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This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

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Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

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Metabolomics studies rely on the availability of suitable analytical platforms to determine a vast collection of chemically diverse metabolites in complex biospecimens. Liquid chromatography-mass spectrometry operated under reversed-phase conditions is the most commonly used platform in metabolomics, which offers extensive coverage for nonpolar and moderately polar compounds. However, complementary techniques are required to obtain adequate separation of polar and ionic metabolites, which are involved in several fundamental metabolic pathways. This chapter focuses on the main mass-spectrometry-based analytical platforms used to determine polar and/or ionizable compounds in metabolomics (GC-MS, HILIC-MS, CE-MS, IPC-MS, and IC-MS). Rather than comprehensively describing recent applications related to GC-MS, HILIC-MS, and CE-MS, which have been covered in a regular basis in the literature, a brief discussion focused on basic principles, main strengths, limitations, as well as future trends is presented in this chapter, and only key applications with the purpose of illustrating important analytical aspects of each platform are highlighted. On the other hand, due to the relative novelty of IPC-MS and IC-MS in the metabolomics field, a thorough compilation of applications for these two techniques is presented here.

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Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

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Zika virus (ZIKV), an emerging virus belonging to the Flaviviridae family, causes severe neurological clinical complications and has been associated with Guillain-Barré syndrome, fetal abnormalities known collectively as congenital Zika syndrome, and microcephaly. Studies have shown that ZIKV infection can alter cellular metabolism, directly affecting neural development. Brain growth requires controlled cellular metabolism, which is essential for cell proliferation and maturation. However, little is known regarding the metabolic profile of ZIKV-infected newborns and possible associations related to microcephaly. Furthering the understanding surrounding underlying mechanisms is essential to developing personalized treatments for affected individuals. Thus, metabolomics, the study of the metabolites produced by or modified in an organism, constitutes a valuable approach in the study of complex diseases. Here, 26 serum samples from ZIKV-positive newborns with or without microcephaly, as well as controls, were analyzed using an untargeted metabolomics approach involving gas chromatography-mass spectrometry (GC-MS). Significant alterations in essential and non-essential amino acids, as well as carbohydrates (including aldohexoses, such as glucose or mannose) and their derivatives (urea and pyruvic acid), were observed in the metabolic profiles analyzed. Our results provide insight into relevant metabolic processes in patients with ZIKV and microcephaly.

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Endophytes are microorganisms that live inside vegetal tissues without causing any loss to the host plant. They display wide biosynthetic capacity when producing several bioactive secondary metabolites, whose induction could be related to activation of genes, which might be silent or expressed depending on the geographic characteristics from where the endophytic was isolated. The extraordinary richness of the Brazilian biodiversity has encouraged several research groups in the endophytic bioprospecting. This review covers natural products reported by studies on from the Brazilian endophytic fungi cultures and classified them into three chemical classes (terpenes, phenolic, and nitrogen-containing compounds). For discussion purposes, Principal Component Analysis (PCA) was used as an unsupervised explorative method to evaluate the chemical variation in the Brazilian endophyte dataset. In addition, the dendrogram from the Hierarchical Clustering Analysis (HCA) confirmed the PCA results, and HCA could identify some main endophytic clusters. Our analysis clarified how the secondary metabolites were distributed in the different Brazilian endophyte strains, and this information will be a reliable guide that will support researchers to design microbial culture strategies.

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A RPLC-DAD method for the analysis of eight anthocyanins was developed, validated and applied to strawberry extracts. The chromatographic method was conducted under gradient elution in acidulated water-methanol mobile phase and octadecyl-silica columns. An ultrasound extraction procedure was optimized by a 3(2) factorial design (%HCl in methanol, temperature, and time) and response surface methodology. Method validation was performed according to the following parameters: linearity (R(2)>0.99, p-value<10(-4), F>725), LOD (3-7 µmol L(-1)) and LOQ (9-22 µmol L(-1)), selectivity/specificity (baseline separation of all analytes and peak purity), instrumental precision (<6.4%CV), repeatability (<6.3%CV) and intermediate precision (<9.9%CV), recovery (83-99%), robustness (mobile phase pH, column temperature and flow rate) and stability (high temperatures and storage; 1st order kinetics). The antioxidant power of anthocyanins was measured on-line (ABTS(+) reaction; Trolox as reference). Ten strawberry extracts were quantified (average values: 24.2 µg/g for cyanidin-3-glucoside and 49.1 µg/g for pelargonidin-3-glucoside).

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l-Arginine is an essential amino acid in Leishmania (Leishmania) amazonensis metabolism. A key enzyme for parasite l-arginine metabolism is arginase (ARG) that uses arginine to produce urea and ornithine, a precursor of polyamine pathway guaranteeing parasite replication in both insect and mammal hosts. There is an alternative pathway to produce ornithine via l-proline and glutamate, but this mechanism is not described in Leishmania. In the mammal host, two enzymes can use l-arginine as substrate, the host ARG and the induced nitric oxide synthase that produces nitric oxide. The competition between induced nitric oxide synthase and both parasite and host ARG can favor the success of the infection or its control. Here, we established the metabolomics profile of the polyamine pathway of wild type (WT) L. (L.) amazonensis, submitted or not to l-arginine starvation, and compared to the ARG-knockout mutant (arg- ). Our results indicated that arginine starvation induces a decrease in arginine, ornithine, and putrescine, but we could not detect the significative level changes of spermidine, spermine, or agmatine. However, the absence of ARG on the arg- induced an increase of arginine and citrulline levels, but decreased the levels of ornithine and putrescine. Similarly to the WT arginine-starved parasites, the arg- parasites presented lower levels of proline when compared to the WT ones. This could be indicative of an alternative pathway to surpass the enzyme or its substrate absence.

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This review article compiles in a critical manner literature publications regarding seven neglected diseases (ND) prioritized in Brazil (Chagas disease, dengue, leishmaniasis, leprosy, malaria, schistosomiasis, and tuberculosis) under the perspective of metabolomics. Both strategies, targeted and untargeted metabolomics, were considered in the compilation. The majority of studies focused on biomarker discovery for diagnostic purposes, and on the search of novel or alternative therapies against the ND under consideration, although temporal progression of the infection at metabolic level was also addressed. Tuberculosis, followed by schistosomiasis, malaria and leishmaniasis are the diseases that received larger attention in terms of number of publications. Dengue and leprosy were the least studied and Chagas disease received intermediate attention. NMR and HPLC-MS technologies continue to predominate among the analytical platforms of choice in the metabolomic studies of ND. A plethora of metabolites were identified in the compiled studies, with expressive predominancy of amino acids, organic acids, carbohydrates, nucleosides, lipids, fatty acids, and derivatives.