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Keywords = Podolica breed

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24 pages, 1421 KB  
Article
Transcriptome Profiling of Milk Somatic Cells in Holstein, Simmental, Simmental × Holstein Crossbreed and Podolica Cattle at Two Lactation Stages and Production Systems
by Alessandra Crisà, Marco Milanesi, Giovanni Chillemi and Cinzia Marchitelli
Ruminants 2026, 6(1), 16; https://doi.org/10.3390/ruminants6010016 - 20 Feb 2026
Cited by 1 | Viewed by 1294
Abstract
Lactation is a dynamic process characterised by a production peak at 6–8 weeks, followed by a steady decline. To understand the molecular drivers of these phases and the influence of production systems, this study aims to provide a transcriptomic characterisation of bovine milk [...] Read more.
Lactation is a dynamic process characterised by a production peak at 6–8 weeks, followed by a steady decline. To understand the molecular drivers of these phases and the influence of production systems, this study aims to provide a transcriptomic characterisation of bovine milk somatic cells (BMSCs) in Holstein (HO), Simmental (SM), Simmental × Holstein crossbreed (SM × HO), and Podolica (POD) cows at 60 and 120 days in milk (DIM). Total RNA was sequenced at high coverage, and differential expression and functional enrichment analyses were performed. While a core set of milk protein and fatty acid genes was identified, breed-specific analysis showed SM × HO had the highest variation (677 differentially expressed genes, DEGs). Genes upregulated at 120 DIM involved mitochondrial metabolism and oxidative phosphorylation, while downregulated genes were associated with nuclear transcriptional regulation. At 60 DIM, SM × HO vs. HO showed 66 DEGs, with upregulated genes linked to chromatin remodelling and immune regulation. Comparing production systems, 28 DEGs between POD and HO/SM highlighted differences in mitochondrial activity and transcriptional regulation. This study bridges a knowledge gap by profiling the milk transcriptome of unexplored cattle breeds, providing novel insights into the molecular regulation of lactation. Full article
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14 pages, 1653 KB  
Article
Detection of Bioactive Peptides’ Signature in Podolica Cow’s Milk
by Rosario De Fazio, Antonella Di Francesco, Pierluigi Aldo Di Ciccio, Vincenzo Cunsolo, Domenico Britti, Carmine Lomagistro, Paola Roncada and Cristian Piras
Foods 2025, 14(5), 877; https://doi.org/10.3390/foods14050877 - 4 Mar 2025
Cited by 3 | Viewed by 1984
Abstract
The aim of this study was to identify and characterize the bioactive peptide profile of Podolica cow’s milk. This dairy product is known for its nutritional properties related to the presence of peculiar lipids and is a typical breed traditionally reared in southern [...] Read more.
The aim of this study was to identify and characterize the bioactive peptide profile of Podolica cow’s milk. This dairy product is known for its nutritional properties related to the presence of peculiar lipids and is a typical breed traditionally reared in southern Italy. Using top-down peptidomics, we identified 2213 peptides in milk samples from four different farms, with 19 matching bioactive sequences. Bioactivities include dipeptidyl peptidase-IV (DPP-IV) inhibition, angiotensin-converting enzyme (ACE) inhibition, antioxidant activity, enhanced calcium uptake, and other peptides with potential antimicrobial effects. DPP-IV-inhibitory peptides (e.g., LDQWLCEKL and VGINYWLAHK) suggest potential for type 2 diabetes management, while ACE inhibitors (such as YLGY and FFVAPFPEVFGK) could support cardiovascular health by reducing hypertension. Antimicrobial peptides such as SDIPNPIGSENSEK and VLNENLLR showed broad spectrum of activity against various harmful microorganisms, positioning Podolica milk as a promising source for natural antimicrobial agents. Additionally, peptides with osteoanabolic, antianxiety, and immunomodulatory properties further highlight the multifaceted health benefits associated with this type of milk. Our findings underline the functional richness of Podolica milk peptides with various bioactivity properties, which could enhance the value of derived dairy products and contribute to sustainable agricultural practices. Future research will aim to explore these bioactivity properties in vivo, establishing a foundation for functional foods and supplements based on Podolica milk. Full article
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14 pages, 3831 KB  
Article
Detection of Antimicrobial Proteins/Peptides and Bacterial Proteins Involved in Antimicrobial Resistance in Raw Cow’s Milk from Different Breeds
by Cristian Piras, Rosario De Fazio, Antonella Di Francesco, Francesca Oppedisano, Anna Antonella Spina, Vincenzo Cunsolo, Paola Roncada, Rainer Cramer and Domenico Britti
Antibiotics 2024, 13(9), 838; https://doi.org/10.3390/antibiotics13090838 - 3 Sep 2024
Cited by 11 | Viewed by 2736
Abstract
Proteins involved in antibiotic resistance (resistome) and with antimicrobial activity are present in biological specimens. This study aims to explore the presence and abundance of antimicrobial peptides (AMPs) and resistome proteins in bovine milk from diverse breeds and from intensive (Pezzata rossa, Bruna [...] Read more.
Proteins involved in antibiotic resistance (resistome) and with antimicrobial activity are present in biological specimens. This study aims to explore the presence and abundance of antimicrobial peptides (AMPs) and resistome proteins in bovine milk from diverse breeds and from intensive (Pezzata rossa, Bruna alpina, and Frisona) and non-intensive farming (Podolica breeds). Liquid atmospheric pressure matrix-assisted laser desorption/ionization (LAP-MALDI) mass spectrometry (MS) profiling, bottom-up proteomics, and metaproteomics were used to comprehensively analyze milk samples from various bovine breeds in order to identify and characterize AMPs and to investigate resistome proteins. LAP-MALDI MS coupled with linear discriminant analysis (LDA) machine learning was employed as a rapid classification method for Podolica milk recognition against the milk of other bovine species. The results of the LAP-MALDI MS analysis of milk coupled with the linear discriminant analysis (LDA) demonstrate the potential of distinguishing between Podolica and control milk samples based on MS profiles. The classification accuracy achieved in the training set is 86% while it reaches 98.4% in the test set. Bottom-up proteomics revealed approximately 220 quantified bovine proteins (identified using the Bos taurus database), with cathelicidins and annexins exhibiting higher abundance levels in control cows (intensive farming breeds). On the other hand, the metaproteomics analysis highlighted the diversity within the milk’s microbial ecosystem with interesting results that may reflect the diverse environmental variables. The bottom-up proteomics data analysis using the Comprehensive Antibiotic Resistance Database (CARD) revealed beta-lactamases and tetracycline resistance proteins in both control and Podolica milk samples, with no relevant breed-specific differences observed. Full article
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11 pages, 1191 KB  
Article
Spectral Profiling (Fourier Transform Infrared Spectroscopy) and Machine Learning for the Recognition of Milk from Different Bovine Breeds
by Anna Antonella Spina, Carlotta Ceniti, Rosario De Fazio, Francesca Oppedisano, Ernesto Palma, Enrico Gugliandolo, Rosalia Crupi, Sayed Haidar Abbas Raza, Domenico Britti, Cristian Piras and Valeria Maria Morittu
Animals 2024, 14(9), 1271; https://doi.org/10.3390/ani14091271 - 24 Apr 2024
Cited by 4 | Viewed by 2377
Abstract
The Podolica cattle breed is widespread in southern Italy, and its productivity is characterized by low yields and an extraordinary quality of milk and meats. Most of the milk produced is transformed into “Caciocavallo Podolico” cheese, which is made with 100% Podolica milk. [...] Read more.
The Podolica cattle breed is widespread in southern Italy, and its productivity is characterized by low yields and an extraordinary quality of milk and meats. Most of the milk produced is transformed into “Caciocavallo Podolico” cheese, which is made with 100% Podolica milk. Fourier Transform Infrared Spectroscopy (FTIR) is the technique that, in this research work, was applied together with machine learning to discriminate 100% Podolica milk from contamination of other Calabrian cattle breeds. The analysis on the test set produced a misclassification percentage of 6.7%. Among the 15 non-Podolica samples in the test set, 2 were misclassified and recognized as Podolica milk even though the milk was from other species. The correct classification rate improved to 100% when the same method was applied to the recognition of Podolica and Pezzata Rossa milk produced by the same farm. Furthermore, this technique was tested for the recognition of Podolica milk mixed with milk from other bovine species. The multivariate model and the respective confusion matrices obtained showed that all the 14 Podolica samples (test set) mixed with 40% non-Podolica milk were correctly classified. In addition, Pezzata Rossa milk produced by the same farm was detected as a contaminant in Podolica milk from the same farm down to concentrations as little as 5% with a 100% correct classification rate in the test set. The method described yielded higher accuracy values when applied to the discrimination of milks from different breeds belonging to the same farm. One of the reasons for this phenomenon could be linked to the elimination of the environmental variable. However, the results obtained in this work demonstrate the possibility of using FTIR to discriminate between milks from different breeds. Full article
(This article belongs to the Collection Monitoring of Cows: Management and Sustainability)
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15 pages, 2581 KB  
Article
A Study on Milk and Caciocavallo Cheese from Podolica Breed in Basilicata, Italy
by Giuseppe Natrella, Pasquale De Palo, Aristide Maggiolino and Michele Faccia
Dairy 2023, 4(3), 482-496; https://doi.org/10.3390/dairy4030032 - 31 Aug 2023
Cited by 10 | Viewed by 3197
Abstract
A study was undertaken on milk and caciocavallo cheese from Podolica cattle in the Basilicata Region (Southern Italy), with a view of the possible identification of specific traits useful to protect them from imitations. More than 800 individual milk samples and 29 bulk [...] Read more.
A study was undertaken on milk and caciocavallo cheese from Podolica cattle in the Basilicata Region (Southern Italy), with a view of the possible identification of specific traits useful to protect them from imitations. More than 800 individual milk samples and 29 bulk milk samples were taken in spring–early summer from cows registered in the genealogical book of the breed; moreover, 18 samples of caciocavallo cheese were taken in the same geographical area, 9 of which had been manufactured from Podolica milk. The obtained results confirmed the high aptitude of Podolica milk to cheesemaking, even though the exceptional dry weather in the period of sampling decreased the fat content with respect to the literature data. The presence of the variant A of α-lactalbumin, a characteristic trait of Podolica milk, was ascertained in only 14% of the animals considered in the study, indicating that this feature is disappearing in the population under study. The results on caciocavallo gave useful indications, because some possible peculiar characteristics were identified, such as the lower protein to fat ratio and some aroma descriptors. More research is needed to assess if these characteristics can be used for developing a multi-functional protocol, to be extended to all Italian Podolica populations, able to discriminate the cheese from imitations. In this perspective, the application of selection strategies for increasing the frequency of the variant A of α-lactalbumin should be carefully evaluated. Full article
(This article belongs to the Section Milk Processing)
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10 pages, 496 KB  
Article
Sialyloligosaccharides Content in Mature Milk of Different Cow Breeds
by Carmela Lovallo, Cinzia Marchitelli, Francesco Napolitano, Salvatore Claps and Alessandra Crisà
Sustainability 2022, 14(5), 2805; https://doi.org/10.3390/su14052805 - 28 Feb 2022
Cited by 7 | Viewed by 3259
Abstract
Sialyloligosaccharides (SOS) are bioactive molecules that play an important role in brain development and the increase in immunity in infants. In adults, they act as prebiotics, enhancing protection against microbial pathogens. In the present work, we aimed to analyze the levels of SOS [...] Read more.
Sialyloligosaccharides (SOS) are bioactive molecules that play an important role in brain development and the increase in immunity in infants. In adults, they act as prebiotics, enhancing protection against microbial pathogens. In the present work, we aimed to analyze the levels of SOS in mature milk, at days 60 and 120 after calving in four cow breeds: Holstein (HO), Simmental × Holstein (SM × HO), Simmental (SM), all fed with total mixed ration (TMR) in intensive production, and Podolica (POD) raised on pasture in an extensive system. The concentrations of SOS (3′-sialyllactose = 3′-SL, 6′-sialyllactose = 6′-SL, 6′-Sialyl-N-acetyllactosamine = 6′-SLN, disialyllactose = DSL, expressed in mg/L) were determined using HPAEC-PAD, a high-performance anion-exchange chromatography with pulsed amperometric detection. Results showed both breed and lactation effects. The contents of 3′-SL, 6′-SL, 6′-SLN, and DSL were higher at 60 than 120 days (p < 0.001), as well as in POD, as compared to the other breeds (p < 0.001). Furthermore, SM showed a significantly greater level of 3′-SL than HO (p < 0.001), as well as a significantly higher level of 6′-SLN in SM than HO (p < 0.001) and SM × HO (p < 0.001). Our findings may have implications for several areas of sustainability that might be used in the cattle management system. Full article
(This article belongs to the Special Issue Biodiversity 2021: Agriculture, Environment and Wellbeing)
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15 pages, 1582 KB  
Article
Milk Fat Depression and Trans-11 to Trans-10 C18:1 Shift in Milk of Two Cattle Farming Systems
by Simona Rinaldi, Michela Contò, Salvatore Claps, Cinzia Marchitelli, Gianluca Renzi, Alessandra Crisà and Sebastiana Failla
Sustainability 2022, 14(2), 977; https://doi.org/10.3390/su14020977 - 16 Jan 2022
Cited by 7 | Viewed by 4261
Abstract
Milk fat depression (MFD) syndrome, a consistent decrease in milk fat content, is related to important changes in fatty acid composition due to feed imbalances and the consequent ruminal metabolism alteration. Milk produced in two different farming systems was compared: Holstein Friesian fed [...] Read more.
Milk fat depression (MFD) syndrome, a consistent decrease in milk fat content, is related to important changes in fatty acid composition due to feed imbalances and the consequent ruminal metabolism alteration. Milk produced in two different farming systems was compared: Holstein Friesian fed with unified in intensive production and Podolica raised on a pasture in an extensive system. Milk chemical characteristics and fatty acid composition were determined comparing milk with a normal fat level (>3.8%) to milk with a low fat level (<3.2%) in each breeding system. Holstein Friesian milk showed the decrease in trans-11 and increase in trans-10 C18:1 (shift from trans-11 to trans-10 C18:1) in low fat with respect to normal fat milk with a consequent decrease in the trans-11/trans-10 C18:1 ratio. Even conjugated linoleic acid (CLA), C18:2 cis-9, trans-11, was lower while CLA trans-10, cis-12 was higher in low fat milk than in normal fat milk from Holstein Friesian. These changes, that are indicators of MFD syndrome, were not found in Podolica milk between fat levels. Holstein Friesian milk showed less short-chain fatty acids (9.48 % vs. 11.05%, p < 0.001), trans vaccenic acid (C18:1 trans-11, 0.51% vs. 3.39%, p < 0.001), rumenic acid (CLA C18:2 cis-9, trans-11, 0.32% vs. 1.45%, p < 0.001) and total CLA (0.53% vs. 1.91%, p < 0.001) contents than Podolica milk. Further losses of these human healthy nutrients in low fat Friesian milk reduced the nutritional quality of the milk, while the milk from animals raised on the pasture was of better quality even when the level of fat was low. Full article
(This article belongs to the Special Issue Biodiversity 2021: Agriculture, Environment and Wellbeing)
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