Detection of Antimicrobial Proteins/Peptides and Bacterial Proteins Involved in Antimicrobial Resistance in Raw Cow’s Milk from Different Breeds

Author:

Piras Cristian12ORCID,De Fazio Rosario1ORCID,Di Francesco Antonella3ORCID,Oppedisano Francesca14ORCID,Spina Anna Antonella1ORCID,Cunsolo Vincenzo3ORCID,Roncada Paola1ORCID,Cramer Rainer5ORCID,Britti Domenico12ORCID

Affiliation:

1. Department of Health Sciences, Magna Græcia University of Catanzaro, 88100 Catanzaro, Italy

2. Interdepartmental Center Veterinary Service for Human and Animal Health, University “Magna Graecia” of Catanzaro, CISVetSUA, 88100 Catanzaro, Italy

3. Laboratory of Organic Mass Spectrometry, Department of Chemical Sciences, University of Catania, 88100 Catanzaro, Italy

4. Institute of Research for Food Safety & Health (IRC-FSH), Department of Health Sciences, University of Catanzaro Magna Græcia, 88100 Catanzaro, Italy

5. Department of Chemistry, University of Reading, Whiteknights, Reading RG6 6DX, UK

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 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.

Funder

Magna Græcia University

Publisher

MDPI AG

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