Food Fingerprinting: Using a Two-Tiered approach to Monitor and Mitigate Food Fraud in Rice.

BACKGROUND: Rice is an important staple food that is consumed around the world. Like many foods, the price of rice varies considerably, from very inexpensive for a low-quality product to premium pricing for highly prized varieties from specific locations. Therefore, like other foods it is vulnerable to economically motivated adulteration through substitution or misrepresentation of inferior-quality rice for more expensive varieties. OBJECTIVE: In this article we describe results of a research project focused on addressing potential food fraud issues related to rice supplies in China, India, Vietnam, and Ghana. Rice fraud manifests differently in each country; therefore, tailored solutions were required. METHOD: Here we describe a two-tiered testing regime of rapid screening using portable Near Infrared technology supported by second tier testing using mass spectrometry-based analysis of suspicious samples. RESULTS: Portable Near Infrared spectroscopy models and laboratory-based Gas Chromatography-Mass Spectrometry methods were developed to differentiate between: high-value Basmati rice varieties and their potential adulterants; six Geographic Indicated protected rice varieties from specific regions within China; various qualities of rice in Ghana and Vietnam; and locally produced and imported rice in Ghana. Furthermore, an Inductively Coupled Plasma-Mass Spectrometry method was developed to support the Chinese rice varieties methods as well as a Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry method for quality differentiation in Vietnam. CONCLUSIONS/HIGHLIGHTS: This two-tier approach can provide a substantially increased level of testing through rapid screening outside of the laboratory with the reassurance of corroborating mass spectrometry-based laboratory analysis to support decision making.

Global metabolite profiles of rice brown planthopper-resistant traits reveal potential secondary metabolites for both constitutive and inducible defenses.

INTRODUCTION: Brown planthopper (BPH) is a phloem feeding insect that causes annual disease outbreaks, called hopper burn in many countries throughout Asia, resulting in severe damage to rice production. Currently, mechanistic understanding of BPH resistance in rice plant is limited, which has caused slow progression on developing effective rice varieties as well as effective farming practices against BPH infestation. OBJECTIVE: To reveal rice metabolic responses during 8 days of BPH attack, this study examined polar metabolome extracts of BPH-susceptible (KD) and its BPH-resistant isogenic line (IL308) rice leaves. METHODS: Ultra high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QToF-MS) was combined with multi-block PCA to analyze potential metabolites in response to BPH attack. RESULTS: This multivariate statistical model revealed different metabolic response patterns between the BPH-susceptible and BPH-resistant varieties during BPH infestation. The metabolite responses of the resistant IL308 variety occurred on Day 1, which was significantly earlier than those of the susceptible KD variety which showed an induced response by Days 4 and 8. BPH infestation caused metabolic perturbations in purine, phenylpropanoid, flavonoid, and terpenoid pathways. While found in both susceptible and resistant rice varieties, schaftoside (1.8 fold), iso-schaftoside (1.7 fold), rhoifolin (3.4 fold) and apigenin 6-C-α-L-arabinoside-8-C-ß-L-arabinoside levels (1.6 fold) were significantly increased in the resistant variety by Day 1 post-infestation. 20-hydroxyecdysone acetate (2.5 fold) and dicaffeoylquinic acid (4.7 fold) levels were considerably higher in the resistant rice variety than those in the susceptible variety, both before and after infestation, suggesting that these secondary metabolites play important roles in inducible and constitutive defenses against the BPH infestation. CONCLUSIONS: These potential secondary metabolites will be useful as metabolite markers and/or bioactive compounds for effective and durable approaches to address the BPH problem.

The Health Promoting Bioactivities of Lactuca sativa can be Enhanced by Genetic Modulation of Plant Secondary Metabolites.

Plant secondary metabolites are protective dietary constituents and rol genes evidently increase the synthesis of these versatile phytochemicals. This study subjected a globally important vegetable, lettuce (Lactuca sativa) to a combination of untargeted metabolomics (LC-QTof-MS) and in vitro bioactivity assays. Specifically, we examined the differences between untransformed cultured lettuce (UnT), lettuce transformed with either rolABC (RA) or rolC (RC) and commercially grown (COM) lettuce. Of the 5333 metabolite features aligned, deconvoluted and quantified 3637, 1792 and 3737 significantly differed in RA, RC and COM, respectively, compared with UnT. In all cases the number of downregulated metabolites exceeded the number increased. In vitro bioactivity assays showed that RA and RC (but not COM) significantly improved the ability of L. sativa to inhibit α-glucosidase, inhibit dipeptidyl peptidase-4 (DPP-4) and stimulate GLP-1 secretion. We putatively identified 76 lettuce metabolites (sesquiterpene lactones, non-phenolic and phenolic compounds) some of which were altered by several thousand percent in RA and RC. Ferulic acid levels increased 3033-9777%, aminooxononanoic acid increased 1141-1803% and 2,3,5,4'tetrahydroxystilbene-2-O-ß-d-glucoside increased 40,272-48,008%. Compound activities were confirmed using commercially obtained standards. In conclusion, rol gene transformation significantly alters the metabolome of L.sativa and enhances its antidiabetic properties. There is considerable potential to exploit rol genes to modulate secondary metabolite production for the development of novel functional foods. This investigation serves as a new paradigm whereby genetic manipulation, metabolomic analysis and bioactivity techniques can be combined to enable the discovery of novel natural bioactives and determine the functional significance of plant metabolites.

Simultaneous authentication of species identity and geographical origin of shrimps: Untargeted metabolomics to recurrent biomarker ions.

Mandatory disclosure of the species identity, production method, and geographical origin are embedded in the regulations and traceability systems, governing international seafood trade. A high-resolution mass spectrometry-based metabolomics approach could simultaneously authenticate the species identity and geographical origin of commercially important shrimps. The highly innovative approach spared the need for multiple testing methods which are in routine use currently. A robust chemometric model, developed using the metabolite fingerprint dataset, could accurately predict the species identity of the shrimp samples. Subsequently, species-specific biomarkers were discovered and a tandem mass spectrometry method for authentication of the species was developed. Two other chemometric models from the metabolomics experiment accurately predicted the geographical origin of king prawns and tiger prawns. The study has shown for the first time that food-metabolomics along with chemometrics can simultaneously check for multiple seafood fraud issues in the global seafood supply-chain.

Rapid detection and specific identification of offals within minced beef samples utilising ambient mass spectrometry.

The morphological transformation of beef tissues after various processing treatments facilitates the addition of cheap offal products. Undetectable to the naked eye, analytical techniques are required to identify such scenarios within minced and processed products. DNA methodologies are ill-equipped to detect adulteration of offal cuts from the same species and vibrational spectroscopic studies, although rapid and non-destructive, have proved inconclusive as to whether the specific adulterant can be identified. For the first time we present a mass spectrometric approach employing an ambient ionisation process to eliminate sample preparation and provide near-instantaneous results. Rapid evaporative ionisation mass spectrometry (REIMS) was used to assess its capabilities of detecting minced beef adulteration with beef brain, heart, kidney, large intestine and liver tissues and chemometric analysis enabled unique or significant markers to be identified. The adulteration levels detected with the REIMS technology when analysing raw adulterated beef burgers were; brain (5%); heart (1-10%); kidney (1-5%); large intestine (1-10%) and liver (5-10%). For boiled adulterated samples; brain (5-10%); heart (1-10%); kidney (1-5%); large intestine (1-10%) and liver (5-10%). REIMS allows rapid and specific identification of offal cuts within adulterated beef burgers and could provide a paradigm shift across many authenticity applications.

DIVA metabolomics: Differentiating vaccination status following viral challenge using metabolomic profiles.

Bovine Respiratory Disease (BRD) is a major source of economic loss within the agricultural industry. Vaccination against BRD-associated viruses does not offer complete immune protection and vaccine failure animals present potential routes for disease spread. Serological differentiation of infected from vaccinated animals (DIVA) is possible using antigen-deleted vaccines, but during virus outbreaks DIVA responses are masked by wild-type virus preventing accurate serodiagnosis. Previous work by the authors has established the potential for metabolomic profiling to reveal metabolites associated with systemic immune responses to vaccination. The current study builds on this work by demonstrating for the first time the potential to use plasma metabolite profiling to differentiate between vaccinated and non-vaccinated animals following infection-challenge. Male Holstein Friesian calves were intranasally vaccinated (Pfizer RISPOVAL®PI3+RSV) and subsequently challenged with Bovine Parainfluenza Virus type-3 (BPI3V) via nasal inoculation. Metabolomic plasma profiling revealed that viral challenge led to a shift in acquired plasma metabolite profiles from day 2 to 20 p.i., with 26 metabolites identified whose peak intensities were significantly different following viral challenge depending on vaccination status. Elevated levels of biliverdin and bilirubin and decreased 3-indolepropionic acid in non-vaccinated animals at day 6 p.i. may be associated with increased oxidative stress and reactive oxygen scavenging at periods of peak virus titre. During latter stages of infection, increased levels of N-[(3α,5ß,12α)-3,12-dihydroxy-7,24-dioxocholan-24-yl]glycine and lysophosphatidycholine and decreased enterolactone in non-vaccinated animals may reflect suppression of innate immune response mechanisms and progression to adaptive immune responses. Levels of hexahydrohippurate were also shown to be significantly elevated in non-vaccinated animals from days 6 to 20 p.i. These findings demonstrate the potential of metabolomic profiling to identify plasma markers that can be employed in disease diagnostic applications to both differentially identify infected non-vaccinated animals during disease outbreaks and provide greater information on the health status of infected animals.

A real time metabolomic profiling approach to detecting fish fraud using rapid evaporative ionisation mass spectrometry.

INTRODUCTION: Fish fraud detection is mainly carried out using a genomic profiling approach requiring long and complex sample preparations and assay running times. Rapid evaporative ionisation mass spectrometry (REIMS) can circumvent these issues without sacrificing a loss in the quality of results. OBJECTIVES: To demonstrate that REIMS can be used as a fast profiling technique capable of achieving accurate species identification without the need for any sample preparation. Additionally, we wanted to demonstrate that other aspects of fish fraud other than speciation are detectable using REIMS. METHODS: 478 samples of five different white fish species were subjected to REIMS analysis using an electrosurgical knife. Each sample was cut 8-12 times with each one lasting 3-5 s and chemometric models were generated based on the mass range m/z 600-950 of each sample. RESULTS: The identification of 99 validation samples provided a 98.99% correct classification in which species identification was obtained near-instantaneously (≈ 2 s) unlike any other form of food fraud analysis. Significant time comparisons between REIMS and polymerase chain reaction (PCR) were observed when analysing 6 mislabelled samples demonstrating how REIMS can be used as a complimentary technique to detect fish fraud. Additionally, we have demonstrated that the catch method of fish products is capable of detection using REIMS, a concept never previously reported. CONCLUSIONS: REIMS has been proven to be an innovative technique to help aid the detection of fish fraud and has the potential to be utilised by fisheries to conduct their own quality control (QC) checks for fast accurate results.

Distribution of serum levels of persistent organic pollutants, heterocyclic aromatic amine theoretical intake and nutritional cofactors in a semi-rural island population.

Persistent organic pollutant (POP) exposure is strongly associated with negative health effects in humans. Heterocyclic aromatic amines (HAAs) are formed during high temperature cooking of foods (i.e. meat and fish). Human exposure to HAA is through food consumption and from similar food groups to POPs. A study of serum samples for POPs in a non-occupational exposed population (n = 149, age range 18-80 years, recruited in 2012) and comparison with estimated HAA daily intake calculations based on food diaries were undertaken. Three different age groups (group 1, 18-29 years; group 2, 30-44 years; and group 3, 45-80 years) were used to explore possible relationships between POP levels present in blood, HAA intake and nutritional cofactors. Significant differences (p < 0.05) between groups (1 and 3) for POP levels were found for p,p'-DDE, polychlorinated biphenyl (PCB) 153, PCB 138 and the sum of PCBs. A similar trend was found between groups 2 and 3 for PCB 153 and sum of PCBs. Significant differences were found between groups 1 and 3 and groups 2 and 3 for HAA intake., i.e. HAA intake was lowest in those of middle age, which may well reflect a different pathway of human exposure between HAA and POPs through the diet preferences.

Untargeted metabolomic analysis of human serum samples associated with different levels of red meat consumption: A possible indicator of type 2 diabetes?

Red meat consumption has been associated with negative health effects. A study to identify biomarkers of meat consumption was undertaken using serum samples collected from combining high resolution mass spectrometry (UPLC-QTof-MS) and chemometrics. Using orthogonal partial last-squares discriminant analysis (OPLS-DA), multivariate models were created for both modes of acquisition (ESI-/ESI+) and red meat intake classes (YES/NO). In the serum samples, a total 3280 and 3225 ions of interest were detected in positive and negative modes, respectively. Of these, 62 were found to be significantly different (p<0.05) between the two groups. Glycerophospholipids as well as other family lipids, such as lysophospholipids or sphingomyelin, were found significantly (p<0.05) different between yes and no red meat intake groups. This study has shown metabolomics fingerprints have the capability to identify potential biomarkers of red meat consumption, as well as possible health risk factors (e.g., key metabolic families related to the risk of development type 2 diabetes).

Untargeted metabolomic analysis of human serum samples associated with exposure levels of Persistent organic pollutants indicate important perturbations in Sphingolipids and Glycerophospholipids levels.

Persistent organic pollutants (POPs) are distributed globally and are associated with adverse health effects in humans. A study combining gas chromatography-mass spectrometry (GC-MS), high resolution mass spectrometry (UPLC-QTof-MS) and chemometrics for the analysis of adult human serum samples was undertaken. Levels of serum POPs found were in the low range of what has been reported in similar populations across Europe (median 33.84 p, p'-DDE, 3.02 HCB, 83.55 ß-HCH, 246.62 PCBs ng/g lipids). Results indicated that compounds concentrations were significantly different between the two groups of POPs exposure (high vs low) and classes (DDE, ß-HCH, HCB, PCBs). Using orthogonal partial last-squares discriminant analysis (OPLS-DA), multivariate models were created for both modes of acquisition and POPs classes, explaining the maximum amount of variation between sample groups (positive mode R2 = 98-90%; Q2 = 94-75%; root mean squared error of validation (RMSEV) = 12-20%: negative mode R2 = 98-91%; Q2 = 94-81%; root mean squared error of validation (RMSEV) = 10-19%. In the serum samples analyzed, a total 3076 and 3121 ions of interest were detected in positive and negative mode respectively. Of these, 40 were found to be significantly different (p < 0.05) between exposure levels. Sphingolipids and Glycerophospholipids lipids families were identified and found significantly (p < 0.05) different between high and low POPs exposure levels. This study has shown that the elucidation of metabolomic fingerprints may have the potential to be classified as biomarkers of POPs exposure.

ß-methylamino-L-alanine (BMAA) is not found in the brains of patients with confirmed Alzheimer's disease.

Controversy surrounds the proposed hypothesis that exposure to ß-methylamino-L-alanine (BMAA) could play a role in various neurodegenerative conditions including Alzheimer's disease (AD). Here we present the results of the most comprehensive scientific study on BMAA detection ever undertaken on brain samples from patients pathologically confirmed to have suffered from AD, and those from healthy volunteers. Following the full validation of a highly accurate and sensitive mass spectrometric method, no trace of BMAA was detected in the diseased brain or in the control specimens. This contradicts the findings of other reports and calls into question the significance of this compound in neurodegenerative disease. We have attempted to explain the potential causes of misidentification of BMAA in these studies.

Non-thermal Plasma Exposure Rapidly Attenuates Bacterial AHL-Dependent Quorum Sensing and Virulence.

The antimicrobial activity of atmospheric pressure non-thermal plasma has been exhaustively characterised, however elucidation of the interactions between biomolecules produced and utilised by bacteria and short plasma exposures are required for optimisation and clinical translation of cold plasma technology. This study characterizes the effects of non-thermal plasma exposure on acyl homoserine lactone (AHL)-dependent quorum sensing (QS). Plasma exposure of AHLs reduced the ability of such molecules to elicit a QS response in bacterial reporter strains in a dose-dependent manner. Short exposures (30-60 s) produce of a series of secondary compounds capable of eliciting a QS response, followed by the complete loss of AHL-dependent signalling following longer exposures. UPLC-MS analysis confirmed the time-dependent degradation of AHL molecules and their conversion into a series of by-products. FT-IR analysis of plasma-exposed AHLs highlighted the appearance of an OH group. In vivo assessment of the exposure of AHLs to plasma was examined using a standard in vivo model. Lettuce leaves injected with the rhlI/lasI mutant PAO-MW1 alongside plasma treated N-butyryl-homoserine lactone and n-(3-oxo-dodecanoyl)-homoserine lactone, exhibited marked attenuation of virulence. This study highlights the capacity of atmospheric pressure non-thermal plasma to modify and degrade AHL autoinducers thereby attenuating QS-dependent virulence in P. aeruginosa.

Identification of the Species of Origin for Meat Products by Rapid Evaporative Ionization Mass Spectrometry.

Increasingly abundant food fraud cases have brought food authenticity and safety into major focus. This study presents a fast and effective way to identify meat products using rapid evaporative ionization mass spectrometry (REIMS). The experimental setup was demonstrated to be able to record a mass spectrometric profile of meat specimens in a time frame of <5 s. A multivariate statistical algorithm was developed and successfully tested for the identification of animal tissue with different anatomical origin, breed, and species with 100% accuracy at species and 97% accuracy at breed level. Detection of the presence of meat originating from a different species (horse, cattle, and venison) has also been demonstrated with high accuracy using mixed patties with a 5% detection limit. REIMS technology was found to be a promising tool in food safety applications providing a reliable and simple method for the rapid characterization of food products.

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach.

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

Determination of the Mycotoxin Content in Distiller's Dried Grain with Solubles Using a Multianalyte UHPLC-MS/MS Method.

There are more than 300 potential mycotoxins that can contaminate food and feed and cause adverse effects in humans and animals. The data on the co-occurrence of mycotoxins in novel animal feed materials, such as distiller's dried grain with solubles (DDGS), are limited. Thus, a UHPLC-MS/MS method for the quantitation of 77 mycotoxins and other fungal metabolites was used to analyze 169 DDGS samples produced from wheat, maize, and barley and 61 grain samples. All DDGS samples analyzed were contaminated with 13-34 different mycotoxins. Fumonisins were present in all 52 maize DDGS samples (81.0-6890 µg/kg for fumonisin B1), and deoxynivalenol was present in all 99 wheat DDGS samples (39.3-1120 µg/kg). A number of co-occurring mycotoxins were also identified. Due to the high co-occurrence of mycotoxins, routine screening of the animal feed ingredients is highly recommended to allow the highlighted risks to be effectively managed.

Identification of systemic immune response markers through metabolomic profiling of plasma from calves given an intra-nasally delivered respiratory vaccine.

Vaccination procedures within the cattle industry are important disease control tools to minimize economic and welfare burdens associated with respiratory pathogens. However, new vaccine, antigen and carrier technologies are required to combat emerging viral strains and enhance the efficacy of respiratory vaccines, particularly at the point of pathogen entry. New technologies, specifically metabolomic profiling, could be applied to identify metabolite immune-correlates representative of immune protection following vaccination aiding in the design and screening of vaccine candidates. This study for the first time demonstrates the ability of untargeted UPLC-MS metabolomic profiling to identify metabolite immune correlates characteristic of immune responses following mucosal vaccination in calves. Male Holstein Friesian calves were vaccinated with Pfizer Rispoval® PI3 + RSV intranasal vaccine and metabolomic profiling of post-vaccination plasma revealed 12 metabolites whose peak intensities differed significantly from controls. Plasma levels of glycocholic acid, N-[(3α,5ß,12α)-3,12-Dihydroxy-7,24-dioxocholan-24-yl]glycine, uric acid and biliverdin were found to be significantly elevated in vaccinated animals following secondary vaccine administration, whereas hippuric acid significantly decreased. In contrast, significant upregulation of taurodeoxycholic acid and propionylcarnitine levels were confined to primary vaccine administration. Assessment of such metabolite markers may provide greater information on the immune pathways stimulated from vaccine formulations and benchmarking early metabolomic responses to highly immunogenic vaccine formulations could provide a means for rapidly assessing new vaccine formulations. Furthermore, the identification of metabolic systemic immune response markers which relate to specific cell signaling pathways of the immune system could allow for targeted vaccine design to stimulate key pathways which can be assessed at the metabolic level.

Untargeted metabolomic analysis of human plasma indicates differentially affected polyamine and L-arginine metabolism in mild cognitive impairment subjects converting to Alzheimer's disease.

This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7µm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.

Metabolomic profiling of in vivo plasma responses to dioxin-associated dietary contaminant exposure in rats: implications for identification of sources of animal and human exposure.

Dioxin contamination of the food chain typically occurs when cocktails of combustion residues or polychlorinated biphenyl (PCB) containing oils become incorporated into animal feed. These highly toxic compounds are bioaccumulative with small amounts posing a major health risk. The ability to identify animal exposure to these compounds prior to their entry into the food chain may be an invaluable tool to safeguard public health. Dioxin-like compounds act by a common mode of action and this suggests that markers or patterns of response may facilitate identification of exposed animals. However, secondary co-contaminating compounds present in typical dioxin sources may affect responses to compounds. This study has investigated for the first time the potential of a metabolomics platform to distinguish between animals exposed to different sources of dioxin contamination through their diet. Sprague-Dawley rats were given feed containing dioxin-like toxins from hospital incinerator soot, a common PCB oil standard and pure 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (normalized at 0.1 µg/kg TEQ) and acquired plasma was subsequently biochemically profiled using ultra high performance liquid chromatography (UPLC) quadropole time-of-flight-mass spectrometry (QTof-MS). An OPLS-DA model was generated from acquired metabolite fingerprints and validated which allowed classification of plasma from individual animals into the four dietary exposure study groups with a level of accuracy of 97-100%. A set of 24 ions of importance to the prediction model, and which had levels significantly altered between feeding groups, were positively identified as deriving from eight identifiable metabolites including lysophosphatidylcholine (16:0) and tyrosine. This study demonstrates the enormous potential of metabolomic-based profiling to provide a powerful and reliable tool for the detection of dioxin exposure in food-producing animals.

Comparison of sample preparation methods, validation of an UPLC-MS/MS procedure for the quantification of tetrodotoxin present in marine gastropods and analysis of pufferfish.

Tetrodotoxin (TTX) is one of the most potent marine neurotoxins reported. The global distribution of this toxin is spreading with the European Atlantic coastline now being affected. Climate change and increasing pollution have been suggested as underlying causes for this. In the present study, two different sample preparation techniques were used to extract TTX from Trumpet shells and pufferfish samples. Both extraction procedures (accelerated solvent extraction (ASE) and a simple solvent extraction) were shown to provide good recoveries (80-92%). A UPLC-MS/MS method was developed for the analysis of TTX and validated following the guidelines contained in the Commission Decision 2002/657/EC for chemical contaminant analysis. The performance of this procedure was demonstrated to be fit for purpose. This study is the first report on the use of ASE as a mean for TTX extraction, the use of UPLC-MS/MS for TTX analysis, and the validation of this method for TTX in gastropods.

Investigation of the human brain metabolome to identify potential markers for early diagnosis and therapeutic targets of Alzheimer's disease.

A study combining high resolution mass spectrometry (liquid chromatography-quadrupole time-of-flight-mass spectrometry, UPLC-QTof-MS) and chemometrics for the analysis of post-mortem brain tissue from subjects with Alzheimer's disease (AD) (n = 15) and healthy age-matched controls (n = 15) was undertaken. The huge potential of this metabolomics approach for distinguishing AD cases is underlined by the correct prediction of disease status in 94-97% of cases. Predictive power was confirmed in a blind test set of 60 samples, reaching 100% diagnostic accuracy. The approach also indicated compounds significantly altered in concentration following the onset of human AD. Using orthogonal partial least-squares discriminant analysis (OPLS-DA), a multivariate model was created for both modes of acquisition explaining the maximum amount of variation between sample groups (Positive Mode-R2 = 97%; Q2 = 93%; root mean squared error of validation (RMSEV) = 13%; Negative Mode-R2 = 99%; Q2 = 92%; RMSEV = 15%). In brain extracts, 1264 and 1457 ions of interest were detected for the different modes of acquisition (positive and negative, respectively). Incorporation of gender into the model increased predictive accuracy and decreased RMSEV values. High resolution UPLC-QTof-MS has not previously been employed to biochemically profile post-mortem brain tissue, and the novel methods described and validated herein prove its potential for making new discoveries related to the etiology, pathophysiology, and treatment of degenerative brain disorders.