Metabolomics in chronic hepatitis C: Decoding fibrosis grading and underlying pathways.

BACKGROUND: Chronic Hepatitis C (CHC) affects 71 million people globally and leads to liver issues such as fibrosis, cirrhosis, cancer, and death. A better understanding and prognosis of liver involvement are vital to reduce morbidity and mortality. The accurate identification of the fibrosis stage is crucial for making treatment decisions and predicting outcomes. Tests used to grade fibrosis include histological analysis and imaging but have limitations. Blood markers such as molecular biomarkers can offer valuable insights into fibrosis. AIM: To identify potential biomarkers that might stratify these lesions and add information about the molecular mechanisms involved in the disease. METHODS: Plasma samples were collected from 46 patients with hepatitis C and classified into fibrosis grades F1 (n = 13), F2 (n = 12), F3 (n = 6), and F4 (n = 15). To ensure that the identified biomarkers were exclusive to liver lesions (CHC fibrosis), healthy volunteer participants (n = 50) were also included. An untargeted metabolomic technique was used to analyze the plasma metabolites using mass spectrometry and database verification. Statistical analyses were performed to identify differential biomarkers among groups. RESULTS: Six differential metabolites were identified in each grade of fibrosis. This six-metabolite profile was able to establish a clustering tendency in patients with the same grade of fibrosis; thus, they showed greater efficiency in discriminating grades. CONCLUSION: This study suggests that some of the observed biomarkers, once validated, have the potential to be applied as prognostic biomarkers. Furthermore, it suggests that liquid biopsy analyses of plasma metabolites are a good source of molecular biomarkers capable of stratifying patients with CHC according to fibrosis grade.

Unraveling the Metabolic Alterations Induced by Zika Infection in Prostate Epithelial (PNT1a) and Adenocarcinoma (PC-3) Cell Lines.

The outbreak of Zika virus infection in 2016 led to the identification of its presence in several types of biofluids, including semen. Later discoveries associated Zika infection with sexual transmission and persistent replication in cells of the male reproductive tract. Prostate epithelial and carcinoma cells are favorable to virus replication, with studies pointing to transcriptomics alterations of immune and inflammation genes upon persistence. However, metabolome alterations promoted by the Zika virus in prostate cells are unknown. Given its chronic effects and oncolytic potential, we aim to investigate the metabolic alterations induced by the Zika virus in prostate epithelial (PNT1a) and adenocarcinoma (PC-3) cells using an untargeted metabolomics approach and high-resolution mass spectrometry. PNT1a cells were viable up to 15 days post ZIKV infection, in contrast to its antiproliferative effect in the PC-3 cell lineage. Remarkable alterations in the PNT1a cell metabolism were observed upon infection, especially regarding glycerolipids, fatty acids, and acylcarnitines, which could be related to viral cellular resource exploitation, in addition to the over-time increase in oxidative stress metabolites associated with carcinogenesis. The upregulation of FA20:5 at 5 dpi in PC-3 cells corroborates the antiproliferative effect observed since this metabolite was previously reported to induce PC-3 cell death. Overall, Zika virus promotes extensive lipid alterations on both PNT1a and PC-3 cells, promoting different outcomes based on the cellular metabolic state.

Effect of in vitro digestion on the bioaccessibility and bioactivity of phenolic compounds in fractions of Eugenia pyriformis fruit.

Uvaia is a Brazilian fruit species that has great economic and nutritional potential, in addition to being a good source of compounds of biological interest. In this study, we evaluated for the first time the influence of in vitro gastrointestinal digestion on the bioaccessibility and bioactivity of phenolic compounds from two fractions of uvaia (edible and seed). It was observed that the content of total phenolic compounds was about 3 times higher in the seed (undigested extract), but reduced significantly after intestinal digestion (-50.08%). In turn, the total flavonoid content was about 5 times higher in the undigested seed extract. After intestinal digestion, the flavonoid content increased in the edible fraction (+109.49%) and decreased in the uvaia seed (-70.20%). The heatmap analysis showed that after intestinal digestion, there was an increase in the relative intensity of the flavonoids, while phenolic acids reduced their intensity. The antioxidant capacity of the undigested extract was 4-7 times greater for the seed, but decreased after intestinal digestion (-8.04-27.23%), while the antioxidant capacity of the edible fraction increased by 72.12-107.89% in this same stage of digestion. Thus, the content of phenolic compounds and antioxidant capacity were higher in the uvaia seed, and the bioaccessibility of the bioactive compounds in this fruit were dependent on the fraction and digestive phase evaluated. These results can contribute to the establishment of uvaia as a novel ingredient for preparations with functional claims.

Metabolic shift of chronic myeloid leukemia patients under imatinib-pioglitazone regimen and discontinuation.

The Estudo de Descontinuação de Imatinibe após Pioglitazona (EDI-PIO) is a single-center, longitudinal, prospective, phase 2, non-randomized, open, clinical trial (NCT02852486, August 2, 2016 retrospectively registered) for the discontinuation of imatinib after concomitant use of pioglitazone, being the first of its kind in a Brazilian population with chronic myeloid leukemia. Due to remaining of leukemic quiescent cells that are not affected by tyrosine kinase inhibitors, it has been suggested the use of pioglitazone, a PPARγ agonist, together with imatinib as a strategy for the maintenance of deep molecular response. The clinical benefit to this association is still controversial, and the metabolic alteration along this process remains unclear. Therefore, we applied a metabolomic protocol using high-resolution mass spectrometry to profile plasmatic metabolic response of a prospective cohort of ten individuals under discontinuation of imatinib and pioglitazone protocol. By comparing patients under pioglitazone and imatinib treatment with imatinib monotherapy and discontinuation phase, we were able to annotate 41 and 36 metabolites, respectively. The metabolic alterations observed during imatinib-pioglitazone combined therapy are associated with an extensive lipid remodeling, with activation of ß-oxidation pathway, in addition to the presence of markers that suggest mitochondrial dysfunction.

Evaluation of antioxidant capacity, fatty acid profile, and bioactive compounds from buritirana (Mauritiella armata Mart.) oil: A little-explored native Brazilian fruit.

Buritirana (Mauritiella armata Mart.) is a fruit species native to the Amazon and Cerrado region, belonging to the Arecaceae family. It has high nutritional and functional potential, yet little explored. In this study, we evaluated for the first time the overall yield, behavior of total carotenoids in the extraction kinetics, fatty acid profile, bioactive compounds, and the antioxidant capacity of the oil from buritirana fractions obtained by supercritical CO2. The highest extraction yield was found in the pulp and whole without seed at 60 °C (18.06 ± 0.40 and 14.55 ± 1.10 g 100 g-1 of the freeze-dried sample (fdw), respectively), and in the peel at 40 °C (8.31 ± 0.73 g 100 g-1 fdw). During the extraction kinetics, the pulp had the highest yields of oil (41.57%) and total carotenoids (8.34 mg g-1) after 61 min at 40 °C. The antioxidant potential, fatty acid profile, and α-tocopherol content were dependent on both fraction and temperature, with oleic acid being the main fatty acid. The oil from the whole fraction without seed had the largest number (20) of identified phenolic compounds. The extraction at 60 °C reduced the relative intensity of most compounds in the whole without seed and pulp. Moreover, it increased the intensity of the compounds in the peel. These results suggest that buritirana is a good oil source with great bioactive potential to produce new products with functional claims.

Chemical characterization of Eugenia stipitata: A native fruit from the Amazon rich in nutrients and source of bioactive compounds.

Eugenia stipitata is a fruit native to the Brazilian Amazonian region, belonging to the Myrtaceae family whose chemical composition has been little evidenced. In this study, we evaluated for the first time the nutritional composition, bioactive compounds and antioxidant properties of two fractions of this fruit. It was observed that the edible fraction had a higher content of minerals such as K, Ca and Mg (827.66 ± 14.51; 107.16 ± 1.54; and 75.65 ± 1.28 mg 100 g-1 dw, respectively), sucrose (38.01 ± 2.94 mg g-1 dw), fructose (17.58 ± 0.80 mg g-1 dw), and maltotetraose (1.63 ± 0.09 mg g-1 dw). In this same fraction, about 30 volatile compounds were found, mainly biciclo(3.2.1)octan-3-one, 6 (2-hydroxyethyl)-, endo-; butanoic acid, 2-methyl-, hexyl ester and p-ocimene. In turn, the seed had the highest number of compounds identified by ESI-LTQ-MS/MS (including vanillic acid, gallic acid hexoside, catechin hexoside, luteolin hexoside, among others), higher content of phenolics (142.43 ± 0.82 mg GAE g-1 dw), flavonoids (43.73 ± 0.23 mg CE g-1 dw), and antioxidant capacity (139.59 ± 2.47; 447.94 ± 2.70; and 100.07 ± 10.50 µM TE g-1 dw for DPPH, ABTS, and ORAC, respectively). These results suggest that Eugenia stipitata has excellent nutritional value and great functional potential, and may contribute to a greater commercial exploitation of this fruit, not only in food, but also in the pharmaceutical and cosmetic industries.

Influence of high-intensity ultrasound on color, chemical composition and antioxidant properties of araçá-boi pulp.

In this study, we evaluated the influence of the ultrasound application on five levels of energy density (1000; 3000; 5000 and 7000 J g-1) compared to two pasteurization techniques (70 °C/5 min and 94 °C/0.5 min) on color parameters, polyphenoloxidase activity, chemical composition, and antioxidant properties of araçá-boi pulp. Ultrasound caused changes in the parameters brightness/darkness, hue angle, and total color difference, but did not change chroma, yellowness/blueness, color index, and yellow index. Moreover, this technique was efficient for inactivating polyphenoloxidase. Ultrasound at 7000 J g-1 was responsible for an increase in soluble solids (16%), vitamin C (46.5%), phenolics (15.65%), flavonoids (50%) and antioxidant capacity in relation to untreated pulp, while ultrasound at 5000 J g-1 increased the relative intensity of compounds of biological interest. Thus, ultrasound can be considered as a promising technique to maintain the shelf life, without drastically affecting the nutritional and functional qualities of this fruit.

Distribution of nutrients and functional potential in fractions of Eugenia pyriformis: An underutilized native Brazilian fruit.

Uvaia is a Brazilian native species whose fruit has few studies on the nutritional composition and antioxidant properties. In this study, we evaluated for the first time the proximate composition, mineral content, carbohydrate profile, identification of organic compounds, and determination of antioxidant properties in two fractions of this fruit (edible fraction and seed). Edible fraction showed the highest content of ash, lipids, proteins, total fibers, minerals mainly K and Mg (1557.61 and 124.40 mg 100 g-1, respectively), and carbohydrates such as fructose, sucrose, glucose (123.08; 64.40; and 42.39 mg g-1, respectively), and maltotetraose (G4). From the ESI-LTQ-XL-MS/MS analysis, it was possible to identify 22 compounds in the edible fraction and 16 compounds in the uvaia seed, including organic acids, phenolic acids and flavonoids. On the other hand, uvaia seed had the highest content of total phenolics, flavonoids and antioxidant capacity. These results suggest that this fruit has great potential to be used in industry, with emphasis on making food with functional claims.

Metabolomics and Machine Learning Approaches Combined in Pursuit for More Accurate Paracoccidioidomycosis Diagnoses.

Brazil and many other Latin American countries are areas of endemicity for different neglected diseases, and the fungal infection paracoccidioidomycosis (PCM) is one of them. Among the clinical manifestations, pneumopathy associated with skin and mucosal lesions is the most frequent. PCM definitive diagnosis depends on yeast microscopic visualization and immunological tests, but both present ambiguous results and difficulty in differentiating PCM from other fungal infections. This research has employed metabolomics analysis through high-resolution mass spectrometry to identify PCM biomarkers in serum samples in order to improve diagnosis for this debilitating disease. To upgrade the biomarker selection, machine learning approaches, using Random Forest classifiers, were combined with metabolomics data analysis. The proposed combination of these two analytical methods resulted in the identification of a set of 19 PCM biomarkers that show accuracy of 97.1%, specificity of 100%, and sensitivity of 94.1%. The obtained results are promising and present great potential to improve PCM definitive diagnosis and adequate pharmacological treatment, reducing the incidence of PCM sequelae and resulting in a better quality of life.IMPORTANCE Paracoccidioidomycosis (PCM) is a fungal infection typically found in Latin American countries, especially in Brazil. The identification of this disease is based on techniques that may fail sometimes. Intending to improve PCM detection in patient samples, this study used the combination of two of the newest technologies, artificial intelligence and metabolomics. This combination allowed PCM detection, independently of disease form, through identification of a set of molecules present in patients' blood. The great difference in this research was the ability to detect disease with better confidence than the routine methods employed today. Another important point is that among the molecules, it was possible to identify some indicators of contamination and other infection that might worsen patients' condition. Thus, the present work shows a great potential to improve PCM diagnosis and even disease management, considering the possibility to identify concomitant harmful factors.

Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers.

Weight gain is a metabolic disorder that often culminates in the development of obesity and other comorbidities such as diabetes. Obesity is characterized by the development of a chronic, subclinical systemic inflammation, and is regarded as a remarkably important factor that contributes to the development of such comorbidities. Therefore, laboratory methods that allow the identification of subjects at higher risk for severe weight-associated morbidity are of utter importance, considering the health, and safety of populations. This contribution analyzed the plasma of 180 Brazilian individuals, equally divided into a eutrophic control group and case group, to assess the presence of biomarkers related to weight gain, aiming at characterizing the phenotype of this population. Samples were analyzed by mass spectrometry and most discriminant features were determined by a machine learning approach using Random Forest algorithm. Five biomarkers related to the pathogenesis and chronicity of inflammation in weight gain were identified. Two metabolites of arachidonic acid were upregulated in the case group, indicating the presence of inflammation, as well as two other molecules related to dysfunctions in the cycle of nitric oxide (NO) and increase in superoxide production. Finally, a fifth case group marker observed in this study may indicate the trigger for diabetes in overweight and obesity individuals. The use of mass spectrometry combined with machine learning analyses to prospect and characterize biomarkers associated with weight gain will pave the way for elucidating potential therapeutic and prognostic targets.

Molecular signatures associated with prostate cancer cell line (PC-3) exposure to inactivated Zika virus.

The recent outbreak of Zika virus (ZIKV) infection associated with microcephaly cases has elicited much research on the mechanisms involved in ZIKV-host cell interactions. It has been described that Zika virus impairs cell growth, raising a hypothesis about its oncolytic potential against cancer cells. ZIKV tumor cell growth inhibition was later confirmed for glioblastoma. It was also demonstrated that an inactivated ZIKV prototype (ZVp) based on bacterial outer membrane vesicles has antiproliferative activity upon other cancer cell lines, such as PC-3 prostate cancer cell. This study aims at understanding the pathways that might be involved with the antiproliferative effect of Zika virus against prostate cancer cells. A metabolomic approach based on high-resolution mass spectrometry analysis led to the identification of 21 statistically relevant markers of PC-3 cells treated with ZVp. The markers were associated with metabolic alterations that trigger lipid remodeling, endoplasmic reticulum stress, inflammatory mediators, as well as disrupted porphyrin and folate metabolism. These findings highlight molecular signatures of ZVp-induced response that may be involved on cellular pathways triggered by its antiproliferative effect. To our knowledge, this is the first reported metabolomic assessment of ZIKV effect on prostate cancer cells, a promising topic for further research.