Laboratory Learning Program 2023 - NMR-based metabolic reflection of OCD in horses using statistical analysis of prerecorded data (CHE-02)

Research Opportunity Number: CHE-02

Project Title:  NMR-based metabolic reflection of OCD in horses using statistical analysis of prerecorded data

Project Summary: Osteochondrosis dissecans (OCD) is a common orthopedic developmental disease of growing animals, such as horses. My research focuses on NMR-based metabolomics to diagnose and characterize such a disease condition and understand better the underlying biochemistry with aim to find nutritional or other treatment.

There are multiple datasets collected earlier and waiting for statistical analysis to identify metabolic correlations with disease of the cohorts and also to identify specific metabolic interactions in the highly multidimensional metabolic interactome.

Beyond this baseline investigation we have learned lately that the horses demonstrate sex-specific response to the disease condition, which is a novel observation.
The student will be provided with an original raw NMR dataset for processing and analysis using existing protocols using software we have available in-house.  These are MestreNova for NMR data processing and preparing input for the statistical analysis by SIMCA, a powerful, yet very user-friendly statistical analysis package. Next to the multivariate statistical analysis a Matlab-based software script, called STOCSY, will be used to trace metabolic interactions starting from selected ingredients. The untargeted analysis will explore the unique sex-specific response specifically.

All this activity is computational-based, therefore, it is highly flexible and has no involvement in wet-lab work or dealing with actual biofluid samples. The student participant will be exposed to cutting edge concepts of metabolic profiling and biochemical characterization, which is revolutionizing the medicinal chemistry and diagnosis, with a strong potential for becoming an author on a joint paper.

Student Roles and Responsibilities: The student is expected to be educated on the project, understand the concept and learn the processing and analysis tools. Conduct processing the data, analyze the statistical results and metabolic information, survey and learn relevant literature, synthesize the knowledge and understanding in a final report. Keep close and constant communication with the supervisor (IP).

Additional Considerations:  4-6 hours of daily involvement in this project is sufficient and it can be done in a flexible arrangement. It is preferred to be in the laboratory/building most of the time, potentially joining other summer students participating in local programs (SURF-C, NSF-REU), joining group meetings, exchange ideas, give presentations for group members about intermediate results.

Department/Institute:  Chemistry

Faculty Sponsor:   István Pelczer

Participation Dates: June 5 -August 4, 2023

Stipend Offered:  TBD

Number of Internships Available: 0-1

Application Deadline: March 15, 2023, midnight eastern daylight time