Metabolomics:Open Access

We tested a strategy for multiplexed (4-plex) quantification of metabolites using the MISSILE identification method with liquid chromatography coupled to tandem mass spectrometry. We applied this methodology to study the metabolic effect of the proteasome inhibitor and chemotherapeutic drug Bortezomib in yeast cells. Using JUMPm software version 1.1 we simultaneously identified and quantified 95 metabolites across four experimental conditions and found that Bortezomib increased the accumulation of dipeptides but decreased the levels of specific lipid molecules (e.g. phosphtidylethanolamines) in a dose-dependent manner. This method combines metabolite identification and quantification, making untargeted metabolomics experiments more informative.

Caseous Lymphadenitis (CLA) is a disease that affects animals, such as sheep, whose etiologic agent is Corynebacterium pseudotuberculosis. In sheep, it causes enormous damages, expressed through a reduction in milk, meat and wool production, or death of infected animals, and, also, difficulties in sterilizing infected animals habitats. Another problem in the control of this disease is its late diagnosis. Thus, we present the pioneer results on NMRbased metabolomics applied in CLA with the aim to detect blood serum profile alterations provoked by a pathogen in C. pseudotuberculosis seropositive sheep. We have compared two types of serum samples: The ones taken from the seropositive animals, which we called infected, and others taken from the seronegative (healthy) animals. Significant metabolomics profile changes occurred in the spectral regions δ: 0.20 to 2.20; 3.20 to 4.40 and 6.40 to 8.00 that refer to hydrogen atoms of proteins, organic acids, alcohols, lipids and some amino acids, correspondingly. When applying chemometrics, a significative separation of 59 serum samples into two groups, sick and healthy animals, was achieved. Additionally, key-metabolites that were only present in the group of sick animals and that can be considered as exclusively bacteria derived were pointed as possible biomarkers for CLA. Therefore, these data might contribute to the development of a non-invasive NMR-based diagnostic method, as well as to bring new insights into the development of new immunoprohylaxis tools.

Engineering plant primary metabolism is currently recognized as a major approach to gain improved productivity. Most of the current efforts in plant metabolic engineering focused on either individual enzymes or a few enzymes in a particular pathway without fully consider the potential interactions between metabolisms. More and more evidences suggested that engineering a particular pathway without consideration of the interacting pathways only generated limited success. Therefore, a long term goal of metabolic engineering is being able to engineer metabolism with consideration of the effects of external or internal perturbation on the whole plant primary metabolism. In this paper, we developed a constraint-based model of C3 Plant Primary Metabolism (C3PMM), which is generic for C3 plants such as rice, Arabidopsis, and soybean. The C3PMM was first combined with transcriptome data to demonstrate that there is substantial coordination of mesophyll primary metabolism at both transcriptome and metabolism levels in response to elevated CO2 concentration. Secondly, maximizing CO2 uptake is a plausible target function for metabolism of a typical C3 mesophyll cell. Finally, C3PMM predicted a decrease in nitrate assimilation flux coordinated with photorespiration, and increase in ammonium assimilation flux, when CO2 concentration increases. This suggested a potential mechanistic linkage between differences in the response of ecosystems differing in nitrogen source to elevated CO2. In conclusion, all the coordination of C3 plant primary metabolism at both transcriptome level and metabolism level, and the coordination between nitrate assimilation and photorespiration under elevated CO2 concentration, are beneficial for maximized CO2 uptake rate.

Sclerocarya birrea (S. birrea) is an African tree used traditionally to treat various human ailments. The origin of S. birrea can be determined by its biochemical composition. This study identifies the biochemical composition of S. birrea leaf extracts from 5 provinces within South Africa namely Limpopo, KwaZulu-Natal, North-West, Gauteng and Mpumalanga by both 1H Nuclear Magnetic Resonance (NMR) and Liquid Chromatography Mass Spectroscopy (LCMS), followed by multivariate data analysis. The Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) and Partial Least Squares Discriminant Analysis (PLS-DA) from 1HNMR and LC-MS respectively, clearly discriminated between extracts from five provinces. Putatively annotated metabolites including kaempferol, quercetin, gallic acid, sucrose and glutamate contributed to discriminating the geographical origin of S. birrea extracts. These results established biochemical profiles of S. birrea extracts and indicate that the two techniques; NMR and LC-MS can be used in the discrimination of the geographical origin of S. birrea.

In this mini-review, we focus on essential and semi-essential amino acid concentrations in plasma as potential biomarkers for clinical consequences related to protein malnutrition. In Japan, protein malnutrition is common across varying populations, especially in elderly adults and young women, which could cause increased risk of sarcopenia, heart failure, impaired immune response, and conditions specific to women. After establishing clinical reference intervals for plasma free amino acid concentrations, we have reported the clinical characteristics of a Japanese subpopulation with low plasma free essential and semi-essential amino acid concentrations (Low-EAA), which we hypothesized to be potential protein malnutrition. Intriguingly, the ratio of the subjects with Low-EAA was varied depending on age and gender, with elderly subjects and young women having higher ratio of subjects with Low-EAA. After adjusting for age, sex, and BMI, Low-EAA was significantly associated with surrogate markers of protein malnutrition, anemia, cardiovascular diseases and infectious diseases. Plasma free amino acid concentrations could be not only a potential biomarker, but also a predictor for health problems associated with malnutrition.