We have located links that may give you full text access.
Multifragment melting analysis of yeast species isolated from spoiled fruits.
Journal of Applied Microbiology 2018 Februrary
AIMS: In this study, we developed a novel approach, multifragment melting analysis (MFMA), based on the simultaneous analysis of the melting characteristics of multiple DNA fragments for the differentiation and identification of yeast species isolated from spoiled fruits.
METHODS AND RESULTS: In total, 183 yeast isolates recovered from spoiled fruit samples were differentiated and grouped using MFMA. Six different DNA fragments of the 26S rRNA gene showing a high interspecific heterogeneity were amplified, and the PCR products were individually subjected to MFMA. An excellent discrimination and classification were obtained when the melting characteristics of all target DNA fragments for each species were simultaneously assessed. Species-level identification was performed by sequence analysis of representative isolates from each group. In the fruit samples, Hanseniaspora uvarum (Kloeckera apiculata) was found to be the most frequently isolated species followed by members of the Pichia genus, namely P. kluyveri, P. fermentans and P. kudriavzevii (Issatchenkia orientalis).
CONCLUSIONS: Multifragment melting analysis provided a rapid and reliable approach for discrimination and grouping of a large number of yeast isolates recovered from fruit samples prior to sequence analysis-based identification.
SIGNIFICANCE AND IMPACT OF THE STUDY: The MFMA has great potential for fast and accurate investigation of yeast communities associated with food spoilage to determine their sources and routes and to prevent contamination.
METHODS AND RESULTS: In total, 183 yeast isolates recovered from spoiled fruit samples were differentiated and grouped using MFMA. Six different DNA fragments of the 26S rRNA gene showing a high interspecific heterogeneity were amplified, and the PCR products were individually subjected to MFMA. An excellent discrimination and classification were obtained when the melting characteristics of all target DNA fragments for each species were simultaneously assessed. Species-level identification was performed by sequence analysis of representative isolates from each group. In the fruit samples, Hanseniaspora uvarum (Kloeckera apiculata) was found to be the most frequently isolated species followed by members of the Pichia genus, namely P. kluyveri, P. fermentans and P. kudriavzevii (Issatchenkia orientalis).
CONCLUSIONS: Multifragment melting analysis provided a rapid and reliable approach for discrimination and grouping of a large number of yeast isolates recovered from fruit samples prior to sequence analysis-based identification.
SIGNIFICANCE AND IMPACT OF THE STUDY: The MFMA has great potential for fast and accurate investigation of yeast communities associated with food spoilage to determine their sources and routes and to prevent contamination.
Full text links
Related Resources
Trending Papers
Challenges in Septic Shock: From New Hemodynamics to Blood Purification Therapies.Journal of Personalized Medicine 2024 Februrary 4
Molecular Targets of Novel Therapeutics for Diabetic Kidney Disease: A New Era of Nephroprotection.International Journal of Molecular Sciences 2024 April 4
The 'Ten Commandments' for the 2023 European Society of Cardiology guidelines for the management of endocarditis.European Heart Journal 2024 April 18
A Guide to the Use of Vasopressors and Inotropes for Patients in Shock.Journal of Intensive Care Medicine 2024 April 14
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app