Raw milk is a continued threat to public health due to possible contamination with zoonotic pathogens. Enterocytozoon bieneusi is one of the most prevalent pathogenic fungi in a wide range of vertebrate hosts, causing diarrheal disease. Although there has been some evidence, the role and potential risk of raw milk of dairy animals in the transmission dynamics of E. bieneusi is not clear. Therefore, we aimed to determine the occurrence and genotypes of E. bieneusi in raw milk of dairy animals in several farms of the Central Anatolia Region. We also investigated if there is a relation between the presence of E. bieneusi and mastitis. Genomic DNAs from a total of 450 raw milk including 200, 200 and 50 samples from cattle, sheep and water buffalo respectively were analyzed using nested PCR, targeting the internal transcribed spacer of E. bieneusi. Totally milk samples of 9 (4.5%) dairy cattle, 36 (18.0%) sheep, and 1 (2.0%) water buffalo were PCR-positive. A significant relationship was determined between mastitis and the presence of E. bieneusi. Sequence analysis revealed the presence of eight genotypes: two known (ERUSS1, BEB6) and six novel genotypes (named as TREb1 to TREb6). The genotype ERUSS1 and BEB6 were the most common genotypes, found in all cattle and sheep farms. Phylogenetic analysis clustered all the identified genotypes in Group 2. This study provides novel findings that contribute to the transmission dynamics and molecular epidemiology of E. bieneusi. Our study also highlighted the potential risk of raw milk for public health with respect to microsporidia infections.
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http://dx.doi.org/10.1016/j.ijfoodmicro.2020.108828 | DOI Listing |
BMC Res Notes
December 2024
Department of Microbiology and Parasitology, Faculty of Science, University of Buea, Box 63, Buea, Cameroon.
Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) is a zoonotic pathogen that poses a serious threat to veterinary and public health worldwide. We investigated mastitis milk samples for contamination with MRSA and also characterized the MRSA isolates by investigating antimicrobial resistance and virulence factors.
Result: We confirmed MRSA in 69 of 201 (34.
Vet Sci
November 2024
Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram 4225, Bangladesh.
Antimicrobial resistance (AMR) is a growing global concern and poses a significant threat to public health. The emergence of multidrug-resistant organisms, including , also presents a risk of transmission to humans through the food chain, including milk. This study aimed to investigate the prevalence of in raw milk in the Chattogram metropolitan area (CMA) of Bangladesh and their phenotypic and genotypic antimicrobial resistance patterns.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, Universitat de València, Camino de Vera s/n, E46022 Valencia, Spain.
(1) Background: In drug discovery and pharmaceutical quality control, a challenge is to assess protein extracts used for allergy therapy and in vivo diagnosis, such as prick tests. Indeed, there are significant differences between the features of marketed products due to variations in raw materials, purification processes, and formulation techniques. (2) Methods: A protein array technology has been developed to provide comprehensive information on protein-biomarker interactions on a large scale to support the pharmaceutical industry and clinical research.
View Article and Find Full Text PDFJ Food Prot
December 2024
Université Paris-Saclay, Micalis Institute, INRAE, AgroParisTech, 78352 Jouy en Josas, France. Electronic address:
Staphylococcus aureus is a pathogenic microorganism often found in animal-derived foods and is known for its ability to readily develop resistance to antibiotic treatments. This study was designed to determine prevalence of S. aureus strains in raw milk and meat in Italy and to evaluate their antibiotic resistance profiles and biofilm production.
View Article and Find Full Text PDFWei Sheng Yan Jiu
November 2024
National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Objective: To improve the accuracy of food intelligent recognition and weight estimation technology, establish a large-scale food image dataset.
Methods: Building large-scale food image and ingredient datasets based on web crawler technology, professional manual collection, and regular user uploads.
Results: A big dataset was constructed containing over 1.
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