Konstantinos A. Kouremenos

Metabolic profiling of infant urine using comprehensive two-dimensional gas chromatography: Application to the diagnosis of organic acidurias and biomarker discovery

Comprehensive two-dimensional gas chromatography (GCxGC) time-of-flight mass spectrometry (ToFMS) was applied to the analysis of urinary organic acids from patients with inborn errors of metabolism. Abnormal profiles were obtained from all five patients studied. Methylmalonic academia and deficiencies of 3-methylcrotonyl-CoA carboxylase and medium chain acyl-CoA dehydrogenase gave diagnostic profiles while deficiencies of very long chain acyl-CoA dehydrogenase and mitochondrial 3-hydroxy-3-methylglutaryl CoA synthase gave profiles with significant increases in dicarboxylic acids suggestive of these disorders. The superior resolving power of GCxGC with ToFMS detection was useful in separating isomeric organic acids that were not resolved using one-dimensional GC. A novel urinary metabolite, crotonyl glycine, was also discovered in the mitochondrial 3-hydroxy-3-methylglutaryl CoA synthase sample which may be a useful specific diagnostic marker for this disorder. The quantitative aspects of GCxGC were investigated using stable isotope dilution analyses of glutaric, glyceric, orotic, 4-hydroxybutyric acids and 3-methylcrotonylglycine. Correlation coefficients for linear calibrations of the analytes ranged from 0.9805 to 0.9993 (R(2)) and analytical recoveries from 77% to 99%. This study illustrates the potential of GCxGC-ToFMS for the diagnosis of organic acidurias and detailed analysis of the complex profiles that are often associated with these disorders.

Current and Future Perspectives on the Structural Identification of Small Molecules in Biological Systems

Although significant advances have been made in recent years, the structural elucidation of small molecules continues to remain a challenging issue for metabolite profiling. Many metabolomic studies feature unknown compounds; sometimes even in the list of features identified as “statistically significant” in the study. Such metabolic “dark matter” means that much of the potential information collected by metabolomics studies is lost. Accurate structure elucidation allows researchers to identify these compounds. This in turn, facilitates downstream metabolite pathway analysis, and a better understanding of the underlying biology of the system under investigation. This review covers a range of methods for the structural elucidation of individual compounds, including those based on gas and liquid chromatography hyphenated to mass spectrometry, single and multi-dimensional nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry and includes discussion of data standardization. Future perspectives in structure elucidation are also discussed; with a focus on the potential development of instruments and techniques, in both nuclear magnetic resonance spectroscopy and mass spectrometry that, may help solve some of the current issues that are hampering the complete identification of metabolite structure and function.

One-pot microwave derivatization of target compounds relevant to metabolomics with comprehensive two-dimensional gas chromatography.

Metabolomics has been defined as the quantitative measurement of all low molecular weight metabolites (sugars, amino acids, organic acids, fatty acids and others) in an organisms cells at a specified time under specific environmental/biological conditions. Currently, there is considerable interest in developing a single method of derivatization and separation that satisfies the needs for metabolite analysis while recognizing the many chemical classes that constitute the metabolome. Chemical derivatization considerably increases the sensitivity and specificity of gas chromatography-mass spectrometry for compounds that are polar and have derivatizable groups. Microwave-assisted derivatization (MAD) of a set of standards spanning a wide range of metabolites of interest demonstrates the potential of MAD for metabolic profiling. A final protocol of 150 W power for 90 s was selected as the derivatization condition, based upon the study of each chemical class. A study of the generation of partially derivatized components established the conditions where this could potentially be a problem; the use of greater volumes of reagent ensured this would not arise. All compounds analyzed by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry in a standard mixture showed good area ratio reproducibility against a naphthalene internal standard (RSD<10% in all but one case). Concentrations tested ranged from 1 microg/mL to 1000 microg/mL, and the calibration curves for the standard mixtures were satisfactory with regression coefficients generally better than 0.998. The application to gas chromatography-quadrupole mass spectrometry and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry for a typical reference standard of relevance to metabolomics is demonstrated.

Metabolic Profiling for Detection of Staphylococcus aureus Infection and Antibiotic Resistance

Due to slow diagnostics, physicians must optimize antibiotic therapies based on clinical evaluation of patients without specific information on causative bacteria. We have investigated metabolomic analysis of blood for the detection of acute bacterial infection and early differentiation between ineffective and effective antibiotic treatment. A vital and timely therapeutic difficulty was thereby addressed: the ability to rapidly detect treatment failures because of antibiotic-resistant bacteria. Methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive S. aureus (MSSA) were used in vitro and for infecting mice, while natural MSSA infection was studied in humans. Samples of bacterial growth media, the blood of infected mice and of humans were analyzed with combined Gas Chromatography/Mass Spectrometry. Multivariate data analysis was used to reveal the metabolic profiles of infection and the responses to different antibiotic treatments. In vitro experiments resulted in the detection of 256 putative metabolites and mice infection experiments resulted in the detection of 474 putative metabolites. Importantly, ineffective and effective antibiotic treatments were differentiated already two hours after treatment start in both experimental systems. That is, the ineffective treatment of MRSA using cloxacillin and untreated controls produced one metabolic profile while all effective treatment combinations using cloxacillin or vancomycin for MSSA or MRSA produced another profile. For further evaluation of the concept, blood samples of humans admitted to intensive care with severe sepsis were analyzed. One hundred thirty-three putative metabolites differentiated severe MSSA sepsis (n = 6) from severe Escherichia coli sepsis (n = 10) and identified treatment responses over time. Combined analysis of human, in vitro, and mice samples identified 25 metabolites indicative of effective treatment of S. aureus sepsis. Taken together, this study provides a proof of concept of the utility of analyzing metabolite patterns in blood for early differentiation between ineffective and effective antibiotic treatment in acute S. aureus infections.

Advances in gas chromatographic methods for the identification of biomarkers in cancer

Screening complex biological specimens such as exhaled air, tissue, blood and urine to identify biomarkers in different forms of cancer has become increasingly popular over the last decade, mainly due to new instruments and improved bioinformatics. However, despite some progress, the identification of biomarkers has shown to be a difficult task with few new biomarkers (excluding recent genetic markers) being considered for introduction to clinical analysis. This review describes recent advances in gas chromatographic methods for the identification of biomarkers in the detection, diagnosis and treatment of cancer. It presents a general overview of cancer metabolism, the current biomarkers used for cancer diagnosis and treatment, a background to metabolic changes in tumors, an overview of current GC methods, and collectively presents the scope and outlook of GC methods in oncology.

A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research

The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.

Accelerating analysis for metabolomics, drugs and their metabolites in biological samples using multidimensional gas chromatography

Gas chromatography (GC) with mass spectrometry (MS) is one of the great enabling analytical tools available to the chemical and biochemical analyst for the measurement of volatile and semi-volatile compounds. From the analysis result, it is possible to assess progress in chemical reactions, to monitor environmental pollutants in a wide range of soil, water or air samples, to determine if an athlete or horse trainer has contravened doping laws, or if crude oil has migrated through subsurface rock to a reservoir. Each of these scenarios and samples has an associated implementation method for GC-MS. However, few samples and the associated interpretation of data is as complex or important as biochemical sample analysis for trace drugs or metabolites. Improving the analysis in both the GC and MS domains is a continual search for better separation, selectivity and sensitivity. Multidimensional methods are playing important roles in providing quality data to address the needs of analysts.

Liquid chromatography time of flight mass spectrometry based environmental metabolomics for the analysis of Pseudomonas putida Bacteria in potable water

Water supply biofilms have the potential to harbour waterborne diseases, accelerate corrosion, and contribute to the formation of tuberculation in metallic pipes. One particular species of bacteria known to be found in the water supply networks is Pseudomonas sp., with the presence of Pseudomonas putida being isolated to iron pipe tubercles. Current methods for detecting and analysis pipe biofilms are time consuming and expensive. The application of metabolomics techniques could provide an alternative method for assessing biofilm risk more efficiently based on bacterial activity. As such, this paper investigates the application of metabolomic techniques and provides a proof-of-concept application using liquid chromatography coupled with time-of-flight mass spectrometry (LC-ToF-MS) to three biologically independent P. putida samples, across five different growth conditions exposed to solid and soluble iron (Fe). Analysis of the samples in +ESI and -ESI mode yielded 887 and 1789 metabolite features, respectively. Chemometric analysis of the +ESI and -ESI data identified 34 and 39 significant metabolite features, respectively, where features were considered significant if the fold change was greater than 2 and obtained a p-value less than 0.05. Metabolite features were subsequently identified according to the Metabolomics Standard Initiative (MSI) Chemical Analysis Workgroup using analytical standards and standard online LC-MS databases. Possible markers for P. putida growth, with and without being exposed to solid and soluble Fe, were identified from a diverse range of different chemical classes of metabolites including nucleobases, nucleosides, dipeptides, tripeptides, amino acids, fatty acids, sugars, and phospholipids.

Metal and metalloid containing natural products and a brief overview of their applications in biology, biotechnology and biomedicine

Bioinorganic natural product chemistry is a relatively unexplored but rapidly developing field with enormous potential for applications in biology, biotechnology (especially in regards to nanomaterial development, synthesis and environmental cleanup) and biomedicine. In this review the occurrence of metals and metalloids in natural products and their synthetic derivatives are reviewed. A broad overview of the area is provided followed by a discussion on the more common metals and metalloids found in natural sources, and an overview of the requirements for future research. Special attention is given to metal hyperaccumulating plants and their use in chemical synthesis and bioremediation, as well as the potential uses of metals and metalloids as therapeutic agents. The potential future applications and development in the field are also discussed.

Comparative Metabolomics of Mycoplasma bovis and Mycoplasma gallisepticum Reveals Fundamental Differences in Active Metabolic Pathways and Suggests Novel Gene Annotations

Mycoplasmas are pathogenic bacteria that cause serious chronic infections in production animals, resulting in considerable losses worldwide, as well as causing disease in humans. These bacteria have extremely reduced genomes and are thought to have limited metabolic flexibility, even though they are highly successful persistent parasites in a diverse number of species. The extent to which different Mycoplasma species are capable of catabolizing host carbon sources and nutrients, or synthesizing essential metabolites, remains poorly defined. We have used advanced metabolomic techniques to identify metabolic pathways that are active in two species of Mycoplasma that infect distinct hosts (poultry and cattle). We show that these species exhibit marked differences in metabolite steady-state levels and carbon source utilization. This information has been used to functionally characterize previously unknown genes in the genomes of these pathogens. These species-specific differences are likely to reflect important differences in host nutrient levels and pathogenic mechanisms. ABSTRACT Mycoplasmas are simple, but successful parasites that have the smallest genome of any free-living cell and are thought to have a highly streamlined cellular metabolism. Here, we have undertaken a detailed metabolomic analysis of two species, Mycoplasma bovis and Mycoplasma gallisepticum, which cause economically important diseases in cattle and poultry, respectively. Untargeted gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry analyses of mycoplasma metabolite extracts revealed significant differences in the steady-state levels of many metabolites in central carbon metabolism, while 13C stable isotope labeling studies revealed marked differences in carbon source utilization. These data were mapped onto in silico metabolic networks predicted from genome wide annotations. The analyses elucidated distinct differences, including a clear difference in glucose utilization, with a marked decrease in glucose uptake and glycolysis in M. bovis compared to M. gallisepticum, which may reflect differing host nutrient availabilities. The 13C-labeling patterns also revealed several functional metabolic pathways that were previously unannotated in these species, allowing us to assign putative enzyme functions to the products of a number of genes of unknown function, especially in M. bovis. This study demonstrates the considerable potential of metabolomic analyses to assist in characterizing significant differences in the metabolism of different bacterial species and in improving genome annotation. IMPORTANCE Mycoplasmas are pathogenic bacteria that cause serious chronic infections in production animals, resulting in considerable losses worldwide, as well as causing disease in humans. These bacteria have extremely reduced genomes and are thought to have limited metabolic flexibility, even though they are highly successful persistent parasites in a diverse number of species. The extent to which different Mycoplasma species are capable of catabolizing host carbon sources and nutrients, or synthesizing essential metabolites, remains poorly defined. We have used advanced metabolomic techniques to identify metabolic pathways that are active in two species of Mycoplasma that infect distinct hosts (poultry and cattle). We show that these species exhibit marked differences in metabolite steady-state levels and carbon source utilization. This information has been used to functionally characterize previously unknown genes in the genomes of these pathogens. These species-specific differences are likely to reflect important differences in host nutrient levels and pathogenic mechanisms.