Preliminary investigation on the presence of peptides inhibiting the growth of Listeria innocua and Listeria monocytogenes in Asiago d’Allevo cheese

Effect of supercritical carbon dioxide on protein structure modification and antimicrobial peptides production of Mongolian cheese and its in vitro digestion

The aim of this research was to investigate the effects of supercritical carbon dioxide (SC-CO2) treatment on protein structure in Mongolian cheese. The peptides during the digestive process of the SC-CO2 treated cheese were also studied. SC-CO2 technology was utilized to treat Mongolian cheese at three temperatures (45, 55 and 65 °C) and three pressures (7.5, 12.5 and 17.5 MPa). The results of fluorescence, ultraviolet-visible, Fourier transform infrared spectroscopy and free sulfhydryl groups showed that SC-CO2, particularly at 65 °C and 17.5 MPa, modified the protein structure in Mongolian cheese effectively. The data of LC-MS/MS-based peptidomics showed that the content of antimicrobial peptides found in the SC-CO2 treated Mongolian cheese was 1.55 times that of the untreated Mongolian cheese; the content of unique antimicrobial peptides in the digested SC-CO2 treated Mongolian cheese was 1.46 times that of the digested untreated Mongolian cheese, which proved that SC-CO2 could help produce antimicrobial peptides in cheese not only during the process of SC-CO2 treatment but during subsequent simulated gastrointestinal digestion as well. In conclusion, SC-CO2 could be considered a promising method to develop cheese products with potential health benefits.

Nutritional, antimicrobial and medicinal properties of Camel's milk: A review

Camel's milk is an important part of staple diet in several parts of the world, particularly in the arid and semi-arid zones. Camel's milk is rich in health-beneficial substances, such as bioactive peptides, lactoferrin, zinc, and mono and polyunsaturated fatty acids. These substances could help in the treatment of some important human diseases like tuberculosis, asthma, gastrointestinal diseases, and jaundice. Camel's milk composition is more variable compared to cow's milk. The effects of feed, breed, age, and lactation stage on milk composition are more significant in camel. Region and season significantly change the ratio of compounds in camel's milk. Camel's whey protein is not only composed of numerous soluble proteins, but also has indigenous proteases such as chymotrypsin A and cathepsin D. In addition to their high nutritional value, these whey proteins have unique characteristics, including physical, chemical, physiological, functional, and technological features that are useful in the food application. The hydrolysis of camel's milk proteins leads to the formation of bioactive peptides, which affect major organ systems of the body and impart physiological functions to these systems. The camel's milk has antioxidant, antimicrobial, angiotensin-I-converting enzyme (ACE)-inhibitory peptides, antidiabetic as well as anticholesterol activities.

1H NMR Metabolic Profile to Discriminate Pasture Based Alpine Asiago PDO Cheeses

Simple Summary

Nowadays, alpine cheese from grazing dairy herds has a premium market value because consumers perceive its higher degree of healthiness and sustainability. The authenticity of pasture-based cheese should be safeguarded from local hay-based milk analogues. The study aimed at assessing the reliability of proton nuclear magnetic resonance (¹H NMR) to discriminate pasture-based alpine Asiago PDO cheeses of different ripening time from similar hay-based samples processed in the same dairy plant. Cheeses were produced from raw milk collected from grazing or hay-fed alpine dairy herds and they were ripened for 2 (Pressato), 4 (Allevo_4), and 6 (Allevo_6) months. Samples of the cheeses were submitted to wet chemistry and nuclear magnetic resonance analysis. The outcomes of the ¹H NMR spectroscopy were used in a multivariate discriminant procedure. Choline, 2,3-butanediol, lysine, and tyrosine and some residual sugar-like compounds were water-soluble biomarkers of cows’ feeding system. However, the application of ¹H NMR based metabolomics was an effective fingerprinting method to correctly identify only cheese samples with the shortest ripening period. The classification of more aged cheese samples according to the cows’ feeding system was less accurate likely due to the chemical and biochemical changes induced by a prolonged maturation process.

Abstract

The study was carried out in an alpine area of North-Eastern Italy to assess the reliability of proton nuclear magnetic resonance ¹H NMR to fingerprint and discriminate Asiago PDO cheeses processed in the same dairy plant from upland pasture-based milk or from upland hay-based milk. Six experimental types of Asiago cheese were made from raw milk considering 2 cows’ feeding systems (pasture- vs. hay-based milk) and 3 ripening times (2 months, Pressato vs. 4 months, Allevo_4 vs. 6 months, Allevo_6). Samples (n = 55) were submitted to chemical analysis and to ¹H NMR coupled with multivariate canonical discriminant analysis. Choline, 2,3-butanediol, lysine, tyrosine, and some signals of sugar-like compounds were suggested as the main water-soluble metabolites useful to discriminate cheese according to cows’ feeding system. A wider pool of polar biomarkers explained the variation due to ripening time. The validation procedure based on a predictive set suggested that ¹H NMR based metabolomics was an effective fingerprinting tool to identify pasture-based cheese samples with the shortest ripening period (Pressato). The classification to the actual feeding system of more aged cheese samples was less accurate likely due to their chemical and biochemical changes induced by a prolonged maturation process.

Potential antimicrobial and antiproliferative activities of autochthonous starter cultures and protease EPg222 in dry-fermented sausages

This work studied the presence of nitrogen compounds with bioactive properties in Iberian pork sausages that were manufactured using different autochthonous starter cultures and protease EPg222.

New milk protein-derived peptides with potential antimicrobial activity: an approach based on bioinformatic studies

New peptides with potential antimicrobial activity, encrypted in milk protein sequences, were searched for with the use of bioinformatic tools. The major milk proteins were hydrolyzed in silico by 28 enzymes. The obtained peptides were characterized by the following parameters: molecular weight, isoelectric point, composition and number of amino acid residues, net charge at pH 7.0, aliphatic index, instability index, Boman index, and GRAVY index, and compared with those calculated for known 416 antimicrobial peptides including 59 antimicrobial peptides (AMPs) from milk proteins listed in the BIOPEP database. A simple analysis of physico-chemical properties and the values of biological activity indicators were insufficient to select potentially antimicrobial peptides released in silico from milk proteins by proteolytic enzymes. The final selection was made based on the results of multidimensional statistical analysis such as support vector machines (SVM), random forest (RF), artificial neural networks (ANN) and discriminant analysis (DA) available in the Collection of Anti-Microbial Peptides (CAMP database). Eleven new peptides with potential antimicrobial activity were selected from all peptides released during in silico proteolysis of milk proteins.