Tumours display different cell populations with distinct metabolic phenotypes. Thus, subpopulations can adjust to different environments, particularly with regard to oxygen and nutrient availability. Our results indicate that progression to metastasis requires mitochondrial function. Our research, centered on cell lines that display increasing degrees of malignancy, focused on metabolic events, especially those involving mitochondria, which could reveal which stages are mechanistically associated with metastasis. Melanocytes were subjected to several cycles of adhesion impairment, producing stable cell lines exhibiting phenotypes representing a progression from non-tumorigenic to metastatic cells. Metastatic cells (4C11+) released the highest amounts of lactate, part of which was derived from glutamine catabolism. The 4C11+ cells also displayed an increased oxidative metabolism, accompanied by enhanced rates of oxygen consumption coupled to ATP synthesis. Enhanced mitochondrial function could not be explained by an increase in mitochondrial content or mitochondrial biogenesis. Furthermore, 4C11+ cells had a higher ATP content, and increased succinate oxidation (complex II activity) and fatty acid oxidation. In addition, 4C11+ cells exhibited a 2-fold increase in mitochondrial membrane potential (ΔΨmit). Consistently, functional assays showed that the migration of cells depended on glutaminase activity. Metabolomic analysis revealed that 4C11+ cells could be grouped as a subpopulation with a profile that was quite distinct from the other cells investigated in the present study. The results presented here have centred on how the multiple metabolic inputs of tumour cells may converge to compose the so-called metastatic phenotype.

Osteoarthritis (OA) is the main cause of disability worldwide, due to progressive articular cartilage loss and degeneration. According to recent research, OA is more than just a degenerative disease due to some metabolic components associated to its pathogenesis. However, no biomarker has been identified to detect this disease at early stages or to track its development. Metabolomics is an emerging field and has the potential to detect many metabolites in a single spectrum using high resolution nuclear magnetic resonance (NMR) techniques or mass spectrometry (MS). NMR is a reproducible and reliable non-destructive analytical method. On the other hand, MS has a lower detection limit and is more destructive, but it is more sensitive. NMR and MS are useful for biological fluids, such as urine, blood plasma, serum, or synovial fluid, and have been used for metabolic profiling in dogs, mice, sheep, and humans. Thus, many metabolites have been listed as possibly associated to OA pathogenesis. The goal of this review is to provide an overview of the studies in animal models and humans, regarding the use of metabolomics as a tool for early osteoarthritis diagnosis. The concept of osteoarthritis as a metabolic disease and the importance of detecting a biomarker for its early diagnosis are highlighted. Then, some studies in plasma and synovial tissues are shown, and finally the application of metabolomics in the evaluation of synovial fluid is described.

Sensitivity and resolution are key considerations for NMR applications in general, and for metabolomics in particular, where complex mixtures containing hundreds of metabolites over a large range of concentrations are commonly encountered. There is a strong demand for advanced methods that can provide maximal information in the shortest possible time frame. Here we present the optimization and application of the recently introduced 2D real-time BIRD 1 H-13 C HSQC experiment for NMR-based metabolomics at 13 C natural abundance of aqueous samples. For mouse urine samples, it is demonstrated how this real-time pure shift sensitivity improved Heteronuclear Single Quantum Correlation (HSQC-SI) method provides broadband homonuclear decoupling along the proton detection dimension and thereby significantly improves spectral resolution in regions that are affected by spectral overlap. Moreover, the collapse of the scalar multiplet structure of cross-peaks leads to a sensitivity gain of about 40% -50% over a traditional 2D HSQC-SI experiment. The experiment works well over a range of magnetic field strengths and is particularly useful when resonance overlap in crowded regions of the HSQC spectra hampers accurate metabolite identification and quantitation.

Tumor cells are subjected to a broad range of selective pressures. As a result of the imposed stress, subpopulations of surviving cells exhibit individual biochemical phenotypes that reflect metabolic reprograming. The present work aimed at investigating metabolic parameters of cells displaying increasing degrees of metastatic potential. The metabolites present in cell extracts fraction of tongue fibroblasts and of cell lines derived from human tongue squamous cell carcinoma lineages displaying increasing metastatic potential (SCC9 ZsG, LN1 and LN2) were analyzed by 1H NMR (nuclear magnetic resonance) spectroscopy. Living, intact cells were also examined by the non-invasive method of fluorescence lifetime imaging microscopy (FLIM) based on the auto fluorescence of endogenous NADH. The cell lines reproducibly exhibited distinct metabolic profiles confirmed by Partial Least-Square Discriminant Analysis (PLS-DA) of the spectra. Measurement of endogenous free and bound NAD(P)H relative concentrations in the intact cell lines showed that ZsG and LN1 cells displayed high heterogeneity in the energy metabolism, indicating that the cells would oscillate between glycolysis and oxidative metabolism depending on the microenvironment’s composition. However, LN2 cells appeared to have more contributions to the oxidative status, displaying a lower NAD(P)H free/bound ratio. Functional experiments of energy metabolism, mitochondrial physiology, and proliferation assays revealed that all lineages exhibited similar energy features, although resorting to different bioenergetics strategies to face metabolic demands. These differentiated functions may also promote metastasis. We propose that lipid metabolism is related to the increased invasiveness as a result of the accumulation of malonate, methyl malonic acid, n-acetyl and unsaturated fatty acids (CH2)n in parallel with the metastatic potential progression, thus suggesting that the NAD(P)H reflected the lipid catabolic/anabolic pathways.

Synovial fluid holds a population of mesenchymal stem cells (MSC) that could be used for clinical treatment. Our goal was to characterize the inflammatory and metabolomic profile of the synovial fluid from osteoarthritic patients and to identify its modulatory effect on synovial fluid cells. Synovial fluid was collected from non-OA and OA patients, which was centrifuged to isolate cells. Cells were cultured for 21 days, characterized with specific markers for MSC, and exposed to a specific cocktail to induce chondrogenic, osteogenic, and adipogenic differentiation. Then, we performed a MTT assay exposing SF cells from non-OA and OA patients to a medium containing non-OA and OA synovial fluid. Synovial fluid from non-OA and OA patients was submitted to ELISA to evaluate BMP-2, BMP-4, IL-6, IL-10, TNF-α, and TGF-β1 concentrations and to a metabolomic evaluation using 1H-NMR. Synovial fluid cells presented spindle-shaped morphology in vitro. Samples from OA patients formed a higher number of colonies than the ones from non-OA patients. After 21 days, the colony-forming cells from OA patients differentiated into the three mesenchymal cell lineages, under the appropriated induction protocols. Synovial fluid cells increased its metabolic activity after being exposed to the OA synovial fluid. ELISA assay showed that OA synovial fluid samples presented higher concentration of IL-10 and TGF-β1 than the non-OA, while the NMR showed that OA synovial fluid presents higher concentrations of glucose and glycerol. In conclusion, SFC activity is modulated by OA synovial fluid, which presents higher concentration of IL-10, TGF-β, glycerol, and glucose.

COVID-19 is an emergent, worldwide public health concern. Joint efforts have been made by scientific communities of various fields to better understand the mechanisms of action of SARS-CoV-2. The need to understand the pathophysiological fingerprint and pathways of this disease make metabolomics-related approaches an indispensable tool for properly answering concerns relating to disease course. Determination of the metabolomic profile may help to explain the heterogeneous spectra of COVID-19 clinical phenotypes and be useful in monitoring disease progression as well as therapeutic treatments. In this sense, saliva has proven to be a strategic biofluid, owing not only to its appeal as a noninvasive sampling method but also due to the capacity of the virus to invade epithelial cells of the oral mucosa and salivary gland ducts via ACE2 receptors. Accordingly, important changes in metabolism have been described relating to COVID-19, indicating that metabolomics may open new avenues for understanding the pathophysiology of this disease, especially via longitudinal study designs. Thus, we discuss the importance of comprehending the SARS-CoV-2 salivary metabolomic fingerprint and also highlight the situation of Brazil on the frontlines of the war against COVID-19.

Background In 1957, Francis Crick drew a linear diagram on a blackboard. This diagram is often called the “central dogma.” Subsequently, the relationships between different steps of the “central dogma” have been shown to be considerably complex, mostly because of the emerging world of small molecules. It is noteworthy that metabolites can be generated from the diet through gut microbiome metabolism, serve as substrates for epigenetic modifications, destabilize DNA quadruplexes, and follow Lamarckian inheritance. Small molecules were once considered the missing link in the “central dogma”; however, recently they have acquired a central role, and their general perception as downstream products has become reductionist. Metabolomics is a large-scale analysis of metabolites, and this emerging field has been shown to be the closest omics associated with the phenotype and concomitantly, the basis for all omics. Aim of review Herein, we propose a broad updated perspective for the flux of information diagram centered in metabolomics, including the influence of other factors, such as epigenomics, diet, nutrition, and the gut- microbiome. Key scientific concepts of review Metabolites are the beginning and the end of the flux of information.

Idiopathic interstitial pneumonias include complex diseases that have a strong interaction between genetic makeup and environmental factors. However, in many cases, no infectious agent can be demonstrated, and these clinical diseases rapidly progress to death. Theoretically, idiopathic interstitial pneumonias could be caused by the Epstein-Barr virus, cytomegalovirus, adenovirus, hepatitis C virus, respiratory syncytial virus, and herpesvirus, which may be present in such small amounts or such configuration that routine histopathological analysis or viral culture techniques cannot detect them. To test the hypothesis that immunohistochemistry provides more accurate results than the mere histological demonstration of viral inclusions, this method was applied to 37 open lung biopsies obtained from patients with idiopathic interstitial pneumonias. As a result, immunohistochemistry detected measles virus and cytomegalovirus in diffuse alveolar damage-related histological patterns of acute exacerbation of idiopathic pulmonary fibrosis and nonspecific interstitial pneumonia in 38 and 10% of the cases, respectively. Alveolar epithelium infection by cytomegalovirus was observed in 25% of organizing pneumonia patterns. These findings were coincident with nuclear cytopathic effects but without demonstration of cytomegalovirus inclusions. These data indicate that diffuse alveolar damage-related cytomegalovirus or measles virus infections enhance lung injury, and a direct involvement of these viruses in diffuse alveolar damage-related histological patterns is likely. Immunohistochemistry was more sensitive than the histological demonstration of cytomegalovirus or measles virus inclusions. We concluded that all patients with diffuse alveolar damage-related histological patterns should be investigated for cytomegalovirus and measles virus using sensitive immunohistochemistry in conjunction with routine procedures.