Piras Cristian, De Fazio Rosario, Di Francesco Antonella, Oppedisano Francesca, Spina Anna Antonella, Cunsolo Vincenzo, Roncada Paola, Cramer Rainer, Britti Domenico
Department of Health Sciences, Magna Græcia University of Catanzaro, 88100 Catanzaro, Italy.
Interdepartmental Center Veterinary Service for Human and Animal Health, University "Magna Graecia" of Catanzaro, CISVetSUA, 88100 Catanzaro, Italy.
Antibiotics (Basel). 2024 Sep 3;13(9):838. doi: 10.3390/antibiotics13090838.
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 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.
参与抗生素耐药性（耐药组）和具有抗菌活性的蛋白质存在于生物标本中。本研究旨在探索不同品种以及集约养殖（佩扎塔罗萨牛、布伦纳阿尔皮纳牛和弗里生牛）和非集约养殖（波多利卡牛品种）的牛奶中抗菌肽（AMPs）和耐药组蛋白的存在情况及丰度。采用液体常压基质辅助激光解吸/电离（LAP-MALDI）质谱（MS）分析、自下而上蛋白质组学和宏蛋白质组学对来自不同牛品种的牛奶样本进行综合分析，以鉴定和表征AMPs，并研究耐药组蛋白。LAP-MALDI MS结合线性判别分析（LDA）机器学习被用作一种快速分类方法，用于识别波多利卡牛奶与其他牛种牛奶。牛奶的LAP-MALDI MS分析结果与线性判别分析（LDA）表明，基于MS图谱有区分波多利卡牛奶和对照牛奶样本的潜力。训练集中达到的分类准确率为86%，而在测试集中达到98.4%。自下而上蛋白质组学揭示了大约220种定量的牛蛋白质（使用数据库鉴定），在对照奶牛（集约养殖品种）中，cathelicidins和膜联蛋白表现出更高的丰度水平。另一方面，宏蛋白质组学分析突出了牛奶微生物生态系统内的多样性，其有趣的结果可能反映了不同的环境变量。使用综合抗生素耐药性数据库（CARD）进行的自下而上蛋白质组学数据分析显示，对照牛奶样本和波多利卡牛奶样本中均存在β-内酰胺酶和四环素耐药蛋白，未观察到相关的品种特异性差异。
