Gas Chromatography-Mass Spectrometry-Based Metabolite Profiling for the Assessment of Freshness in Gilthead Sea Bream (Sparus aurata)

Ammonia/pH super-sensitive colorimetric labels based on gellan gum, sodium carboxymethyl cellulose, and dyes for monitoring freshness of lamb meat

This study aimed to develop an ammonia and pH super-sensitive label by incorporating methyl red and bromothymol blue (MR-BTB, MB) into gellan gum/sodium carboxymethyl cellulose (GG/CMC-Na, GC). Furthermore, E-nose as an auxiliary tool combined with the labels to monitor meat freshness. Results showed that MB had more color change than pure MR or BTB, and the detection limit of ammonia about the MR-BTB (1:2) group was only 2.82 ppm. The addition of MB significantly increased tensile strength, moisture content, and water solubility, but decreased elongation at break and transmittance of the GC label (p < 0.05). The result of FTIR and SEM indicated the formation of hydrogen bonds and well compatibility between MB and GC. Furthermore, the color of the GC-10.0MB label was constantly obviously changing during meat storage, indicating that the GC-10.0MB label had great potential for monitoring the freshness of the lamb meat. A high correlation was found between ΔE of GC-10.0MB label and TVB-N (R2 = 0.9092) and pH (R2 = 0.9114) of meat. Interestingly, the high correlation between ΔE of GC-10.0 MB label and the response value of S2 (R2 = 0.7531), S6 (R2 = 0.9921), and S7 sensor (R2 = 0.8325) of E-nose was also found.

Metabolomics-based analysis of the diatom Cheatoceros tenuissimus combining NMR and GC-MS techniques

Metabolomics, a recent addition to omics sciences, studies small molecules across plants, animals, humans, and marine organisms. Nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC-MS) are widely used in those studies, including microalgae metabolomics. NMR is non-destructive and highly reproducible but has limited sensitivity, which could be supplemented by joining GC-MS analysis. Extracting metabolites from macromolecules requires optimization for trustworthy results. Different extraction methods yield distinct profiles, emphasizing the need for optimization. The results indicated that the optimized extraction procedure successfully identified NMR and GC-MS-based metabolites in MeOH, CHCl3, and H2O extraction solvents. The findings represented the spectral information related to carbohydrates, organic molecules, and amino acids from the water-soluble metabolites fraction and a series of fatty acid chains, lipids, and sterols from the lipid fraction. Our study underscores the benefit of combining NMR and GC-MS techniques to comprehensively understand microalgae metabolomes, including high and low metabolite concentrations and abundances.•In this study, we focused on optimizing the extraction procedure and combining NMR and GC-MS techniques to overcome the low NMR sensitivity and the different detected range limits of NMR and GC-MS.•We explored metabolome diversity in a tropical strain of the small cells' diatom Cheatoceros tenuissimus.

Effect of low-voltage electrostatic field-assisted partial freezing on large yellow croaker protein properties and metabolomic analysis during storage

BACKGROUND

Large yellow croaker is highly perishable during storage because of high protein and moisture content. The degradation of the fish is mainly attributed to microbial growth and enzyme activity, so it is important to find an efficient storage method to extend its shelf life.

METHODOLOGY

This study investigated the effect of a low-voltage electrostatic field combined with partial freezing treatment on the physicochemical properties of myofibrillar protein (MP) and metabolomic analysis of large yellow croaker during preservation. The samples in chilled storage (C), partial freezing storage (PF) and 6 kV/m low-voltage electrostatic field partial freezing storage (LVEF-PF) were analyzed during an 18 day storage period.

RESULTS

In comparison with the C and PF groups, LVEF-PF delayed the oxidation of MP by inhibiting the formation of carbonyl groups (2.25 nmol/mg pro), and maintaining higher sulfhydryl content (29.73 nmol/mg pro). Fourier transform infrared (FTIR) spectroscopy and fluorescence spectroscopy analysis also demonstrated that the LVEF-PF treatment maintained the stability of the protein structure by increasing the a-helix ratio (19.88%) and reducing the random coil ratio (17.83%). Scanning electron microscopy showed that, compared with the LVEF-PF group, there was more degeneration and aggregation of MP in the C and PF groups after 18 days' storage. The results of untargeted metabolomic analysis showed that 415 kinds of differential metabolites were identified after storage, and the difference levels of differential metabolites were least between the samples treated with LVEF-PF stored on the ninth day and the fresh samples. The main differential metabolic pathways during storage were amino acid metabolism and lipid metabolism.

CONCLUSION

The LVEF-PF treatment could maintain the stability of myofibrillar protein in large yellow croaker during storage. These results showed a potential application of the LVEF-PF method for aquatic product preservation. © 2023 Society of Chemical Industry.

Current applications and future trends of artificial senses in fish freshness determination: A review

Fish is a highly demanding food product and the determination of fish freshness is crucial as it is a fundamental factor in fish quality. Therefore, the fishery industry has been working on developing rapid fish freshness determination methods to monitor freshness levels. Artificial senses that mimic human senses are developed as convenient emerging technologies for fish freshness determination. Computer vision, electronic nose (e-nose), and electronic tongue (e-tongue) are the emerging artificial senses for fish freshness determination. This review article is uniquely worked upon to investigate the current applications of the artificial senses in fish freshness determination while describing the steps, and fundamental principles behind each artificial sense, comparing them with their advantages and limitations, and future trends related to fish freshness determination. Among the artificial senses, computer vision determines the freshness of fish in a completely nondestructive way while the e-tongue determines the freshness of fish in a completely destructive way. There are developed e-noses for fish freshness determination in both destructive and nondestructive ways. By analyzing visual cues such as color, computer vision systems can assess fish quality without the need for physical contact and it makes computer vision suitable for large-scale industrial fish quality assessing applications. Overall, this review study reveals artificial senses as a proven replacement for traditional sensory panels in determining fish freshness precisely and conveniently. As future trends, there is a demand for developing applications for consumers to determine fish freshness based on artificial senses.

Identification of Illicit Conservation Treatments in Fresh Fish by Micro-Raman Spectroscopy and Chemometric Methods

In the field of food control for fresh products, the identification of foods subjected to illicit conservation treatments to extend their shelf life is fundamental. Fresh fish products are particularly subjected to this type of fraud due to their high commercial value and the fact that they often have to be transported over a long distance, keeping their organoleptic characteristics unaltered. Treatments of this type involve, e.g., the bleaching of the meat and/or the momentary abatement of the microbial load, while the degradation process continues. It is therefore important to find rapid methods that allow the identification of illicit treatments. The study presented here was performed on 24 sea bass samples divided into four groups: 12 controls (stored on ice in the fridge for 3 or 24 h), and 12 treated with a Cafodos-like solution for 3 or 24 h. Muscle and skin samples were then characterized using micro-Raman spectroscopy. The data were pre-processed by smoothing and taking the first derivative and then PLS-DA models were built to identify short- and long- term effects on the fish's muscle and skin. All the models provided the perfect classification of the samples both in fitting and cross-validation and an analysis of the bands responsible for the effects was also reported. To the best of the authors' knowledge, this is the first time Raman spectroscopy has been applied for the identification of a Cafodos-like illicit treatment, focusing on both fish muscle and skin evaluation. The procedure could pave the way for a future application directly on the market through the use of a portable device.

Tapping into Plant-Microbiome Interactions through the Lens of Multi-Omics Techniques

This review highlights the pivotal role of root exudates in the rhizosphere, especially the interactions between plants and microbes and between plants and plants. Root exudates determine soil nutrient mobilization, plant nutritional status, and the communication of plant roots with microbes. Root exudates contain diverse specialized signaling metabolites (primary and secondary). The spatial behavior of these metabolites around the root zone strongly influences rhizosphere microorganisms through an intimate compatible interaction, thereby regulating complex biological and ecological mechanisms. In this context, we reviewed the current understanding of the biological phenomenon of allelopathy, which is mediated by phytotoxic compounds (called allelochemicals) released by plants into the soil that affect the growth, survival, development, ecological infestation, and intensification of other plant species and microbes in natural communities or agricultural systems. Advances in next-generation sequencing (NGS), such as metagenomics and metatranscriptomics, have opened the possibility of better understanding the effects of secreted metabolites on the composition and activity of root-associated microbial communities. Nevertheless, understanding the role of secretory metabolites in microbiome manipulation can assist in designing next-generation microbial inoculants for targeted disease mitigation and improved plant growth using the synthetic microbial communities (SynComs) tool. Besides a discussion on different approaches, we highlighted the advantages of conjugation of metabolomic approaches with genetic design (metabolite-based genome-wide association studies) in dissecting metabolome diversity and understanding the genetic components of metabolite accumulation. Recent advances in the field of metabolomics have expedited comprehensive and rapid profiling and discovery of novel bioactive compounds in root exudates. In this context, we discussed the expanding array of metabolomics platforms for metabolome profiling and their integration with multivariate data analysis, which is crucial to explore the biosynthesis pathway, as well as the regulation of associated pathways at the gene, transcript, and protein levels, and finally their role in determining and shaping the rhizomicrobiome.

Health risks of inhalation exposure to BTEX in a municipal wastewater treatment plant in Middle East city: Shiraz, Iran

Benzene, toluene, ethylbenzene, and xylene, known as BTEX, adversely affect human health. This study aimed to measure BTEX concentration and assess the health risk through inhalation exposure to these compounds in a municipal wastewater treatment plant. The ambient air samples were collected using the active sampling method in summer and winter. Sampling sites were close to wastewater treatment units, including bar screen & grit chamber (Site-1), aeration tank & secondary clarifiers (Site-2), anaerobic sludge digester (Site-3), and office & control building (Site-4). Results indicate that the mean levels of benzene and toluene in winter were higher than in summer. The levels of benzene and toluene were below the occupational exposure levels of the American Conference of Governmental Industrial Hygienists (ACGIH) and Occupational Safety and Health Administration (OSHA). The carcinogenic risk (CR) and hazard quotient (HQ) were assessed using the United States Environmental Protection Agency (U.S.EPA) method, and Monte Carlo simulation (MCS) was applied to quantify the uncertainty and sensitivity analysis. The CRs for all sampling sites were below the U.S.EPA threshold limit (1.0 × 10^-4). The HQ values for benzene nearby Site-2 were above 1.0, indicating inhalation exposure could pose a health hazard. Besides, the HQ results for exposure to toluene in all sampling sites were less than 1.0. The sensitivity analysis had shown that the risk determinant for carcinogenic and non-carcinogenic risk was exposure time, followed by concentration.

Current State of Metabolomics Research in Meat Quality Analysis and Authentication

In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.

Characterization of chilled chicken spoilage using an integrated microbiome and metabolomics analysis

Spoilage of chilled chicken can occur as a result of microbial development and consumption of meat nutrients by spoilage bacteria, ultimately resulting in the release of undesired metabolites. Characterizing the profiles of the microbiota and metabolites and clarifying their relationships will contribute to an improved understanding of the mechanism underlying chilled chicken spoilage. In the present study, 16S rRNA gene sequencing and ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS)-based untargeted metabolomics analyses were applied to determine the microbial and metabolic profiles in chicken during chilled storage. The microbial and metabolic datasets were subjected to combined analysis using weighted gene co-expression network analysis (WGCNA) and Spearman's correlation analysis. Brochothrix, Carnobacterium, Photobacterium, Pseudomonas, Acinetobacter, Serratia, Kurthia, Shewanella, and Obesumbacterium genera were identified as the dominant spoilage bacteria in chilled chicken. Ten metabolic pathways, including histidine metabolism and purine metabolism, were identified as potential mechanisms underlying chilled chicken spoilage. Correlation analysis demonstrated that spoilage bacterial genera were highly correlated with spoilage-related metabolites. Taken together, the present study proposed an integrated microbiome and metabolomics approach to investigate the mechanism of chilled chicken spoilage caused by microbial activity. The results obtained by this approach provide a comprehensive insight into changes in the microbial and metabolic profiles of chilled chicken during spoilage.