Alessandra Sussulini

Metabolic Profiling of Human Blood Serum from Treated Patients with Bipolar Disorder Employing 1H NMR Spectroscopy and Chemometrics

Metabolic profiling employing hydrogen nuclear magnetic resonance (1H NMR) spectroscopy and chemometric analysis of human blood serum samples taken from the control group (n = 25) and patients with bipolar disorder (n = 25) was performed to identify molecular changes related to the disorder and to different drug treatments: lithium (n = 15) versus other medications (n = 10). This strategy showed significant potential for exploring pathophysiological and toxicological features involved in bipolar disorder. The investigated groups (control and patients with bipolar disorder under different treatments) could be distinguished according to their metabolic profiles, and the main differential metabolites found were lipids, lipid-metabolism-related molecules (acetate, choline, and myo-inositol), and some key amino acids (glutamate, glutamine). Our results suggest that some of the 24 identified metabolites may be linked to lithium- and other-medication-provoked metabolic changes or may even be directly related to the disorder. Thus, these findings may contribute to paving the way for future studies aiming at identifying potential biomarkers for bipolar disorder.

Comparative metallomics for transgenic and non-transgenic soybeans

In this work, a comparative metallomics of transgenic and non-transgenic soybeans [Glycine max (L.) Merrill] was performed. Soybean proteins were extracted with a proper buffer and separated by two-dimensional polyacrylamide gel electrophoresis. Metal ions bound to a set of eight proteins randomly selected (ranging from 13.98 to 54.87 kDa), were characterized by matrix-assisted laser desorption-ionization quadrupole-time of flight mass spectrometry and mapped using synchrotron radiation X-ray spectrometry. The metal ions detected were: Ca(II), Cu(II), Fe(II), Mn(II), Ni(II) and Zn(II). Transgenic and non-transgenic soybeans proteins were found to display typical and random profiles for metal ions binding. To test the reliability of the qualitative metal ions profiles, quantification of Ca(II), Cu(II) and Fe(II) was performed via microwave-assisted decomposition in mini-vials followed by atomic absorption spectrometry determination. Qualitative and quantitative metallomics was found to be coherent and to match profiles expected from the known protein functions. The protein of spot 5, with molar mass of 37.62 kDa (amino acid sequence presented), was found to display the most characteristic change in metal ions content, with higher Ca(II), Cu(II) and Fe(II) concentrations for transgenic soybeans.

Laser ablation ICP-MS: Application in biomedical research

In the last decade, the development of diverse bioanalytical methodologies based on mass spectrometry imaging has increased, as has their application in biomedical questions. The distribution analysis of elements (metals, semimetals, and non-metals) in biological samples is a point of interest in life sciences, especially within the context of metallomics, which is the scientific field that encompasses the global analysis of the entirety of elemental species inside a cell or tissue. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been efficiently employed to generate qualitative and quantitative maps of elemental distribution in thin tissue sections of a variety of biological samples, for example, brain, cartilage, spinal cord, etc. The combination of elemental with molecular mass spectrometry allows obtaining information about the elements bound to proteins, when they are previously separated by gel electrophoresis (metalloproteomics), and also adding a new dimension to molecular mass spectrometry imaging by the correlation of molecular and elemental distribution maps in definite regions in a biological tissue. In the present review, recent biomedical applications in LA-ICP-MS imaging as a stand-alone technique and in combination with molecular mass spectrometry imaging techniques are discussed. Applications of LA-ICP-MS in the study of neurodegenerative diseases, distribution of contrast agents and metallodrugs, and metalloproteomics will be focused in this review.

Analytical approaches for lipidomics and its potential applications in neuropsychiatric disorders.

Abstract Objectives: In this review, the authors discuss an overview of lipidomics followed by in-depth discussion of its application to the study of human diseases, including extraction methods of lipids, analytical techniques and clinical research in neuropsychiatric disorders. Methods: Lipidomics is a lipid-targeted metabolomics approach aiming at the comprehensive analysis of lipids in biological systems. Recent technological advancements in mass spectrometry and chromatography have greatly enhanced the development and applications of metabolic profiling of diverse lipids in complex biological samples. Results: An effective evaluation of the clinical course of diseases requires the application of very precise diagnostic and assessment approaches as early as possible. In order to achieve this, “omics” strategies offer new opportunities for biomarker identification and/or discovery in complex diseases and may provide pathological pathways understanding for diseases beyond traditional methodologies. Conclusions: This review highlights the importance of lipidomics for the future perspectives as a tool for biomarker identification and discovery and its clinical application.

Metabolomics: Definitions and Significance in Systems Biology

Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

Metabolomic Strategies Involving Mass Spectrometry Combined with Liquid and Gas Chromatography

Amongst all omics sciences, there is no doubt that metabolomics is undergoing the most important growth in the last decade. The advances in analytical techniques and data analysis tools are the main factors that make possible the development and establishment of metabolomics as a significant research field in systems biology. As metabolomic analysis demands high sensitivity for detecting metabolites present in low concentrations in biological samples, high-resolution power for identifying the metabolites and wide dynamic range to detect metabolites with variable concentrations in complex matrices, mass spectrometry is being the most extensively used analytical technique for fulfilling these requirements. Mass spectrometry alone can be used in a metabolomic analysis; however, some issues such as ion suppression may difficultate the quantification/identification of metabolites with lower concentrations or some metabolite classes that do not ionise as well as others. The best choice is coupling separation techniques, such as gas or liquid chromatography, to mass spectrometry, in order to improve the sensitivity and resolution power of the analysis, besides obtaining extra information (retention time) that facilitates the identification of the metabolites, especially when considering untargeted metabolomic strategies. In this chapter, the main aspects of mass spectrometry (MS), liquid chromatography (LC) and gas chromatography (GC) are discussed, and recent clinical applications of LC-MS and GC-MS are also presented.

Imaging of Selenium by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) in 2-D Electrophoresis Gels and Biological Tissues

Selenium and selenoproteins are important components of living organisms that play a role in different biological processes. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is a powerful analytical technique that has been employed to obtain distribution maps of selenium in biological tissues in a direct manner, as well as in selenoproteins, previously separated by their molecular masses and isoelectric points using two-dimensional polyacrylamide gel electrophoresis (2-D PAGE). In this chapter, we present the protocols to perform LA-ICP-MS imaging experiments, allowing the distribution visualization and determination of selenium and/or selenoproteins in biological systems.

A preliminary study of bipolar disorder type I by mass spectrometry-based serum lipidomics

The present study aimed at investigating possible alterations in the serum lipid profile of euthymic patients with bipolar disorder type I (BD) compared to healthy controls (HC). Thirty-five individuals from both genders were recruited, with 14 diagnosed and treated as BD patients (BD group) and 21 healthy subjects (HC group). Clinical assessment was based on the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), Young Mania Rating Scale (YMRS), and 17-items of Hamilton Depression Rating Scale (HDRS-17) data, which were used to confirm diagnosis, to verify psychiatric comorbidities, and to estimate the severity of manic and depressive symptoms. Ultra-high performance liquid chromatography (UHPLC) coupled to high resolution mass spectrometry (HRMS) was applied to analyze the lipids extracted from all serum samples from both studied groups. In this pioneer and exploratory study, we observed different serum lipid profiles for BD and HC groups, especially regarding glycerophospholipid, glycerolipid, and sphingolipid distribution. Multivariate statistical analyses indicated that 121 lipids were significantly different between BD and HC. Phosphatidylinositols were identified as the most altered lipids in BD patient sera. The results of this preliminary study reinforce the role of lipid abnormalities in BD and offer additional methodological possibilities for investigation in the field.