Dr. Chris Nogiec is an exercise biologist, where his main research focus is using computational models of muscle metabolism to investigate performance, recovery, and benefits from exercise. He obtained his PhD from Boston University (Boston, MA), his Masters from Northeastern University (Boston, MA), and his Bachelors from Boston College (Chestnut Hill, MA).

Selected Publications

Metabolic Modeling of Muscle Metabolism Identifies Key Reactions Linked to Insulin Resistance Phenotypes.

Nogiec CD, Burkart A, Dreyfuss JM, Lerin C, Kasif S, Patti ME (2015).

Molecular Metabolism, March 2015.

Abstract:

Objective: Dysregulated muscle metabolism is a cardinal feature of human insulin resistance (IR) and associated diseases, including type 2 diabetes (T2D). However, specific reactions contributing to abnormal energetics and metabolic inflexibility in IR are unknown.

Methods: We utilize flux balance computational modeling to develop the first systems-level analysis of IR metabolism in fasted and fed states, and varying nutrient conditions. We systematically perturb the metabolic network to identify reactions that reproduce key features of IR-linked metabolism.

Results: While reduced glucose uptake is a major hallmark of IR, model-based reductions in either extracellular glucose availability or uptake do not alter metabolic flexibility, and thus are not sufficient to fully recapitulate IR-linked metabolism. Moreover, experimentally-reduced flux through single reactions does not reproduce key features of IR-linked metabolism. However, dual knockdowns of pyruvate dehydrogenase (PDH), in combination with reduced lipid uptake or lipid/amino acid oxidation (ETFDH), does reduce ATP synthesis, TCA cycle flux, and metabolic flexibility. Experimental validation demonstrates robust impact of dual knockdowns in PDH/ETFDH on cellular energetics and TCA cycle flux in cultured myocytes. Parallel analysis of transcriptomic and metabolomics data in humans with IR and T2D demonstrates downregulation of PDH subunits and upregulation of its inhibitory kinase PDK4, both of which would be predicted to decrease PDH flux, concordant with the model.

Conclusions: Our results indicate that complex interactions between multiple biochemical reactions contribute to metabolic perturbations observed in human IR, and that the PDH complex plays a key role in these metabolic phenotypes.

To Supplement or Not to Supplement: A Metabolic Network Framework for Human Nutritional Supplements.

Nogiec CD, Kasif S (2013).

PLOS ONE 8(8): e68751.

Abstract:

Flux balance analysis and constraint based modeling have been successfully used in the past to elucidate the metabolism of single cellular organisms. However, limited work has been done with multicellular organisms and even less with humans. The focus of this paper is to present a novel use of this technique by investigating human nutrition, a challenging field of study. Specifically, we present a steady state constraint based model of skeletal muscle tissue to investigate amino acid supplementation’s effect on protein synthesis. We implement several in silico supplementation strategies to study whether amino acid supplementation might be beneficial for increasing muscle contractile protein synthesis. Concurrent with published data on amino acid supplementation’s effect on protein synthesis in a post resistance exercise state, our results suggest that increasing bioavailability of methionine, arginine, and the branched-chain amino acids can increase the flux of contractile protein synthesis. The study also suggests that a common commercial supplement, glutamine, is not an effective supplement in the context of increasing protein synthesis and thus, muscle mass. Similar to any study in a model organism, the computational modeling of this research has some limitations. Thus, this paper introduces the prospect of using systems biology as a framework to formally investigate how supplementation and nutrition can affect human metabolism and physiology.

Experimental Procedure:

The figure below describes the work flow used for the experiment. A flux balance model of 374 reactions and 341 metabolites describing human muscle tissue was developed. Flux constraints based on fasting (Cynober 2002) and fed (Cynober et al 2002, Aoki et al 1976, Pozefsky et al 1969) levels of glucose, fatty acids, and amino acids in blood was added. With the given constraint, the contractile protein flux was determined. Supplementation was simulated by relaxing the constraint on amino acids singly and in all combinations from 2-7 amino acids. If the resultant flux was greater than the control flux, then the flux and conditions were recorded. (The contractile protein schematic is from Spirito, et al 1997.)