Allergenicity evaluation of five types of commercial food-derived oligopeptide products.

Food-derived oligopeptides are low in molecular weight and have a variety of biological activities. However, many of them are derived from allergens, which may pose a threat to allergic consumers. This study aimed to assess the allergenicity of five types of oligopeptides industrially derived from allergenic foods (soybean, wheat, oyster, salmon skin, and haddock skin). Referring to the decision tree proposed by the FAO/WHO for the allergenicity evaluation of genetically modified food, we included three kinds of bioinformatic tools (AlgPred, AllerCatPro, and AllerTOP), SDS-PAGE, ELISA, cell and animal experiments in this study. The variation of effector levels (IL-4, IFN-γ, His, and mMCP-1) was determined in mouse models. The results revealed that the oligopeptides were all predicted to contain allergenic peptides, of which the soybean one had the highest number of allergenic peptides. Moreover, there were anti-enzymatic peptides present in the soybean oligopeptide. Unexpectedly, the serum IgE binding ability of the peptides was lower than the positive threshold. In addition, no statistical divergence was found between the oligopeptide groups and the control groups in the effector and ß-hexosaminidase levels. Overall, the five types of oligopeptides, though derived from allergens, had low allergenicity.

Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model.

BACKGROUND: Peanut allergy (PA) has become a clinical and public health problem, which is mainly regulated by genetics, immune responses, and environmental factors. Diagnosis and treatment for PA have always remained huge challenges due to its multiple triggers. Studies have shown that long non-coding RNAs (lncRNAs) play a critical role in the development of allergic diseases. METHOD AND RESULTS: In the current study, we examined the plasma lncRNA expression profiles of peanut allergy Brown Norway rats and healthy controls and 496 differently expressed lncRNAs were identified, including 411 up-regulated genes and 85 down-regulated genes. We screened 8 lncRNAs based on the candidate principle and the candidates were verified in individual samples by quantitative real-time PCR. Then, the four lncRNA-based diagnostic model was established by least absolute shrinkage and selection operator (LASSO) and logistic regression, which was proved by area under the receiver operating characteristic curve (AUC). CONCLUSIONS: In summary, we assessed the correlation between lncRNA expression levels and the diagnosis of peanut allergy, which may perform a vital role in guiding the management of peanut allergy.

Sialic acid and food allergies: The link between nutrition and immunology.

Food allergies (FA), a major public health problem recognized by the World Health Organization, affect an estimated 3%-10% of adults and 8% of children worldwide. However, effective treatments for FA are still lacking. Recent advances in glycoimmunology have demonstrated the great potential of sialic acids (SAs) in the treatment of FA. SAs are a group of nine-carbon α-ketoacids usually linked to glycoproteins and glycolipids as terminal glycans. They play an essential role in modulating immune responses and may be an effective target for FA intervention. As exogenous food components, sialylated polysaccharides have anti-FA effects. In contrast, as endogenous components, SAs on immunoglobulin E and immune cell surfaces contribute to the pathogenesis of FA. Given the lack of comprehensive information on the effects of SAs on FA, we reviewed the roles of endogenous and exogenous SAs in the pathogenesis and treatment of FA. In addition, we considered the structure-function relationship of SAs to provide a theoretical basis for the development of SA-based FA treatments.

Peanut allergen induces more serious allergic reactions than other allergens involving MAPK signaling pathways.

There is no universally accepted uniform research to classify the severity of allergic reactions triggered by different food allergens. We established a food allergy model based on repeated intragastric administrations of proteins from peanut, egg, milk, or soybean mixed with cholera toxin followed by oral food challenges with a high dose of the sensitizing proteins. Increased specific IgE, specific IgG1, allergic symptom scores, histamine, murine mast cell proteases-1, vascular leakage, Th2 cytokines, and mast cell infiltration in the lungs and intestine were found in the allergic groups via enzyme-linked immunosorbent assay, hematoxylin-eosin, and toluidine blue staining. Each sensitized group showed a decrease in body temperature and Th1 cytokines after oral food challenge. The increased levels of Th2 cytokines, IL-25, IL-33, and TSLP, and related asthma genes ARG1, DCN, LTB4R1 and NFKBIA as well as the activation of MAPK signaling pathways were also revealed by quantitative real-time PCR and western blotting. In terms of the severity of food allergies, peanut allergy was the most serious followed by egg and milk, and soybean allergy was the least severe. Compared to other allergic groups, asthma genes were regulated through the MAPK signaling pathways to produce related Th2 cytokines in peanut allergy; consequently, mice in the peanut group exhibited more severe allergic reactions. Comparison of the severity of food allergies is required for the development of milder prevention for severe food allergies.

Identification of Allergens in White- and Red-Fleshed Pitaya (Selenicereus undatus and Selenicereus costaricensis) Seeds Using Bottom-Up Proteomics Coupled with Immunoinformatics.

White-fleshed pitaya (Selenicereus undatus) and red-fleshed pitaya (Selenicereus costaricensis) are becoming increasingly popular because of their nutritional and medicinal benefits. However, in addition to their beneficial properties, allergy to pitaya fruits has occurred in daily life. In this study, we investigated the protein profile of pitaya fruit seeds and focused on the most reactive proteins against immunoglobulin E (IgE) in sera from allergic patients by immunoblotting. A protein band of approximately 20 kDa displayed a clear reaction with the serum IgE. The protein bands of interest were excised, in-gel digested, and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), followed by data searching against a restricted database (Caryophyllales in UniProtKB) for protein identification. Immunoinformatic tools were used to predict protein allergenicity. The potential allergens included cupin_1 and heat shock protein 70 (HSP70) in white-fleshed pitaya seeds, and cupin_1, heat shock protein 70, and heat shock protein sti1-like in red-fleshed pitaya seeds are potential allergens. The expression of potential allergens was further verified at the transcriptional level in the species of S. undatus and S. costaricensis.

Antibiotic-Induced Gut Microbiota Dysbiosis Damages the Intestinal Barrier, Increasing Food Allergy in Adult Mice.

(1) Background: The use of antibiotics affects the composition of gut microbiota. Studies have suggested that the colonization of gut microbiota in early life is related to later food allergies. Still, the relationship between altered intestinal microbiota in adulthood and food allergies is unclear. (2) Methods: We established three mouse models to analyze gut microbiota dysbiosis' impact on the intestinal barrier and determine whether this effect can increase the susceptibility to and severity of food allergy in later life. (3) Results: The antibiotic-induced gut microbiota dysbiosis significantly reduced Lachnospiraceae, Muribaculaceae, and Ruminococcaceae, and increased Enterococcaceae and Clostridiales. At the same time, the metabolic abundance was changed, including decreased short-chain fatty acids and tryptophan, as well as enhanced purine. This change is related to food allergies. After gut microbiota dysbiosis, we sensitized the mice. The content of specific IgE and IgG1 in mice serum was significantly increased, and the inflammatory response was enhanced. The dysbiosis of gut microbiota caused the sensitized mice to have more severe allergic symptoms, ruptured intestinal villi, and a decrease in tight junction proteins (TJs) when re-exposed to the allergen. (4) Conclusions: Antibiotic-induced gut microbiota dysbiosis increases the susceptibility and severity of food allergies. This event may be due to the increased intestinal permeability caused by decreased intestinal tight junction proteins and the increased inflammatory response.

Gender differences in food allergy depend on the PPAR γ/NF-κB in the intestines of mice.

AIMS: Epidemiology shows that gender affects the incidence of food allergy. However, there is a lack of evidence of gender differences in food allergies and little is known about the mechanisms. The aim of this study was to excavate potential reasons for gender differences in food allergy based on estrogen. MAIN METHODS: Female and male BALB/c mice sensitized with ovalbumin (OVA) were established to analyze the difference in food allergy. The systemic anaphylactic, including OVA-specific IgE, OVA-specific IgG, histamine, and cytokines, was assessed using an enzyme-linked immunosorbent assay (ELISA). ELISA also detected the estradiol in serum. Western blotting and immunofluorescence were used to detect the estrogen receptor. Peroxisome proliferator-activated receptor gamma (PPARγ) implicated in immune homeostasis and nuclear factor kappa-B (NF-κB) were determined by western blotting. Immunohistochemistry and hematoxylin-eosin (H&E) staining were used to detect zonula occludens-1 (ZO-1), tryptase, forkhead box protein P3 (Foxp3), and intestinal morphology, respectively. KEY FINDINGS: Female mice were more vulnerable to food allergy. Female mice treated with OVA did exhibit more serious systemic anaphylaxis than male mice. We observed increased levels of estradiol in serum, estrogen receptor, NF-κB, and decreased levels of PPAR γ in female mice. Furthermore, the intestinal mucosal integrity and intestinal permeability were more impaired in female mice treated with OVA than male mice. SIGNIFICANCE: Clarify the mechanism of gender differences in food allergies can provide targets in female mice and provide personalized diagnosis, management, and treatment of food allergy for female mice.

A Comparative Analysis of Novel Deep Learning and Ensemble Learning Models to Predict the Allergenicity of Food Proteins.

Traditional food allergen identification mainly relies on in vivo and in vitro experiments, which often needs a long period and high cost. The artificial intelligence (AI)-driven rapid food allergen identification method has solved the above mentioned some drawbacks and is becoming an efficient auxiliary tool. Aiming to overcome the limitations of lower accuracy of traditional machine learning models in predicting the allergenicity of food proteins, this work proposed to introduce deep learning model-transformer with self-attention mechanism, ensemble learning models (representative as Light Gradient Boosting Machine (LightGBM) eXtreme Gradient Boosting (XGBoost)) to solve the problem. In order to highlight the superiority of the proposed novel method, the study also selected various commonly used machine learning models as the baseline classifiers. The results of 5-fold cross-validation showed that the area under the receiver operating characteristic curve (AUC) of the deep model was the highest (0.9578), which was better than the ensemble learning and baseline algorithms. But the deep model need to be pre-trained, and the training time is the longest. By comparing the characteristics of the transformer model and boosting models, it can be analyzed that, each model has its own advantage, which provides novel clues and inspiration for the rapid prediction of food allergens in the future.

Cold-induced ginsenosides accumulation is associated with the alteration in DNA methylation and relative gene expression in perennial American ginseng (Panax quinquefolius L.) along with its plant growth and development process.

BACKGROUND: Ginsenosides accumulation responses to temperature are critical to quality formation in cold-dependent American ginseng. However, the studies on cold requirement mechanism relevant to ginsenosides have been limited in this species. METHODS: Two experiments were carried out: one was a multivariate linear regression analysis between the ginsenosides accumulation and the environmental conditions of American ginseng from different sites of China and the other was a synchronous determination of ginsenosides accumulation, overall DNA methylation, and relative gene expression in different tissues during different developmental stages of American ginseng after experiencing different cold exposure duration treatments. RESULTS: Results showed that the variation of the contents as well as the yields of total and individual ginsenosides Rg1, Re, and Rb1 in the roots were closely associated with environmental temperature conditions which implied that the cold environment plays a decisive role in the ginsenoside accumulation of American ginseng. Further results showed that there is a cyclically reversible dynamism between methylation and demethylation of DNA in the perennial American ginseng in response to temperature seasonality. And sufficient cold exposure duration in winter caused sufficient DNA demethylation in tender leaves in early spring and then accompanied the high expression of flowering gene PqFT in flowering stages and ginsenosides biosynthesis gene PqDDS in green berry stages successively, and finally, maximum ginsenosides accumulation occurred in the roots of American ginseng. CONCLUSION: We, therefore, hypothesized that cold-induced DNA methylation changes might regulate relative gene expression involving both plant development and plant secondary metabolites in such cold-dependent perennial plant species.