The Repository @ St. Cloud State

Open Access Knowledge and Scholarship

Date of Award


Culminating Project Type


Degree Name

Biological Sciences - Cell and Molecular: M.S.




College of Science and Engineering

First Advisor

Ryan C. Fink

Second Advisor

Matthew P. Davis

Third Advisor

Omar Al-Azzam

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Keywords and Subject Headings

MALDI-TOF, Mastitis, 16S rRNA sequencing, Dairy



The proposed research study is a field validation study to benchmark against proven methods, a new methodology for the detection of microorganisms (Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry or MALDI-ToF) isolated from dairy farm and critical for safety and quality. The MALDI-TOF is a relatively new molecular technique extremely advantageous in terms of cost effectiveness, sample preparation easiness, turn-around time and result analysis accessibility. Although already successfully deployed in clinical diagnostic, it has not been evaluated for agricultural applications yet. In the dairy industry, Mastitis causes the most financial loss and a rapid diagnostic method as MALDI-TOF, will assist in the control and prevention program of mastitis, in addition to the sanitation and safety level of the dairy farms and processing facility. In the present study, we prospectively compared MALDI-TOF MS to the conventional 16S rRNA sequencing method for the identification of environmental mastitis isolates (481) and thermoduric isolates of pasteurized milk (248). Among the 481 environmental isolates, 454 (94.4%) were putatively identified to the genus level by MALDI-TOF MS and 426 (88.6%) were identified to the species level, but no reliable identification was obtained for 17 (3.5%), and 27 (5.6%) discordant results were identified. Future studies can help to overcome the limitation of MALDI database and additional sample preparation steps might help to reduce the number of discordance in identification. In conclusion, our results show that MALDI-TOF MS is a fast and reliable technique which has the potential to replace conventional identification methods for most dairy pathogens, routinely isolated from the milk and dairy products. Thus it’s adoption will strengthen the capacity, quality, and possibly the scope of diagnostic services to support the dairy industry.



This work is supported by the grant form dairy industries in Minnesota and Veterinary Diagnostic Lab (VDL). We are grateful to VDL (College of veterinary medicine), Udder Health Lab (UHL) and Department of Food Science and Nutrition, University of Minnesota for their technical assistance. Special thanks to Dr. Sandra Godden and Jennifer Timmerman for conducting a major part of the study and providing samples and results. I appreciate my fellow graduate students; Billie Johnson, Cassey Kipping, Rene Martin, Wesley Davis, Rebecca Jensch, Sandra hinz and Miezan Echimane, who guided me and assisted in the lab and related coursework. I would further like to thank Mary Norbeck, Sadhana Bom, Mathew Yang, Ryan Wolfe, Megan Stein, Megan Jones, Brittany Campion, and Kavitha Gobalan, for their assistance in the sample preparation and conducting related experiments of the study. I also thank Professor Louise Millis for her constant guidance and inspiration. A special thanks to my graduate committee members: Dr. Matthew P. Davis and Dr. Omar Al-Azzam for all of their knowledge and assistance. Finally I would like to extend a heartfelt thanks to my mentor Dr. Ryan C. Fink for all his guidance and moral support during the study. I further thank him for his confidence in me that I will be able to finish this extensive research work. Last but not the least, I would like to thank my husband and my parents for believing in me and extending their constant support towards my study and career goals.



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