Metabolomics reveals biomarkers in human urine and plasma to predict cytochrome P450 2D6 (CYP2D6) activity.

Individualized assessment of cytochrome P450 2D6 (CYP2D6) activity is usually performed through phenotyping following administration of a probe drug to measure the enzyme's activity. To avoid any iatrogenic harm (allergic drug reaction, dosing error) related to the probe drug, the development of non-burdensome tools for real-time phenotyping of CYP2D6 could significantly contribute to precision medicine. This study focuses on the identification of markers of the CYP2D6 enzyme in human biofluids using an LC-high-resolution mass spectrometry-based metabolomic approach. Plasma and urine samples from healthy volunteers were analysed before and after intake of a daily dose of paroxetine 20 mg over 7 days. CYP2D6 genotyping and phenotyping, using single oral dose of dextromethorphan 5 mg, were also performed in all participants. We report four metabolites of solanidine and two unknown compounds as possible novel CYP2D6 markers. Mean relative intensities of these features were significantly reduced during the inhibition session compared with the control session (n = 37). Semi-quantitative analysis showed that the largest decrease (-85%) was observed for the ion m/z 432.3108 normalized to solanidine (m/z 398.3417). Mean relative intensities of these ions were significantly higher in the CYP2D6 normal-ultrarapid metabolizer group (n = 37) compared with the poor metabolizer group (n = 6). Solanidine intensity was more than 15 times higher in CYP2D6-deficient individuals compared with other volunteers. The applied untargeted metabolomic strategy identified potential novel markers capable of semi-quantitatively predicting CYP2D6 activity, a promising discovery for personalized medicine

Tree height strongly affects estimates of water-use efficiency responses to climate and CO2 using isotopes

Various studies report substantial increases in intrinsic water-use efficiency (Wi), estimated using carbon isotopes in tree rings, suggesting trees are gaining increasingly more carbon per unit water lost due to increases in atmospheric CO2. Usually, reconstructions do not, however, correct for the effect of intrinsic developmental changes in Wi as trees grow larger. Here we show, by comparingWi across varying tree sizes at one CO2 level, that ignoring such developmental effects can severely affect inferences of trees' Wi. Wi doubled or even tripled over a trees' lifespan in three broadleaf species due to changes in tree height and light availability alone, and there are also weak trends for Pine trees. Developmental trends in broadleaf species are as large as the trends previously assigned to CO2 and climate. Credible future tree ring isotope studies require explicit accounting for species-specific developmental effects before CO2 and climate effects are inferred.Peer reviewe

第808回千葉医学会例会・第5回磯野外科例会 31.

Additional file 5. Supplemental methods

Administration of defined microbiota is protective in a murine Salmonella infection model.

Salmonella typhimurium is a major cause of diarrhea and causes significant morbidity and mortality worldwide, and perturbations of the gut microbiota are known to increase susceptibility to enteric infections. The purpose of this study was to investigate whether a Microbial Ecosystem Therapeutic (MET-1) consisting of 33 bacterial strains, isolated from human stool and previously used to cure patients with recurrent Clostridium difficile infection, could also protect against S. typhimurium disease. C57BL/6 mice were pretreated with streptomycin prior to receiving MET-1 or control, then gavaged with S. typhimurium. Weight loss, serum cytokine levels, and S. typhimurium splenic translocation were measured. NF-κB nuclear staining, neutrophil accumulation, and localization of tight junction proteins (claudin-1, ZO-1) were visualized by immunofluorescence. Infected mice receiving MET-1 lost less weight, had reduced serum cytokines, reduced NF-κB nuclear staining, and decreased neutrophil infiltration in the cecum. MET-1 also preserved cecum tight junction protein expression, and reduced S. typhimurium translocation to the spleen. Notably, MET-1 did not decrease CFUs of Salmonella in the intestine. MET-1 may attenuate systemic infection by preserving tight junctions, thereby inhibiting S. typhimurium from gaining access to the systemic circulation. We conclude that MET-1 may be protective against enteric infections besides C. difficile infection

Role of OH variability in the stalling of the global atmospheric CH4 growth rate from 1999 to 2006

The growth in atmospheric methane (CH4) concentrations over the past two decades has shown large variability on a timescale of several years. Prior to 1999 the globally averaged CH4 concentration was increasing at a rate of 6.0 ppb/yr, but during a stagnation period from 1999 to 2006 this growth rate slowed to 0.6 ppb/yr. From 2007 to 2009 the growth rate again increased to 4.9 ppb/yr. These changes in growth rate are usually ascribed to variations in CH4 emissions. We have used a 3-D global chemical transport model, driven by meteorological reanalyses and variations in global mean hydroxyl (OH) concentrations derived from CH3CCl3 observations from two independent networks, to investigate these CH4 growth variations. The model shows that between 1999 and 2006, changes in the CH4 atmospheric loss contributed significantly to the suppression in global CH4 concentrations relative to the pre-1999 trend. The largest factor in this is relatively small variations in global mean OH on a timescale of a few years, with minor contributions of atmospheric transport of CH4 to its sink region and of atmospheric temperature. Although changes in emissions may be important during the stagnation period, these results imply a smaller variation is required to explain the observed CH4 trends. The contribution of OH variations to the renewed CH4 growth after 2007 cannot be determined with data currently available

Rising atmospheric methane: 2007-2014 growth and isotopic shift

From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7±1.2ppb yr$^{-1}$. Simultaneously, $\delta^{13}$C$_\text{CH4}$ (a measure of the $^{13}$C/$^{12}$C isotope ratio in methane) has shifted to significantly more negative values since 2007. Growth was extreme in 2014, at 12.5±0.4ppb, with a further shift to more negative values being observed at most latitudes. The isotopic evidence presented here suggests that the methane rise was dominated by significant increases in biogenic methane emissions, particularly in the tropics, for example, from expansion of tropical wetlands in years with strongly positive rainfall anomalies or emissions from increased agricultural sources such as ruminants and rice paddies. Changes in the removal rate of methane by the OH radical have not been seen in other tracers of atmospheric chemistry and do not appear to explain short-term variations in methane. Fossil fuel emissions may also have grown, but the sustained shift to more $^{13}$C-depleted values and its significant interannual variability, and the tropical and Southern Hemisphere loci of post-2007 growth, both indicate that fossil fuel emissions have not been the dominant factor driving the increase. A major cause of increased tropical wetland and tropical agricultural methane emissions, the likely major contributors to growth, may be their responses to meteorological change.This work was supported by the UK Natural Environment Research Council projects NE/N016211/1 The Global Methane Budget, NE/M005836/1 Methane at the edge, NE/K006045/1 The Southern Methane Anomaly and NE/I028874/1 MAMM. We thank the UK Meteorological Office for flask collection and hosting the continuous measurement at Ascension, the Ascension Island Government for essential support, and Thumeka Mkololo for flask collection in Cape Tow

Identifying and Seeing beyond Multiple Sequence Alignment Errors Using Intra-Molecular Protein Covariation

BACKGROUND: There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively important residue pairs in a sequence alignment. Different alignments of the same protein family give different results demonstrating that covariation depends on the quality of the sequence alignment. We thus hypothesized that current criteria are insufficient to build alignments for use with covariation analyses. METHODOLOGY/PRINCIPAL FINDINGS: We show that current criteria are insufficient to build alignments for use with covariation analyses as systematic sequence alignment errors are present even in hand-curated structure-based alignment datasets like those from the Conserved Domain Database. We show that current non-parametric covariation statistics are sensitive to sequence misalignments and that this sensitivity can be used to identify systematic alignment errors. We demonstrate that removing alignment errors due to 1) improper structure alignment, 2) the presence of paralogous sequences, and 3) partial or otherwise erroneous sequences, improves contact prediction by covariation analysis. Finally we describe two non-parametric covariation statistics that are less sensitive to sequence alignment errors than those described previously in the literature. CONCLUSIONS/SIGNIFICANCE: Protein alignments with errors lead to false positive and false negative conclusions (incorrect assignment of covariation and conservation, respectively). Covariation analysis can provide a verification step, independent of traditional criteria, to identify systematic misalignments in protein alignments. Two non-parametric statistics are shown to be somewhat insensitive to misalignment errors, providing increased confidence in contact prediction when analyzing alignments with erroneous regions because of an emphasis on they emphasize pairwise covariation over group covariation

Identifying specific causes of kidney allograft loss

The causes of kidney allograft loss remain unclear. Herein we investigated these causes in 1317 conventional kidney recipients. The cause of graft loss was determined by reviewing clinical and histologic information the latter available in 98% of cases. During 50.3 ± 32.6 months of follow-up, 330 grafts were lost (25.0%), 138 (10.4%) due to death with function, 39 (2.9%) due to primary nonfunction and 153 (11.6%) due to graft failure censored for death. The latter group was subdivided by cause into: glomerular diseases (n = 56, 36.6%); fibrosis/atrophy (n = 47, 30.7%); medical/surgical conditions (n = 25, 16.3%); acute rejection (n = 18, 11.8%); and unclassifiable (n = 7, 4.6%). Glomerular pathologies leading to failure included recurrent disease (n = 23), transplant glomerulopathy (n = 23) and presumed nonrecurrent disease (n = 10). In cases with fibrosis/atrophy a specific cause(s) was identified in 81% and it was rarely attributable to calcineurin inhibitor (CNI) toxicity alone (n = 1, 0.7%). Contrary to current concepts, most cases of kidney graft loss have an identifiable cause that is not idiopathic fibrosis/atrophy or CNI toxicity. Glomerular pathologies cause the largest proportion of graft loss and alloinmunity remains the most common mechanism leading to failure. This study identifies targets for investigation and intervention that may result in improved kidney transplantation outcomes