World Bank-FOMEC Program, Argentina, Postdoctoral Fellowship - 2000; National Research Council, Argentina (CONICET), Postdoctoral Fellowship - 2000; Antorchas Foundation, Argentina, Postdoctoral Fellowship - 2000; Society of Analytical Chemists of Pittsburgh Award - 2004; American Society for Mass Spectrometry Research Award - 2005, "Professor Doctor Federico Luis Leloir" Award (Special Mention, Buenos Aires Univ.)-2006, Blanchard Assistant Professorship (Georgia Institute of Technology)-2006, NSF CAREER Award-2007; 3M Non-tenured Faculty Award-2008; CETL/BP Junior Faculty Teaching... (read more)
Bioanalytical Mass Spectrometry: Ambient Sampling/Ionization & Molecular Imaging, Ion Mobility Spectrometry, Metabolomics, Pharmaceutical Forensics.
Mass Spectrometry (MS) is one of the key analytical methods used to identify and characterize small quantities of molecules embedded in complex matrices. Although MS has found widespread use, technical improvements in its instrumentation and better understanding of the fundamentals are needed to extend its application to the grand challenges that face the biological, chemical and biomedical sciences.
Ambient Sampling/Ionization & Imaging MS.
The first wide-spread attention to the concept of ambient ionization/sampling prior to MS analysis was the introduction of desorption electrospray ionization (DESI) by Cooks and coworkers in 2004 when they reported on the ability of performing both qualitative and quantitative chemical analysis by MS in the open air. The central idea was that the surface of real-life objects such as a piece of leather, a nitrile glove, a plant seed cut in half, an intact tomato, the tip of a finger, etc. could be directly examined by MS without extraction of the molecules of interest or pretreatment of the object itself. Contemporary with the development of DESI was the work of several other researchers exploring a similar chemical analysis philosophy. Examples include the development of Direct Analysis in Real Time (DART), Shiea’s work on laser based ion sources, and work by the Van Berkel group at Oak Ridge National Laboratory on surface sampling probes (SSPs) for direct thin layer chromatography scanning. The excitement about the new analysis opportunities offered by DESI, DART and other ambient techniques has triggered a renaissance in the development of new ion generation approaches, and their application to real-life analytical and diagnostic challenges. Ambient MS techniques enable ionization in the absence of enclosures (i.e. open air operation), sample preparation (i.e. direct analysis), are interfaceable to most types of mass spectrometers, and generate ions softly, with amounts of internal energy deposited equal or lower than those in their atmospheric pressure counterparts.
Our group is developing new types of ambient plasma, laser, and spray-based ion generation technologies that can be used for a number of applications, including those in the field and in space, or as new detectors for traditional chemical separation approaches, such as LC. We focus a large amount of our efforts on understanding the ionization mechanisms prevailing in ambient ion generation, and the fluid dynamic processes affecting ion transmission. We are also developing new instrumentation for applying ambient ionization approaches in microprobe MS imaging (MSI) modes. Ambient MSI applications in our lab include studies in traumatic brain injuries, imaging of surface chemical defenses on marine algae, and imaging of organics on minerals. All these projects are pursued in collaboration with researchers at GT (BME, Center for Chemical Evolution, Biology) or elsewhere.
Ion Mobility Spectrometry.
Ion Mobility Spectrometry (IMS) is a gas phase structural and chemical separation technique based on differences in ion-neutral collisional cross sections. It has become widely accepted for the detection of chemical warfare agents, explosives and narcotics as well as for pharmaceutical quality control and pesticide screening. It can also be combined with MS (IM-MS) for obtaining conformational information of ions of interest, or as an enhancement in overall method peak capacity. With industrial sponsorship, our group is developing high resolution IM instrumentation based on drift-tube (DTIMS) approaches for pharmaceutical applications, and developing new interfaces for ambient MS ion sources to be coupled to IMS and IM-MS. This instrumentation is designed to minimize the frequency of false positive and false negative analysis results, without compromising instrument simplicity, serviceability, and cost. As part of our activities within the Center for Chemical Evolution, we are developing new shape-sensitive ion mobility detectors for UPLC separations, developing IM-MS approaches to identifying and quantifying the products of Miller-type experiments, and sequencing proto informational polymers generated as the product of dynamic combinatorial libraries.
Also, differential mobility spectrometry (DMS), a specific type of ion mobility separation based on the electric field dependency of the ionic mobility, is being investigated as a type of “molecular filter” to aid in enhancing the contrast of images created by MSI experiments. This is particularly useful when obtaining spatially-resolved information from trace level natural compounds or low abundance biomarkers that would otherwise be overshadowed by background signals. Signal-to-noise ratio enhancements in MSI afforded by addition of ion mobility filters not only increase detectability, but also improve lateral resolution, as signals can be resolved more easily.
Medicine in the 21st century is shifting from a reactive to a proactive discipline to provide personalized, predictive, preventive, and participatory (P4) care, not just treating disease, but also maximizing wellness. P4 medicine is propelled by data-driven systems approaches to understand disease, and emerging analytical technologies and tools. It aims at integrating billions of genomic, transcriptomic, proteomic and metabolomics “data points” for each patient to develop predictive multivariate models that can be used to guide personalized patient treatment. This is especially true for complex conditions such as ovarian cancer (OC) which, under the classical classification scheme, may actually encompass several different disease subtypes (endometrioid, serous papillary, mucinous, clear cell, etc.). Hence the proper sub-classification of the disease could be critical to developing a personalized -and perhaps different- treatment strategy for each individual patient.
The early molecular events in the development of ovarian carcinomas are unknown, making it difficult to develop sensitive and specific screening tests for ovarian cancer. The current state of OC diagnosis is that there is no screening test rapid, simple, cost effective, sensitive and specific enough to be applicable for general public screening. Metabolomes, the “mirror on the wall” for complex proteomes and transcriptomes show strong promise for generating new hypothesis regarding the early stages of ovarian cancer development, and for revealing biomarker panels providing multivariate diagnostic indexes. Mass spectrometry-based metabolome profiling technologies have a demonstrated potential for early disease detection in clinical settings (e.g. newborn screening), provided the specific assays employed have the sample throughput, robustness and reproducibility necessary to handle numerous clinical samples adequately. To a great extent, typical MS-based metabolomic workflows based on LC-MS lack the speed and long term reproducibility desirable for cost-effective clinical screening of large numbers of patients, creating the bottleneck of any study aimed towards development and validation of a disease-specific screening technology. Our group is applying conventional (NMR, UPLC-MS) and ambient MS metabolomic tools to study ovarian and other types of cancer, and develop cancer IVDMIAs (In Vitro Diagnostic Multivariate Assays). IVDMIAs are emerging diagnostic approaches growing in popularity for a wide variety of diseases. These assays harness multiple molecular markers to produce a diagnostic, prognostic and/or predictive index (value) for a patient. These efforts are being carried out in collaboration with researchers from the Integrated Cancer Research Center (ICRC) and the GT College of Computing. We are also extending similar metabolomic approaches to study questions in marine ecology, in collaboration with colleagues from the School of Biology and the Georgia Aquarium.
As with disease pandemics, the globalization of the pharmaceutical trade has the potential to rapidly spread poor-quality medicines worldwide before adequate detection and intervention are possible. There are three main categories of poor quality medicines; degraded, substandard and falsified (counterfeit). Substandard products arise as a result of lack of expertise, poor manufacturing practices, or insufficient infrastructure whilst those falsified are the ‘products’ of criminals. Degraded medicines arise from poor storage conditions. Falsified drugs may not contain the active ingredient, may contain the wrong ingredients or may even contain toxic compounds. Substandard drugs, for example, may contain active pharmaceutical ingredient (API) amounts that are in excess of ±15% of the stated amount. Distinguishing between these three classes requires simultaneously identifying and quantifying the expected (or wrong) APIs.
Our group applies conventional and ambient MS technologies to large-scale drug quality surveys in developing countries and to case studies involving counterfeit anti-infectives and contraceptives as part of the Counterfeit Drug Forensic Investigation Network (CODFIN) of the ACT Consortium. CODFIN facilitates the forensic chemical and biological analysis of suspected poor quality drugs and the dissemination of this information. The chemical and biological results are returned to the organization submitting the samples as soon as possible, and it is also forwarded to the International Medical Products Anti-Counterfeiting Taskforce (IMPACT). We also collaborate with the WorldWide Antimalarial Resistance Network (WWARN) in the development of their data collation and mapping tools. On-going efforts also include the development of fieldable ion mobility instrumentation for poor quality drug detection.
The Analyst (RSC)