Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/21711
Title: Investigation of donkey milk bacterial diversity by 16S rDNA high-throughput sequencing on a Cyprus donkey farm
Authors: Papademas, Photis 
Kamilari, E. 
Aspri, Maria 
Anagnostopoulos, Dimitrios A. 
Mousikos, P 
Kamilaris, Andreas 
Tsaltas, Dimitrios 
Major Field of Science: Agricultural Sciences
Field Category: Animal and Dairy Science
Keywords: 16S rDNA sequencing;bacterial communities;high-throughput sequencing;donkey milk
Issue Date: Jan-2021
Source: Journal of dairy science, 2021, vol. 104, no.1, pp. 167-178
Volume: 104
Issue: 1
Start page: 167
End page: 178
Journal: Journal of dairy science 
Abstract: The interest in milk originating from donkeys is growing worldwide due to its claimed functional and nutritional properties, especially for sensitive population groups, such as infants with cow milk protein allergy. The current study aimed to assess the microbiological quality of donkey milk produced in a donkey farm in Cyprus using culture-based and high-throughput sequencing techniques. The culture-based microbiological analysis showed very low microbial counts, whereas important food-borne pathogens were not detected in any sample. In addition, high-throughput sequencing was applied to characterize the bacterial communities of donkey milk samples. Donkey milk mostly composed of gram-negative Proteobacteria, including Sphingomonas, Pseudomonas, Mesorhizobium, and Acinetobacter; lactic acid bacteria, including Lactobacillus and Streptococcus; the endospores forming Clostridium; and the environmental genera Flavobacterium and Ralstonia, detected in lower relative abundances. The results of the study support existing findings that donkey milk contains mostly gram-negative bacteria. Moreover, it raises questions regarding the contribution of (1) antimicrobial agents (i.e., lysozyme, peptides) in shaping the microbial communities and (2) bacterial microbiota to the functional value of donkey milk.
Description: The authors acknowledge the technical support and welcoming environment from Golden Donkeys Farm, Cyprus, for the milk samples collection. Author contributions: conceptualization, D.T. and P.P.; methodology, E.K., D.A., and M.A.; formal analysis, E.K., M.A., and A.K.; investigation, E.K., D.A. and M.A.; resources, D.T., P.P., and P.M.; data curation, E.K.; writing—original draft preparation, E.K. and M.A.; writing—review and editing, E.K., D.T., and P.P.; supervision, D.T. and P.P.; project administration, D.T.; funding acquisition, D.T. All authors have read and agreed to the published version of the manuscript. Funding: this research was funded by INTERREG Greece–Cyprus 2014-2020 Program [Project AGRO-ID, which is co-funded by the European Union (ERDF) and National Resources of Greece and Cyprus] and project DELIVER by the Research and Innovation Foundation (RIF) of Cyprus. Andreas Kamilaris has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 739578 complemented by the government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development. The authors declare no conflict of interest.
URI: https://hdl.handle.net/20.500.14279/21711
ISSN: 00220302
DOI: 10.3168/jds.2020-19242
Rights: © 2021 American Dairy Science Association
Type: Article
Affiliation : Cyprus University of Technology 
University of Twente 
Research Center on Interactive Media, Smart Systems and Emerging Technologies 
Funding: Horizon 2020 Framework Programme Interreg European Commission European Regional Development Fund
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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