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Quantitative Detection of Methicillin Resistant Staphylococcus aureus from the Surfaces of Canned Drinks Sold in University of Benin Shopping Complexes

Authors: Ogofure AG, Saidu JZ, Olannye PG, Ahonsi CO, Emoghene AO

DOI Info: N/A

ABSTRACT

This study was carried out to detect the presence methicillin resistant Staphylococcus aureus from the surfaces of canned drinks sold in University of Benin shopping complexes. Standard culture-based techniques were used to screen for MRSA from one hundred canned drinks samples. Total bacteria count was enumerated from the surfaces of canned drinks while staphylococci and MRSA were identified using mannitol salt agar and Oxacillin resistant screening agar base supplemented with ORSAB supplement (Oxoid) along with other tests. Hemolysin production was carried out on Columbia agar blood base (Oxoid). The antibiogram and multiple antibiotic resistance were evaluated using standard methods. The results obtained in this study shows that bacterial contamination of refrigerated canned drink surfaces was found to be 5%, 20% and 10% for basement, life sciences and physical sciences shopping complexes respectively. About 37.5% and 12.5 % of canned drink surfaces stored in the crates were found to be contaminated in Physical Sciences and June 12 shopping complex. The highest Staphylococcal count from the surface of canned drinks was found to be 1.15 x 103 cfu/cm2. A few samples which had over 300 colonies (too numerous to count) in 50% of the shopping complexes evaluated in the study while there were also samples which were devoid of staphylococcal contamination. All isolated Staphylococcal species were found to be hemolytic and the MRSA strains were coagulase positive. The MRSA strains had higher antibiotic resistance index of 0.51 compared to 0.47 for other staphylococci and they are of public health importance.


Affiliations: Department of Microbiology, Faculty of Life Sciences, University of Benin, Benin City, Nigeria.
Keywords: Surfaces Of Canned Drinks, MRSA, Pathogenic Bacteria, Quantitative Detection, Public Health
Published date: 2019/06/30

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ISSN: 2635-3342 (Print)

ISSN: 2635-3350 (Online)

DOI: In progress

ISI Impact Factor: In progress

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