Rapid and sustained systemic circulation of conjugated gut microbial catabolites after single-dose black tea extract consumption.

Gut microbial catabolites of black tea polyphenols (BTPs) have been proposed to exert beneficial cardiovascular bioactivity. This hypothesis is difficult to verify because the conjugation patterns and pharmacokinetics of these catabolites are largely unknown. The objective of our study was to identify, quantify, and assess the pharmacokinetics of conjugated BTP metabolites in plasma of healthy humans by means of an a priori untargeted LC-MS-based metabolomics approach. In a randomized, open, placebo-controlled, crossover study, 12 healthy men consumed a single bolus of black tea extract (BTE) or a placebo. The relative and, in several cases, absolute concentrations of a wide range of metabolites were determined using U(H)PLC-LTQ-Orbitrap-FTMS. Following BTE consumption, a kinetic response in plasma was observed for 59 BTP metabolites, 11 of these in a quantitative manner. Conjugated and unconjugated catechins appeared in plasma without delay, at 2-4 h, followed by a range of microbial catabolites. Interindividual variation in response was greater for gut microbial catabolites than for directly absorbed BTPs. The rapid and sustained circulation of conjugated catabolites suggests that these compounds may be particularly relevant to proposed health benefits of BTE. Their presence and effects may depend on individual variation in catabolic capacity of the gut microbiota.

Interactive seminars or small group tutorials in preclinical medical education: results of a randomized controlled trial.

BACKGROUND: Learning in small group tutorials is appreciated by students and effective in the acquisition of clinical problem-solving skills but poses financial and resource challenges. Interactive seminars, which accommodate large groups, might be an alternative. This study examines the educational effectiveness of small group tutorials and interactive seminars and students' preferences for and satisfaction with these formats. METHODS: Students in year three of the Leiden undergraduate medical curriculum, who agreed to participate in a randomized controlled trial (RCT, n = 107), were randomly allocated to small group tutorials (n = 53) or interactive seminars (n = 54). Students who did not agree were free to choose either format (n = 105). Educational effectiveness was measured by comparing the participants' results on the end-of-block test. Data on students' reasons and satisfaction were collected by means of questionnaires. Data was analyzed using student unpaired t test or chi-square test where appropriate. RESULTS: There were no significant differences between the two educational formats in students' test grades. Retention of knowledge through active participation was the most frequently cited reason for preferring small group tutorials, while a dislike of compulsory course components was mentioned more frequently by students preferring interactive seminars. Small group tutorials led to greater satisfaction. CONCLUSIONS: We found that small group tutorials leads to greater satisfaction but not to better learning results. Interactive learning in large groups might be might be an effective alternative to small group tutorials in some cases and be offered as an option.

Structure and co-occurrence patterns of bacterial communities associated with white faeces disease outbreaks in Pacific white-leg shrimp Penaeus vannamei aquaculture.

Bacterial diseases cause production failures in shrimp aquacultures. To understand environmental conditions and bacterial community dynamics contributing to white faeces disease (WFD) events, we analysed water quality and compared bacterial communities in water as well as in intestines and faeces of healthy and diseased shrimps, respectively, via 16S rRNA gene sequencing and qPCR of transmembrane regulatory protein (toxR), thermolabile haemolysin (tlh), and thermostable direct haemolysin genes of pathogenic Vibrio parahaemolyticus as a proxy for virulence. WFD occurred when pH decreased to 7.71-7.84, and Alteromonas, Pseudoalteromonas and Vibrio dominated the aquatic bacterial communities. The disease severity further correlated with increased proportions of Alteromonas, Photobacterium, Pseudoalteromonas and Vibrio in shrimp faeces. These opportunistic pathogenic bacteria constituted up to 60% and 80% of the sequences in samples from the early and advances stages of the disease outbreak, respectively, and exhibited a high degree of co-occurrence. Furthermore, toxR and tlh were detected in water at the disease event only. Notably, bacterial community resilience in water occurred when pH was adjusted to 8. Then WFD ceased without a mortality event. In conclusion, pH was a reliable indicator of the WFD outbreak risk. Dissolved oxygen and compositions of water and intestinal bacteria may also serve as indicators for better prevention of WFD events.

Parameter selection for peak alignment in chromatographic sample profiling: objective quality indicators and use of control samples.

In chromatographic profiling applications, peak alignment is often essential as most chromatographic systems exhibit small peak shifts over time. When using currently available alignment algorithms, there are several parameters that determine the outcome of the alignment process. Selecting the optimum set of parameters, however, is not straightforward, and the quality of an alignment result is at least partly determined by subjective decisions. Here, we demonstrate a new strategy to objectively determine the quality of an alignment result. This strategy makes use of a set of control samples that are analysed both spiked and non-spiked. With this set, not only the system and the method can be checked but also the quality of the peak alignment can be evaluated. The developed strategy was tested on a representative metabolomics data set using three software packages, namely Markerlynx, MZmine and MetAlign. The results indicate that the method was able to assess and define the quality of an alignment process without any subjective interference of the analyst, making the method a valuable contribution to the data handling process of chromatography-based metabolomics data.

Whole-genome sequencing of a large collection of Myroides odoratimimus and Myroides odoratus isolates and antimicrobial susceptibility studies.

The genus Myroides comprises several species of Gram-negative, non-motile, and non-fermenting bacteria, which have been regarded as non-pathogenic for decades. Multiple recent reports, however, underscore the pathogenic potential that Myroides sp. possesses for humans. These bacteria seem to be resistant to a wide range of antibiotics (including ß-lactams and aminoglycosides). Therefore, treatment options are limited. Knowledge of antimicrobial resistance, however, is based on only one meaningful comprehensive study and on data published from case reports. This lack of data motivated us to test 59 strains from our Myroides collection (43 M. odoratimimus and 16 M. odoratus) for resistance against 20 commonly used antibiotics. We also performed molecular analyses to reveal whether our bacteria harbor the genus-specific M. odoratimimus metallo-ß-lactamase (MUS-1) or the M. odoratus metallo ß-lactamase (TUS-1), and other ß-lactamases, which may provide an explanation for the extended antimicrobial resistance.

Development of a resolution metric for comprehensive two-dimensional chromatography.

A new resolution metric for two-dimensional chromatography is proposed and tested. This resolution measurement is based on the concept of the (one-dimensional) valley-to-peak ratio, which has been adapted and modified for two-dimensional chromatography. Two questions are considered related to the computation of the resolution of a given (two-dimensional) peak. First, the concept of peak neighbourhood is revised, since it changes drastically from one- to two-dimensional chromatography. In a chromatogram resulting from a two-dimensional analysis, one peak may be surrounded by more than two neighbouring peaks. However, the neighbouring peaks can be remote from the peak or some interfering peaks may be in between. In these cases, it is not meaningful to compute the resolution between them. A method is proposed to determine whether a resolution measurement between two two-dimensional peaks is reasonable. Second, a measurement of the valley-to-peak ratio in two-dimensional chromatography is proposed. The measurement is based on the concept of the saddle point (which is defined for two-dimensional surface plots). A study of the correlation of the valley-to-peak ratio with the error obtained for quantification is presented. The new metric can be used as an estimator of the quantification errors. Also, valley-to-peak ratios can be calculated for one or more target peak(s) to estimate the separation quality of the entire chromatogram. This makes the proposed measurement suitable for optimisation purposes. Although the algorithm was developed for GC x GC, preliminary studies suggested that its application to other two-dimensional separation methods (e.g. LC x LC) should only require minor modification (if any).

Development of an algorithm for peak detection in comprehensive two-dimensional chromatography.

A method for peak detection in two-dimensional chromatography is presented. The algorithm applies first the methods developed for peak detection in one-dimensional chromatography to detect peaks in one dimension. In a second step, a decision tree is applied to decide which one-dimensional peaks are originated from the same compound and have to be 'merged' into one two-dimensional peak. To this end, different features of the peaks (second-dimension peak regions and second-dimension retention times) are compared and different criteria (common peak regions, retention time differences, unimodality in the first dimension) are applied. Different options can be used, depending on the nature of the data. The user controls this decision tree by establishing several options and "switches". The algorithm was tested with GCxGC chromatograms obtained for a commercial air-freshener sample, detecting and merging the modulated peaks belonging to the same compound. Recommendations for the set of options and switches are given. A utility that calculates and sums peak areas from merged peaks is added to facilitate automated quantification. Although the algorithm was developed for GCxGC, its application to comprehensive two-dimensional liquid chromatography (LCxLC) data should at most require minor modifications.

Development of a nucleic acid lateral flow immunoassay (NALFIA) for reliable, simple and rapid detection of the methicillin resistance genes mecA and mecC.

The gene mecA and its homologue mecC confer methicillin resistance in Staphylococcus aureus and other staphylococci. Methicillin-resistant staphylococci (MRS) are considered resistant to all ß-lactam antibiotics. To avoid the use of ß-lactam antibiotics for the control of MRS infections, there is an urgent need for a fast and reliable screening assay for mecA and mecC that can easily be integrated in routine laboratory diagnostics. The aim of this study was the development of such a rapid detection method for methicillin resistance based on nucleic acid lateral flow immunoassay (NALFIA) technology. In NALFIA, the target sequences are PCR-amplified, immobilized via antigen-antibody interaction and finally visualized as distinct black bars resulting from neutravidin-labeled carbon particles via biotin-neutravidin interaction. A screening of 60 defined strains (MRS and non-target bacteria) and 28 methicillin-resistant S. aureus (MRSA) isolates from clinical samples was performed with PCR-NALFIA in comparison to PCR with subsequent gel electrophoresis (PCR-GE) and real-time PCR. While all samples were correctly identified with all assays, PCR-NALFIA was superior with respect to limits of detection. Moreover, this assay allowed for differentiation between mecA and mecC by visualizing the two alleles at different positions on NALFIA test stripes. However, since this test system only targets the mecA and mecC genes, it does not allow to determine in which staphylococcal species the mec gene is included. Requiring only a fraction of the time needed for cultural methods (i.e. the gold standard), the PCR-NALFIA presented here is easy to handle and can be readily integrated into laboratory diagnostics.

Impact of Proteins on the Uptake, Distribution, and Excretion of Phenolics in the Human Body.

Polyphenols, a complex group of secondary plant metabolites, including flavonoids and phenolic acids, have been studied in depth for their health-related benefits. The activity of polyphenols may, however, be hampered when consumed together with protein-rich food products, due to the interaction between polyphenols and proteins. To that end we have tested the bioavailability of representatives of a range of polyphenol classes when consumed for five days in different beverage matrices. In a placebo-controlled, randomized, cross-over study, 35 healthy males received either six placebo gelatine capsules consumed with 200 mL of water, six capsules with 800 mg polyphenols derived from red wine and grape extracts, or the same dose of polyphenols incorporated into 200 mL of either pasteurized dairy drink, soy drink (both containing 3.4% proteins) or fruit-flavoured protein-free drink . At the end of the intervention urine and blood was collected and analysed for a broad range of phenolic compounds using Gas Chromatography-Mass Spectrometry (GC-MS), Liquid Chromatography-Multiple Reaction Monitoring-Mass Spectrometry (LC-MRM-MS), and Nuclear Magnetic Resonance (NMR) spectroscopy techniques. The plasma and urine concentrations of the polyphenols identified increased with all formats, including the protein-rich beverages. Compared to capsule ingestion, consumption of polyphenol-rich beverages containing either dairy, soy or no proteins had minor to no effect on the bioavailability and excretion of phenolic compounds in plasma (118% ± 9%) and urine (98% ± 2%). We conclude that intake of polyphenols incorporated in protein-rich drinks does not have a major impact on the bioavailability of a range of different polyphenols and phenolic metabolites.

A new method for the automated selection of the number of components for deconvolving overlapping chromatographic peaks.

Mathematical deconvolution methods can separate co-eluting peaks in samples for which (chromatographic) separation fail. However, these methods often heavily rely on manual user-input and interpretation. This is not only time-consuming but also error-prone and automation is needed if such methods are to be applied in a routine manner. One major hurdle when automating deconvolution methods is the selection of the correct number of components used for building the model. We propose a new method for the automatic determination of the optimum number of components when applying multivariate curve resolution (MCR) to comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) data. It is based on a two-fold cross-validation scheme. The obtained overall cross-validation error decreases when adding components and increases again once over-fitting of the data starts to occur. The turning point indicates that the optimum number of components has been reached. Overall, the method is at least as good as and sometimes superior to the inspection of the eigenvalues when performing singular-value decomposition. However, its strong point is that it can be fully automated and it is thus more efficient and less prone to subjective interpretation. The developed method has been applied to two different-sized regions in a GC×GC-MS chromatogram. In both regions, the cross-validation scheme resulted in selecting the correct number of components for applying MCR. The pure concentration and mass spectral profiles obtained can then be used for identification and/or quantification of the compounds. While the method has been developed for applying MCR to GC×GC-MS data, a transfer to other deconvolution methods and other analytical systems should only require minor modifications.

An automated method for the analysis of phenolic acids in plasma based on ion-pairing micro-extraction coupled on-line to gas chromatography/mass spectrometry with in-liner derivatisation.

A new method is presented for the analysis of phenolic acids in plasma based on ion-pairing 'Micro-extraction in packed sorbent' (MEPS) coupled on-line to in-liner derivatisation-gas chromatography-mass spectrometry (GC-MS). The ion-pairing reagent served a dual purpose. It was used both to improve extraction yields of the more polar analytes and as the methyl donor in the automated in-liner derivatisation method. In this way, a fully automated procedure for the extraction, derivatisation and injection of a wide range of phenolic acids in plasma samples has been obtained. An extensive optimisation of the extraction and derivatisation procedure has been performed. The entire method showed excellent repeatabilities of under 10% and linearities of 0.99 or better for all phenolic acids. The limits of detection of the optimised method for the majority of phenolic acids were 10ng/mL or lower with three phenolic acids having less-favourable detection limits of around 100 ng/mL. Finally, the newly developed method has been applied in a human intervention trial in which the bioavailability of polyphenols from wine and tea was studied. Forty plasma samples could be analysed within 24h in a fully automated method including sample extraction, derivatisation and gas chromatographic analysis.

Impact of short-term intake of red wine and grape polyphenol extract on the human metabolome.

Red wine and grape polyphenols are considered to promote cardiovascular health and are involved in multiple biological functions. Their overall impact on the human metabolome is not known. Therefore, exogenous and endogenous metabolic effects were determined in fasting plasma and 24 h urine from healthy male adults consuming a mix of red wine and grape juice extracts (WGM) for 4 days in a placebo-controlled, crossover study. Syringic acid, 3-hydroxyhippuric acid, pyrogallol, 3-hydroxyphenylacetic acid, and 3-hydroxyphenylpropionic acid were confirmed as the strongest urinary markers of WGM intake. Overall, WGM had a mild impact on the endogenous metabolism. Most noticeable were changes in several amino acids deriving from tyrosine and tryptophan. Reductions in the microbial metabolites p-cresol sulfate and 3-indoxylsulfuric acid and increases in indole-3-lactic acid and nicotinic acid were observed in urine. In plasma, tyrosine was reduced. The results suggest that short-term intake of WGM altered microbial protein fermentation and/or amino acid metabolism.

Untargeted metabolite discovery in kinetic data from multi-dose intervention studies.

A new strategy for biomarker discovery is presented that is based on multi-dose kinetic metabolomics data. Gas chromatography-mass spectrometry (GC-MS) data sets recorded in the full scan mode are scanned for compounds showing a meaningful trend following the different doses and sampling time points. From a biological point of view, a meaningful trend denotes a compound that responds similarly at all doses and follows a smooth trend along the time points. This type of information can be used to distinguish relevant metabolites from those compounds not following the expected trends. The method is based on analysing the time and dosage trends of each compound via principal component analysis. As only local information is analysed at a time (meaning no correlation with other metabolites is taken into account), the proposed model flags relevant metabolites even if their trend is different from that of any other compound. The new method is therefore an attractive way to reduce the long list of detected compounds in a metabolomics sample set to include only those having the expected smooth time profile that is common for all doses. The new strategy is tested on a sample set obtained from a gut fermentation study of a polyphenol-rich diet. For this study, the initial list of over 25,000 potentially interesting features was reduced to less than 250, thus significantly reducing the expensive and time-consuming manual examination.

Trend analysis of time-series data: A novel method for untargeted metabolite discovery.

A new strategy for biomarker discovery is presented that uses time-series metabolomics data. Data sets from samples analysed at different time points after an intervention are searched for compounds that show a meaningful trend following the intervention. Obviously, this requires new data-analytical tools to distinguish such compounds from those showing only random variation. Two univariate methods, autocorrelation and curve-fitting, are used either as stand-alone methods or in combination to discover unknown metabolites in data sets originating from target-compound analysis. Both techniques reduce the long list of detected compounds in the kinetic sample set to include only those having a pre-defined interesting time profile. Thus, new metabolites may be discovered within data structures that are usually only used for target-compound analysis. The new strategy is tested on a sample set obtained from a gut fermentation study of a polyphenol-rich diet. For this study, the initial list of over 9000 potentially interesting features was reduced to less than 150, thus significantly reducing the expensive and time-consuming manual examination.

In vitro bioconversion of polyphenols from black tea and red wine/grape juice by human intestinal microbiota displays strong interindividual variability.

Dietary polyphenols in tea and wine have been associated with beneficial health effects. After ingestion, most polyphenols are metabolized by the colonic microbiota. The current study aimed at exploring the interindividual variation of gut microbial polyphenol bioconversion from 10 healthy human subjects. In vitro fecal batch fermentations simulating conditions in the distal colon were performed using polyphenols from black tea and a mixture of red wine and grape juice. Microbial bioconversion was monitored by NMR- and GC-MS-based profiling of diverse metabolites and phenolics. The complex polyphenol mixtures were degraded to a limited number of key metabolites. Each subject displayed a specific metabolite profile differing in composition and time courses as well as levels of these metabolites. Moreover, clear differences depending on the polyphenol sources were observed. In conclusion, varying metabolite pathways among individuals result in different metabolome profiles and therefore related health effects are hypothesized to differ between subjects.