Irinotecan treats a range of solid tumors, but its effectiveness is severely limited by gastrointestinal (GI) tract toxicity caused by gut bacterial β-glucuronidase (GUS) enzymes. Targeted bacterial GUS inhibitors have been shown to partially alleviate irinotecan-induced GI tract damage and resultant diarrhea in mice. Here, we unravel the mechanistic basis for GI protection by gut microbial GUS inhibitors using in vivo models. We use in vitro, in fimo, and in vivo models to determine whether GUS inhibition alters the anticancer efficacy of irinotecan. We demonstrate that a single dose of irinotecan increases GI bacterial GUS activity in 1 d and reduces intestinal epithelial cell proliferation in 5 d, both blocked by a single dose of a GUS inhibitor. In a tumor xenograft model, GUS inhibition prevents intestinal toxicity and maintains the antitumor efficacy of irinotecan. Remarkably, GUS inhibitor also effectively blocks the striking irinotecan-induced bloom of Enterobacteriaceae in immunedeficient mice. In a genetically engineered mouse model of cancer, GUS inhibition alleviates gut damage, improves survival, and does not alter gut microbial composition; however, by allowing dose intensification, it dramatically improves irinotecan's effectiveness, reducing tumors to a fraction of that achieved by irinotecan alone, while simultaneously promoting epithelial regeneration. These results indicate that targeted gut microbial enzyme inhibitors can improve cancer chemotherapeutic outcomes by protecting the gut epithelium from microbial dysbiosis and proliferative crypt damage. microbiome | chemotherapy | cancer | gastrointestinal toxicity I rinotecan (CPT-11) is essential for treating colorectal and pancreatic cancers and is frequently administered as a mixture with 5-fluorouracil and/or oxaliplatin. Ongoing clinical trials seek to extend irinotecan to other forms of cancer. However, irinotecan causes both myelosuppression and gastrointestinal (GI) side effects, including mucositis and late-onset diarrhea, which are often dose limiting: 88% of irinotecan patients develop diarrhea, with 30% experiencing acute grade 3 to 4 diarrhea (1-3). This toxicity is frequently refractory to antimotility drugs. Thus, treating irinotecaninduced diarrhea is a significant clinical need (4, 5).The irinotecan prodrug is activated in vivo to SN38, a potent topoisomerase I inhibitor (6) that retards the growth of rapidly proliferating cells in tumors and the intestinal epithelium, which renews every 5 d. SN38 is detoxified through the addition of glucuronic acid (GlcA) to form SN38-G, a compound marked for elimination via the GI tract. Gut commensal bacterial β-glucuronidase (GUS) proteins remove GlcA from SN38-G. Reactivated SN38 inflicts epithelial damage, resulting in bleeding diarrhea and acute weight loss in animal models (7). We reduced irinotecan-induced gut toxicity using inhibitors that selectively, nonlethally, and potently block the actions of gut bacterial GUS enzymes (8,9). The utility of GUS inhibition also extends to drugs be...

Clostridium difficile is a Gram-positive spore-forming anaerobe and a major cause of antibiotic-associated diarrhoea. Disruption of the commensal microbiota, such as through treatment with broad-spectrum antibiotics, is a critical precursor for colonisation by C. difficile and subsequent disease. Furthermore, failure of the gut microbiota to recover colonisation resistance can result in recurrence of infection. An unusual characteristic of C. difficile among gut bacteria is its ability to produce the bacteriostatic compound para-cresol (p-cresol) through fermentation of tyrosine. Here, we demonstrate that the ability of C. difficile to produce p-cresol in vitro provides a competitive advantage over gut bacteria including Escherichia coli, Klebsiella oxytoca and Bacteroides thetaiotaomicron. Metabolic profiling of competitive co-cultures revealed that acetate, alanine, butyrate, isobutyrate, p-cresol and p-hydroxyphenylacetate were the main metabolites responsible for differentiating the parent strain C. difficile (630Δerm) from a defined mutant deficient in p-cresol production. Moreover, we show that the p-cresol mutant displays a fitness defect in a mouse relapse model of C. difficile infection (CDI). Analysis of the microbiome from this mouse model of CDI demonstrates that colonisation by the p-cresol mutant results in a distinctly altered intestinal microbiota, and metabolic profile, with a greater representation of Gammaproteobacteria, including the Pseudomonales and Enterobacteriales. We demonstrate that Gammaproteobacteria are susceptible to exogenous p-cresol in vitro and that there is a clear divide between bacterial Phyla and their susceptibility to p-cresol. In general, Gram-negative species were relatively sensitive to p-cresol, whereas Gram-positive species were more tolerant. This study demonstrates that production of p-cresol by C. difficile has an effect on the viability of intestinal bacteria as well as the major metabolites produced in vitro. These observations are upheld in a mouse model of CDI, in which p-cresol production affects the biodiversity of gut microbiota and faecal metabolite profiles, suggesting that p-cresol production contributes to C. difficile survival and pathogenesis.

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A comprehensive Collision Cross Section (CCS) library was obtained via travelling wave ion guide mobility measurements through direct infusion (DI). The library consists of CCS and Mass Spectral (MS) data in negative and positive ElectroSpray Ionisation (ESI) mode for 463 and 479 endogenous metabolites, respectively. For both ionisation modes combined, TW CCSN2 data were obtained for 542 non-redundant metabolites. These data were acquired on two different ion mobility orthogonal acceleration QToF MS systems in two different laboratories, with the majority of the resulting TW CCSN2 values (from detected compounds) found to be within 1% of one another. Validation of these results against two independent, external TW CCSN2 data sources and predicted CCS values indicated be within 1-2% of these other values. The same metabolites were then analysed using a rapid reversed-phase ultra (high) performance liquid chromatographic (U(H)PLC) separation combined with IM and MS (IM-MS) thus providing retention time (tr), m/z and TW CCSN2 values (with the latter compared with the DI-IM-MS data). Analytes for which TW CCSN2 values were obtained by U(H)PLC-IM-MS showed good agreement with the results obtained from DI-IM-MS. The repeatability of the TW CCSN2 values obtained for these metabolites on the different ion mobility QToF systems, using either DI or LC, encouraged the further evaluation of the U(H)PLC-IM-MS approach via the analysis of samples of rat urine, from control and methotrexate-treated animals, in order to assess the potential of the approach for metabolite identification and profiling in metabolic phenotyping studies. Based on the database derived from the standards 63 metabolites were identified in rat urine, using positive ESI, based on the combination of tr, TW CCSN2 and MS data.

Methotrexate (MTX) is a chemotherapeutic agent that can cause a range of toxic side effects including gastrointestinal damage, hepatotoxicity, myelosuppression, and nephrotoxicity and has potentially complex interactions with the gut microbiome. Following untargeted UPLC-qtof-MS analysis of urine and fecal samples from male Sprague–Dawley rats administered at either 0, 10, 40, or 100 mg/kg of MTX, dose-dependent changes in the endogenous metabolite profiles were detected. Semiquantitative targeted UPLC-MS detected MTX excreted in urine as well as MTX and two metabolites, 2,4-diamino- N -10-methylpteroic acid (DAMPA) and 7-hydroxy-MTX, in the feces. DAMPA is produced by the bacterial enzyme carboxypeptidase glutamate 2 (CPDG2) in the gut. Microbiota profiling (16S rRNA gene amplicon sequencing) of fecal samples showed an increase in the relative abundance of Firmicutes over the Bacteroidetes at low doses of MTX but the reverse at high doses. Firmicutes relative abundance was positively correlated with DAMPA excretion in feces at 48 h, which were both lower at 100 mg/kg compared to that seen at 40 mg/kg. Overall, chronic exposure to MTX appears to induce community and functionality changes in the intestinal microbiota, inducing downstream perturbations in CPDG2 activity, and thus may delay MTX detoxication to DAMPA. This reduction in metabolic clearance might be associated with increased gastrointestinal toxicity.

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Lichens are symbiotic organisms known for producing unique secondary metabolites with attractive cosmetic and pharmacological properties. In this paper, we investigated three standard methods of preparation of Pseudevernia furfuracea (blender grinding, ball milling, pestle and mortar). The materials obtained were characterized by electronic microscopy, nitrogen adsorption and compared from the point of view of extraction. Their microscopic structure is related to extraction efficiency. In addition, it is shown using thalline reactions and mass spectrometry mapping (TOF-SIMS) that these metabolites are not evenly distributed throughout the organism. Particularly, atranorin (a secondary metabolite of interest) is mainly present in the cortex of P. furfuracea. Finally, using microwave assisted extraction (MAE) we obtained evidence that an appropriate preparation can increase the extraction efficiency of atranorin by a factor of five.

Hyperpolarized nuclear magnetic resonance (NMR) offers an ensemble of methods that remarkably address the sensitivity issues of conventional NMR. Dissolution Dynamic Nuclear Polarization (d-DNP) provides a unique and general way to detect 13 C NMR signals with a sensitivity enhanced by several orders of magnitude. The expanding application scope of d-DNP now encompasses the analysis of complex mixtures at natural 13 C abundance. However, the application of d-DNP in this area has been limited to metabolite extracts. Here, we report the first d-DNP-enhanced 13 C NMR analysis of a biofluid -urine-at natural abundance, offering unprecedented resolution and sensitivity for this challenging type of sample. We also show that accurate quantitative information on multiple targeted metabolites can be retrieved through a standard addition procedure.