Targeted Metabolomics Analysis Identifies Intestinal Microbiota-Derived Urinary Biomarkers of Colonization Resistance in Antibiotic-Treated Mice

Host microbiome depletion attenuates biofluid metabolite responses following radiation exposure

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we 'knocked out' the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman's correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay.

Nano polystyrene microplastics could accumulate in Nile tilapia (Oreochromis niloticus): Negatively impacts on the intestinal and liver health through water exposure

Microplastics (MPs) have become a significant concern for their potential toxicity. However, the correlation between the size of plastic particles and their toxicity remains inconclusive. Here, we investigate the toxic effects of different sizes (80 nm, 800 nm, 8 µm and 80 µm) polystyrene MPs (PS-MPs) on the model organism Nile tilapia (Oreochromis niloticus). The results of bioluminescent imaging indicate that the 80 nm PS-MPs are more likely to invade the body. H&E staining shows severe damage on the intestinal villi and distinct hepatic steatosis in the 80 nm group. EdU labeling shows that the proliferation activity of intestinal and liver cells reduces significantly in the 80 nm group. The gut microbiome analysis shows a severe imbalance of gut microbiota homeostasis in the 80 nm group. The analysis of liver transcriptomics and metabolomics shows that the liver lipid metabolism is disordered in the 80 nm group. In conclusion, this study confirms that the 80 nm PS-MPs are more likely to induce intestinal and liver toxicity. All the above lay the foundation for further study on the pathological damage of MPs to other organisms.

LC-MS/MS platform-based serum untargeted screening reveals the diagnostic biomarker panel and molecular mechanism of breast cancer

BACKGROUND

Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach.

METHODS

In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30). The multivariate data analysis, determination of the fold change and the Mann-Whitney U test were used to screen out the differential metabolites. Additionally, machine learning methods including receiver operating curve analysis and logistic regression analysis were conducted to establish diagnostic biomarker panels.

RESULTS

There were 36 metabolites found to be significantly different between BC and non-BC groups, and 12 metabolites discovered to be significantly different between TNBC and non-TNBC patients. Results also showed that four metabolites, including N-acetyl-D-tryptophan, 2-arachidonoylglycerol, pipecolic acid and oxoglutaric acid, were considered as vital biomarkers for the diagnosis of BC and non-BC with an area under the curve (AUC) of 0.995. Another two-metabolite panel of N-acetyl-D-tryptophan and 2-arachidonoylglycerol was discovered to discriminate TNBC from non-TNBC and produced an AUC of 0.965.

CONCLUSION

This study demonstrated that serum metabolomics can be used to identify BC specifically and identified promising serum metabolic markers for TNBC diagnosis.

Bridging the Gap from Enterotypes to Personalized Dietary Recommendations: A Metabolomics Perspective on Microbiome Research

Advances in high-throughput DNA sequencing have propelled research into the human microbiome and its link to metabolic health. We explore microbiome analysis methods, specifically emphasizing metabolomics, how dietary choices impact the production of microbial metabolites, providing an overview of studies examining the connection between enterotypes and diet, and thus, improvement of personalized dietary recommendations. Acetate, propionate, and butyrate constitute more than 95% of the collective pool of short-chain fatty acids. Conflicting data on acetate's effects may result from its dynamic signaling, which can vary depending on physiological conditions and metabolic phenotypes. Human studies suggest that propionate has overall anti-obesity effects due to its well-documented chemistry, cellular signaling mechanisms, and various clinical benefits. Butyrate, similar to propionate, has the ability to reduce obesity by stimulating the release of appetite-suppressing hormones and promoting the synthesis of leptin. Tryptophan affects systemic hormone secretion, with indole stimulating the release of GLP-1, which impacts insulin secretion, appetite suppression, and gastric emptying. Bile acids, synthesized from cholesterol in the liver and subsequently modified by gut bacteria, play an essential role in the digestion and absorption of dietary fats and fat-soluble vitamins, but they also interact directly with intestinal microbiota and their metabolites. One study using statistical methods identified primarily two groupings of enterotypes Bacteroides and Ruminococcus. The Prevotella-dominated enterotype, P-type, in humans correlates with vegetarians, high-fiber and carbohydrate-rich diets, and traditional diets. Conversely, individuals who consume diets rich in animal fats and proteins, typical in Western-style diets, often exhibit the Bacteroides-dominated, B-type, enterotype. The P-type showcases efficient hydrolytic enzymes for plant fiber degradation but has limited lipid and protein fermentation capacity. Conversely, the B-type features specialized enzymes tailored for the degradation of animal-derived carbohydrates and proteins, showcasing an enhanced saccharolytic and proteolytic potential. Generally, models excel at predictions but often struggle to fully elucidate why certain substances yield varied responses. These studies provide valuable insights into the potential for personalized dietary recommendations based on enterotypes.

Urinary Metabolome Analysis Reveals Potential Microbiota Alteration and Electrophilic Burden Induced by High Red Meat Diet: Results from the French NutriNet-Santé Cohort and an In Vivo Intervention Study in Rats

SCOPE

High red and processed meat consumption is associated with several adverse outcomes such as colorectal cancer and overall global mortality. However, the underlying mechanisms remain debated and need to be elucidated.

METHODS AND RESULTS

Urinary untargeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics data from 240 subjects from the French cohort NutriNet-Santé are analyzed. Individuals are matched and divided into three groups according to their consumption of red and processed meat: high red and processed meat consumers, non-red and processed meat consumers, and at random group. Results are supported by a preclinical experiment where rats are fed either a high red meat or a control diet. Microbiota derived metabolites, in particular indoxyl sulfate and cinnamoylglycine, are found impacted by the high red meat diet in both studies, suggesting a modification of microbiota by the high red/processed meat diet. Rat microbiota sequencing analysis strengthens this observation. Although not evidenced in the human study, rat mercapturic acid profile concomitantly reveals an increased lipid peroxidation induced by high red meat diet.

CONCLUSION

Novel microbiota metabolites are identified as red meat consumption potential biomarkers, suggesting a deleterious effect, which could partly explain the adverse effects associated with high red and processed meat consumption.

Polyphenols and Small Phenolic Acids as Cellular Metabolic Regulators

Polyphenols and representative small phenolic acids and molecules derived from larger constituents are dietary antioxidants from fruits, vegetables and largely other plant-based sources that have ability to scavenge free radicals. What is often neglected in polyphenol metabolism is bioavailability and the role of the gut microbiota (GMB), which has an essential role in health and disease and participates in co-metabolism with the host. The composition of the gut microbiota is in constant flux and is modified by multiple intrinsic and extrinsic factors, including antibiotics. Dietary or other factors are key modulators of the host gut milieu. In this review, we explore the role of polyphenols and select phenolic compounds as metabolic or intrinsic biochemistry regulators and explore this relationship in the context of the microbiota–gut–target organ axis in health and disease.

Quantification of Gut Microbiota Dysbiosis-Related Organic Acids in Human Urine Using LC-MS/MS

Urine organic acid contains water-soluble metabolites and/or metabolites—derived from sugars, amino acids, lipids, vitamins, and drugs—which can reveal a human’s physiological condition. These urine organic acids—hippuric acid, benzoic acid, phenylacetic acid, phenylpropionic acid, 4-hydroxybenzoic acid, 4-hydroxyphenyl acetic acid, 3-hydroxyphenylpropionic acid, 3,4-dihydroxyphenyl propionic acid, and 3-indoleacetic acid—were the eligible candidates for the dysbiosis of gut microbiota. The aim of this proposal was to develop and to validate a liquid chromatography−tandem mass spectrometry (LC-MS/MS) bioanalysis method for the nine organic acids in human urine. Stable-labeled isotope standard (creatinine-d3) and acetonitrile were added to the urine sample. The supernatant was diluted with deionized water and injected into LC-MS/MS. This method was validated with high selectivity for the urine sample, a low limit of quantification (10−40 ng/mL), good linearity (r > 0.995), high accuracy (85.8−109.7%), and high precision (1.4−13.3%). This method simultaneously analyzed creatinine in urine, which calibrates metabolic rate between different individuals. Validation has been completed for this method; as such, it could possibly be applied to the study of gut microbiota clinically.

Bacterial Metabolomics: Sample Preparation Methods

Metabolomics is a comprehensive analysis of metabolites existing in biological systems. As one of the important "omics" tools, the approach has been widely employed in various fields in helping to better understand the complex cellular metabolic states and changes. Bacterial metabolomics has gained a significant interest as bacteria serve to provide a better subject or model at systems level. The approach in metabolomics is categorized into untargeted and targeted which serves different paradigms of interest. Nevertheless, the bottleneck in metabolomics has been the sample or metabolite preparation method. A custom-made method and design for a particular species or strain of bacteria might be necessary as most studies generally refer to other bacteria or even yeast and fungi that may lead to unreliable analysis. The paramount aspect of metabolomics design comprises sample harvesting, quenching, and metabolite extraction procedures. Depending on the type of samples and research objective, each step must be at optimal conditions which are significantly important in determining the final output. To date, there are no standardized nor single designated protocols that have been established for a specific bacteria strain for untargeted and targeted approaches. In this paper, the existing and current developments of sample preparation methods of bacterial metabolomics used in both approaches are reviewed. The review also highlights previous literature of optimized conditions used to propose the most ideal methods for metabolite preparation, particularly for bacterial cells. Advantages and limitations of methods are discussed for future improvement of bacterial metabolomics.

Interactive relationship between Trp metabolites and gut microbiota: The impact on human pathology of disease

Tryptophan (Trp), an α-amino acid, is the precursor of serotonin (5-hydroxytryptamine, 5-HT), which is involved in a variety of features of metabolic function and human nutrition. Evidence highlights the role of Trp metabolites (exclusively 5-HT) in the gastrointestinal (GI) tract; however, the mechanisms of action involved in the release of 5-HT in the GI tract are still unknown. Considering the fact that variations of 5-HT may facilitate the growth of certain GI disorders, gaining a better understanding of the function and release of 5-HT in the GI tract would be beneficial. Additionally, investigating Trp metabolism may clarify the relationship between Trp and gut microbiota. It is believed that other metabolites of Trp (mostly that of the kynurenine pathway) may play a significant role in controlling gut microbiota function. In this review, we have attempted to summarize the current research investigating the relationship of gut microbiota, Trp, and 5-HT metabolism (with particular attention paid to their metabolite type, as well as a discussion of the research methods used in each study). Taking together, regarding the role that Trp/5-HT plays in a range of physical and mental diseases, the gut bacterial types, as well as the related disorders, have been exclusively considered.

Small phenolic and indolic gut-dependent molecules in the primate central nervous system: levels vs. bioactivity

INTRODUCTION

A rapidly growing body of data documents associations between disease of the brain and small molecules generated by gut-microbiota (GMB). While such metabolites can affect brain function through a variety of mechanisms, the most direct action would be on the central nervous system (CNS) itself.

OBJECTIVE

Identify indolic and phenolic GMB-dependent small molecules that reach bioactive concentrations in primate CNS.

METHODS

We conducted a PubMed search for metabolomic studies of the primate CNS [brain tissue or cerebrospinal fluid (CSF)] and then selected for phenolic or indolic metabolites that (i) had been quantified, (ii) were GMB-dependent. For each chemical we then conducted a search for studies of bioactivity conducted in vitro in human cells of any kind or in CNS cells from the mouse or rat.

RESULTS

36 metabolites of interests were identified in primate CNS through targeted metabolomics. Quantification was available for 31/36 and in vitro bioactivity for 23/36. The reported CNS range for 8 metabolites 2-(3-hydroxyphenyl)acetic acid, 2-(4-hydroxyphenyl)acetic acid, 3-(3-hydroxyphenyl)propanoic acid, (E)-3-(3,4-dihydroxyphenyl)prop-2-enoic acid [caffeic acid], 3-hydroxybenzoic acid, 4-hydroxybenzoic acid, 2-acetamido-3-(1H-indol-3-yl)propanoic acid [N-acetyltryptophan], 1H-indol-3-yl hydrogen sulfate [indoxyl-3-sulfate] overlapped with a bioactive concentration. However, the number and quality of relevant studies of CNS neurochemistry as well as of bioactivity were highly limited. Structural isomers, multiple metabolites and potential confounders were inadequately considered.

CONCLUSION

The potential direct bioactivity of GMB-derived indolic and phenolic molecules on primate CNS remains largely unknown. The field requires additional strategies to identify and prioritize screening of the most promising small molecules that enter the CNS.

Urine metabolites for the identification of Onchocerca volvulus infections in patients from Cameroon

Background

The tropical disease onchocerciasis (river blindness), caused by Onchocerca volvulus filarial nematodes, is targeted for elimination by mass treatment with nematocidal and antimicrobial drugs. Diagnosis of O. volvulus infections is based on counts of skin-borne microfilariae, but additional diagnostic tools, e.g. worm- or host-derived small RNAs, proteins or metabolites, are required for high-throughput screening. N-acetyltyramine-O,β-glucuronide (NATOG) was suggested as a biomarker for onchocerciasis but its viability as diagnostic tool has been challenged.

Methods

We performed a screening program of urine samples from individuals from Cameroon infected with O. volvulus, Loa loa, Mansonella perstans or a combination thereof. Urine metabolites were measured by liquid chromatography–mass spectrometry (LC-MS). Principle component analysis (PCA) revealed that onchocerciasis causes complex changes of the urine metabolome.

Results

The mean NATOG content was elevated in urine of O. volvulus-infected compared with non-infected individuals, but NATOG levels showed considerable variation. However, 13.8% of all O. volvulus-infected individuals had high NATOG levels never reached by individuals without filarial infections or only infected with L. loa or M. perstans. Therefore, the identification of individuals with high NATOG levels might be used to screen for the elimination of onchocerciasis after mass drug application. Additional metabolites, including a compound identified as cinnamoylglycine, had high PC1/PC2 loadings in the data set. Mean levels of cinnamoylglycine were increased in O. volvulus-infected individuals, and 17.2% of all O. volvulus individuals had elevated cinnamoylglycine levels not reached by the controls.

Conclusions

On an individual level, NATOG alone had poor discriminative power distinguishing infected from non-infected individuals. However, 13.8% of all O. volvulus-infected individuals had NATOG levels never reached by individuals without filarial infections or infected with only L. loa or M. perstans. Discrimination of O. volvulus infections from controls or individuals suffering from multiple infections was improved by the measurement of additional metabolites, e.g. cinnamoylglycine. Thus, measuring a combination of urine metabolites may provide a way to assess onchocerciasis on the population level. This provides the possibility to design a strategy for large-scale onchocerciasis epidemiological screening programs based on urine rather than invasive techniques.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-04893-1.

Serum metabolites reflecting gut microbiome alpha diversity predict type 2 diabetes

Type 2 diabetes (T2D) is associated with reduced gut microbiome diversity, although the cause is unclear. Metabolites generated by gut microbes also appear to be causative factors in T2D. We therefore searched for serum metabolites predictive of gut microbiome diversity in 1018 females from TwinsUK with concurrent metabolomic profiling and microbiome composition. We generated a Microbial Metabolites Diversity (MMD) score of six circulating metabolites that explained over 18% of the variance in microbiome alpha diversity. Moreover, the MMD score was associated with a significantly lower odds of prevalent (OR[95%CI] = 0.22[0.07;0.70], P = .01) and incident T2D (HR[95%CI] = 0.31[0.11,0.90], P = .03). We replicated our results in 1522 individuals from the ARIC study (prevalent T2D: OR[95%CI] = 0.79[0.64,0.96], P = .02, incident T2D: HR[95%CI] = 0.87[0.79,0.95], P = .003). The MMD score mediated 28%[15%,94%] of the total effect of gut microbiome on T2D after adjusting for confounders. Metabolites predicting higher microbiome diversity included 3-phenylpropionate(hydrocinnamate), indolepropionate, cinnamoylglycine and 5-alpha-pregnan-3beta,20 alpha-diol monosulfate(2) of which indolepropionate and phenylpropionate have already been linked to lower incidence of T2D. Metabolites correlating with lower microbial diversity included glutarate and imidazole propionate, of which the latter has been implicated in insulin resistance. Our results suggest that the effect of gut microbiome diversity on T2D is largely mediated by microbial metabolites, which might be modifiable by diet.

Profiling of polar urine metabolite extracts from Chinese colorectal cancer patients to screen for potential diagnostic and adverse-effect biomarkers

Background: Metabolomics has demonstrated its potential in the early diagnosis, drug safety evaluation and personalized toxicology research of various cancers. Objectives: We aim to screen for potential diagnostic and capecitabine-related adverse effect (CRAE) biomarkers from urinary endogenous metabolites in Chinese colorectal cancer (CRC) patients. Methods: The metabolic profiles of 139 CRC patients and 50 non-neoplastic controls were analyzed using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry. Results: There were 41 metabolites identified between the CRC patients and the non-neoplastic controls, and 19 metabolites were identified between CRC patients with and without CRAE. Based on these identified metabolites, bioinformatic analysis and prediction model construction were completed. Most of these differential metabolites have important roles in cell proliferation and differentiation and the immune system. Based on binary logistic regression, a CRC prediction model, composed of 3-methylhistidine, N-heptanoylglycine, N1,N12-diacetylspermine and hippurate, was established, with an area under curve (AUC) of 0.980 (95% CI: 0.953-1.000; sensitivity: 94.3%; specificity: 92.0%) in the training set, and an AUC of 0.968 (95% CI: 0.933-1.000; sensitivity: 89.9%; specificity: 92.0%) in the testing set. In addition, methionine and 4-pyridoxic acid can be combined to predict hand foot syndrome, with an AUC of 0.884; ubiquinone-1 and 4-pyridoxic acid can be combined to predict anemia, with an AUC of 0.889; and 5-acetamidovalerate and 3,4-methylenesebacic acid can be combined to predict neutropenia, with an AUC of 0.882. Conclusion: The profiling of urine polar metabolites has great potential in the early detection of CRC and the prediction of CRAE.

The Role of the Microbiota-Gut-Brain Axis and Antibiotics in ALS and Neurodegenerative Diseases

The human gut hosts a wide and diverse ecosystem of microorganisms termed the microbiota, which line the walls of the digestive tract and colon where they co-metabolize digestible and indigestible food to contribute a plethora of biochemical compounds with diverse biological functions. The influence gut microbes have on neurological processes is largely yet unexplored. However, recent data regarding the so-called leaky gut, leaky brain syndrome suggests a potential link between the gut microbiota, inflammation and host co-metabolism that may affect neuropathology both locally and distally from sites where microorganisms are found. The focus of this manuscript is to draw connection between the microbiota–gut–brain (MGB) axis, antibiotics and the use of “BUGS AS DRUGS” for neurodegenerative diseases, their treatment, diagnoses and management and to compare the effect of current and past pharmaceuticals and antibiotics for alternative mechanisms of action for brain and neuronal disorders, such as Alzheimer disease (AD), Amyotrophic Lateral Sclerosis (ALS), mood disorders, schizophrenia, autism spectrum disorders and others. It is a paradigm shift to suggest these diseases can be largely affected by unknown aspects of the microbiota. Therefore, a future exists for applying microbial, chemobiotic and chemotherapeutic approaches to enhance translational and personalized medical outcomes. Microbial modifying applications, such as CRISPR technology and recombinant DNA technology, among others, echo a theme in shifting paradigms, which involve the gut microbiota (GM) and mycobiota and will lead to potential gut-driven treatments for refractory neurologic diseases.

Polyethylene microplastics affect the distribution of gut microbiota and inflammation development in mice

Environmental pollution caused by plastics has become a public health problem. However, the effect of microplastics on gut microbiota, inflammation development and their underlying mechanisms are not well characterized. In the present study, we assessed the effect of exposure to different amounts of polyethylene microplastics (6, 60, and 600 μg/day for 5 consecutive weeks) in a C57BL/6 mice model. Treatment with a high concentration of microplastics increased the numbers of gut microbial species, bacterial abundance, and flora diversity. Feeding groups showed a significant increase in Staphylococcus abundance alongside a significant decrease in Parabacteroides abundance, as compared to the blank (untreated) group. In addition, serum levels of interleukin-1α in all feeding groups were significantly greater than that in the blank group. Of note, treatment with microplastics decreased the percentage of Th17 and Treg cells among CD4⁺ cells, while no significant difference was observed between the blank and treatment groups with respect to the Th17/Treg cell ratio. The intestine (colon and duodenum) of mice fed high-concentration microplastics showed obvious inflammation and higher TLR4, AP-1, and IRF5 expression. Thus, polyethylene microplastics can induce intestinal dysbacteriosis and inflammation, which provides a theoretical basis for the prevention and treatment of microplastics-related diseases.

Urinary Metabolites of Green Tea as Potential Markers of Colonization Resistance to Pathogenic Gut Bacteria in Mice

Background

The gut microbiome (GMB) generates numerous chemicals that are absorbed systemically and excreted in urine. Antibiotics can disrupt the GMB ecosystem and weaken its resistance to colonization by enteric pathogens such as Clostridium difficile. If the changes in GMB composition and metabolism are sufficiently large, they can be reflected in the urinary metabo-lome. Characterizing these changes could provide a potentially valuable biomarker of the status of the GMB. While preliminary studies suggest such a possibility, the high level of data variance presents a challenge to translational applications. Since many GMB-generated chemicals are derived from the biotransformation of plant-derived dietary polyphenols, administering an oral precursor challenge should amplify GMB-dependent changes in urinary metabolites.

Methods

A course of antibiotics (clindamycin, piperacillin/tazobactam, or aztreonam) was administered SC daily (days 1 and 2) to mice receiving polyphenol-rich green tea in drinking water. Urine was collected at baseline as well as days 3, 7, and 11. Levels of pyrogallol and pyrocatechol, two phenolic molecules unequivocally GMB-dependent in humans but that had not been similarly examined in mice, were quantified.

Results

In confirmation of our hypothesis, differential changes in murine urinary pyrogallol levels identified the treatments (clindamycin, piperacillin/tazobactam) previously associated with a weakening of colonization resistance to Clostridium difficile. The changes in pyrocatechol levels did not withstand corrections for multiple comparisons.

Conclusions

In the mouse, urinary pyrogallol and, in all likelihood, pyrocatechol levels, are GMB-dependent and, in combination with precursor challenge, deserve further consideration as potential metabolomic biomarkers for the health and dysbiotic vulnerability of the GMB.

Metabolomics reveals elevated urinary excretion of collagen degradation and epithelial cell turnover products in irritable bowel syndrome patients

INTRODUCTION

Irritable bowel syndrome (IBS), the most commonly diagnosed functional gastrointestinal (GI) disorder in developed countries, is characterized by chronic abdominal pain, and altered bowel habits.

OBJECTIVES

Accurate and timely diagnosis is challenging as it relies on symptoms and an evolving set of exclusion criteria to distinguish it from other related GI disorders reflecting a complex etiology that remains poorly understood. Herein, nontargeted metabolite profiling of repeat urine specimens collected from a cohort of IBS patients (n = 42) was compared to healthy controls (n = 20) to gain insights into the underlying pathophysiology.

METHODS

An integrated data workflow for characterization of the urine metabolome with stringent quality control was developed to authenticate reliably measured (CV < 30%) and frequently detected (> 75%) metabolites using multisegment injection-capillary electrophoresis-mass spectrometry. Complementary statistical methods were then used to rank differentially excreted urinary metabolites after normalization to osmolality that were subsequently identified by high resolution tandem mass spectrometry and their electrophoretic migration behavior.

RESULTS

Our work revealed ten consistently elevated urinary metabolites in repeat samples collected from IBS patients at two different time points (q < 0.05 after age and Benjamini-Hochberg/FDR adjustment), which were associated with greater collagen degradation and intestinal mucosal turn-over processes likely due to low-grade inflammation. IBS-specific metabolites identified in urine included a series of hydroxylysine metabolites (O-glycosylgalactosyl-hydroxylysine, O-galactosyl-hydroxylysine, lysine), mannopyranosy-L-tryptophan, imidazole propionate, glutamine, serine, ornithine, dimethylglycine and dimethylguanosine. A major limitation in this retrospective case-control study was significant co-morbidity of IBS patients with other illnesses, including depression and prescribed medications as compared to healthy controls.

CONCLUSION

This work provides new mechanistic insights into the pathophysiology of IBS while also offering a convenient way to monitor patient disease progression and treatment responses to therapy based on a panel of urinary metabolites that avoids invasive blood sampling, colonoscopy and/or tissue biopsies.

Strain-Level Differentiation of Bacteria by Paper Spray Ionization Mass Spectrometry

Paper spray ionization mass spectrometry (PSI-MS) is a relatively new analytical technique allowing for rapid mass spectrometric analysis of biological samples with little or no sample preparation. The expeditious nature of the analysis and minimal requirement for sample preparation make PSI-MS a promising avenue for future clinical assays with one potential application in the identification of different types of bacteria. Although past PSI-MS studies have demonstrated the ability to distinguish between bacteria of different species and morphological classes, achieving within-species strain-level differentiation has never been performed. In this report, we demonstrate the first strain-level bacterial differentiation by PSI-MS with the mammalian intestinal bacterium Oxalobacter formigenes ( Oxf). This novel application holds promising clinical significance as it could be used to differentiate between pathogenic bacteria and their harmless, commensal relatives, saving time and money in clinical diagnostics. Both whole cells and cell lysates of  Oxf strains HC1 and OxWR were analyzed using the Prosolia Velox 360TM PSI source coupled to a Thermo Scientific Q Exactive high-resolution mass spectrometer with a rapid 30 s analytical method. Multivariate statistical analysis followed by examination of significant features provided for and confirmed differentiation between Oxf HC1 and OxWR. We report a panel of strain-exclusive metabolites that could serve as potential strain-indicating biomarkers.

Exploratory metabolomics of nascent metabolic syndrome

INTRODUCTION

Metabolic syndrome (MetS) is a disorder defined by having three of five features: increased waist circumference (WC), hypertriglyceridemia, decreased high-density lipoprotein-cholesterol, hypertension and an elevated blood glucose (BG). Metabolic Syndrome ( MetS) affects 35% of American adults and significantly increases risk for Atherosclerotic cardiovascular disease (ASCVD) and type-2 diabetes (T2DM). An understanding of the metabolome will help elucidate the pathogenesis of MetS and lead to better management. We hypothesize that the metabolites, gamma-aminobutyric acid (GABA), d-pyroglutamic acid (PGA) and N-acetyl-d-tryptophan (NAT) will be altered in nascent MetS patients without the confounding of ASCVD or T2DM. We also correlated these metabolites with biomarkers of inflammation.

PATIENTS AND METHODS

This was an exploratory study of 30 patients with nascent MetS and 20 matched controls undertaken in 2018. Metabolites were evaluated from patient's frozen early morning urine samples and were correlated with biomarkers of inflammation and adipokines. They were assayed by the NIH Western Metabolomics Center using liquid chromatography/mass spectrometry and standardized to urinary creatinine. All patients had normal hepatic and renal function.

RESULTS

GABA and PGA levels were significantly increased in MetS patients compared to controls: 2.8-fold and 2.9-fold median increases respectively with p < 0.0001 and p = 0.004, possibly deriving from glutamate. NAT was significantly decreased by 90% in MetS patients compared to controls, p < 0.001. GABA correlates significantly with cardio-metabolic (CM) features including WC, blood pressure systolic (BP-S) while NAT correlated inversely with WC, BP-S, blood glucose (BG) and triglycerides (TG). GABA correlated positively with chemerin, leptin, Fetuin A and endotoxin. NAT correlated inversely with WC, BP-S, BG, TG, high sensitivity C - reactive protein (hsCRP), toll-like receptor-4 (TLR-4), lipopolysaccharide binding protein (LBP), chemerin and retinol binding protein-4 (RBP-4).

CONCLUSIONS

We make the novel observation of increased GABA and PGA with decreased NAT in patients with MetS. While GABA and PGA correlates positively with CM features and biomediators of inflammation, the metabolite NAT correlated inversely. Thus, GABA and PGA could contribute to the pro-inflammatory state of MetS while NAT could mitigate this pro-inflammatory response.

Targeted metabolomics for the quantitative measurement of 9 gut microbiota-host co-metabolites in rat serum, urine and feces by liquid chromatography-tandem mass spectrometry

Gut microbiota-host co-metabolites play an essential role in maintaining homeostasis, and their concentration changes are closely related to a variety of diseases. Developing a targeted metabolomics analytical platform for these co-metabolites will help to elucidate the relationship between intestinal flora and host. Here we present a simple and sensitive liquid chromatography-tandem mass spectrometry method for the analysis of nine gut microbiota-host co-metabolites in rat serum, urine and feces. The compounds were separated on a reversed-phase C₁₈ column using gradient elution with a solvent system consisting of methanol and water (containing 0.05% formic acid) and a 7-min run time. All of the calibration curves exhibited good linear relationships (R² ≥ 0.9984, Percent Residual Accuracy ≥93.27%). The intra- and interday precision, expressed as relative standard deviation (RSD), was ≤ 14.84%. The accuracy was within 100 ± 13.16% for all analytes. The recovery of the nine compounds in biological samples was ≥ 85.80% with an appropriate RSD (≤12.04%). The validated method was successfully applied to monitor the global changes of these metabolites in obesity. Taken together, these results demonstrate that the method can simultaneously determine the nine co-metabolites in multiple biological matrices and is an essential part of the targeted metabolomics analytical platform, which may become an approach to evaluate the occurrence, development and therapeutic effects of metabolic diseases.

Quantification of phenolic acid metabolites in humans by LC-MS: a structural and targeted metabolomics approach

AIM

Co-metabolism between a human host and the gastrointestinal microbiota generates many small phenolic molecules such as 3-hydroxy-3-(3-hydroxyphenyl)propanoic acid (3,3-HPHPA), which are reported to be elevated in schizophrenia and autism. Characterization of these chemicals, however, has been limited by analytic challenges.

METHODOLOGY/RESULTS

We applied HPLC to separate and quantify over 50 analytes, including multiple structural isomers of 3,3-HPHPA in human cerebrospinal fluid, serum and urine. Confirmation of identity was provided by NMR, by MS and other detection methods. The highly selective methods support rapid quantification of multiple metabolites and exhibit superior chromatographic behavior.

CONCLUSION

An improved ultra-HPLC-MS/MS and structural approaches can accurately quantify 3,3-HPHPA and related analytes in human biological matrices.

The Intersection Between Colonization Resistance, Antimicrobial Stewardship, and Clostridium difficile

PURPOSE OF REVIEW

Colonization resistance refers to the innate defense provided by the indigenous microbiota against colonization by pathogenic organisms. We aim to describe how this line of defense is deployed against Clostridium difficile and what the implications are for interventions directed by Antimicrobial Stewardship Programs.

RECENT FINDINGS

The indigenous microbiota provides colonization resistance through depletion of nutrients, prevention of access to adherence sites within the gut mucosa, production of inhibitory substances, and stimulation of the host's immune system. The ability to quantify colonization resistance could provide information regarding periods of maximal vulnerability to colonization with pathogens and also allow the identification of mechanisms of restoration of colonization resistance. Methods utilized to determine the composition of the gut microbiota include sequencing technologies and measurement of concentration of specific bacterial metabolites. Use of innovations in the quantification of colonization resistance can expand the role of Antimicrobial Stewardship from prevention of disruption of the indigenous microbiota to restoration of colonization resistance.

Clostridium difficile Exposures, Colonization, and the Microbiome: Implications for Prevention

New studies have been published regarding the epidemiology of Clostridium difficile in topics such as asymptomatic C. difficile colonization, community-associated C. difficile infection, environmental contamination outside healthcare settings, animal colonization, and the interactions between C. difficile and the gut microbiome. In addition to summarizing these findings, this review offers a perspective on the potential impact of high-throughput sequencing and other potential techniques on the prevention of C. difficile.Infect Control Hosp Epidemiol 2018;39:596-602.