UHPLC-MS/MS and GC-MS Metabolic Profiling of a Medicinal Flourensia Fiebrigii Chemotype.

The comparative metabolic profiling and their biological properties of eight extracts obtained from diverse parts (leaves, flowers, roots) of the medicinal plant Flourensia fiebrigii S.F. Blake, a chemotype growing in highland areas (2750 m a.s.l.) of northwest Argentina, were investigated. The extracts were analysed by GC-MS and UHPLC-MS/MS. GC-MS analysis revealed the presence of encecalin (relative content: 24.86 %) in ethereal flower extract (EF) and this benzopyran (5.93 %) together sitosterol (11.35 %) in the bioactive ethereal leaf exudate (ELE). By UHPLC-MS/MS the main compounds identified in both samples were: limocitrin, (22.31 %), (2Z)-4,6-dihydroxy-2-[(4-hydroxy-3,5-dimethoxyphenyl)methylidene]-1-benzofuran-3-one (21.31 %), isobavachin (14.47 %), naringenin (13.50 %), and sternbin, (12.49 %). Phytocomplexes derived from aerial parts exhibited significant activity against biofilm production of Pseudomonas aeruginosa and Staphylococcus aureus, reaching inhibitions of 74.7-99.9 % with ELE (50 µg/mL). Notably, the extracts did not affect nutraceutical and environmental bacteria, suggesting a selective activity. ELE also showed the highest reactive species scavenging ability. This study provides valuable insights into the potential applications of this chemotype.

Unlocking hot trub's potential: a simple method for extracting bitter acids and xanthohumol.

BACKGROUND: Hot trub is a macronutrient- and micronutrient-rich by-product generated in the brewing industry, which is still underrated as a raw material for reprocessing purposes. In this context, this study aimed to investigate the extraction of bitter acids' and xanthohumol from hot trub as well as identify the significance of parameters for the process. The research assessed various extraction parameters, such as pH, ethanol concentration, temperature, and solid-to-liquid ratio, using a Plackett-Burman design. RESULTS: Ethanol concentration and pH were the most significant parameters affecting extraction yield. ß-acids were found to be the principal components of the bitter acids, with a maximum concentration near 16 mg g-1, followed by iso-α-acids and α-acids achieving 6 and 3.6 mg g-1, respectively. The highest yields of bitter acids were observed in the highest ethanol concentration, while pH was relevant to extraction process in treatments with low ethanol ratios. Concerning the xanthohumol extraction, the approach achieved maximum concentration (239 µg g-1) in treatments with ethanol concentration above 30%. Despite their variances, the phytochemicals exhibited comparable extraction patterns, indicating similar interactions with macromolecules. Moreover, the characterization of the solid residues demonstrated that the extraction process did not bring about any alterations to the chemical and total protein profiles. CONCLUSION: Ethanol concentration was found to have the most significant impact on the extraction of bitter acids and xanthohumol, while temperature had no significant effect. The solid remains resulting from the extraction showed potential for use as a protein source. © 2024 Society of Chemical Industry.

An overview of metabolomic and proteomic profiling in bipolar disorder and its clinical value.

INTRODUCTION: Bipolar disorder (BD) is a complex psychiatric disease characterized by alternating mood episodes. As for any other psychiatric illness, currently there is no biochemical test that is able to support diagnosis or therapeutic decisions for BD. In this context, the discovery and validation of biomarkers are interesting strategies that can be achieved through proteomics and metabolomics. AREAS COVERED: In this descriptive review, a literature search including original articles and systematic reviews published in the last decade was performed with the objective to discuss the results of BD proteomic and metabolomic profiling analyses and indicate proteins and metabolites (or metabolic pathways) with potential clinical value. EXPERT OPINION: A large number of proteins and metabolites have been reported as potential BD biomarkers; however, most studies do not reach biomarker validation stages. An effort from the scientific community should be directed toward the validation of biomarkers and the development of simplified bioanalytical techniques or protocols to determine them in biological samples, in order to translate proteomic and metabolomic findings into clinical routine assays.

MS-Driven Metabolic Alterations Are Recapitulated in iPSC-Derived Astrocytes.

OBJECTIVE: Astrocytes play a significant role in the pathology of multiple sclerosis (MS). Nevertheless, for ethical reasons, most studies in these cells were performed using the Experimental Autoimmune Encephalomyelitis model. As there are significant differences between human and mouse cells, we aimed here to better characterize astrocytes from patients with MS (PwMS), focusing mainly on mitochondrial function and cell metabolism. METHODS: We obtained and characterized induced pluripotent stem cell (iPSC)-derived astrocytes from three PwMS and three unaffected controls, and performed electron microscopy, flow cytometry, cytokine and glutamate measurements, gene expression, in situ respiration, and metabolomics. We validated our findings using a single-nuclei RNA sequencing dataset. RESULTS: We detected several differences in MS astrocytes including: (i) enrichment of genes associated with neurodegeneration, (ii) increased mitochondrial fission, (iii) increased production of superoxide and MS-related proinflammatory chemokines, (iv) impaired uptake and enhanced release of glutamate, (v) increased electron transport capacity and proton leak, in line with the increased oxidative stress, and (vi) a distinct metabolic profile, with a deficiency in amino acid catabolism and increased sphingolipid metabolism, which have already been linked to MS. INTERPRETATION: Here we describe the metabolic profile of iPSC-derived astrocytes from PwMS and validate this model as a very powerful tool to study disease mechanisms and to perform non-invasive drug targeting assays in vitro. Our findings recapitulate several disease features described in patients and provide new mechanistic insights into the metabolic rewiring of astrocytes in MS, which could be targeted in future therapeutic studies. ANN NEUROL 2022;91:652-669.

Understanding ayahuasca effects in major depressive disorder treatment through in vitro metabolomics and bioinformatics.

Emerging insights from metabolomic-based studies of major depression disorder (MDD) are mainly related to biochemical processes such as energy or oxidative stress, in addition to neurotransmission linked to specific metabolite intermediates. Hub metabolites represent nodes in the biochemical network playing a critical role in integrating the information flow in cells between metabolism and signaling pathways. Limited technical-scientific studies have been conducted to understand the effects of ayahuasca (Aya) administration in the metabolism considering MDD molecular context. Therefore, this work aims to investigate an in vitro primary astrocyte model by untargeted metabolomics of two cellular subfractions: secretome and intracellular content after pre-defined Aya treatments, based on DMT concentration. Mass spectrometry (MS)-based metabolomics data revealed significant hub metabolites, which were used to predict biochemical pathway alterations. Branched-chain amino acid (BCAA) metabolism, and vitamin B6 and B3 metabolism were associated to Aya treatment, as "housekeeping" pathways. Dopamine synthesis was overrepresented in the network results when considering the lowest tested DMT concentration (1 µmol L-1). Building reaction networks containing significant and differential metabolites, such as nicotinamide, L-DOPA, and L-leucine, is a useful approach to guide on dose decision and pathway selection in further analytical and molecular studies.

Metabolomic and proteomic profiling in bipolar disorder patients revealed potential molecular signatures related to hemostasis.

INTRODUCTION: Bipolar disorder (BD) is a mood disorder characterized by the occurrence of depressive episodes alternating with episodes of elevated mood (known as mania). There is also an increased risk of other medical comorbidities. OBJECTIVES: This work uses a systems biology approach to compare BD treated patients with healthy controls (HCs), integrating proteomics and metabolomics data using partial correlation analysis in order to observe the interactions between altered proteins and metabolites, as well as proposing a potential metabolic signature panel for the disease. METHODS: Data integration between proteomics and metabolomics was performed using GC-MS data and label-free proteomics from the same individuals (N = 13; 5 BD, 8 HC) using generalized canonical correlation analysis and partial correlation analysis, and then building a correlation network between metabolites and proteins. Ridge-logistic regression models were developed to stratify between BD and HC groups using an extended metabolomics dataset (N = 28; 14 BD, 14 HC), applying a recursive feature elimination for the optimal selection of the metabolites. RESULTS: Network analysis demonstrated links between proteins and metabolites, pointing to possible alterations in hemostasis of BD patients. Ridge-logistic regression model indicated a molecular signature comprising 9 metabolites, with an area under the receiver operating characteristic curve (AUROC) of 0.833 (95% CI 0.817-0.914). CONCLUSION: From our results, we conclude that several metabolic processes are related to BD, which can be considered as a multi-system disorder. We also demonstrate the feasibility of partial correlation analysis for integration of proteomics and metabolomics data in a case-control study setting.

Metabolomics: A Powerful Tool to Understand the Schizophrenia Biology.

ABSVTRACT: Schizophrenia, as any other psychiatric disorder, is a multifactorial and complex illness whose etiology is not completely established. Therefore, studies involving strategies that are able to describe the molecular alterations caused by the disease and, consequently, indicate the altered metabolic pathways are of increasing interest. Metabolomics is a very suitable approach that can be applied for this task, since it consists of the evaluation of the set of metabolites contained in a biological system undergoing a biological process, such as a disease or treatment. In metabolomics, state-of-the-art analytical techniques (mass spectrometry and nuclear magnetic resonance) are employed to identify and quantify the metabolites present in the studied biological samples, and chemometric and bioinformatic tools are applied to determine the specific metabolites and metabolic pathways that are relevant to the biological process under investigation. The aim of this chapter is to describe the basic principles of metabolomics, how this strategy can improve the understanding of the schizophrenia biology, and the findings obtained so far.

Chronic Methylmercury Intoxication Induces Systemic Inflammation, Behavioral, and Hippocampal Amino Acid Changes in C57BL6J Adult Mice.

Methylmercury (MeHg) is highly toxic to the human brain. Although much is known about MeHg neurotoxic effects, less is known about how chronic MeHg affects hippocampal amino acids and other neurochemical markers in adult mice. In this study, we evaluated the MeHg effects on systemic lipids and inflammation, hippocampal oxidative stress, amino acid levels, neuroinflammation, and behavior in adult male mice. Challenged mice received MeHg in drinking water (2 mg/L) for 30 days. We assessed weight gain, total plasma cholesterol (TC), triglycerides (TG), endotoxin, and TNF levels. Hippocampal myeloperoxidase (MPO), malondialdehyde (MDA), acetylcholinesterase (AChE), amino acid levels, and cytokine transcripts were evaluated. Mice underwent open field, object recognition, Y, and Barnes maze tests. MeHg-intoxicated mice had higher weight gain and increased the TG and TC plasma levels. Elevated circulating TNF and LPS confirmed systemic inflammation. Higher levels of MPO and MDA and a reduction in IL-4 transcripts were found in the hippocampus. MeHg-intoxication led to increased GABA and glycine, reduced hippocampal taurine levels, delayed acquisition in the Barnes maze, and poor locomotor activity. No significant changes were found in AChE activity and object recognition. Altogether, our findings highlight chronic MeHg-induced effects that may have long-term mental health consequences in prolonged exposed human populations.

Rapid and direct detection of artificially aged papers employing easy ambient sonic-spray ionization mass spectrometry.

RATIONALE: The effort to make fake documents look real leads to the use of crickets and beverages to produce artificially aged papers, as land titles, based on yellowing caused by the use of these methods. An old practice in Brazil, called "cricketing", has led to the misappropriation of Brazilian land using these documents. We propose a rapid, simple, instantaneous and non-destructive method to identify artificially aged papers by easy ambient sonic-spray ionization mass spectrometry (EASI-MS) analysis. METHODS: Three typical aging procedures were used to obtain artificially aged papers using coffee, cola drink, and crickets, with the papers being analyzed by EASI-MS. Multivariate statistical analyses were performed on the data to find the sample groups and to study the most relevant ions of each ageing procedure. High-resolution MS (HRMS) was used to obtain the exact masses and attribute formulae to relevant ions present in the samples. RESULTS: The combination of EASI-MS and multivariate statistical analyses allowed us to identify the most relevant ions to classify the adulteration of documents and HRMS identified most of these relevant ions. TMS fingerprinting in combination with multivariate analysis also demonstrated that this approach can qualitatively differentiate all the examined paper samples. CONCLUSIONS: We developed a cheap, fast and easy method that can help to elucidate counterfeit documents that have been artificially aged, helping to identify chemical additives and one that can be used in forensic laboratories.

Laser ablation ICP-MS: Application in biomedical research.

In the last decade, the development of diverse bioanalytical methodologies based on mass spectrometry imaging has increased, as has their application in biomedical questions. The distribution analysis of elements (metals, semimetals, and non-metals) in biological samples is a point of interest in life sciences, especially within the context of metallomics, which is the scientific field that encompasses the global analysis of the entirety of elemental species inside a cell or tissue. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been efficiently employed to generate qualitative and quantitative maps of elemental distribution in thin tissue sections of a variety of biological samples, for example, brain, cartilage, spinal cord, etc. The combination of elemental with molecular mass spectrometry allows obtaining information about the elements bound to proteins, when they are previously separated by gel electrophoresis (metalloproteomics), and also adding a new dimension to molecular mass spectrometry imaging by the correlation of molecular and elemental distribution maps in definite regions in a biological tissue. In the present review, recent biomedical applications in LA-ICP-MS imaging as a stand-alone technique and in combination with molecular mass spectrometry imaging techniques are discussed. Applications of LA-ICP-MS in the study of neurodegenerative diseases, distribution of contrast agents and metallodrugs, and metalloproteomics will be focused in this review. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:47-57, 2017.

Elemental fingerprinting of schizophrenia patient blood plasma before and after treatment with antipsychotics.

Antipsychotics are the main line of treatment for schizophrenia, a disorder that affects about 1% of the worldwide population. Considering the poor performance of antipsychotics on patients, this work aimed at detecting alterations in the elemental profile resulting from the use of this type of medication using an elemental fingerprinting strategy. We evaluated 56 plasma samples from schizophrenia patients by inductively coupled plasma mass spectrometry (ICP-MS) before (t0) and after 6 weeks (t6) of treatment. The level of response of the patients (good vs. poor responders) and the medications taken were considered. Zinc, aluminum, phosphorus, and iron levels were found to be increased, whereas sodium, potassium, calcium, and magnesium levels decreased after treatment. Aluminum presented a higher level in poor responders at t0 when compared to good responders. At t6, iron showed an increased level when compared to t0 for good responders; however, its level remained constant in poor responders. The results of this exploratory study provide clues for further investigations on the role of metal ions in the treatment of schizophrenia.

Metallomics Applied to the Study of Neurodegenerative and Mental Diseases.

Biochemical imbalances, provoked by aging or a secondary illness, might directly affect the brain, causing severe problems, such as loss of memory or alteration of behavior patterns. Brain disorders are usually classified as injuries (such as stroke, hematomas, and concussions), tumors, and neurodegenerative (such as Parkinson's and Alzheimer's diseases) and mental (such as depression, bipolar disorder, schizophrenia) diseases. As the pathophysiology of these illnesses is not completely established and multiple factors are involved, metallomics, a bioanalytical strategy that allows the detection of metal ions and metalloproteins in diverse biological matrices, is of extreme relevance in identifying which elements are affected by a disease and/or treatment. Thus, determining which element ions suffer disturbances in their homeostasis during the disease progress is relevant to understand the biochemical changes and propose new drug targets. In addition, it is well known that oxidative stress plays an important role in the development of pathological neurodegenerative and mental diseases, which may be caused by metal ion dyshomeostasis, so it is also important to understand endogenous antioxidant metalloprotein and metalloenzyme mechanisms in this regard. In this context, recent applications of metallomics in the study of neurodegenerative and mental disorders are discussed in this chapter, as well as future trends in this research area.

Metabolomic Strategies Involving Mass Spectrometry Combined with Liquid and Gas Chromatography.

Amongst all omics sciences, there is no doubt that metabolomics is undergoing the most important growth in the last decade. The advances in analytical techniques and data analysis tools are the main factors that make possible the development and establishment of metabolomics as a significant research field in systems biology. As metabolomic analysis demands high sensitivity for detecting metabolites present in low concentrations in biological samples, high-resolution power for identifying the metabolites and wide dynamic range to detect metabolites with variable concentrations in complex matrices, mass spectrometry is being the most extensively used analytical technique for fulfilling these requirements. Mass spectrometry alone can be used in a metabolomic analysis; however, some issues such as ion suppression may difficultate the quantification/identification of metabolites with lower concentrations or some metabolite classes that do not ionise as well as others. The best choice is coupling separation techniques, such as gas or liquid chromatography, to mass spectrometry, in order to improve the sensitivity and resolution power of the analysis, besides obtaining extra information (retention time) that facilitates the identification of the metabolites, especially when considering untargeted metabolomic strategies. In this chapter, the main aspects of mass spectrometry (MS), liquid chromatography (LC) and gas chromatography (GC) are discussed, and recent clinical applications of LC-MS and GC-MS are also presented.

Metabolomics: Definitions and Significance in Systems Biology.

Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

Caffeine quantification in dietary supplements using high-throughput on-line solid phase extraction coupled to Venturi easy ambient sonic-spray ionization mass spectrometry.

Caffeine is present in a large number of beverages and is an additive used in dietary supplements. Therefore, the concern about its quality and safety for consumers has been increasing and hence requires faster and simpler analytical methods to determine the caffeine amount. The high-throughput analysis is an appropriate solution to pharmaceuticals, bioanalysis, forensic and food laboratory routines. In this sense, Venturi easy ambient sonic-spray ionization mass spectrometry (V-EASI-MS), a specific ambient ionization source, is suitable to enable direct analysis of sample solutions in real time and is appropriate to be coupled to liquid chromatography (LC). The development of an on-line solid phase extraction system coupled to V-EASI-MS optimizes the advantages of LC-MS hyphenation by enhancing the figures of merit of the analytical method according to AOAC guidelines and simultaneously minimizing the runtime analysis to 1.5 min per sample, as well as sample preparation steps and solvent consumption, which is currently a challenge for quantitative applications of ambient ionization MS.

The influence of growth time on the identification of Bartonella henselae strains by MALDI-TOF mass spectrometry.

Bartonella spp. are bacteria responsible for neglected diseases worldwide. Bartonella henselae is the species most associated with human infections. It is associated with a large spectrum of clinical manifestations and is potentially fatal. The identification of Bartonella spp. is considered a challenge in clinical routine. These bacteria are fastidious, and the time required to isolate them varies from one to six weeks. MALDI-TOF mass spectrometry has emerged as an application for research on Bartonella spp. , and has still been little explored. We investigated whether three different B. henselae strains with different growth times-14 and 28 days-could be correctly identified by MALDI-TOF mass spectra fingerprint comparison and matching. We found that the spectra from strains with different growth times do not match each other, leading to misidentification. We suggest creating database entries with multiple spectra from strains with different growth times to increase the chances of accurate identification of Bartonella spp. by MALD-TOF MS.

Application of Lipidomics in Psychiatry: Plasma-Based Potential Biomarkers in Schizophrenia and Bipolar Disorder.

In this study, we obtained a lipidomic profile of plasma samples from drug-naïve patients with schizophrenia (SZ) and bipolar disorder (BD) in comparison to healthy controls. The sample cohort consisted of 30 BD and 30 SZ patients and 30 control individuals. An untargeted lipidomics strategy using liquid chromatography coupled with high-resolution mass spectrometry was employed to obtain the lipid profiles. Data were preprocessed, then univariate (t-test) and multivariate (principal component analysis and orthogonal partial least squares discriminant analysis) statistical tools were applied to select differential lipids, which were putatively identified. Afterward, multivariate receiver operating characteristic tests were performed, and metabolic pathway networks were constructed, considering the differential lipids. Our results demonstrate alterations in distinct lipid pathways, especially in glycerophospholipids, sphingolipids and glycerolipids, between SZ and BD patients. The results obtained in this study may serve as a basis for differential diagnosis, which is crucial for effective treatment and improving the quality of life of patients with psychotic disorders.

Metabolomic analysis reveals stress tolerance mechanisms in common bean (Phaseolus vulgaris L.) related to treatment with a biostimulant obtained from Corynebacterium glutamicum.

Microbial biostimulants have emerged as a sustainable alternative to increase the productivity and quality of important crops. Despite this, the effects of the treatment on plant metabolism are poorly understood. Thus, this study investigated the metabolic response of common bean (Phaseolus vulgaris) related to the treatment with a biostimulant obtained from the extract of Corynebacterium glutamicum that showed positive effects on the development, growth, and yield of crops previously. By untargeted metabolomic analysis using UHPLC-MS/MS, plants and seeds were subjected to treatment with the biostimulant. Under ideal growth conditions, the plants treated exhibited higher concentration levels of glutamic acid, nicotiflorin and glycosylated lipids derived from linolenic acid. The foliar application of the biostimulant under water stress conditions increased the chlorophyll content by 17% and induced the accumulation of flavonols, mainly quercetin derivatives. Also, germination seed assays exhibited longer radicle lengths for seeds treated compared to the untreated control even in the absence of light (13-18% increase, p-value <0.05). Metabolomic analysis of the seeds indicated changes in concentration levels of amino acids (tryptophan, phenylalanine, tyrosine, glutamine, and arginine) and their derivatives. The results point out the enhancement of abiotic stress tolerance and the metabolic processes triggered in this crop associated with the treatment with the biostimulant, giving the first insights into stress tolerance mechanisms in P. vulgaris.

Bioaccumulation and speciation of arsenic in plankton from tropical soda lakes along a salinity gradient.

Uptake and transformation of arsenic (As) by living organisms can alter its distribution and biogeochemical cycles in the environment. Although well known for its toxicity, several aspects of As accumulation and biological transformation by field species are still little explored. In this study, the bioaccumulation and speciation of As in phytoplankton and zooplankton from five soda lakes in the Brazilian Pantanal wetland were studied. Such lakes exhibited contrasting biogeochemical characteristics along an environmental gradient. Additionally, the influence of contrasting climatic events was assessed by collecting samples during an exceptional drought in 2017 and a flood in 2018. Total As (AsTot) content and speciation were determined using spectrometric techniques, while a suspect screening of organoarsenicals in plankton samples was carried out by high-resolution mass spectrometry. Results showed that AsTot content ranged from 16.9 to 62.0 mg kg-1 during the dry period and from 2.4 to 12.3 mg kg-1 during the wet period. The bioconcentration and bioaccumulation factors (BCF and BAF) in phytoplankton and zooplankton were found to be highly dependent on the lake typology, which is influenced by an ongoing evapoconcentration process in the region. Eutrophic and As-enriched lakes exhibited the lowest BCF and BAF values, possibly due to the formation of non-labile As complexes with organic matter or limited uptake of As by plankton caused by high salinity stress. The season played a decisive role in the results, as significantly higher BCF and BAF values were observed during the flooding event when the concentration of dissolved As in water was low. The diversity of As species was found to be dependent on the lake typology and on the resident biological community, cyanobacteria being responsible for a significant portion of As metabolism. Arsenosugars and their degradation products were detected in both phytoplankton and zooplankton, providing evidence for previously reported detoxification pathways. Although no biomagnification pattern was observed, the diet seemed to be an important exposure pathway for zooplankton.