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Jeremy K Nicholson

Publications and source records attributed to Jeremy K Nicholson.

At least 19 recordsLinked to original sources

Characterizing the metabolic effects of the selective inhibition of gut microbial β-glucuronidases in mice.

The hydrolysis of xenobiotic glucuronides by gut bacterial glucuronidases reactivates previously detoxified compounds resulting in severe gut toxicity for the host. Selective bacterial β-glucuronidase inhibitors can mitigate this toxicity but their impact on wider host metabolic processes has not been studied. To investigate this the inhibitor 4-(8-(piperazin-1-yl)-1,2,3,4-tetrahydro-[1,2,3]triazino[4',5':4,5]thieno[2,3-c]isoquinolin-5-yl)morpholine (UNC10201652, Inh 9) was administered to mice to selectively inhibit a narrow range of bacterial β-glucuronidases in the gut. The metabolomic profiles of the intestinal contents, biofluids, and several tissues involved in the enterohepatic circulation were measured and compared to control animals. No biochemical perturbations were observed in the plasma, liver or gall bladder. In contrast, the metabolite profiles of urine, colon contents, feces and gut wall were altered compared to the controls. Changes were largely restricted to compounds derived from gut microbial metabolism. This work establishes that inhibitors targeted towards bacterial β-glucuronidases modulate the functionality of the intestinal microbiota without adversely impacting the host metabolic system.

Mice↗

The influence of pharmacogenetics on fatty liver disease in the wistar and kyoto rats: a combined transcriptomic and metabonomic study.

Although fatty liver disease is caused by a number of toxicological insults and the metabolic syndrome, the exact mechanisms by which many of these pathophysiological stimulii induce fatty liver are unknown. The rapid and profound steatosis caused by orotic acid, resulting from an impairment in the production of ApoB, has been investigated in the Wistar strain rat using a combined transcriptomic and metabonomic/metabolomic approach. Analysis of liver tissue from rats exposed to orotic acid for 1, 3, and 14 days was performed by DNA microarrays and high resolution 1H NMR spectroscopy based metabonomics of both tissue extracts and intact tissue (n = 3). Data were analyzed using a combination of ANOVA and principal components analysis, used as a data reduction tool to visualize the most perturbed transcripts and metabolites. Orotic acid produced a profound 8-fold increase in total lipids, and in particular increases in resonances associated with polyunsaturated fats (CH=CH and CH2CH=CH groups). This was accompanied by increases in the concentrations of trimethylamine-oxide (TMAO), betaine, choline, and phosphocholine, as well as a relative decrease in glucose and glycogen. At the transcriptional level, perturbations were detected in both oxidative stress and osmoregulation/pH homeostasis. However, this contrasts with a previous transcriptomic/metabolic study of fatty liver disease in a combined data set of Wistar (out-bred) and Kyoto (in-bred) strains of rats, with only 4 transcripts being found to be in common between the two analyses. This emphasizes the need to understand how strain background interacts with a given toxic lesion or genetic modification.

Animals↗

Generation of ultrahigh peak capacity LC separations via elevated temperatures and high linear mobile-phase velocities.

The use of a combination of ultraperformance liquid chromatography at approximately 11,000 psi on sub 2-microm particles combined with reversed-phase gradient chromatography at a temperature of 90 degrees C is described as applied to the analysis of endogenous and drug metabolites in human and animal urine. By using elevated temperatures, back pressures can be reduced while maintaining high flow rates and chromatographic efficiency, with peaks 1-3 s wide at the base. Application to urine samples provided a peak capacity of approximately 700 for a 10-min analysis and greater than approximately 1000 in 1 h. Despite the narrow nature of the peaks, good quality mass spectra were also obtained, allowing the identification of typical drug and endogenous metabolites. These ultra-high-resolution chromatograms should be ideal for the analysis of complex samples in, for example, metabolite identification, impurity identification, and metabonomic/metabolomic studies. Applications in natural product analysis and proteomics can also be envisaged.

Acetaminophen↗

Hepatotoxin-induced hypertyrosinemia and its toxicological significance.

A (1)H Nuclear Magnetic Resonance (NMR) spectroscopic investigation of the effects of single doses of four model hepatotoxins on male Sprague-Dawley rats showed that hypertyrosinemia was induced by three of the treatments (ethionine 300 mg/kg, galactosamine hydrochloride 800 mg/kg and isoniazid 400 mg/kg) but not by the fourth (thioacetamide 200 mg/kg). Concomitant histopathological and clinical chemistry analyses showed that hypertyrosinemia could occur with or without substantial hepatic damage and that substantial hepatic damage could occur without hypertyrosinemia. However, in the rats dosed with galactosamine hydrochloride, which showed highly variable amounts of liver damage at ca. 24 h after dosing, a clear relationship was found between the degree of hypertyrosinemia and the extent of the hepatic necrosis induced. In line with the cause of clinically observed Type II Tyrosinemia, we consider that the critical event in the onset of hepatotoxin-induced hypertyrosinemia is likely to be a reduction in hepatic tyrosine aminotransferase (TAT) activity. We discuss mechanisms by which TAT activity could be lost with special consideration given to pyridoxal 5'-phosphate (P5P) depletion and to the inhibition of protein synthesis. This analysis may have implications for the interpretation of clinical measures of liver status such as Fischer's ratio and the branched-chain tyrosine ratio (BTR).

Animals↗

Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice.

Here, we study the intricate relationship between gut microbiota and host cometabolic phenotypes associated with dietary-induced impaired glucose homeostasis and nonalcoholic fatty liver disease (NAFLD) in a mouse strain (129S6) known to be susceptible to these disease traits, using plasma and urine metabotyping, achieved by (1)H NMR spectroscopy. Multivariate statistical modeling of the spectra shows that the genetic predisposition of the 129S6 mouse to impaired glucose homeostasis and NAFLD is associated with disruptions of choline metabolism, i.e., low circulating levels of plasma phosphatidylcholine and high urinary excretion of methylamines (dimethylamine, trimethylamine, and trimethylamine-N-oxide), coprocessed by symbiotic gut microbiota and mammalian enzyme systems. Conversion of choline into methylamines by microbiota in strain 129S6 on a high-fat diet reduces the bioavailability of choline and mimics the effect of choline-deficient diets, causing NAFLD. These data also indicate that gut microbiota may play an active role in the development of insulin resistance.

Animals↗

Coordinated multitissue transcriptional and plasma metabonomic profiles following acute caloric restriction in mice.

Caloric restriction (CR) increases healthy life span in a range of organisms. The underlying mechanisms are not understood but appear to include changes in gene expression, protein function, and metabolism. Recent studies demonstrate that acute CR alters mortality rates within days in flies. Multitissue transcriptional changes and concomitant metabolic responses to acute CR have not been described. We generated whole genome RNA transcript profiles in liver, skeletal muscle, colon, and hypothalamus and simultaneously measured plasma metabolites using proton nuclear magnetic resonance in mice subjected to acute CR. Liver and muscle showed increased gene expressions associated with fatty acid metabolism and a reduction in those involved in hepatic lipid biosynthesis. Glucogenic amino acids increased in plasma, and gene expression for hepatic gluconeogenesis was enhanced. Increased expression of genes for hormone-mediated signaling and decreased expression of genes involved in protein binding and development occurred in hypothalamus. Cell proliferation genes were decreased and cellular transport genes increased in colon. Acute CR captured many, but not all, hepatic transcriptional changes of long-term CR. Our findings demonstrate a clear transcriptional response across multiple tissues during acute CR, with congruent plasma metabolite changes. Liver and muscle switched gene expression away from energetically expensive biosynthetic processes toward energy conservation and utilization processes, including fatty acid metabolism and gluconeogenesis. Both muscle and colon switched gene expression away from cellular proliferation. Mice undergoing acute CR rapidly adopt many transcriptional and metabolic changes of long-term CR, suggesting that the beneficial effects of CR may require only a short-term reduction in caloric intake.

Animals↗

Metabolome, transcriptome, and bioinformatic cis-element analyses point to HNF-4 as a central regulator of gene expression during enterocyte differentiation.

DNA-binding transcription factors bind to promoters that carry their binding sites. Transcription factors therefore function as nodes in gene regulatory networks. In the present work we used a bioinformatic approach to search for transcription factors that might function as nodes in gene regulatory networks during the differentiation of the small intestinal epithelial cell. In addition we have searched for connections between transcription factors and the villus metabolome. Transcriptome data were generated from mouse small intestinal villus, crypt, and fetal intestinal epithelial cells. Metabolome data were generated from crypt and villus cells. Our results show that genes that are upregulated during fetal to adult and crypt to villus differentiation have an overrepresentation of potential hepatocyte nuclear factor (HNF)-4 binding sites in their promoters. Moreover, metabolome analyses by magic angle spinning (1)H nuclear magnetic resonance spectroscopy showed that the villus epithelial cells contain higher concentrations of lipid carbon chains than the crypt cells. These findings suggest a model where the HNF-4 transcription factor influences the villus metabolome by regulating genes that are involved in lipid metabolism. Our approach also identifies transcription factors of importance for crypt functions such as DNA replication (E2F) and stem cell maintenance (c-Myc).

Algorithms↗

Impact of analytical bias in metabonomic studies of human blood serum and plasma.

Concurrent with the explosion in the number of publications reporting biomarker discovery by profiling technologies, such as proteomics and pattern recognition, has been the increase in evidence highlighting the susceptibility of these approaches to analytical and experimental bias. The work presented here addresses these timely issues by delivering a detailed characterization of the effect of common sources of bias in clinical studies on serum and plasma profiles generated by a key technology in metabonomics, NMR spectroscopy. Specifically, differences in composition when blood samples were collected onto and in the absence of ice, over a series of serum-clot contact times, the stability of NMR-prepared samples over time and the effect on the metabolic profile of freeze-thawing were examined. While differences between individuals were far greater than variation from any other experimental factor, each of the conditions examined did cause slight alterations to the NMR profile that could produce a systematic bias. Variation due to clotting time caused changes in energy metabolites, which were delayed by ice with no other spectral effects. Room-temperature stability and hence NMR spectral repeatability were high (<1% intrasample variation). Higher molecular weight species such as lipoproteins were more susceptible to the variations present in the examined factors. These observations have implications for profiling study design, and hence, our results form a new and valuable resource for those attempting clinical metabolic profiling, for regulatory agencies involved in the licensing of clinical tests and in the generation of international reporting standards for metabonomics.

Humans↗

Statistical search space reduction and two-dimensional data display approaches for UPLC-MS in biomarker discovery and pathway analysis.

A new analytical strategy for biomarker recovery from directly coupled ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC Tof MS) data on biofluids is presented and exemplified using a study on hydrazine-induced liver toxicity. A key step in the strategy involves a novel procedure for reducing the spectroscopic search space by differential analysis of cohorts of normal and pathological samples using an orthogonal projection to latent structures discriminant analysis (O-PLS-DA). This efficiently sorts principal discriminators of toxicity from the background of thousands of metabolic features commonly observed in data sets generated by UPLC-MS analysis of biological fluids and is thus a powerful tool for biomarker discovery.

Animals↗

Metabonomics techniques and applications to pharmaceutical research & development.

In this review, the background to the approach known as metabonomics is provided, giving a brief historical perspective and summarizing the analytical and statistical techniques used. Some of the major applications of metabonomics relevant to pharmaceutical Research & Development are then reviewed including the study of various influences on metabolism, such as diet, lifestyle, and other environmental factors. The applications of metabonomics in drug safety studies are explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology. Next, the role that metabonomics might have in disease diagnosis and therapy monitoring is provided with some examples, and the concept of pharmacometabonomics as a way of predicting an individual's response to treatment is highlighted. Some discussion is given on the strengths and weaknesses, opportunities of, and threats to metabonomics.

Algorithms↗

Pharmaco-metabonomic phenotyping and personalized drug treatment.

There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.

Acetaminophen↗

Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study.

Large-scale population phenotyping for molecular epidemiological studies is subject to all the usual criteria of analytical chemistry. As part of a major phenotyping investigation we have used high-resolution 1H NMR spectroscopy to characterize 24-h urine specimens obtained from population samples in Aito Town, Japan (n = 259), Chicago, IL (n = 315), and Guangxi, China (n = 278). We have investigated analytical reproducibility, urine specimen storage procedures, interinstrument variability, and split specimen detection. Our data show that the multivariate analytical reproducibility of the NMR screening platform was >98% and that most classification errors were due to urine specimen handling inhomogeneity. Differences in metabolite profiles were then assessed for Aito Town, Chicago, and Guangxi population samples; novel combinations of biomarkers were detected that separated the population samples. These cross-population differences in urinary metabolites could be related to genetic, dietary, and gut microbial factors.

Biomarkers↗

Scaling and normalization effects in NMR spectroscopic metabonomic data sets.

Considerable confusion appears to exist in the metabonomics literature as to the real need for, and the role of, preprocessing the acquired spectroscopic data. A number of studies have presented various data manipulation approaches, some suggesting an optimum method. In metabonomics, data are usually presented as a table where each row relates to a given sample or analytical experiment and each column corresponds to a single measurement in that experiment, typically individual spectral peak intensities or metabolite concentrations. Here we suggest definitions for and discuss the operations usually termed normalization (a table row operation) and scaling (a table column operation) and demonstrate their need in 1H NMR spectroscopic data sets derived from urine. The problems associated with "binned" data (i.e., values integrated over discrete spectral regions) are also discussed, and the particular biological context problems of analytical data on urine are highlighted. It is shown that care must be exercised in calculation of correlation coefficients for data sets where normalization to a constant sum is used. Analogous considerations will be needed for other biofluids, other analytical approaches (e.g., HPLC-MS), and indeed for other "omics" techniques (i.e., transcriptomics or proteomics) and for integrated studies with "fused" data sets. It is concluded that data preprocessing is context dependent and there can be no single method for general use.

Algorithms↗

NMR spectroscopic studies of the transacylation reactivity of ibuprofen 1-beta-O-acyl glucuronide.

The products arising from the intra-molecular acyl migration reactions of drug ester glucuronides can be reactive towards cellular proteins and have been proposed to cause toxic side effects. The relative reactivity of a range of drug and model glucuronides have previously been determined by measuring the rate of disappearance of a peak characteristic of the 1-beta-O-acyl glucuronide using 1H NMR spectroscopy. Here the degradation rate of ibuprofen 1-beta-O-acyl glucuronide has been investigated using NMR spectroscopy for the first time using material isolated from human urine with solid-phase extraction chromatography (SPEC). The degradation rate was measured by following the disappearance of the 1H NMR signal from the 1-beta-anomeric proton of the glucuronic acid moiety as the reaction progressed in pH 7.4 buffer inside an NMR tube. The measured degradation rate represents a pseudo-first order rate constant, a combination of the transacylation rate (1-beta-isomer to 2-beta-isomer) and the hydrolysis rate, and is presented as a half-life of 3.5 h. This value is compared to those from drug glucuronides where adverse effects have been observed in patients after administration of the drug.

Acylation↗

Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies.

Statistical heterospectroscopy (SHY) is a new statistical paradigm for the coanalysis of multispectroscopic data sets acquired on multiple samples. This method operates through the analysis of the intrinsic covariance between signal intensities in the same and related molecules measured by different techniques across cohorts of samples. The potential of SHY is illustrated using both 600-MHz 1H NMR and UPLC-TOFMS data obtained from control rat urine samples (n = 54) and from a corresponding hydrazine-treated group (n = 58). We show that direct cross-correlation of spectral parameters, viz. chemical shifts from NMR and m/z data from MS, is readily achievable for a variety of metabolites, which leads to improved efficiency of molecular biomarker identification. In addition to structure, higher level biological information can be obtained on metabolic pathway activity and connectivities by examination of different levels of the NMR to MS correlation and anticorrelation matrixes. The SHY approach is of general applicability to complex mixture analysis, if two or more independent spectroscopic data sets are available for any sample cohort. Biological applications of SHY as demonstrated here show promise as a new systems biology tool for biomarker recovery.

Animals↗

UPLC/MS(E); a new approach for generating molecular fragment information for biomarker structure elucidation.

A new approach to obtain fragmentation information in liquid chromatography/mass spectrometry (LC/MS) studies of small molecules in complex mixtures is presented using simultaneous acquisition of exact mass at high and low collision energy, MS(E). LC/MS-TOF and LC/MS/MS-TOF are powerful tools for the analysis of complex mixtures, especially those for biological fluids allowing the elucidation of elemental composition and fragmentation information. In this example the composition of rat urine was studied using this new approach, allowing the structures of several endogenous components to be confirmed in one analytical run by the simultaneous acquisition of exact mass precursor and fragment ion data. The spectral data obtained using this new approach are comparable to those obtained by conventional LC/MS/MS as exemplified by the identification of endogenous metabolites present in rat urine.

Animals↗