Profiling of esterified fatty acids as biomarkers in the blood of dengue fever patients using a microliter-scale extraction followed by gas chromatography and mass spectrometry

Metabolomics applied in the study of emerging arboviruses caused by Aedes aegypti mosquitoes: A review

Arboviruses, such as chikungunya, dengue, yellow fever, and zika, caused by the bite of the Aedes aegypti mosquito, have been a frequent public health problem, with a high incidence of outbreaks in tropical and subtropical countries. These diseases are easily confused with a flu-like illness and present very similar symptoms, difficult to distinguish, and treat appropriately. The effects that these infections cause in the organism are fundamentally derived from complex metabolic processes. A prominent area of science that investigates the changes in the metabolism of complex organisms is the metabolomics. Metabolomics measures the metabolites produced or altered in biological organisms, through the use of robust analytical platforms, such as separation techniques hyphenated with mass spectrometry, combined with bioinformatics. This review article presents an overview of the basic concepts of metabolomics workflow and advances in this field, and compiles research articles that use this omic approach to study these arboviruses. In this context, the metabolomics is applied to search new therapies, understand the viral replication mechanisms, and access the host-virus interactions.

Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases

Viral emergence is an unpredictable but obvious event, particularly in the era of climate change and globalization. Efficient management of viral outbreaks depends on pre-existing knowledge and alertness. The potential hotspots of viral emergence often remain neglected and the information related to them is insufficient, particularly for emerging viruses. Viral replication and transmission rely upon usurping the host metabolic machineries. So altered host metabolic pathways can be exploited for containment of these viruses. Metabolomics provides the insight for tracing out such checkpoints. Consequently introspection of metabolic alteration at virus-host interface has evolved as prime area in current virology research. Chromatographic separation followed by mass spectrometry has been used as the predominant analytical platform in bulk of the analyses followed by nuclear magnetic resonance (NMR) and fluorescence based techniques. Although valuable information regarding viral replication and modulation of host metabolic pathways have been extracted but ambiguity often superseded the real events due to population effect over the infected cells. Exploration of cellular heterogeneity and differentiation of infected cells from the nearby healthy ones has become essential. Single cell metabolomics (SCM) emerges as necessity to explore such minute details. Mass spectrometry imaging (MSI) coupled with several soft ionization techniques such as electrospray ionization (ESI), laser ablation electrospray ionization (LAESI), matrix assisted laser desorption/ionization (MALDI), matrix-free laser desorption ionization (LDI) have evolved as the best suited platforms for SCM analyses. The potential of SCM has already been exploited to resolve several biological conundrums. Thus SCM is knocking at the door of virus-host interface.

Gas chromatography-mass spectrometry-based analytical strategies for fatty acid analysis in biological samples

Fatty acids play critical roles in biological systems. Imbalances in fatty acids are related to a variety of diseases, which makes the measurement of fatty acids in biological samples important. Many analytical strategies have been developed to investigate fatty acids in various biological samples. Due to the structural diversity of fatty acids, many factors need to be considered when developing analytical methods including extraction methods, derivatization methods, column selections, and internal standard selections. This review focused on gas chromatography-mass spectrometry (GC-MS)-based methods. We reviewed several commonly used fatty acid extraction approaches, including liquid-liquid extraction and solid-phase microextraction. Moreover, both acid and base derivatization methods and other specially designed methods were comprehensively reviewed, and their strengths and limitations were discussed. Having good separation efficiency is essential to building an accurate and reliable GC-MS platform for fatty acid analysis. We reviewed the separation performance of different columns and discussed the application of multidimensional GC for improving separations. The selection of internal standards was also discussed. In the final section, we introduced several biomedical studies that measured fatty acid levels in different sample matrices and provided hints on the relationships between fatty acid imbalances and diseases.

Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses

The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host⁻virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans.

Serum fatty acids and progression from dengue fever to dengue haemorrhagic fever/dengue shock syndrome

PUFA might modulate inflammatory responses involved in the development of severe dengue. We aimed to examine whether serum PUFA concentrations in patients diagnosed with dengue fever (DF) were related to the risk of progression to dengue haemorrhagic fever/dengue shock syndrome (DHF/DSS). A secondary aim was to assess correlations between fatty acids (FA) and inflammatory biomarkers in patients with DF. We conducted a prospective case-control study nested within a cohort of patients who were diagnosed with DF and followed during the acute episode. We compared the distribution of individual FA (% of total FA) at onset of fever between 109 cases who progressed to DHF/DSS and 235 DF non-progressing controls using unconditional logistic regression. We estimated correlations between baseline FA and cytokine concentrations and compared FA concentrations between the acute episode and >1 year post-convalescence in a subgroup. DHA was positively related to progression to DHF/DSS (multivariable adjusted OR (AOR) for DHA in quintile 5 v. 1=5·34, 95 % CI 2·03, 14·1; P trend=0·007). Dihomo-γ-linolenic acid (DGLA) was inversely associated with progression (AOR for quintile 5 v. 1=0·30, 95 % CI 0·13, 0·69; P trend=0·007). Pentadecanoic acid concentrations were inversely related to DHF/DSS. Correlations of PUFA with cytokines at baseline were low. PUFA were lower during the acute episode than in a disease-free period. In conclusion, serum DHA in patients with DF predicts higher odds of progression to DHF/DSS whereas DGLA and pentadecanoic acid predict lower odds.

Fatty acid profiling of blood cell membranes by gas chromatography with mass spectrometry

Fatty acids, which are well-known for their influence on human metabolism and signal transduction, are also a substantial component of cellular membranes and regulate the basic properties and functions of membranes. Owing to their multiple functions, fatty acid profiles of cell membranes are of great interest to those who are studying the relationship between membrane biochemical compositions and functions. A HCl-catalyzed derivation method and a gas chromatography with mass spectrometry analysis method were developed to accurately profile the fatty acids in cell membranes of erythrocytes, leukocytes, and platelets. The detection limits of all 35 fatty acids ranged from 0.58 to 22 ng/mL and the limits of quantitation were between 2.1 and 72 ng/mL. Finally, the established method was used to profile the membrane fatty acids of 44 healthy volunteers from the north and south of China. Results revealed significant differences in the fatty acid profiles from the two regions, particularly those of the erythrocytes. This technique may be applied to cell membrane studies to generate new biological hypotheses concerning fatty acid composition and membrane functions as well as to construct related disease profiles.

Fatty acids composition of Caenorhabditis elegans using accurate mass GCMS-QTOF

The free living nematode Caenorhabditis elegans is a proven model organism for lipid metabolism research. Total lipids of C. elegans were extracted using chloroform and methanol in 2:1 ratio (v/v). Fatty acids composition of the extracted total lipids was converted to their corresponding fatty acids methyl esters (FAMEs) and analyzed by gas chromatography/accurate mass quadrupole time of flight mass spectrometry using both electron ionization and chemical ionization techniques. Twenty-eight fatty acids consisting of 12 to 22 carbon atoms were identified, 65% of them were unsaturated. Fatty acids containing 12 to17 carbons were mostly saturated with stearic acid (18:0) as the major constituent. Several branched-chain fatty acids were identified. Methyl-14-methylhexadecanoate (iso- 17:0) was the major identified branched fatty acid. This is the first report to detect the intact molecular parent ions of the identified fatty acids in C. elegans using chemical ionization compared to electron ionization which produced fragmentations of the FAMEs.

Discovery of Candidate Biomarkers

Properly performed, biomarker discovery can lead to effective candidates that can ultimately serve as predictors of disease, medical condition, define therapeutic parameters, and many other applications in medicine. Preferably, biomarkers comprise a panel of indicators, e.g. proteins and/or peptides that can be predictive or diagnostic of the medical condition of interest. Emphasis here is placed on "panel," as single candidates are rarely sufficient to provide the necessary sensitivity and specificity. To develop an effective panel that survives the development process described in Chap. 19 , proper experimental design and attention to important statistical parameters are critical to ensure success. Errors in discovery can lead to an inefficient use of expensive resources, as these may not be uncovered until the latter stages in biomarker development. Hence, accuracy, precision, and an estimate of the power of the proposed analyses are critical in the discovery of the panel of candidate biomarkers by proteomic methods, as is the selection of statistical approaches to refine and appropriately reduce the dataset for subsequent confirmatory assays.

Phospholipidomic identification of potential serum biomarkers in dengue fever, hepatitis B and hepatitis C using liquid chromatography-electrospray ionization-tandem mass spectrometry

The serum phospholipid (PL) profiles of healthy volunteers (HE) and patients with recently diagnosed dengue fever (DF), hepatitis B (HBV), and hepatitis C (HCV) were investigated using liquid chromatography-ion trap-mass spectrometry (LC-IT-MS) and liquid chromatography-triple quad-mass spectrometry (LC-TQ-MS). Major PLs, including lyso-phosphatidylcholins (LPCs), phosphatidylcholins (PCs), phosphatidylinositols (PIs), phosphatidylethanolamines (PEs) and phosphatidylserines (PSs), were characterized in human serum using LC-IT-MS. Thirty-five PLs were quantified using seven non-endogenous odd-carbon PL standards. An MS search protocol for the identification of PLs is described. The analytical method was optimized to achieve maximum recovery and detection. PLs were detected with minimal ionization suppression. The PLs species were characterized on the basis of (i) MS(2) peaks due to polar head, (ii) precursor ion or neutral loss scans, (iii) identification of fatty acid, (iv) identification of sn-1 and sn-2 fatty acid. The quantitation data were subjected to principal component analysis (PCA), and a significant difference was observed between the PL profiles of the investigated diseases and those of HE subjects. The significance of the changes in each lipid among the four groups was statistically assessed using one-way analysis of variance (ANOVA) followed by Bonferroni post hoc multiple comparison. The serum profiles of 28 PLs were determined to be significantly different and enabled the discrimination between HE individuals and the studied patients. Potentially dysregulated PLs were considered as differentiating biomarkers to diagnose DF, HBV, and HCV.