Egg product freshness evaluation: A metabolomic approach

Comparative Metabolomic Profiling of Eggs from 3 Diverse Chicken Breeds Using GC-MS Analysis

Eggs, as a crucial source of essential nutrients for consumers, possess a high nutritional value owing to their rich composition of vital components essential for human health. While previous research has extensively investigated genetic factors influencing egg quality, there has been a limited focus on exploring the impact of specific strains, particularly within the African context, on the polar metabolite profile of eggs. In this extensive study, we conducted an untargeted analysis of the chemical composition of both albumen and yolk from 3 distinct strains of hens-Blue Holland, Sasso, and Wassache-raised under identical feeding conditions. Utilizing gas chromatography coupled with mass spectrometry (GC-MS), we meticulously examined amino acids, carbohydrates, fatty acids, and other small polar metabolites. In total, 38 and 44 metabolites were identified in the whites and yolk, respectively, of the 3 studied strains. The application of chemometric analysis revealed notable differences in metabolite profiles with 8 relevant metabolites in each egg part. These metabolites include amino acids (N-α-Acetyl-L-lysine, lysine, L-valine, L-Tryptophan), fatty acids (oleic acid, linoleic acid, palmitic acid and stearic acid), and carbohydrates (d-glucose, maltose, lactose). These findings shed light on strain-specific metabolic nuances within eggs, emphasizing potential nutritional implications. The ensuing discussion delves into the diverse metabolic pathways influenced by the identified metabolites, offering insights that contribute to a broader understanding of egg composition and its significance in tailoring nutritional strategies for diverse populations.

Untargeted metabolomics liquid chromatography-high resolution mass spectrometry approach for the geographical origin assessment of Italian dehydrated apples

Geographical provenience is nowadays a relevant aspect of the authenticity and the quality of many food commodities. Dehydrated apple cubes/slices represent an ingredient commonly used by food companies for bakery products. However, this apple-based matrix is not so known and studied from an analytical point of view. In the present work, seven compounds were identified as key molecules to distinguish between Italian and non-Italian samples, through an untargeted ultrahigh-pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) approach. This methodology was merged with multivariate statistical analysis, and the principal features were studied and identified considering several identification steps. Samples from 2020 and 2021 harvesting campaigns, with partial and total dehydration rates, with or without peel, and from different apple varieties were considered for the study, for a total of 91 samples. Afterward, the same analysis protocol was applied to an external set (n = 12 samples), included in the statistical models, searching for the key compounds identified in the training set. Interesting and significant results underlined the potentiality of the UHPLC-HRMS technology as a confirmatory strategy for the geographical origin assessment of dehydrated apple commodities.

GC-MS and UHPLC-QTOFMS-assisted identification of the differential metabolites and metabolic pathways in key tissues of Pogostemon cablin

Pogostemon cablin is an important aromatic medicinal herb widely used in the pharmaceutical and perfume industries. However, our understanding of the phytochemical compounds and metabolites within P. cablin remains limited. To our knowledge, no integrated studies have hitherto been conducted on the metabolites of the aerial parts of P. cablin. In this study, twenty-three volatile compounds from the aerial parts of P. cablin were identified by GC-MS, predominantly sesquiterpenes. Quantitative analysis showed the highest level of patchouli alcohol in leaves (24.89 mg/g), which was 9.12 and 6.69-fold higher than in stems and flowers. UHPLC-QTOFMS was used to analyze the non-volatile compounds of leaf, stem and flower tissues. The differences in metabolites between flower and leaf tissues were the largest. Based on 112, 77 and 83 differential metabolites between flower-leaf, flower-stem and leaf-stem, three tissue-specific biomarkers of metabolites were identified, and the differential metabolites were enriched in several KEGG pathways. Furthermore, labeling differential metabolites in the primary and secondary metabolic pathways showed that flowers accumulated more lipids and amino acids, including proline, lysine and tryptophan; the leaves accumulated higher levels of terpenoids, vitamins and flavonoids, and stems contained higher levels of carbohydrate compounds. Based on the role of acetyl coenzyme A, the distribution and possible exchange mechanism of metabolites in leaves, stems and flowers of P. cablin were mapped for the first time, laying the groundwork for future research on the metabolites in P. cablin and their regulatory role.

Non-targeted high-resolution mass spectrometry study for evaluation of milk freshness

Milk freshness is an important parameter for both consumers' health and quality of milk-based products. Up to now there have been neither analytical methods nor specific parameters to uniquely define milk freshness from a complete and univocal chemical perspective. In this study, 8 molecules were selected and identified as responsible for milk aging, using a liquid chromatography-high-resolution mass spectrometry approach followed by chemometric data elaboration. For model setup and marker selection, 30 high-quality pasteurized fresh milk samples were collected directly from the production site and analyzed immediately and after storage at 2 to 8°C for 7 d. The markers were then validated by challenging the model with a set of 10 milk samples, not previously analyzed. Our results demonstrated that the markers identified within this study can be successfully used for the correct classification of non-fresh milk samples, complementing and successfully enhancing parallel evaluations obtainable through sensory measures.

Food Metabolites as Tools for Authentication, Processing, and Nutritive Value Assessment

Secondary metabolites are molecules with unlimited applications that have been gaining importance in various industries and studied from many angles. They are mainly used for their bioactive capabilities, but due to the improvement of sensibility in analytical chemistry, they are also used for authentication and as a quality control parameter for foods, further allowing to help avoid food adulteration and food fraud, as well as helping understand the nutritional value of foods. This manuscript covers the examples of secondary metabolites that have been used as qualitative and authentication molecules in foods, from production, through processing and along their shelf-life. Furthermore, perspectives of analytical chemistry and their contribution to metabolite detection and general perspectives of metabolomics are also discussed.

Integration of Untargeted and Pseudotargeted Metabolomics for Authentication of Three Shrimp Species Using UHPLC-Q-Orbitrap

In this work, an untargeted and pseudotargeted metabolomics combination approach was used for authentication of three shrimp species (Litopenaeus vanmamei, Penaeus japonicus, and Penaeus monodon). The monophasic extraction-based untargeted metabolomics approach enabled comprehensive-coverage and high-throughput analysis of shrimp tissue and revealed 26 potential markers. The pseudotargeted metabolomics approach confirmed 21 markers (including 9 key markers), which realized at least putative identification. The 21 confirmed markers, as well as 9 key markers, were used to develop PLS-DA models, correctly classifying 60/60 testing samples. Furthermore, DD-SIMCA and PLS-DA models were integrated based on the 9 key markers, with 59/60 and 20/20 samples of the species that were involved and uninvolved in model training correctly classified. The results demonstrated the potential of this untargeted and pseudotargeted metabolomics combination approach for shrimp species authentication.

Discovery of Spoilage Markers for Chicken Eggs Using Liquid Chromatography-High Resolution Mass Spectrometry-Based Untargeted and Targeted Foodomics

The current approaches remain insufficient for measuring chicken egg spoilage or present analytical limitations. This study aimed to complement the existing analyses and identify novel markers using liquid chromatography-high resolution mass spectrometry-based foodomics strategies. In the discovery set, comparative untargeted metabolomics was utilized to identify marker candidates in microbially inoculated chicken eggs. Markers were annotated by spectral matching with authentic standards, experimental libraries, or in silico fragmentation. In the validation set, targeted metabolomics was employed to verify the markers in stored chicken eggs from five farms. Statistical differences at a p-value < 0.001 revealed increases in lactic and 3-hydroxybutyric acids and decreases in phosphocholine, LPE(O-18:1), LPC(16:0), and LPC(18:0) in stored eggs. Receiver operating characteristic curve analysis of the six combined markers yielded an AUC of 0.956 and a sensitivity and specificity of ∼90%. Four phospholipids were highlighted as a novel class of spoilage markers. Our findings may contribute to further industrial implementation, benefiting the quality assurance and food safety of poultry egg production.

Monitoring aging of hen egg by integrated quantitative peptidomic procedures

Environmental conditions and timing of egg storage highly affect raw material quality. Aging and endogenous processing of constituent proteins can determine important changes in specific functions and technological properties of inner egg compartments. We here used integrated peptidomic procedures to identify peptide markers of egg freshness. At first, peptides extracted from egg white and yolk plasma taken from eggs stored for different times were subjected to a label-free untargeted quantitation procedure based on nanoLC-ESI-Q-Orbitrap-MS/MS, which identified 836 and 1974 unique variable molecules, respectively. By applying stringent criteria for filtering data, 30 and 66 putative egg aging markers were selected for egg white and yolk plasma, respectively. Proposed molecules were then validated through a targeted label-free parallel reaction monitoring procedure based on nanoLC-ESI-Q-Orbitrap-MS/MS, confirming quantitative trends for 19 and 25 peptides in egg white and yolk plasma, respectively, and generating a robust panel of egg storage markers. Quantitative results reflected physico-chemical phenomena occurring in egg compartments during storage and offered essential information for the development of novel control procedures to assess quality features of fresh/stored raw material.

A Non-Targeted High-Resolution Mass Spectrometry Study for Extra Virgin Olive Oil Adulteration with Soft Refined Oils: Preliminary Findings from Two Different Laboratories

This work presents a non-targeted high-resolution mass spectrometry inter-laboratory study for the detection of new chemical markers responsible of soft refined oils addition to extra virgin olive oils. Refined oils (soft deodorized and soft deacidified) were prepared on a laboratory scale starting from low-quality olive oils and analyzed together with a set of pure extra virgin olive oil (EVOO) samples and with mixtures of adulterated and pure EVOO at different percentages. The same analytical workflow was applied in two different laboratories equipped with two types of instrumentation (Q-Orbitrap and Q-TOF); a group of discriminant molecules was selected, and a tentative identification of compounds was also proposed. In summary, 12 molecules were identified as markers of this specific adulteration, and seven of them were selected as discriminative in both the laboratories, with a similar trend throughout the samples (i.e., propylene glycol 1 stearate). The results obtained in the two laboratories are comparable, concretely demonstrating the inter-laboratory repeatability of non-targeted studies. As a confirmation, the same markers were detected also in "in-house" mixtures and in suspect commercial deodorized mixtures, reinforcing the robustness of the results obtained and proving that, thanks to these molecules, mixtures containing at least 40% of adulterated oils can be detected.

Technical Overview of Orbitrap High Resolution Mass Spectrometry and Its Application to the Detection of Small Molecules in Food (Update Since 2012)

Food safety and quality issues are becoming increasingly important and attract much attention, requiring the development of better analytical platforms. For example, high-resolution (especially Orbitrap) mass spectrometry simultaneously offers versatile functions such as targeted/non-targeted screening while providing qualitative and quantitative information on an almost unlimited number of analytes to facilitate routine analysis and even allows for official surveillance in the food field. This review covers the current state of Orbitrap mass spectrometry (OMS) usage in food analysis based on research reported in 2012-2019, particularly highlighting the technical aspects of OMS application and the achievement of OMS-based screening and quantitative analysis in the food field. The gained insights enhance our understanding of state-of-the-art high-resolution mass spectrometry and highlight the challenges and directions of future research.

Classification of Hen Eggs by HPLC-UV Fingerprinting and Chemometric Methods

Hen eggs are classified into four groups according to their production method: Organic, free-range, barn, or caged. It is known that a fraudulent practice is the misrepresentation of a high-quality egg with a lower one. In this work, high-performance liquid chromatography with ultraviolet detection (HPLC-UV) fingerprints were proposed as a source of potential chemical descriptors to achieve the classification of hen eggs according to their labelled type. A reversed-phase separation was optimized to obtain discriminant enough chromatographic fingerprints, which were subsequently processed by means of principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Particular trends were observed for organic and caged hen eggs by PCA and, as expected, these groupings were improved by PLS-DA. The applicability of the method to distinguish egg manufacturer and size was also studied by PLS-DA, observing variations in the HPLC-UV fingerprints in both cases. Moreover, the classification of higher class eggs, in front of any other with one lower, and hence cheaper, was studied by building paired PLS-DA models, reaching a classification rate of at least 82.6% (100% for organic vs. non-organic hen eggs) and demonstrating the suitability of the proposed method.