NI and MM) at concentrations contaminating maize above legal limits, with differences between expected and measured values of (6.2-12.4% (. p≤. 0.05-. p≤. 0.001) and 4.5-12.3% (. p≤. 0.05-. p≤. 0.001) for NI and MM, respectively. The study introduces for the first time, a holistic approach to identify the impact in terms of toxicity to humans when multiple chemical contaminants are present in foodstuffs. Governmental regulatory bodies must begin to contemplate how to safeguard the population when such mixtures of contaminants are found in foods and this study starts to address this critical issue.

Biosensors for the analysis of microbiological and chemical contaminants in food

Increases in food production and the ever-present threat of food contamination from microbiological and chemical sources have led the food industry and regulators to pursue rapid, inexpensive methods of analysis to safeguard the health and safety of the consumer. Although sophisticated techniques such as chromatography and spectrometry provide more accurate and conclusive results, screening tests allow a much higher throughput of samples at a lower cost and with less operator training, so larger numbers of samples can be analysed. Biosensors combine a biological recognition element (enzyme, antibody, receptor) with a transducer to produce a measurable signal proportional to the extent of interaction between the recognition element and the analyte. The different uses of the biosensing instrumentation available today are extremely varied, with food analysis as an emerging and growing application. The advantages offered by biosensors over other screening methods such as radioimmunoassay, enzyme-linked immunosorbent assay, fluorescence immunoassay and luminescence immunoassay, with respect to food analysis, include automation, improved reproducibility, speed of analysis and real-time analysis. This article will provide a brief footing in history before reviewing the latest developments in biosensor applications for analysis of food contaminants (January 2007 to December 2010), focusing on the detection of pathogens, toxins, pesticides and veterinary drug residues by biosensors, with emphasis on articles showing data in food matrices. The main areas of development common to these groups of contaminants include multiplexing, the ability to simultaneously analyse a sample for more than one contaminant and portability. Biosensors currently have an important role in food safety; further advances in the technology, reagents and sample handling will surely reinforce this position.

Multi-scale approaches to Food Sciences: computational QM and MM explorations at the microscopic level

L'obiettivo principale della politica di sicurezza alimentare è quello di garantire la salute dei consumatori attraverso regole e protocolli di sicurezza specifici. Al fine di rispondere ai requisiti di sicurezza alimentare e standardizzazione della qualità, nel 2002 il Parlamento Europeo e il Consiglio dell'UE (Regolamento (CE) 178/2002 (CE, 2002)), hanno cercato di uniformare concetti, principi e procedure in modo da fornire una base comune in materia di disciplina degli alimenti e mangimi provenienti da Stati membri a livello comunitario. La formalizzazione di regole e protocolli di standardizzazione dovrebbe però passare attraverso una più dettagliata e accurata comprensione ed armonizzazione delle proprietà globali (macroscopiche), pseudo-locali (mesoscopiche), ed eventualmente, locali (microscopiche) dei prodotti alimentari. L'obiettivo principale di questa tesi di dottorato è di illustrare come le tecniche computazionali possano rappresentare un valido supporto per l'analisi e ciò tramite (i) l’applicazione di protocolli e (ii) miglioramento delle tecniche ampiamente applicate. Una dimostrazione diretta delle potenzialità già offerte dagli approcci computazionali viene offerta nel primo lavoro in cui un virtual screening basato su docking è stato applicato al fine di valutare la preliminare xeno-androgenicità di alcuni contaminanti alimentari. Il secondo e terzo lavoro riguardano lo sviluppo e la convalida di nuovi descrittori chimico-fisici in un contesto 3D-QSAR. Denominata HyPhar (Hydrophobic Pharmacophore), la nuova metodologia così messa a punto è stata usata per esplorare il tema della selettività tra bersagli molecolari strutturalmente correlati e ha così dimostrato di possedere i necessari requisiti di applicabilità e adattabilità in un contesto alimentare. Nel complesso, i risultati ci permettono di essere fiduciosi nel potenziale impatto che le tecniche in silico potranno avere nella identificazione e chiarificazione di eventi molecolari implicati negli aspetti tossicologici e nutrizionali degli alimenti.

Combined exposure to multiple mycotoxins in food: are we ready for risk assessment and risk management?

It is nowadays recognized that the risk of human co-exposure to multiple mycotoxins is real. In the last years, a number of studies have approached the issue of co-exposure and the best way to develop a more precise and realistic assessment. Likewise, the growing concern about the combined effects of mycotoxins and their potential impact on human health has been reflected by the increasing number of toxicological studies on the combined toxicity of these compounds. Nevertheless, risk assessment of these toxins, still follows the conventional paradigm of single exposure and single effects, incorporating only the possibility of additivity but not taking into account the complex dynamics associated to interactions between different mycotoxins or between mycotoxins and other food contaminants. Considering that risk assessment is intimately related to the establishment of regulatory guidelines, once the risk assessment is completed, an effort to reduce or manage the risk should be followed to protect public health. Risk assessment of combined human exposure to multiple mycotoxins thus poses several challenges to scientists, risk assessors and risk managers and opens new avenues for research. This presentation aims to give an overview of the different challenges posed by the likelihood of human co-exposure to mycotoxins and the possibility of interactive effects occurring after absorption, towards knowledge generation to support a more accurate human risk assessment and risk management. For this purpose, a physiologically-based framework that includes knowledge on the bioaccessibility, toxicokinetics and toxicodynamics of multiple toxins is proposed. Regarding exposure assessment, the need of harmonized food consumption data, availability of multianalyte methods for mycotoxin quantification, management of left-censored data and use of probabilistic models will be highlight, in order to develop a more precise and realistic exposure assessment. On the other hand, the application of predictive mathematical models to estimate mycotoxins’ combined effects from in vitro toxicity studies will be also discussed. Results from a recent Portuguese project aimed at exploring the toxic effects of mixtures of mycotoxins in infant foods and their potential health impact will be presented as a case study, illustrating the different aspects of risk assessment highlighted in this presentation. Further studies on hazard and exposure assessment of multiple mycotoxins, using harmonized approaches and methodologies, will be crucial towards an improvement in data quality and contributing to holistic risk assessment and risk management strategies for multiple mycotoxins in foodstuffs.

Metal contaminants in cinnamon samples marketed in Portugal

Poster presented at the ICFC 2015 - International Conference on Food Contaminants. Infarmed, Lisbon, 14-15 April 2015

Simultaneous voltammetric determination of four triazine herbicides in water samples with the aid of chemometrics

A novel differential pulse voltammetry (DPV) method was developed for the simultaneous analysis of herbicides in water. A mixture of four herbicides, atrazine, simazine, propazine and terbuthylazine was analyzed simultaneously and the complex, overlapping DPV voltammograms were resolved by several chemometrics methods such as partial least squares (PLS), principal component regression (PCR) and principal component–artificial networks (PC–ANN). The complex profiles of the voltammograms collected from a synthetic set of samples were best resolved with the use of the PC–ANN method, and the best predictions of the concentrations of the analytes were obtained with the PC-ANN model (%RPET = 6.1 and average %Recovery = 99.0). The new method was also used for analysis of real samples, and the obtained results were compared well with those from the GC-MS technique. Such conclusions suggest that the novel method is a viable alternative to the other commonly used methods such as GC, HPLC and GC-MS.

The challenge of LC/MS/MS multi-mycotoxin analysis - Heracles battling the Hydra?

Mycotoxins are secondary metabolites of filamentous fungi. They pose a health risk to humans and animals due to their harmful biological properties and common occurrence in food and feed. Liquid chromatography/mass spectrometry (LC/MS) has gained popularity in the trace analysis of food contaminants. In this study, the applicability of the technique was evaluated in multi-residue methods of mycotoxins aiming at simultaneous detection of chemically diverse compounds. Methods were developed for rapid determination of toxins produced by fungal genera of Aspergillus, Fusarium, Penicillium and Claviceps from cheese, cereal based agar matrices and grains. Analytes were extracted from these matrices with organic solvents. Minimal sample clean-up was carried out before the analysis of the mycotoxins with reversed phase LC coupled to tandem MS (MS/MS). The methods were validated and applied for investigating mycotoxins in cheese and ergot alkaloid occurrence in Finnish grains. Additionally, the toxin production of two Fusarium species predominant in northern Europe was studied. Nine mycotoxins could be determined from cheese with the method developed. The limits of quantification (LOQ) allowed the quantification at concentrations varying from 0.6 to 5.0 µg/kg. The recoveries ranged between 96 and 143 %, and the within-day repeatability (as relative standard deviation, RSDr) between 2.3 and 12.1 %. Roquefortine C and mycophenolic acid could be detected at levels of 300 up to 12000 µg/kg in the mould cheese samples analysed. A total of 29 or 31 toxins could be analysed with the method developed for agar matrices and grains, with the LOQs ranging overall from 0.1 to 1250 µg/kg. The recoveries ranged generally between 44 and 139 %, and the RSDr between 2.0 and 38 %. Type-A trichothecenes and beauvericin were determined from the cereal based agar and grain cultures of F. sporotrichioides and F. langsethiae. T-2 toxin was the main metabolite, the average levels reaching 22000 µg/kg in the grain cultures after 28 days of incubation. The method developed for ten ergot alkaloids from grains allowed their quantification at levels varying from 0.01 to 10 µg/kg. The recoveries ranged from 51 to 139 %, and the RSDr from 0.6 to 13.9 %. Ergot alkaloids were measured in barley and rye at average levels of 59 and 720 µg/kg, respectively. The two most prevalent alkaloids were ergocornine and ergocristine. The LC/MS methods developed enabled rapid detection of mycotoxins in such applications where several toxins co-occurred. Generally, the performance of the methods was good, allowing reliable analysis of the mycotoxins of interest with sufficiently low quantification limits. However, the variation in validation results highlighted the challenges related to optimising this type of multi-residue methods. New data was obtained about the occurrence of mycotoxins in mould cheeses and of ergot alkaloids in Finnish grains. In addition, the study revealed the high mycotoxin-producing potential of two common fungi in Finnish crops. The information can be useful when risks related to fungal and mycotoxin contamination will be assessed.

Advances in biosensor-based analysis for antimicrobial residues in foods

Biosensors are used for a large number of applications within biotechnology, including the pharmaceutical industry and life sciences. Since the production of Biacore surface-plasmon resonance instruments in the early 1990s, there has been steadily growing use of this technology for the detection of food contaminants (e.g., veterinary drugs, mycotoxins, marine toxins, food dyes and processing contaminants). Other biosensing technologies (e.g., electrochemical and piezoelectric) have also been employed for the analysis of small-molecule contaminants. This review concentrates on recent advances made in detection and quantification of antimicrobial compounds with different types of biosensors and on the emergence of multiplexing, which is highly desirable as it increases sample analysis at lower cost and in less time. (C) 2010 Elsevier Ltd. All rights reserved.