Post-COVID-19 Syndrome: Retinal Microcirculation as a Potential Marker for Chronic Fatigue.

Post-COVID-19 syndrome (PCS) is characterized by persisting sequelae after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). PCS can affect patients with all COVID-19 disease severities. As previous studies have revealed impaired blood flow as a provoking factor triggering PCS, it was the aim of the present study to investigate the potential association between self-reported chronic fatigue and retinal microcirculation in patients with PCS, potentially indicating an objective biomarker. A prospective study was performed, including 201 subjects: 173 patients with PCS and 28 controls. Retinal microcirculation was visualized by OCT angiography (OCT-A) and quantified using the Erlangen-Angio-Tool as macula and peripapillary vessel density (VD). Chronic fatigue (CF) was assessed according to the variables of Bell's score, age and gender. VDs in the superficial vascular plexus (SVP), intermediate capillary plexus (ICP) and deep capillary plexus (DCP) were analyzed, considering the repetitions (12 times). Seropositivity for autoantibodies targeting G protein-coupled receptors (GPCR-AAbs) was determined by an established cardiomyocyte bioassay. Taking account of the repetitions, a mixed model was performed to detect possible differences in the least square means between the different groups included in the analysis. An age effect in relation to VD was observed between patients and controls (p < 0.0001). Gender analysis showed that women with PCS showed lower VD levels in the SVP compared to male patients (p = 0.0015). The PCS patients showed significantly lower VDs in the ICP as compared to the controls (p = 0.0001 (CI: 0.32; 1)). Moreover, considering PCS patients, the mixed model revealed a significant difference between those with chronic fatigue (CF) and those without CF with respect to VDs in the SVP (p = 0.0033 (CI: −4.5; −0.92)). The model included variables of age, gender and Bell's score, representing a subjective marker for CF. Consequently, retinal microcirculation might serve as an objective biomarker in subjectively reported chronic fatigue in patients with PCS.

Long COVID: Association of Functional Autoantibodies against G-Protein-Coupled Receptors with an Impaired Retinal Microcirculation.

Long COVID (LC) describes the clinical phenotype of symptoms after infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Diagnostic and therapeutic options are limited, as the pathomechanism of LC is elusive. As the number of acute SARS-CoV-2 infections was and is large, LC will be a challenge for the healthcare system. Previous studies revealed an impaired blood flow, the formation of microclots, and autoimmune mechanisms as potential factors in this complex interplay. Since functionally active autoantibodies against G-protein-coupled receptors (GPCR-AAbs) were observed in patients after SARS-CoV-2 infection, this study aimed to correlate the appearance of GPCR-AAbs with capillary microcirculation. The seropositivity of GPCR-AAbs was measured by an established cardiomyocyte bioassay in 42 patients with LC and 6 controls. Retinal microcirculation was measured by OCT-angiography and quantified as macula and peripapillary vessel density (VD) by the Erlangen-Angio Tool. A statistical analysis yielded impaired VD in patients with LC compared to the controls, which was accentuated in female persons. A significant decrease in macula and peripapillary VD for AAbs targeting adrenergic ß2-receptor, MAS-receptor angiotensin-II-type-1 receptor, and adrenergic α1-receptor were observed. The present study might suggest that a seropositivity of GPCR-AAbs can be linked to an impaired retinal capillary microcirculation, potentially mirroring the systemic microcirculation with consecutive clinical symptoms.

Serum Selenium Levels in Glaucoma: a Pilot Study.

BACKGROUND: Trace elements are assumed to be involved in glaucoma pathogenesis via changes in oxidative stress. Especially serum selenium (Se) has been linked to this neurodegenerative disease. Serum Se levels differ between countries due to nutrition and ethnicity. It was the aim of the present study to investigate serum Se levels in primary open-angle glaucoma (POAG) patients and controls in Germany and to consider potential age and gender effects. MATERIAL AND METHODS: The Se concentration of 39 serum samples (22 patients with POAG, 17 controls) were analyzed by inductively coupled plasma-sector field mass spectrometry (ICP-sf-MS) in high resolution mode. Covariance and percentile regression were analyzed. Age and gender were defined as confounding factors and their different trends were investigated. Moreover, age was examined across different quantiles of Se levels. RESULTS: Total serum least-squares means (LS-means) Se levels were 132.02 µg/L (controls) and 134.86 µg/L (POAG). Total serum Se levels did not differ between the study groups (p > 0.05). Significant age and gender effects of serum Se were observed. Quantile analysis showed that the 1st serum Se quantile decreased with increasing age in POAG patients in contrast to controls. The odds ratios of the 1st serum Se were 1.3 (with 2nd quantile) and 1.3 (with 3rd quantile), respectively. CONCLUSION: The serum Se level of the German cohort was almost half of those of the published US cohort (glaucoma 209.11 ng/mL; control 194.45 ng/mL). Age and gender effects were observed; the serum Se level increased with age in women (controls and POAG), however, Se levels decreased with age in men (controls and POAG).

Metabolic Functions of Gut Microbes Associate With Efficacy of Tumor Necrosis Factor Antagonists in Patients With Inflammatory Bowel Diseases.

BACKGROUND & AIMS: Altered interactions between the mucosal immune system and intestinal microbiota contribute to pathogenesis of inflammatory bowel diseases (IBD). It is not clear how inhibitors of cytokines, such as antagonists of tumor necrosis factor (anti-TNF), affect the intestinal microbiome. We investigated the effects of anti-TNF agents on gut microbe community structure and function in a longitudinal 2-step study of patients with IBD. We correlated our findings with outcomes of treatment and investigated patterns of metabolites in fecal samples before and after anti-TNF therapy. METHODS: We performed a prospective study of 2 cohorts of patients in Germany; the discovery cohort comprised 12 patients with IBD, 17 patients with rheumatic disease, and 19 healthy individuals (controls); fecal samples were collected at baseline and 2, 6, and 30 weeks after induction of anti-TNF therapy. The validation cohort comprised 23 patients with IBD treated with anti-TNF or vedolizumab (anti-α4ß7 integrin) and 99 healthy controls; fecal samples were collected at baseline and at weeks 2, 6, and 14. Fecal microbiota were analyzed by V3-V4 16S ribosomal RNA gene amplicon sequencing. Clinical response and remission were determined by clinical disease activity scores. Metabolic network reconstruction and associated fecal metabolite level inference was performed in silico using the AGORA (Assembly of Gut Organisms through Reconstruction and Analysis) resource. Metabolomic analyses of fecal samples from a subset of patients were performed to validate metabolites associated with treatment outcomes. RESULTS: Anti-TNF therapy shifted the diversity of fecal microbiota in patients with IBD, but not with rheumatic disease, toward that of controls. Across timepoints, diversity indices did not vary significantly between patients with IBD who did or did not achieve clinical remission after therapy. In contrast, in silico modeling of metabolic interactions between gut microbes found metabolite exchange to be significantly reduced at baseline in fecal samples from patients with IBD and to be associated with later clinical remission. Predicted levels of butyrate and substrates involved in butyrate synthesis (ethanol or acetaldehyde) were significantly associated with clinical remission following anti-TNF therapy, verified by fecal metabolomic analyses. CONCLUSIONS: Metabolic network reconstruction and assessment of metabolic profiles of fecal samples might be used to identify patients with IBD likely to achieve clinical remission following anti-TNF therapy and increase our understanding of the heterogeneity of IBD.

OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility.

AIM: The aim of the present study was to investigate the reliability of macular microvasculature measurements in normal subjects by Heidelberg Spectralis II optical coherence tomography angiography (OCT-A) in combination with a newly made software. SUBJECTS AND METHODS: This prospective study included 23 eyes of 23 persons from the Erlangen Glaucoma Registry (ISSN 2191-5008, CS-2011; NTC00494923). The subjects underwent a complete clinical, standardized ophthalmologic examination to rule out any eye disease. En face OCT-A imaging was done using Heidelberg Spectralis II OCT (Heidelberg, Germany). Images were recorded with a 15 × 15° angle and a lateral resolution of 5.7 µm/pixel, resulting in a retinal section of 2.9 × 2.9 mm. The Erlangen-Angio-Tool (EA-Tool) OCT-A application performed multiple segmentations, allowing analysis of the vessel density in 12 segments. The software was coded in MATLAB. Macular data on the superficial vascular plexus (SVP), intermediate capillary plexus (ICP), and deep capillary plexus (DCP) were exported into the application and analyzed separately. The EA-Tool calculated the percentage of "white area" in the "total area" of the region of interest, called vessel density. Foveolar avascular zones (FAZs) of the SVP, ICP, and DCP were calculated manually. To investigate the reproducibility of the new software, individual scans (SVP, ICP, and DCP) were analyzed twice with the EA-Tool and intraclass coefficients (ICCs) of the vessel density values were calculated. Statistical analysis was performed with SPSS version 21.0. RESULTS: The mean vessel density of the SVP ranged between 30.4 and 33.5, that of the ICP between 20.9 and 24.7, and that of the DCP between 23.5 and 27.6. Bland-Altman plots showed a good reliability of two consecutive scans of each sector (S1-S12) in the SVP, ICP, and DCP. Testing reproducibility, no statistically significantly different sectorial coefficients of variation of the SVP, ICP, and DCP were observed (p > 0.05). The mean FAZ area of the SVP was 0.43 ± 0.16 mm2, that of the ICP 0.28 ± 0.1 mm2, and that of the DCP 0.44 ± 0.12 mm2. CONCLUSIONS: Spectralis OCT II, in combination with the semiautomated vessel density software EA-Tool, showed good or even excellent ICCs in 75% of all segments of the SVP, ICP, and DCP. The ICCs for the FAZ area in the SVP, ICP, and DCP were excellent.

Previously unknown class of metalorganic compounds revealed in meteorites.

The rich diversity and complexity of organic matter found in meteorites is rapidly expanding our knowledge and understanding of extreme environments from which the early solar system emerged and evolved. Here, we report the discovery of a hitherto unknown chemical class, dihydroxymagnesium carboxylates [(OH)2MgO2CR]-, in meteoritic soluble organic matter. High collision energies, which are required for fragmentation, suggest substantial thermal stability of these Mg-metalorganics (CHOMg compounds). This was corroborated by their higher abundance in thermally processed meteorites. CHOMg compounds were found to be present in a set of 61 meteorites of diverse petrological classes. The appearance of this CHOMg chemical class extends the previously investigated, diverse set of CHNOS molecules. A connection between the evolution of organic compounds and minerals is made, as Mg released from minerals gets trapped into organic compounds. These CHOMg metalorganic compounds and their relation to thermal processing in meteorites might shed new light on our understanding of carbon speciation at a molecular level in meteorite parent bodies.

Mass Difference Maps and Their Application for the Recalibration of Mass Spectrometric Data in Nontargeted Metabolomics.

Modern high-resolution mass spectrometry provides the great potential to analyze exact masses of thousands of molecules in one run. In addition, the high instrumental mass accuracy allows for high-precision formula assignments narrowing down tremendously the chemical space of unknown compounds. The adequate values for a mass accuracy are normally achieved by a proper calibration procedure that usually implies using known internal or external standards. This approach might not always be sufficient in cases when systematic error is highly prevalent. Therefore, additional recalibration steps are required. In this work, the concept of mass difference maps (MDiMs) is introduced with a focus on the visualization and investigation of all the pairwise differences between considered masses. Given an adequate reference list of sufficient size, MDiMs can facilitate the detection of a systematic error component. Such a property can be potentially applied for spectral recalibration. Consequently, a novel approach to describe the process of the correction of experimentally derived masses is presented. The method is based on the estimation of the density of data points on MDiMs using Gaussian kernels followed by a curve fitting with an adapted version of the particle swarm optimization algorithm. The described recalibration procedure is examined on simulated as well as real mass spectrometric data. For the latter case, blood plasma samples were analyzed by Fourier transform ion cyclotron resonance mass spectrometry. Nevertheless, due to its inherent flexibility, the method can be easily extended to other low- and high-resolution platforms and/or sample types.

Systems chemical analytics: introduction to the challenges of chemical complexity analysis.

Understanding complex (bio/geo)systems is a pivotal challenge in modern sciences that fuels a constant development of modern analytical technology, finding innovative solutions to resolve and analyse. In this introductory paper to the Faraday Discussion "Challenges in the analysis of complex natural systems", we aim to present concepts of complexity, and complex chemistry in systems subjected to biotic and abiotic transformations, and introduce the analytical possibilities to disentangle chemical complexity into its elementary parts (i.e. compositional and structural resolution) as a global integrated approach termed systems chemical analytics.

Microbiome-Triggered Transformations of Trace Organic Chemicals in the Presence of Effluent Organic Matter in Managed Aquifer Recharge (MAR) Systems.

It is widely assumed that biodegradation of trace organic chemicals (TOrCs) in managed aquifer recharge (MAR) systems occurs via a cometabolic transformation with dissolved organic carbon serving as primary substrate. Hence, the composition facilitating bioavailability of the organic matter seems to have a great impact on TOrCs transformation in MAR systems. The aim of this study was to elucidate the character of effluent organic matter present in the feedwater of a simulated sequential MAR system throughout the infiltration by use of FT-ICR-MS analyses as well as spectroscopic methods. Furthermore, compositional changes were correlated with TOrCs targeted throughout the system as well as the abundance of different microbial phyla. On the basis of their behavior throughout the infiltration system in which different redox and substrate conditions prevailed, TOrCs were classified in four groups: easily degradable, redox insensitive, redox sensitive, and persistent. Masses correlating with persistent TOrCs were mainly comprised of CHNO-containing molecules but also of CHO which are known as carboxyl-rich alicyclic molecules, while CHOS and CHNOS can be neglected. Easily degradable TOrCs could be associated with CHNO-, CHO-, and CHOS-containing compounds. However, a shift of molecular compounds to mostly CHOS was observed for redox-insensitive TOrCs. Three hundred thirty eight masses correlated with removal of redox-sensitive TOrCs, but no distinct clustering was identified.

Chemical messages in 170-year-old champagne bottles from the Baltic Sea: Revealing tastes from the past.

Archaeochemistry as the application of the most recent analytical techniques to ancient samples now provides an unprecedented understanding of human culture throughout history. In this paper, we report on a multiplatform analytical investigation of 170-y-old champagne bottles found in a shipwreck at the bottom of the Baltic Sea, which provides insight into winemaking practices used at the time. Organic spectroscopy-based nontargeted metabolomics and metallomics give access to the detailed composition of these wines, revealing, for instance, unexpected chemical characteristics in terms of small ion, sugar, and acid contents as well as markers of barrel aging and Maillard reaction products. The distinct aroma composition of these ancient champagne samples, first revealed during tasting sessions, was later confirmed using state-of-the-art aroma analysis techniques. After 170 y of deep sea aging in close-to-perfect conditions, these sleeping champagne bottles awoke to tell us a chapter of the story of winemaking and to reveal their extraordinary archaeometabolome and elemental diversity in the form of chemical signatures related to each individual step of champagne production.

Oral versus intravenous iron replacement therapy distinctly alters the gut microbiota and metabolome in patients with IBD.

OBJECTIVE: Iron deficiency is a common complication in patients with IBD and oral iron therapy is suggested to exacerbate IBD symptoms. We performed an open-labelled clinical trial to compare the effects of per oral (PO) versus intravenous (IV) iron replacement therapy (IRT). DESIGN: The study population included patients with Crohn's disease (CD; N=31), UC (N=22) and control subjects with iron deficiency (non-inflamed, NI=19). After randomisation, participants received iron sulfate (PO) or iron sucrose (IV) over 3 months. Clinical parameters, faecal bacterial communities and metabolomes were assessed before and after intervention. RESULTS: Both PO and IV treatments ameliorated iron deficiency, but higher ferritin levels were observed with IV. Changes in disease activity were independent of iron treatment types. Faecal samples in IBD were characterised by marked interindividual differences, lower phylotype richness and proportions of Clostridiales. Metabolite analysis also showed separation of both UC and CD from control anaemic participants. Major shifts in bacterial diversity occurred in approximately half of all participants after IRT, but patients with CD were most susceptible. Despite individual-specific changes in phylotypes due to IRT, PO treatment was associated with decreased abundances of operational taxonomic units assigned to the species Faecalibacterium prausnitzii, Ruminococcus bromii, Dorea sp. and Collinsella aerofaciens. Clear IV-specific and PO-specific fingerprints were evident at the level of metabolomes, with changes affecting cholesterol-derived host substrates. CONCLUSIONS: Shifts in gut bacterial diversity and composition associated with iron treatment are pronounced in IBD participants. Despite similar clinical outcome, oral administration differentially affects bacterial phylotypes and faecal metabolites compared with IV therapy. TRIAL REGISTRATION NUMBER: clinicaltrial.gov (NCT01067547).

MetICA: independent component analysis for high-resolution mass-spectrometry based non-targeted metabolomics.

BACKGROUND: Interpreting non-targeted metabolomics data remains a challenging task. Signals from non-targeted metabolomics studies stem from a combination of biological causes, complex interactions between them and experimental bias/noise. The resulting data matrix usually contain huge number of variables and only few samples, and classical techniques using nonlinear mapping could result in computational complexity and overfitting. Independent Component Analysis (ICA) as a linear method could potentially bring more meaningful results than Principal Component Analysis (PCA). However, a major problem with most ICA algorithms is the output variations between different runs and the result of a single ICA run should be interpreted with reserve. RESULTS: ICA was applied to simulated and experimental mass spectrometry (MS)-based non-targeted metabolomics data, under the hypothesis that underlying sources are mutually independent. Inspired from the Icasso algorithm, a new ICA method, MetICA was developed to handle the instability of ICA on complex datasets. Like the original Icasso algorithm, MetICA evaluated the algorithmic and statistical reliability of ICA runs. In addition, MetICA suggests two ways to select the optimal number of model components and gives an order of interpretation for the components obtained. CONCLUSIONS: Correlating the components obtained with prior biological knowledge allows understanding how non-targeted metabolomics data reflect biological nature and technical phenomena. We could also extract mass signals related to this information. This novel approach provides meaningful components due to their independent nature. Furthermore, it provides an innovative concept on which to base model selection: that of optimizing the number of reliable components instead of trying to fit the data. The current version of MetICA is available at https://github.com/daniellyz/MetICA.

Proposed Guidelines for Solid Phase Extraction of Suwannee River Dissolved Organic Matter.

This paper proposes improved guidelines for dissolved organic matter (DOM) isolation by solid phase extraction (SPE) with a styrene-divinylbenzene copolymer (PPL) sorbent, which has become an established method for the isolation of DOM from natural waters, because of its ease of application and appreciable carbon recovery. Suwannee River water was selected to systematically study the effects of critical SPE variables such as loading mass, concentration, flow rate, and up-scaling on the extraction selectivity of the PPL sorbent. High-field Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) and proton nuclear magnetic resonance ((1)H NMR) spectroscopy were performed to interpret the DOM chemical space of eluates, as well as permeates and wash liquids with molecular resolution. Up to 89% dissolved organic carbon (DOC) recovery was obtained with a DOC/PPL mass ratio of 1:800 at a DOC concentration of 20 mg/L. With the application of larger loading volumes, low proportions of highly oxygenated compounds were retained on the PPL sorbent. The effects of the flow rate on the extraction selectivity of the sorbent were marginal. Up-scaling had a limited effect on the extraction selectivity with the exception of increased self-esterification with a methanol solvent, resulting in methyl ester groups. Furthermore, the SPE/PPL extract exhibited highly authentic characteristics in comparison with original water and reverse osmosis samples. These findings will be useful for reproducibly isolating DOM with representative molecular compositions from various sources and concentrations and minimizing potential inconsistencies among interlaboratory comparative studies.

Solutions for low and high accuracy mass spectrometric data matching: a data-driven annotation strategy in nontargeted metabolomics.

Ultra high pressure liquid chromatography coupled to mass spectrometry (UHPLC-MS) has become a widespread analytical technique in metabolomics investigations, however the benefit of high-performance chromatographic separation is often blunted due to insufficient mass spectrometric accuracy. A strategy that allows for the matching of UHPLC-MS data to highly accurate direct infusion electrospray ionization (DI-ESI) Fourier transform ion cyclotron resonance/mass spectrometry (FTICR/MS) data is developed in this manuscript. Mass difference network (MDiN) based annotation of FTICR/MS data and matching to unique UHPLC-MS peaks enables the consecutive annotation of the chromatographic data set. A direct comparison of experimental m/z values provided no basis for the matching of both platforms. The matching of annotation-based exact neutral masses finally enabled the integration of platform specific multivariate statistical evaluations, minimizing the danger to compare artifacts generated on either platform. The approach was developed on a non-alcoholic fatty liver disease (NAFLD) data set.

Diverse Serum Manganese Species Affect Brain Metabolites Depending on Exposure Conditions.

Occupational and environmental exposure to increased concentrations of manganese (Mn) can lead to an accumulation of this element in the brain. The consequence is an irreversible damage of dopaminergic neurons leading to a disease called manganism with a clinical presentation similar to the one observed in Parkinson's disease. Human as well as animal studies indicate that Mn is mainly bound to low molecular mass (LMM) compounds such as Mn-citrate when crossing neural barriers. The shift toward LMM compounds might already take place in serum due to elevated Mn concentrations in the body. In this study, we investigated Mn-species pattern in serum in two different animal models by size exclusion chromatography-inductively coupled plasma mass spectrometry (SEC-ICP-MS). A subchronic feeding of rats with elevated levels of Mn led to an increase in LMM compounds, mainly Mn-citrate and Mn bound to amino acids. In addition, a single i.v. injection of Mn showed an increase in Mn-transferrin and Mn bound to amino acids 1 h after injection, while species values were more or less rebalanced 4 days after the injection. Results from Mn-speciation were correlated to the brain metabolome determined by means of electrospray ionization ion cyclotron resonance Fourier transform mass spectrometry (ESI-ICR/FT-MS). The powerful combination of Mn-speciation in serum with metabolomics of the brain underlined the need for Mn-speciation in exposure scenarios instead of the determination of whole Mn concentrations in blood. The progress of Mn-induced neuronal injury might therefore be assessed on the basis of known serum Mn-species.

DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans-Pseudomonas aeruginosa infection model.

In metabolomics there is an ever-growing need for faster and more comprehensive analysis methods to cope with the increasing size of biological studies. Direct-infusion ion-cyclotron-resonance Fourier-transform spectrometry (DI-ICR-FT-MS) is used in non-targeted metabolomics to obtain high-resolution snapshots of the metabolic state of a system. We applied this technology to a Caenorhabditis elegans-Pseudomonas aeruginosa infection model and optimized times needed for cultivation and mass-spectrometric analysis. Our results reveal that DI-ICR-FT-MS is a promising tool for high-throughput in-depth non-targeted metabolomics. We performed whole-worm metabolomics and recovered markers of the induced metabolic changes in C. elegans brought about by interaction with pathogens. In this investigation, we reveal complex metabolic phenotypes enabling clustering based upon challenge. Specifically, we observed a marked decrease in amino-acid metabolism with infection by P. aeruginosa and a marked increase in sugar metabolism with infection by Salmonella enterica. We were also able to discriminate between infection with a virulent wild-type Pseudomonas and with an attenuated mutant, making it possible to use this method in larger genetic screens to identify host and pathogen effectors affecting the metabolic phenotype of infection.

Importance of sulfur-containing metabolites in discriminating fecal extracts between normal and type-2 diabetic mice.

A metabolic disorder such as Type-2 Diabetes mellitus (T2DM) is a complex disease induced by genetic, environmental, and nutritional factors. The db/db mouse model, bearing a nonfunctional leptin receptor, is widely used to investigate the pathophysiology of T2DM. Fecal extracts of db/db and wild-type littermates were studied to unravel a broad spectrum of new and relevant metabolites related to T2DM as proxies of the interplay of gut microbiome and murine metabolomes. The nontargeted metabolomics approach consists of an integrated analytical concept of high-resolution mass spectrometry FT-ICR-MS, followed by UPLC-TOF-MS/MS experiments. We demonstrate that a metabolic disorder such as T2DM affects the gastrointestinal tract environment, thereby influencing different metabolic pathways and their respective metabolites in diabetic mice. Fatty acids, bile acids concerning cholic and deoxycholic acid, and steroid metabolism were highly discriminative comparing fecal meta-metabolomes of wt and db/db mice. Furthermore, sulfur-(S)-containing metabolites including N-acyl taurines were altered in diabetic mice, enabling us to focus on S-containing metabolites, especially the sulfate and taurine conjugates of bile and fatty acids. Different sulfate containing bile acids including sulfocholic acid, oxocholic acid sulfate, taurocholic acid sulfate, and cyprinol sulfate were significantly altered in diabetic mice. Moreover, we identified 12 new sulfate and taurine conjugates of hydroxylated fatty acids with significant importance in T2DM metabolism in db/db mice.

Preanalytical aspects and sample quality assessment in metabolomics studies of human blood.

BACKGROUND: Metabolomics is a powerful tool that is increasingly used in clinical research. Although excellent sample quality is essential, it can easily be compromised by undetected preanalytical errors. We set out to identify critical preanalytical steps and biomarkers that reflect preanalytical inaccuracies. METHODS: We systematically investigated the effects of preanalytical variables (blood collection tubes, hemolysis, temperature and time before further processing, and number of freeze-thaw cycles) on metabolomics studies of clinical blood and plasma samples using a nontargeted LC-MS approach. RESULTS: Serum and heparinate blood collection tubes led to chemical noise in the mass spectra. Distinct, significant changes of 64 features in the EDTA-plasma metabolome were detected when blood was exposed to room temperature for 2, 4, 8, and 24 h. The resulting pattern was characterized by increases in hypoxanthine and sphingosine 1-phosphate (800% and 380%, respectively, at 2 h). In contrast, the plasma metabolome was stable for up to 4 h when EDTA blood samples were immediately placed in iced water. Hemolysis also caused numerous changes in the metabolic profile. Unexpectedly, up to 4 freeze-thaw cycles only slightly changed the EDTA-plasma metabolome, but increased the individual variability. CONCLUSIONS: Nontargeted metabolomics investigations led to the following recommendations for the preanalytical phase: test the blood collection tubes, avoid hemolysis, place whole blood immediately in ice water, use EDTA plasma, and preferably use nonrefrozen biobank samples. To exclude outliers due to preanalytical errors, inspect the biomarker signal intensities reflecting systematic as well as accidental and preanalytical inaccuracies before processing the bioinformatics data.

Activity of native hydrolytic enzymes and their association with the cell wall of three ectomycorrhizal fungi.

The ecological and biogeochemical relevance of hydrolytic enzymes associated with the fungal cell wall has been poorly studied in ectomycorrhizal (ECM) fungi. We used a modified sequential extraction procedure to investigate the activity of various hydrolytic enzymes (ß-glucosidase, acid-phosphatase, leucine-aminopeptidase, chitinase, xylanase and glucuronidase) and their association with the cell wall of three ECM fungi (Rhizopogon roseolus, Paxillus involutus and Piloderma croceum). Fungi were grown on C-rich solid medium under three different P concentrations (3.7, 0.37 and 0.037 mM). The sequential extraction procedure classifies enzymes as: (a) cytosolic, (b) loosely bound, (c) hydrophobically bound, (d) ionically bound and (e) covalently bound. Results showed that for the same fungus absolute enzymatic activity was affected by P concentration, whilst enzymatic compartmentalization among the cytosol and the cell wall fractions was not. The association of enzymes with the cell wall was fungus- and enzyme-specific. Our data indicate also that enzymes best known for being either extracellular or cytosolic or both, do act in muro as well. The ecological implications of cell wall-bound enzymes and the potential applications and limitations of sequential extractions are further discussed.

The influence of trace elements on the therapeutic success of suprachoroidal draining devices.

PURPOSE: The therapeutic success of minimal invasive glaucoma surgery (MIGS) is challenging due to many factors including fibrotic or occlusive events. Recent clinical data show sudden peaks of intraocular pressure (IOP) in the postoperative care of glaucoma patients after suprachoroidal draining stents. Yet, the reasons for the IOP peaks are speculative. As a link between trace elements and fibrosis had been previously observed in systemic disorders, the present study aimed to investigate the impact of trace elements on the therapeutic success of the suprachoroidal draining stents in patients with open-angle glaucoma (OAG). MATERIAL AND METHODS: An analysis of a prospective single-center study was done: fifty-five eyes of patients with OAG (29 female, 26 male) underwent Cypass Micro-Stent implantation either as a stand-alone procedure or combined with cataract surgery. All patients underwent pre-operatively an ophthalmological examination which included slit lamp biomicroscopy and fundoscopy. IOP was measured by Goldmann applanation tonometry. Functional and morphometric data were assessed by Octopus G1-perimetry, which included measurement of retinal nerve fiber layer thickness (Spectralis OCT). Data of the patients' follow-ups were recorded during 18 months post-operatively. The therapeutic success of CyPass Micro-Stent was classified as 'success' (IOP reduction ≥20% compared to a pre-operative baseline without any medication), 'qualified success' (IOP reduction ≥20 % with same or lower additional eye medication), and 'failure' (IOP reduction ≤20 % or additional surgical treatment necessary). Aqueous humour was extracted once during surgery for analysis of the level of 14 trace elements: Copper (Cu), Cadmium (Cd), Cobalt (Co), Chromium (Cr), Iron (Fe), Lithium (Li), Magnesium (Mg), Manganese (Mn), Phosphorus (P), Lead (Pb), Titanium (Ti), Uranium (U), Vanadium (V), and Zinc (Zn). Analysis of the trace elements was done using an ELEMENT 2, ICP-sf-MS instrument (Thermo-Fisher Scientific, Bremen, Germany). Analysis of levels of trace elements was done across the patients' groups of the three subclasses of therapeutic success. Statistical investigations for substantial differences were conducted using the method of least squares to fit general linear models and mixed models. The last one for the repeated measurements of IOP. RESULTS: Levels of Mg were significantly lower one month postoperatively in the success group (LS-Mean 1.30 mg/L) compared to the qualified success group (LS-Mean 1.22 mg/L; p-value = 0.04). Fe was significantly increased in the failure group (LS-Mean 2.07 µg/L) compared to the qualified success group (LS-Mean 1.64 µg/L; p-value = 0.019) after 3 months of follow-up. Additionally, Fe levels were significantly lower in the success group (LS-Mean 1.47 µg/L) compared to the failure cohort (LS-Mean 2.07 µg/L; p-value = 0.009). After a period of 18 months, significantly higher levels of Mn were observed in the success group (LS-Mean 1.24 µg/L) than in the failure group (LS Mean 0.30 µg/L, p-value = 0.019). CONCLUSION: The present data might suggest that trace elements can influence therapeutic success of suprachoroidal draining devices postoperatively and thus offer first hints for potential novel therapeutic options.