Visualization of the Distance among Fishes by MALDI MS for Rapid Determination of the Taxonomic Status of Fish Fillets

Taxonomic identification of Morocco scorpions using MALDI-MS fingerprints of venom proteomes and computational modeling

The venom of scorpions has been the subject of numerous studies. However, their taxonomic identification is not a simple task, leading to misidentifications. This study aims to provide a practical approach for identifying scorpions based on the venom molecular mass fingerprint (MFP). Specimens (251) belonging to fifteen species were collected from different regions in Morocco. Their MFPs were acquired using MALDI-MS. These were used as a training dataset to generate predictive models and a library of mean spectral profiles using software programs based on machine learning. The computational model achieved an overall recognition capability of 99 % comprising 32 molecular signatures. The models and the library were tested using a new dataset for external validation and to evaluate their capability of identification. We recorded an accuracy classification with an average of 97 % and 98 % for the computational models and the library, respectively. To our knowledge, this is the first attempt to demonstrate the potential of MALDI-MS and MFPs to generate predictive models capable of discriminating scorpions from family to species levels, and to build a library of species-specific spectra. These promising results may represent a proof of concept towards developing a reliable approach for rapid molecular identification of scorpions in Morocco. SIGNIFICANCE OF THE STUDY: With their clinical importance, scorpions may constitute a desirable study model for many researchers. The first step in studying scorpion is systematically identifying the species of interest. However, it can be a difficult task, especially for the non-experts. The taxonomy of scorpions is primarily based on morphometric characters. In Morocco, the high number of species and subspecies mainly endemic, and the morphological similarities between different species may result in false identifications. This was observed in many reports according to the scorpion experts. In this study, we describe a reliable practical approach for identifying scorpions based on the venom molecular mass fingerprints (MFPs). By using two software programs based on machine learning, we have demonstrated that these MFPs contains sufficient inter-specific variation to differentiate between the scorpion species mentioned in this study with a good accuracy. Using a drop of venom, this new approach could be a rapid, accurate and cost saving method for taxonomic identification of scorpions in Morocco.

Quantum dots (QDs) attached magnetic beads (MBs) for on-chip efficient capture and detection of bacteria in ready-to-eat (RTE) foods

In this study, we established a versatile and simple magnetic-assisted microfluidic method for fast bacterial detection. Quantum dots (QDs) were loaded onto magnetic beads (MBs) to construct performance enhanced on-chip capture of bacteria. Escherichia coli (E. coli), as a model bacterium was studied. CdSe QDs were deposited onto the surface of Fe3O4 MBs through layer-by-layer self-assembly to enhance the loading of antibodies (Abs). MBs functionalized with anti-E. coli antibody molecules in a micropillar-based microfluidic chip were utilized to capture E. coli, and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used for characterization of captured bacteria. This method was found capable of specifically isolating E. coli within the range of 1.0 to 1.0 × 109 CFU/mL, having a detection limit (LOD) of 10 CFU/mL. The average similarity score among mass spectra for the bacterial capture obtained in independent experiments is calculated as 0.97 ± 0.01 (n = 3), which shows this work's excellent reproducibility for bacterial capture. Bacterial growth on ready-to-eat (RTE) foods during its time of storage was successfully monitored. The present protocol has promising potential for microbial control and pathogen detection in the food industry.

MALDI-ToF MS and chemometric analysis as a tool for identifying wild and farmed salmon

In this study, the difference between wild and farmed salmon production was successfully profiled and differentiated by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-ToF MS) combined with chemometric analysis. The established method based on multivariate analysis mainly involved principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) as the screening and verifying tools to provide insights into the distinctive features found in wild and farmed salmon products, respectively. The discrimination between farmed and wild salmon was accomplished with 100% classification accuracy using chemometric models, 100% identification accuracy was also achieved in distinguishing wild Salmo salar and Oncorhynchus nerka samples. The results of the present work suggest that the proposed method could serve as a reference for detecting salmon fraud relating to wild or farmed production and expand the application of MALDI-ToF technology further into food authenticity applications.

Bayesian Fusion Model Enhanced Codfish Classification Using Near Infrared and Raman Spectrum

In this study, a Bayesian-based decision fusion technique was developed for the first time to quickly and non-destructively identify codfish using near infrared (NIRS) and Raman spectroscopy (RS). NIRS and RS spectra from 320 codfish samples were collected, and separate partial least squares discriminant analysis (PLS-DA) models were developed to establish the relationship between the raw data and cod identity for each spectral technique. Three decision fusion methods: decision fusion, data layer or feature layer, were tested and compared. The decision fusion model based on the Bayesian algorithm (NIRS-RS-B) was developed on the optimal discrimination features of NIRS and RS data (NIRS-RS) extracted by the PLS-DA method whereas the other fusion models followed conventional, non-Bayesian approaches. The Bayesian model showed enhanced classification metrics (92% sensitivity, 98% specificity, 98% accuracy) that were significantly superior to those demonstrated by any of other two spectroscopic methods (NIRS, RS) and the two data fusion methods (data layer fused, NIRS-RS-D, or feature layer fused, NIRS-RS-F). This novel proposed approach can provide an alternative classification for codfish and potentially other food speciation cases.

Spectroscopic techniques for authentication of animal origin foods

Milk and milk products, meat, fish and poultry as well as other animal derived foods occupy a pronounced position in human nutrition. Unfortunately, fraud in the food industry is common, resulting in negative economic consequences for customers as well as significant threats to human health and the external environment. As a result, it is critical to develop analytical tools that can quickly detect fraud and validate the authenticity of such products. Authentication of a food product is the process of ensuring that the product matches the assertions on the label and complies with rules. Conventionally, various comprehensive and targeted approaches like molecular, chemical, protein based, and chromatographic techniques are being utilized for identifying the species, origin, peculiar ingredients and the kind of processing method used to produce the particular product. Despite being very accurate and unimpeachable, these techniques ruin the structure of food, are labor intensive, complicated, and can be employed on laboratory scale. Hence the need of hour is to identify alternative, modern instrumentation techniques which can help in overcoming the majority of the limitations offered by traditional methods. Spectroscopy is a quick, low cost, rapid, non-destructive, and emerging approach for verifying authenticity of animal origin foods. In this review authors will envisage the latest spectroscopic techniques being used for detection of fraud or adulteration in meat, fish, poultry, egg, and dairy products. Latest literature pertaining to emerging techniques including their advantages and limitations in comparison to different other commonly used analytical tools will be comprehensively reviewed. Challenges and future prospects of evolving advanced spectroscopic techniques will also be descanted.

The use of various statistical methods for authenticity and detection of adulteration in fish and seafood

Various methodologies including genetic analyses, morphometrics, proteomics, lipidomics, metabolomics, etc. are now used or being developed to authenticate fish and seafood. Such techniques usually lead to the generation of enormous amounts of data. The analysis and interpretation of this information can be particularly challenging. Statistical techniques are therefore commonly used to assist in analyzing these data, visualizing trends and differences and extracting conclusions. This review article aims at presenting and discussing statistical methods used in studies on fish and seafood authenticity and adulteration, allowing researchers to consider their options based on previous successes/failures but also offering some recommendations about the future of such techniques. Techniques such as PCA, AMOVA and FST statistics, that allow the differentiation of genetic groups, or techniques such as MANOVA that allow large data sets of morphometric characteristics or elemental differences to be analyzed are discussed. Furthermore, methods such as cluster analysis, DFA, CVA, CDA and heatmaps/Circos plots that allow samples to be differentiated based on their geographical origin are also reviewed and their advantages and disadvantages as found in past studies are given. Finally, mathematical simulations and modeling are presented in a detailed review of studies using them, together with their advantages and limitations.

The investigation of storage situation of fish muscle via the analysis of its exudate by MALDI-TOF MS

The potential of MALDI-TOF MS was investigated in terms of its capability to determine the change of exudates of fish muscle with different freeze-thaw cycles (0, 1 and 2), and frozen storage periods. The exudates were collected from dead chilled marine fish species, large yellow croacker (Larimichthys crocea, LC) and freshly slaughtered freshwater fish species, Japanese seabass (Lateolabrax japonicus) to be studied as models. 109 proteins, in which, 32 are extracellular proteins, and 15 are intracellular proteins, were identified by analyzing exudate of LC using MALDI-TOF MS and HPLC-MS/MS. The results show that the present method may be able to determine the change of fish muscle foods in a more sensitive mode than K value indicated quality control. The feasibility of verifying the storage situation of fish sample was performed by analyzing fish samples obtained from the local market. It is promising to estimate the storage situation of fishery products or other animal muscle foods by analyzing their muscle exudates based on the presently developed strategy.

Imaging Method by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS) for Tissue or Tumor: A Mini Review

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is an advanced technique that uses minimum fragmented ions from complex molecules for mass spectrometry (MS) analysis (tissue profiling by mass spectrometry). It is able to analyze spatially resolved tissue or tumor sections at the molecular level. It has become a valuable tool for tumor and tissue imaging, due to its ease of operation and high mass resolution, but it still has vast room for development in the instrumentation of larger proteins in some tissues. In this review, we focus on the main components of MALDI-MS instrumentation, sample handling and processing, the working principle of MALDI-MS, and its applications in diagnostic and prognostic assessments, tumor removal and drug development. Although it is less effective at detecting larger proteins in some tissues, it still shows huge potential because of its advancements in instrumentation and processing protocols. This article may benefit those who have interests in MALDI-MS for tissue or tumor imaging.

Rapid Identification between Two Fish Species Using UV-Vis Spectroscopy for Substitution Detection

Fish species substitution and fraud has become a worldwide economic issue in the seafood industry. In this study, an ultraviolet-visible (UV-Vis) spectroscopy-based method was developed for the identification of fish samples. Sixty fish samples from twelve commonly consumed fish species in China were analyzed as models to testify the protocol. The obtained results show that UV-Vis spectroscopy combined with chemometric analysis, such as principal component analysis (PCA), can accurately distinguish two fish species by boiling fish tissue sample in trifluoroacetic acid (TFA) solution for 2 min and analyzing the resultant samples using a UV-Vis spectrometer. The developed strategy was successfully applied to the classification and identification of fish samples on the market. It is a promising strategy that can be applied to the classification and authenticity testing of closely related fish species in order to detect and recognize fish substitution.

Potential value and chemical characterization of gut microbiota derived nitrogen containing metabolites in feces from Periplaneta americana (L.) at different growth stages

The American cockroach, Periplaneta americana (L.), is able to highly survive in various complicated environments around the globe, and often considered as a pest. In contrast, billions of P. americana have been massively reared in China and extensively used as a medicinal insect, due to its function for preventing and treating ulceration and heart failure. Considering the possibility that microbiota-derived metabolites could be an effective source to identify promising candidate drugs, we attempted to establish a rapid method for simultaneous determination of gut microbiota metabolites from medicinal insects. In this study, network pharmacology approach and ultra-performance liquid chromatography (UPLC) technique were employed to reveal the potential pharmacological activity and dynamics variation of nitrogen-containing metabolites (NCMs) originated from the gut microbiota of breeding P. americana at different growth stages. A metabolites-targets-diseases network showed that NCMs are likely to treat diseases such as ulceration and cancer. The analysis of NCMs' content with the growth pattern of P. americana indicated that the content of NCMs declined with P. americana aging. Both principal component analysis and orthogonal partial least squares discriminant analysis suggested that 8-hydroxy-2-quinolinecarboxylic acid and 8-hydroxy-3,4-dihydro-2(1H)-quinolinone are the potential differential metabolic markers for discriminating between nymphs and adults of P. americana. Moreover, the developed UPLC method showed an excellent linearity (R² > 0.999), repeatability (RSD < 2.6%), intra- and inter-day precisions (RSD < 2.2%), and recovery (95.5%–99.0%). Collectively, the study provides a valuable strategy for analyzing gut microbiota metabolites from insects and demonstrates the prospects for discovering novel drug candidates from the feces of P. americana.

Relationship between Micromolecules and Quality Changes of Tilapia Fillets after Partial Freezing Treatment with Polyphenols

The study investigated the main characteristic micromolecular changes in tilapia fillets after partial freezing treatment with polyphenols by ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) analysis. A total of 2121 metabolite ion features were identified. The result suggested that procyanidin treatment increased the sweet, salty, and thick peptides' contents and suppressed the formation of bitter peptides. The levels of cis-4-octenedioic acid, 2-amino-heptanoic acid, indoleacrylic acid, and 2-amino-3-methyl-1-butanol in polyphenol treatments were significantly lower compared to those in the control group (P < 0.05), which delayed the formation of micromolecule of acids and alcohols associated with spoilage and inhibited the protein and lipid oxidation and degradation. Polyphenol treatments suppressed the formation of biogenic amines (lower levels of spermidine and 1-naphthylacetylspermine) and reduced fillet quality deterioration. It provided critical novel insights into the understanding of the molecular mechanism for inhibiting the quality deterioration of fillets treated with polyphenols during storage.