Our laboratory is interested in the biochemical reactions that underlie fundamental physiological processes and associated metabolic derangements that cause disease. By using state-of-the-art mass spectrometers coupled with cutting-edge metabolomic technologies, we take a systems-level approach to study comprehensive metabolism and identify specific pathways that are altered in connection with particular phenotypes. We strive to translate our metabolomic findings into a physiological context through the use of classical biochemical tools and animal models as well as with the development of new technologies such as mass spectrometry-based metabolite imaging and whole-cell NMR. Our specific interests are outlined below.
Modern day mass spectrometers enable the detection of thousands of compounds in the metabolic extract of biological samples with unprecedented sensitivity. The goal of metabolomics is to compare these data across different sample types to gain insight into the metabolic programs that govern distinct biological phenotypes. A major challenge in the field, however, has been the translation of mass spectrometric peaks into metabolic structures and pathways. Indeed, the masses of more than half of the peaks routinely detected from biological samples in our laboratory return no hits when searched in currently available metabolomic databases. A major effort of our research program is to develop new metabolomic technologies that improve the throughput of structural identifications as well as our ability to characterize the pathway, physiological function, and anatomical localization of metabolites that do not fit into canonical metabolic reaction maps. To accomplish these goals, we rely heavily on bioinformatic strategies and modified LC/MS/MS experimental methodologies. Additionally, our strategies include mass spectrometry-based metabolite imaging, whole-cell NMR, and integration with sequencing data.
It is well established that most cancer cells take up an increased amount of glucose relative to that taken up by normal differentiated cells. This phenomenon, known as the Warburg effect, is also observed in other rapidly dividing cells. It is speculated that Warburg metabolism in proliferating cells supports the metabolic demands of cellular growth. However, the fates of glucose and other nutrients taken up by cancer cells have not been comprehensively mapped. We are interested in using untargeted metabolomic technologies to quantitatively determine how cancer cells metabolize nutrients differently than normal differentiated cells. In addition to examining the well-studied pathways of central carbon metabolism, we also seek to study peripheral metabolic pathways and pathways involving unknown compounds that have yet to be characterized.
Although acute pain is important in signaling tissue damage, the evolutionary significance of chronic pain that persists long after tissue injury is not well understood. Yet, more than a third of the population suffers from chronic pain and it amounts to over 550 billion dollars per year in US health-care costs. Current therapies available to treat chronic pain are limited, rarely provide complete therapeutic relief, and are associated with undesirable side effects. A limited understanding of the molecular mechanisms underlying chronic pain has prevented the development of improved treatment options.
Our laboratory is interested in neuropathic pain, a chronic pain state that results from peripheral and/or central nerve injury. By using untargeted metabolomics, we have identified a novel sphingolipid, N,N-dimethylsphingosine (DMS), that is increased in the dorsal horn of rats suffering from neuropathic pain and is sufficient in itself to induce pain-like behaviors when administered intrathecally in healthy rats. A major effort in our laboratory is to identify the metabolic pathways and specific enzymes involved in DMS biosynthesis as well as the biochemical mechanism(s) by which DMS elicits pain-like behavior. Based on preliminary data showing that DMS results in cytokine release from astrocytes in vitro, we are interested in dissecting the role of astrocytes in the neuropathic pain state and the metabolic interrelationships with other surrounding cell types that may be influenced by alterations in sphingolipid production.
The manipulation of distinct signaling pathways and transcription factors has been shown to influence life span in a cell-non-autonomous manner in multicellular model organisms such as Caenorhabditis elegans. These data suggest that coordination of whole-organism aging involves endocrine signaling, however, the molecular identities of such signals have not yet been determined and their potential relevance in humans is unknown. By using metabolomics, we have identified six small molecules that are similarly altered in concentration in more than five mechanistically unique long-lived worm models as candidate "aging signals". With mass spectrometry-based imaging, we have localized these potential age-related endocrine signals to worm muscle and also demonstrated that two of the compounds change as a function of age in healthy human skeletal muscle. We are now interested in: (i) identifying the metabolic pathways that produce these potential aging signals, (ii) elucidating the molecular mechanism linking these pathways to life span regulation, (iii) defining the role of muscle in organismal metabolism and health span, and (iv) testing whether manipulation of these potential age-related signaling pathways in model organisms influence development and longevity. Additionally, we are continuing to build a library of comprehensive metabolite levels in long-lived model organisms. Aging is a complex phenotype involving a multitude of metabolic pathways. To better understand the interplay between pathways in specific life span extension models, we are taking a systems-level approach in which we are constructing intelligible meta-comparisons to identify mechanistically relevant metabolite alterations.