Application of a gas chromatography mass spectrometry computer system for clinical diagnosis

Olfactory learning and memory in the greater short-nosed fruit bat Cynopterus sphinx: the influence of conspecifics distress calls

This study was designed to test whether Cynopterus sphinx distress calls influence olfactory learning and memory in conspecifics. Bats were exposed to distress calls/playbacks (PBs) of distress calls/modified calls and were then trained to novel odors. Bats exposed to distress calls/PBs made significantly fewer feeding attempts and bouts of PBs exposed to modified calls, which significantly induced the expression of c-Fos in the caudomedial neostriatum (NCM) and the amygdala compared to bats exposed to modified calls and trained controls. However, the expression of c-Fos in the hippocampus was not significantly different between the experimental groups. Further, protein phosphatase-1 (PP-1) expression was significantly lower, and the expression levels of E1A homologue of CREB-binding protein (CBP) (P300), brain-derived neurotrophic factor (BDNF) and its tyrosine kinase B1 (TrkB1) receptor were significantly higher in the hippocampus of control/bats exposed to modified calls compared to distress calls/PBs of distress call-exposed bats. Exposure to the call possibly alters the reciprocal interaction between the amygdala and the hippocampus, accordingly regulating the expression levels of PP1, P300 and BDNF and its receptor TrkB1 following training to the novel odor. Thus, the learning and memory consolidation processes were disrupted and showed fewer feeding attempts and bouts. This model may be helpful for understanding the contributions of stressful social communications to human disorders.

Redox proteomics gives insights into the role of oxidative stress in alkaptonuria

Alkaptonuria (AKU) is an ultra-rare metabolic disorder of the catabolic pathway of tyrosine and phenylalanine that has been poorly characterized at molecular level. As a genetic disease, AKU is present at birth, but its most severe manifestations are delayed due to the deposition of a dark-brown pigment (ochronosis) in connective tissues. The reasons for such a delayed manifestation have not been clarified yet, though several lines of evidence suggest that the metabolite accumulated in AKU sufferers (homogentisic acid) is prone to auto-oxidation and induction of oxidative stress. The clarification of the pathophysiological molecular mechanisms of AKU would allow a better understanding of the disease, help find a cure for AKU and provide a model for more common rheumatic diseases. With this aim, we have shown how proteomics and redox proteomics might successfully overcome the difficulties of studying a rare disease such as AKU and the limitations of the hitherto adopted approaches.

Definitions of terms relating to mass spectrometry (IUPAC Recommendations 2013)

This document contains recommendations for terminology in mass spectrometry. Development of standard terms dates back to 1974 when the IUPAC Commission on Analytical Nomenclature issued recommendations on mass spectrometry terms and definitions. In 1978, the IUPAC Commission on Molecular Structure and Spectroscopy updated and extended the recommendations and made further recommendations regarding symbols, acronyms, and abbreviations. The IUPAC Physical Chemistry Division Commission on Molecular Structure and Spectroscopy’s Subcommittee on Mass Spectroscopy revised the recommended terms in 1991 and appended terms relating to vacuum technology. Some additional terms related to tandem mass spectrometry were added in 1993 and accelerator mass spectrometry in 1994. Owing to the rapid expansion of the field in the intervening years, particularly in mass spectrometry of biomolecules, a further revision of the recommendations has become necessary. This document contains a comprehensive revision of mass spectrometry terminology that represents the current consensus of the mass spectrometry community.

Chemometrics in metabolomics--a review in human disease diagnosis

Metabolomics is a post genomic research field concerned with developing methods for analysis of low molecular weight compounds in biological systems, such as cells, organs or organisms. Analyzing metabolic differences between unperturbed and perturbed systems, such as healthy volunteers and patients with a disease, can lead to insights into the underlying pathology. In metabolomics analysis, large amounts of data are routinely produced in order to characterize samples. The use of multivariate data analysis techniques and chemometrics is a commonly used strategy for obtaining reliable results. Metabolomics have been applied in different fields such as disease diagnosis, toxicology, plant science and pharmaceutical and environmental research. In this review we take a closer look at the chemometric methods used and the available results within the field of disease diagnosis. We will first present some current strategies for performing metabolomics studies, especially regarding disease diagnosis. The main focus will be on data analysis strategies and validation of multivariate models, since there are many pitfalls in this regard. Further, we highlight the most interesting metabolomics publications and discuss these in detail; additional studies are mentioned as a reference for the interested reader. A general trend is an increased focus on biological interpretation rather than merely the ability to classify samples. In the conclusions, the general trends and some recommendations for improving metabolomics data analysis are provided.

Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS

An overview is presented of gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS), the two major hyphenated techniques employed in metabolic profiling that complement direct 'fingerprinting' methods such as atmospheric pressure ionization (API) quadrupole time-of-flight MS, API Fourier transform MS, and NMR. In GC/MS, the analytes are normally derivatized prior to analysis in order to reduce their polarity and facilitate chromatographic separation. The electron ionization mass spectra obtained are reproducible and suitable for library matching, mass spectral collections being readily available. In LC/MS, derivatization and library matching are at an early stage of development and mini-reviews are provided. Chemical derivatization can dramatically increase the sensitivity and specificity of LC/MS methods for less polar compounds and provides additional structural information. The potential of derivatization for metabolic profiling in LC/MS is demonstrated by the enhanced analysis of plant extracts, including the potential to measure volatile acids such as formic acid, difficult to achieve by GC/MS. The important role of mass spectral library creation and usage in these techniques is discussed and illustrated by examples.

Identifying Mycobacterium tuberculosis cultures by gas-liquid chromatography and a computer-aided pattern recognition model

A procedure that uses gas-liquid chromatography and a pattern recognition computer model was developed for distinguishing cultures of Mycobacterium tuberculosis from cultures of other mycobacteria, common bacteria, and fungi. In this procedure, a sample of a culture preparation is methanolyzed and trimethylsilylated sequentially and injected into a gas chromatograph equipped with a flame ionization detector. A pattern recognition procedure computes an error score by comparing the gas-liquid chromatography peak responses of a culture to those of a standard M. tuberculosis culture. Ten M. tuberculosis cultures were used in the development of the pattern recognition model. Computed error scores of 5 or less were established for identifying an M. tuberculosis culture. The method was evaluated with two sets of test samples, non-M. tuberculosis and M. tuberculosis cultures. Sample identification was correct for all 14 M. tuberculosis cultures (M. tuberculosis or non-M. tuberculosis), 45 fungal cultures, 94 bacterial cultures, and all but 1 of 18 cultures of mycobacteria other than tuberculosis (MOTT). The false prediction represented an isolate of M. fortuitum. For M. tuberculosis, fungal, bacterial, and MOTT cultures, the ranges of error scores were 1 to 5, 16 to 33, 13 to 34, and 4 to 26, respectively. Therefore, we have demonstrated that this diagnostic model can distinguish M. tuberculosis from non-M. tuberculosis cultures with a high degree of accuracy.

Metabolic profiling with gas chromatography-mass spectrometry and its application to clinical medicine

Nowadays, metabolic profiling is widely applied in clinical medicine for the diagnosis and study of human diseases. The number of these applications and their diversity have increased rapidly in the past few years. This review summarizes recent advances in the methods for sample pretreatment and the clinical application of GC-MS to the study of uraemia, diabetes mellitus, dicarboxylic aciduria and other organic acidurias. High-resolution GC-MS is well suited to the profile analysis of metabolic disorders.