As a member of the Department of Internal Medicine – Section of Molecular Medicine, I bring 11 years of combined biochemical and mass spectrometry experience to Wake Forest School of Medicine. I have led metabolomics projects identifying metabolite signatures in both baboons and humans using mass spectrometry (MS) based techniques including both liquid chromatography (LC) and gas chromatography (GC). These projects have laid the foundation for identifying metabolic signature of cardio-metabolic disease (Bishop et al., 2018). My graduate and postdoctoral training have focused on biochemical and metabolic analysis of mechanisms impacting human diseases. These studies focused on the biochemical analysis of glycerophosphodiester utilization and metabolism by the fungal pathogen Candida albicans (Bishop et al., 2011, Bishop et al., 2013).

In addition to this work, I joined a collaborative effort to develop and implement GCMS methodologies to measure alcohols excreted by C. albicans during biofilm formation (Ganguly et al., 2011). During my postdoctoral training at the Cleveland Clinic, I led a project developing LCMS methodologies for analyzing biofluids and tissues for steroid and steroidal drug metabolism in a mouse model of castration-resistant prostate cancer (CRPC) (Li et al., 2015). This provided baseline information necessary for quantifying pharmacokinetics of drug targets and measuring endogenous steroid concentrations.

Currently, I lead metabolomics projects focused on profiling metabolites in breath and biofluids that are potentially associated with metabolic dysfunction (Bishop et al., 2018, Misra et al., 2018). Our efforts thus far have been to create a consistent and efficient pipeline for sample collection, LC or GC-MS analysis, and data processing. These metabolomics protocols will be applicable to the analysis of biofluids and tissues associated with other complex diseases we are interested in studying. I will use this technology and information as I focus to implement metabolomics based-analysis at the Wake Forest School of Medicine.

Research Highlights

METABOLOMICS ANALYSIS OF A BREATH AND BIOFLUID

Metabolomics has emerged as an important contributor to a systems biology approach of studying complex diseases. Metabolism is a key function of every cellular process and tools to globally capture a comprehensive fingerprint of metabolism play a major role in understanding the important mechanism involved. Therefore, it is critical to establish standardized methods for metabolomics analysis that can be utilized to gain information from any biological material. I am currently using a metabolomics approach to explore baboon and human breath and biofluid metabolites as a way to discover potential signatures of cardiac dysfunction. Like humans, baboons develop metabolic diseases such as diabetes, obesity, dyslipidemia, cardiovascular disease and hepatic complications. In a model of developmental programing, these metabolic dysregulations are accelerated, allowing us to use this platform to study a disease in a highly controllable setting. In a collaborative project Children’s Hospital of San Antonio and Baylor University, I have a pilot study assessing breath and serum metabolites from pre-diabetic children from the San Antonio area. This study utilizes the state of the art ReCIVA breath collection device from Owlstone Biomedical. By assessing the metabolic state prior to weight management treatment, we will gain metabolic information of pre-diabetic state of this cohort of children.  This establishment of metabolomics analysis will be applicable to studying other complex diseases.

Bishop AC, Libardoni M, Misra B, Choudary A, Lange K, Bernal J, Nijland M, Olivier M, Li C, Nathanielsz  PW, Cox LA, Nonhuman primate breath metabolites correlate with developmental programming and cardio-metabolic status. J Breath Res. 2018;12 036016 doi: 10.1088/1752-7163/aaba84
 

Misra BB, Bassey E, Bishop AC, Kusel DT, Cox LA, Olivier M, High-Resolution gas chromatography/mass spectrometry metabolomics of non-human primate serum. Rapid Commun Mass Spectrom. 2018; 1-10: doi: 10.1002/rcm.8197