Urinary steroids in premenopausal women with breast cancer at the time of surgery

Summary Urinary steroid metabolites were measured by capillary gas chromatogaphy in 10 premenopausal women with operable breast cancer and 16 control women a day before operation. There were significant decreases in the levels of androsterone (A), main cortisol (F) metabolites/tetrahydrocortisone (THE), tetrahydrocortisol (THF), allo-tetrahydrocortisol (aTHF)/and β-cortolone (βCL). The lower adrenal function accompanies breast cancer in premenopausal women. As the number of patients included in the study is small our conclusions must be considered as preliminary. Presented at Balaton Symposium '01 on High-Performance Separation Methods, Siófok, Hungary, September 2–4, 2001     

The interaction between the gut microbiota and dietary carbohydrates in nonalcoholic fatty liver disease

Imbalance between fat production and consumption causes various metabolic disorders. Nonalcoholic fatty liver disease (NAFLD), one such pathology, is characterized by abnormally increased fat synthesis and subsequent fat accumulation in hepatocytes^1,2. While often comorbid with obesity and insulin resistance, this disease can also be found in lean individuals, suggesting specific metabolic dysfunction². NAFLD has become one of the most prevalent liver diseases in adults worldwide, but its incidence in both children and adolescents has also markedly increased in developed nations^3,4. Progression of this disease into nonalcoholic steatohepatitis (NASH), cirrhosis, liver failure, and hepatocellular carcinoma in combination with its widespread incidence thus makes NAFLD and its related pathologies a significant public health concern. Here, we review our understanding of the roles of dietary carbohydrates (glucose, fructose, and fibers) and the gut microbiota, which provides essential carbon sources for hepatic fat synthesis during the development of NAFLD.Subject terms: Metabolic syndrome, Metabolic syndrome     

Exercise training modulates the gut microbiota profile and impairs inflammatory signaling pathways in obese children

Childhood obesity has reached epidemic levels and is a serious health concern associated with metabolic syndrome, nonalcoholic fatty liver disease, and gut microbiota alterations. Physical exercise is known to counteract obesity progression and modulate the gut microbiota composition. This study aims to determine the effect of a 12-week strength and endurance combined training program on gut microbiota and inflammation in obese pediatric patients. Thirty-nine obese children were assigned randomly to the control or training group. Anthropometric and biochemical parameters, muscular strength, and inflammatory signaling pathways in mononuclear cells were evaluated. Bacterial composition and functionality were determined by massive sequencing and metabolomic analysis. Exercise reduced plasma glucose levels and increased dynamic strength in the upper and lower extremities compared with the obese control group. Metagenomic analysis revealed a bacterial composition associated with obesity, showing changes at the phylum, class, and genus levels. Exercise counteracted this profile, significantly reducing the Proteobacteria phylum and Gammaproteobacteria class. Moreover, physical activity tended to increase some genera, such as Blautia, Dialister, and Roseburia, leading to a microbiota profile similar to that of healthy children. Metabolomic analysis revealed changes in short-chain fatty acids, branched-chain amino acids, and several sugars in response to exercise, in correlation with a specific microbiota profile. Finally, the training protocol significantly inhibited the activation of the obesity-associated NLRP3 signaling pathway. Our data suggest the existence of an obesity-related deleterious microbiota profile that is positively modified by physical activity intervention. Exercise training could be considered an efficient nonpharmacological therapy, reducing inflammatory signaling pathways induced by obesity in children via microbiota modulation.Subject terms: High-throughput screening, DNA metabolism     

Biotransformation of the saponins in Panax notoginseng leaves mediated by gut microbiota from insomniac patients

Saponins extracted from Panax notoginseng leaves by methanol or water could be orally administrated for insomnia with very low bioavailability, which might be bio-converted by gut microbiota to generate potential bioactive products. Moreover, gut microbiota profiles from insomniac patients are very different from healthy subjects. We aimed to compare the metabolic characteristics and profiles of the two saponins extract by incubation with gut microbiota from insomniac patients. The ginsenosides, notoginsenosides, and metabolites were identified and relatively quantified by high-performance liquid chromatography-tandem mass spectrometry. Gut microbiota was profiled by 16S ribosomal RNA gene sequencing. The results showed that saponins were very different between methanol or water extract groups, which were metabolized by gut microbiota to generate similar yields. The main metabolites included ginsenoside Rd, ginsenoside F₂, ginsenoside C-Mc or ginsenoside C-Y, ginsenoside C-Mx, ginsenoside compound K, and protopanaxadiol in both groups, while gypenoside XVII, notoginsenoside Fe, ginsenoside Rd₂, and notoginsenoside Fd were the intermediates in the methanol group. Moreover, the microbial, Faecalibacterium prausnitzi, could bio-convert the saponins to obtain the corresponding metabolites. Our study implied that saponins extracted from P. notoginseng leaves by methanol or water could be used for insomniac patients due to gut microbiota biotransformation.     

Alterations of the exo- and endometabolite profiles in breast cancer cell lines: A mass spectrometry-based metabolomics approach

In recent years, knowledge about metabolite changes which are characteristic for the physiologic state of cancer cells has been acquired by liquid chromatography coupled to mass spectrometry. Distinct molecularly characterized breast cancer cell lines provide an unbiased and standardized in vitro tumor model reflecting the heterogeneity of the disease. Tandem mass spectrometry is a widely applied analytical platform and highly sensitive technique for analysis of complex biological samples. Endo- and exometabolite analysis of the breast cancer cell lines MDA-MB-231, -453 and BT-474 as well as the breast epithelial cell line MCF-10A has been performed using two different analytical platforms: UPLC-ESI-Q-TOF based on a scheduled precursor list has been applied for highlighting of significant differences between cell lines and HPLC-ESI-QqQ using multiple reaction monitoring has been utilized for a targeted approach focusing on RNA metabolism and interconnected pathways, respectively. Statistical analysis enabled a clear discrimination of the breast epithelial from the breast cancer cell lines. As an effect of oxidative stress, a decreased GSH/GSSG ratio has been detected in breast cancer cell lines. The triple negative breast cancer cell line MDA-MB-231 showed an elevation in nicotinamide, 1-ribosyl-nicotinamide and NAD+ reflecting the increased energy demand in triple negative breast cancer, which has a more aggressive clinical course than other forms of breast cancer. Obtained distinct metabolite pattern could be correlated with distinct molecular characteristics of breast cancer cells. Results and methodology of this preliminary in vitro study could be transferred to in vivo studies with breast cancer patients.     

Real-time identification of gut microbiota with aminopeptidase N using an activable NIR fluorescent probe

A NIR fluorescent probe (DDAA) derived from fluorophore DDAO with alanine as the recognition group was developed for sensing aminopeptidase N (APN) in gut microbiota. Using DDAA as the real-time guidance tool for the fluorescence imaging of intestinal microorganism, target bacteria and saccharomycete possessing active APN were identified successfully from human feces.     

Serum protein profiles of patients with pancreatic cancer and chronic pancreatitis: searching for a diagnostic protein pattern.

In this study, 13 sera from patients with pancreatic cancer, 9 from chronic pancreatitis and 10 from healthy subjects were analyzed by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. The MALDI mass spectra revealed the presence of several low molecular weight peptides, among which some were detected only in the sera from both pathological conditions. On the other hand many peptides were observed only in control sera, and were absent in the sera from the two diseases. Therefore, MALDI analysis of the low molecular weight fraction (<10 000 Da) of sera from patients with pancreatic diseases enabled us to identify the presence of some disease-related signals and also some signals characteristic of normal subjects.     

Biomolecule profiles in inedible wild mushrooms with antioxidant value

The use of natural products isolated from mushrooms, included inedible species, against infection, cancer diseases and other oxidative-stress related diseases is one of the cornerstones of modern medicine. In the present work, the antioxidant molecule profiles of inedible mushroom species were evaluated and compared with those of edible species. The order of antioxidant abundance found in inedible wild mushrooms was: phenolics > flavonoids > ascorbic acid > tocopherols > carotenoids, similar to that of edible species. Furthermore the same energetic biomolecules were found including the disaccharide trehalose, the monosaccharide alcohol derivative mannitol and the fatty acids palmitic, oleic and linoleic acids. Fomitopsis pinicola revealed a very high phenolics concentration (388 mg GAE/g extract) and powerful antioxidant properties, mainly reducing power (EC??) value 60 μg/mL similar to the standard Trolox?). It could find applications in the prevention of free radical-related diseases as a source of bioactive compounds.     

Ganmaidazao decoction alleviated cognitive impairment on Alzheimer's disease rats by regulating gut microbiota and their corresponding metabolites

Traditional Chinese medicine targeted at gut microbiota has good effects in relieving the clinical manifestation of Alzheimer's disease, and intestinal metabolites are considered as a bridge of communication between the brain-gut axis. In order to explore the molecular mechanism of Ganmaidazao decoction treatment, first, the model rats induced by Aβ25-35 and d-gal were used to test the therapy of Ganmaidazao extract using the Morris Water Maze, Western Blot and Elisa. Then the 16S rDNA gene sequencing of the gut microbiota as well as UPLC-QTOF/MS-based metabolomic analysis of feces were carried out. Last, the relationship between Alzheimer's disease, gut microbiota and metabolites was analyzed. Results showed that the abundance and diversity of gut microbiota were rescued and the changes of fecal metabolites in rats with Alzheimer's disease were reversed after Ganmaidazao decoction administration, which were mainly related to lipid metabolism, steroid hormone metabolism, energy metabolism, amino acid metabolism and bile acid metabolism. After associating with Spearman’s correlation analysis, we concluded that gut microbiota and metabolites were closely related and Ganmaidazao decoction could interfere with the balance of gut microbiota and their corresponding metabolites to exert anti- Alzheimer’s disease effect. Combined with PICRUSt2 functional prediction of gut microbiota and metabolomics results, phenylalanine metabolism has been focused as a key metabolic pathway, and Ganmaidazao decoction can reduce the abnormal accumulation of phenylalanine and phenylpyruvate and promote their metabolism by restoring the activity of phenylalanine hydroxylase. This integrated omics approach has potential roles in understanding the complex mechanisms of Ganmaidazao decoction in treating Alzheimer’s disease.     

HS-SPME-GC-MS approach for the analysis of volatile salivary metabolites and application in a case study for the indirect assessment of gut microbiota

In this work, a straightforward analytical approach based on headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry was developed for the analysis of salivary volatile organic compounds without any prior derivatization step. With a sample volume of 500 μL, optimal conditions were achieved by allowing the sample to equilibrate for 10 min at 50 °C and then extracting the samples for 10 min at the same temperature, using a carboxen/polydimethylsiloxane fibre. The method allowed the simultaneous identification and quantification of 20 compounds in sample headspace, including short-chain fatty acids and their derivatives which are commonly analysed after analyte derivatization. The proof of applicability of the methodology was performed with a case study regarding the analysis of the dynamics of volatile metabolites in saliva of a single subject undergoing 5-day treatment with rifaximin antibiotic. Non-stimulated saliva samples were collected over 3 weeks from a nominally healthy volunteer before, during, and after antibiotic treatment. The variations of some metabolites, known to be produced by the microbiota and by bacteria that are susceptible to antibiotics, suggest that the study of the dynamics of salivary metabolites can be an excellent indirect method for analysing the gut microbiota. This approach is novel from an analytical standpoint, and it encourages further studies combining saliva metabolite profiles and gut microbiota dynamics.

Graphical abstract

     

Trace element profiles in the hair of cancer patients

The trace element profiles of the scalp hair of cancer patients were measured and compared with those of healthy people. Significant differences were observed for several elements, especially for Au, I and Se.     

Random walks and their diagnostic value for characterization of atomic environment

A characterization of atomic environments based on counting random walks in a molecular skeleton is outlined. To each atom in a molecule a sequence of integers w₁, w₂, w₃,…, w_n is assigned, where w_i represents the number of self-returning walks of length k, the length being defined by the number of bonds traversed. Properties of the derived atom codes are discussed. The codes display an impressive diversity and are superior to atomic codes based on enumeration of self-avoiding walks (or paths) in discriminating atomic environments. In certain cases the codes of individual atoms are not unique and the same codes appear in different molecules or even within the same molecule. The occurrence of the nonunique codes can be related to special structural situations, associated with the occurrence of isospectral graphs. These isospectral graphs which have atoms with identical codes can generate additional isospectral structures by attaching any arbitrary group to such points. If nonequivalent atoms of a single molecule have identical random walk codes, substitution at the singular points alternatively will produce isospectral graphs. Examples of such situations are given.     

Assessing chromatographic peak purity using condition index and singular value evolving profiles

A new method for determining chromatographic peak purity is presented. The method uses condition index evolving profiles (CIEPs) and singular value evolving profiles (SVEPs). To produce a CIEP or a SVEP, singular value decompositions are performed on data matrices containing the analyte's pure-component spectrum and sample spectra as they evolve over a chromatographic time profile. Visual inspection of condition indices and singular values as they evolve over time enables detection of less than 0.5% of a spectrally similar impurity with no chromatographic resolution (R_s = 0). Additionally, the CIEPs and SVEPs allow estimation of chromatographic pure regions. This method represents an extension of CIEPs which have been used in successful library searches of multicomponent mixtures based on gas chromatography-Fourier transform infrared spectra and liquid chromatography-UV-visible spectra.     

New look inside human breast ducts with Raman imaging. Raman candidates as diagnostic markers for breast cancer prognosis: Mammaglobin,palmitic acid and sphingomyelin

Looking inside the human body fascinated mankind for thousands of years. Current diagnostic and therapy methods are often limited by inadequate sensitivity, specificity and spatial resolution. Raman imaging may bring revolution in monitoring of disease and treatment. The main advantage of Raman imaging is that it gives spatial information about various chemical constituents in defined cellular organelles in contrast to conventional methods (liquid chromatography/mass spectrometry, NMR, HPLC) that rely on bulk or fractionated analyses of extracted components. We demonstrated how Raman imaging can drive the progress on breast cancer just unimaginable a few years ago. We looked inside human breast ducts answering fundamental questions about location and distribution of various biochemical components inside the lumen, epithelial cells of the duct and the stroma around the duct during cancer development. We have identified Raman candidates as diagnostic markers for breast cancer prognosis: carotenoids, mammaglobin, palmitic acid and sphingomyelin as key molecular targets in ductal breast cancer in situ, and propose the molecular mechanisms linking oncogenes with lipid programming.     

Comprehensive classification of USA cannabis samples based on chemical profiles of major cannabinoids and terpenoids

Abstract

Different USA-origin cannabis samples were analyzed by GC-FID to quantify all possible cannabinoids and terpenoids prior to their clustering. Chromatographic analysis confirmed the presence of seven cannabinoids and sixteen terpenoids with variable levels. Among tested cannabinoids, Δ⁹-Tetrahydrocannabinol Δ⁹-THC and cannabinol CBN were available in excess amounts (1.2–8.0?wt%) and (0.22–1.1?wt%), respectively. Fenchol was the most abundant terpenoid with a range of (0.03–1.0?wt%). The measured chemical profile was used to cluster 23 USA states and to group plant samples using different unsupervised multivariate statistical tools. Clustering of plant samples and states was sensitive to the selected cannabinoids/terpenoids. Principal component analysis (PCA) indicated the importance of Δ⁹-THC, CBN, CBG, CBC, THCV, Δ⁸-THC, CBL, and fenchol for samples clustering. Δ⁹-THC was significant to separate California-origin samples while CBN and fenchol were dominant to separate Oregon-origin samples away from the rest of cannabis samples. A special PCA analysis was performed on cannabinoids after excluding Δ⁹-THC (due to its high variability in the same plant) and CBN (as a degradation byproduct for THC). Results indicated that CBL and Δ⁸-THC were necessary to separate Nevada and Washington samples, while, CBC was necessary to isolate Oregon and Illinois plant samples. PCA based on terpenoids content confirmed the significance of caryophyllene, guaiol, limonene, linalool, and fenchol for clustering target. Fenchol played a major role for clustering plant samples that originated from Washington and Nevada. k-means method was more flexible than PCA and generated three different classes; samples obtained from Oregon and California in comparison to the rest of other samples were obviously separated alone, which attributed to their unique chemical profile. Finally, both PCA and k-means were useful and quick guides for cannabis clustering based on their chemical profile. Thus, less effort, time, and materials will be consumed in addition to decreasing operational conditions for cannabis clustering.     

Similarity search profiles as a diagnostic tool for the analysis of virtual screening calculations

An analysis method termed similarity search profiling has been developed to evaluate fingerprint-based virtual screening calculations. The analysis is based on systematic similarity search calculations using multiple template compounds over the entire value range of a similarity coefficient. In graphical representations, numbers of correctly identified hits and other detected database compounds are separately monitored. The resulting profiles make it possible to determine whether a virtual screening trial can in principle succeed for a given compound class, search tool, similarity metric, and selection criterion. As a test case, we have analyzed virtual screening calculations using a recently designed fingerprint on 23 different biological activity classes in a compound source database containing approximately 1.3 million molecules. Based on our predefined selection criteria, we found that virtual screening analysis was successful for 19 of 23 compound classes. Profile analysis also makes it possible to determine compound class-specific similarity threshold values for similarity searching.