Metabolomics analysis identifies intestinal microbiota-derived biomarkers of colonization resistance in clindamycin-treated mice

The metabolomic signature of weight loss and remission in the Diabetes Remission Clinical Trial (DiRECT)

AIMS/HYPOTHESIS

High-throughput metabolomics technologies in a variety of study designs have demonstrated a consistent metabolomic signature of overweight and type 2 diabetes. However, the extent to which these metabolomic patterns can be reversed with weight loss and diabetes remission has been weakly investigated. We aimed to characterise the metabolomic consequences of a weight-loss intervention in individuals with type 2 diabetes.

METHODS

We analysed 574 fasted serum samples collected within an existing RCT (the Diabetes Remission Clinical Trial [DiRECT]) (N=298). In the trial, participating primary care practices were randomly assigned (1:1) to provide either a weight management programme (intervention) or best-practice care by guidelines (control) treatment to individuals with type 2 diabetes. Here, metabolomics analysis was performed on samples collected at baseline and 12 months using both untargeted MS and targeted 1H-NMR spectroscopy. Multivariable regression models were fitted to evaluate the effect of the intervention on metabolite levels.

RESULTS

Decreases in branched-chain amino acids, sugars and LDL triglycerides, and increases in sphingolipids, plasmalogens and metabolites related to fatty acid metabolism were associated with the intervention (Holm-corrected p<0.05). In individuals who lost more than 9 kg between baseline and 12 months, those who achieved diabetes remission saw greater reductions in glucose, fructose and mannose, compared with those who did not achieve remission.

CONCLUSIONS/INTERPRETATION

We have characterised the metabolomic effects of an integrated weight management programme previously shown to deliver weight loss and diabetes remission. A large proportion of the metabolome appears to be modifiable. Patterns of change were largely and strikingly opposite to perturbances previously documented with the development of type 2 diabetes.

DATA AVAILABILITY

The data used for analysis are available on a research data repository ( https://researchdata.gla.ac.uk/ ) with access given to researchers subject to appropriate data sharing agreements. Metabolite data preparation, data pre-processing, statistical analyses and figure generation were performed in R Studio v.1.0.143 using R v.4.0.2. The R code for this study has been made publicly available on GitHub at: https://github.com/lauracorbin/metabolomics_of_direct .

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Whey and Buttermilk-Based Formulas Modulate Gut Microbiota in Mice with Antibiotic-Induced Dysbiosis

SCOPE

Diet is one of the main factors that modifies intestinal microbiota composition. The search for foods that can reverse situations of intestinal dysbiosis such as that induced by antibiotics is of great interest. Buttermilk and whey are the main by-products produced by the dairy industry containing bioactive compounds. The aim of this study is to investigate the ability of whey and buttermilk-based formulas supplemented with lactoferrin and milk fat globule membrane (MFGM) to modulate the effects of clindamycin on mouse intestinal microbiota.

METHODS AND RESULTS

Male C57BL/6 mice are treated with saline (control), clindamycin (Clin), a formula containing whey (F1) or buttermilk (F2), Clin+F1 or Clin+F2, and their fecal microbiota profiles are analyzed by sequencing of 16S rRNA gene using the MinION device. Clin induces alterations in both the composition and metabolic functions of the mice intestinal microbiota. The treatment with F1 or F2 reverses the effects of clindamycin, restoring the levels of Rikenellaceae and Lactobacillaceae families and certain pathways related to short-chain fatty acids production and tetrahydrofolate biosynthesis.

CONCLUSION

Whey and buttermilk supplemented with lactoferrin and MFGM may be a bioactive formula for functional foods to prevent or restore microbiota alterations induced by antibiotic administration.

Effect of Maifan Stone on the Growth of Probiotics and Regulation of Gut Microbiota

Maifan stone is a kind of mineral medicine in Chinese medicine, which has good adsorption, dissolution, mineralization, and biological activity. It has an excellent therapeutic effect on livestock, poultry, and aquatic animals suffering from intestinal diseases. This study explored the effect of Maifan stone on the growth ability of Lacticaseibacillus rhamnosus GG (L. rhamnosus GG) and the effect of Maifan stone-L. rhamnosus GG fermented product on the intestinal inflammation and gut microbiota. We find that Maifan stone can adsorb L. rhamnosus GG to form a carrier bacteria. Maifan stone has the characteristics of acid tolerance and bile salt tolerance and can also improve the activity of L. rhamnosus GG in artificial gastrointestinal juice. The fermented product can reduce the degree of diarrhea and colon pathology in rats to a certain extent and significantly improve intestinal inflammatory factors and gut microbiota. This study improves the application effect of L. rhamnosus GG in the prevention and treatment of diarrhea animals and provide a scientific basis for the rational development of Maifan stone resources.

Gut associated metabolites and their roles in Clostridioides difficile pathogenesis

The nosocomial pathogen Clostridioides difficile is a burden to the healthcare system. Gut microbiome disruption, most commonly by broad-spectrum antibiotic treatment, is well established to generate a state that is susceptible to CDI. A variety of metabolites produced by the host and/or gut microbiota have been shown to interact with C. difficile. Certain bile acids promote/inhibit germination while other cholesterol-derived compounds and amino acids used in the Stickland metabolic pathway affect growth and CDI colonization. Short chain fatty acids maintain intestinal barrier integrity and a myriad of other metabolic compounds are used as nutritional sources or used by C. difficile to inhibit or outcompete other bacteria in the gut. As the move toward non-antibiotic CDI treatment takes place, a deeper understanding of interactions between C. difficile and the host's gut microbiome and metabolites becomes more relevant.

Adaptation of the gut pathobiont Enterococcus faecalis to deoxycholate and taurocholate bile acids

Enterococcus faecalis is a natural inhabitant of the human gastrointestinal tract. This bacterial species is subdominant in a healthy physiological state of the gut microbiota (eubiosis) in adults, but can become dominant and cause infections when the intestinal homeostasis is disrupted (dysbiosis). The relatively high concentrations of bile acids deoxycholate (DCA) and taurocholate (TCA) hallmark eubiosis and dysbiosis, respectively. This study aimed to better understand how E. faecalis adapts to DCA and TCA. We showed that DCA impairs E. faecalis growth and possibly imposes a continuous adjustment in the expression of many essential genes, including a majority of ribosomal proteins. This may account for slow growth and low levels of E. faecalis in the gut. In contrast, TCA had no detectable growth effect. The evolving transcriptome upon TCA adaptation showed the early activation of an oligopeptide permease system (opp2) followed by the adjustment of amino acid and nucleotide metabolisms. We provide evidence that TCA favors the exploitation of oligopeptide resources to fuel amino acid needs in limiting oligopeptide conditions. Altogether, our data suggest that the combined effects of decreased DCA and increased TCA concentrations can contribute to the rise of E. faecalis population during dysbiosis.

Impact of probiotic Limosilactobacillus reuteri DSM 17938 on amino acid metabolism in the healthy newborn mouse

We studied the effect of feeding a single probiotic Limosilactobacillus reuteri DSM 17938 (LR 17938) on the luminal and plasma levels of amino acids and their derivatives in the suckling newborn mouse, using gas chromatography and high-performance liquid chromatography. We found that LR 17938 increased the relative abundance of many amino acids and their derivatives in stool, while it simultaneously significantly reduced the plasma levels of three amino acids (serine, citrulline, and taurine). Many peptides and dipeptides were increased in stool and plasma, notably gamma-glutamyl derivatives of amino acids, following ingestion of the LR 17938. Gamma-glutamyl transformation of amino acids facilitates their absorption. LR 17938 significantly upregulated N-acetylated amino acids, the levels of which could be useful biomarkers in plasma and warrant further investigation. Specific fecal microbiota were associated with higher levels of fecal amino acids and their derivatives. Changes in luminal and circulating levels of amino acid derivatives, polyamines, and tryptophan metabolites may be mechanistically related to probiotic efficacy.

Impact of antibiotics on the human microbiome and consequences for host health

It is well established that the gut microbiota plays an important role in host health and is perturbed by several factors including antibiotics. Antibiotic-induced changes in microbial composition can have a negative impact on host health including reduced microbial diversity, changes in functional attributes of the microbiota, formation, and selection of antibiotic-resistant strains making hosts more susceptible to infection with pathogens such as Clostridioides difficile. Antibiotic resistance is a global crisis and the increased use of antibiotics over time warrants investigation into its effects on microbiota and health. In this review, we discuss the adverse effects of antibiotics on the gut microbiota and thus host health, and suggest alternative approaches to antibiotic use.

Xanthine oxidase inhibitor urate-lowering therapy titration to target decreases serum free fatty acids in gout and suppresses lipolysis by adipocytes

OBJECTIVE

Linked metabolic and cardiovascular comorbidities are prevalent in hyperuricemia and gout. For mechanistic insight into impact on inflammatory processes and cardiometabolic risk factors of xanthine oxidase inhibitor urate-lowering therapy (ULT) titration to target, we performed a prospective study of gout serum metabolomes from a ULT trial.

METHODS

Sera of gout patients meeting the 2015 ACR/EULAR gout classification criteria (n = 20) and with hyperuricemia were studied at time zero and weeks 12 and 24 of febuxostat or allopurinol dose titration ULT. Ultrahigh performance liquid chromatography-tandem mass spectroscopy acquired the serum spectra. Data were assessed using the Metabolon and Metaboloanalyst software. Lipolysis validation assays were done in febuxostat and/or colchicine-treated 3T3-L1 differentiated adipocytes.

RESULTS

Serum urate decreased from time zero (8.21 ±1.139 SD) at weeks 12 (5.965 ± 1.734 SD) and 24 (5.655 ±1.763 SD). Top metabolites generated by changes in nucleotide and certain amino acid metabolism and polyamine pathways were enriched at 12 and 24 weeks ULT, respectively. Decreases in multiple fatty acid metabolites were observed at 24 weeks, linked with obesity. In cultured adipocytes, febuxostat significantly decreased while colchicine increased the lipolytic response to β-adrenergic-agonism or TNF.

CONCLUSION

Metabolomic profiles linked xanthine oxidase inhibitor-based ULT titration to target with reduced serum free fatty acids. In vitro validation studies revealed that febuxostat, but not colchicine, reduced lipolysis in cultured adipocytes. Since soluble urate, xanthine oxidase inhibitor treatment, and free fatty acids modulate inflammation, our findings suggest that by suppressing lipolysis, ULT could regulate inflammation in gout and comorbid metabolic and cardiovascular disease.

An Osmotic Laxative Renders Mice Susceptible to Prolonged Clostridioides difficile Colonization and Hinders Clearance

Antibiotics are a major risk factor for Clostridioides difficile infections (CDIs) because of their impact on the microbiota. However, nonantibiotic medications such as the ubiquitous osmotic laxative polyethylene glycol 3350 (PEG 3350) also alter the microbiota. Clinicians also hypothesize that PEG helps clear C. difficile. But whether PEG impacts CDI susceptibility and clearance is unclear. To examine how PEG impacts susceptibility, we treated C57BL/6 mice with 5-day and 1-day doses of 15% PEG in the drinking water and then challenged the mice with C. difficile 630. We used clindamycin-treated mice as a control because they consistently clear C. difficile within 10 days postchallenge. PEG treatment alone was sufficient to render mice susceptible, and 5-day PEG-treated mice remained colonized for up to 30 days postchallenge. In contrast, 1-day PEG-treated mice were transiently colonized, clearing C. difficile within 7 days postchallenge. To examine how PEG treatment impacts clearance, we administered a 1-day PEG treatment to clindamycin-treated, C. difficile-challenged mice. Administering PEG to mice after C. difficile challenge prolonged colonization up to 30 days postchallenge. When we trained a random forest model with community data from 5 days postchallenge, we were able to predict which mice would exhibit prolonged colonization (area under the receiver operating characteristic curve [AUROC] = 0.90). Examining the dynamics of these bacterial populations during the postchallenge period revealed patterns in the relative abundances of Bacteroides, Enterobacteriaceae, Porphyromonadaceae, Lachnospiraceae, and Akkermansia that were associated with prolonged C. difficile colonization in PEG-treated mice. Thus, the osmotic laxative PEG rendered mice susceptible to C. difficile colonization and hindered clearance.

IMPORTANCE Diarrheal samples from patients taking laxatives are typically rejected for Clostridioides difficile testing. However, there are similarities between the bacterial communities from people with diarrhea and those with C. difficile infections (CDIs), including lower diversity than the communities from healthy patients. This observation led us to hypothesize that diarrhea may be an indicator of C. difficile susceptibility. We explored how osmotic laxatives disrupt the microbiota’s colonization resistance to C. difficile by administering a laxative to mice either before or after C. difficile challenge. Our findings suggest that osmotic laxatives disrupt colonization resistance to C. difficile and prevent clearance among mice already colonized with C. difficile. Considering that most hospitals recommend not performing C. difficile testing on patients taking laxatives, and laxatives are prescribed prior to administering fecal microbiota transplants via colonoscopy to patients with recurrent CDIs, further studies are needed to evaluate if laxatives impact microbiota colonization resistance in humans.

Functional characterization of a gene cluster responsible for inositol catabolism associated with hospital-adapted isolates of Enterococcus faecium

Enterococcus faecium is a nosocomial, multidrug-resistant pathogen. Whole genome sequence studies revealed that hospital-associated E. faecium isolates are clustered in a separate clade A1. Here, we investigated the distribution, integration site and function of a putative iol gene cluster that encodes for myo-inositol (MI) catabolism. This iol gene cluster was found as part of an ~20 kbp genetic element (iol element), integrated in ICEEfm1 close to its integrase gene in E. faecium isolate E1679. Among 1644 E. faecium isolates, ICEEfm1 was found in 789/1227 (64.3 %) clade A1 and 3/417 (0.7 %) non-clade A1 isolates. The iol element was present at a similar integration site in 180/792 (22.7 %) ICEEfm1-containing isolates. Examination of the phylogenetic tree revealed genetically closely related isolates that differed in presence/absence of ICEEfm1 and/or iol element, suggesting either independent acquisition or loss of both elements. E. faecium iol gene cluster containing isolates E1679 and E1504 were able to grow in minimal medium with only myo-inositol as carbon source, while the iolD-deficient mutant in E1504 (E1504∆iolD) lost this ability and an iol gene cluster negative recipient strain gained this ability after acquisition of ICEEfm1 by conjugation from donor strain E1679. Gene expression profiling revealed that the iol gene cluster is only expressed in the absence of other carbon sources. In an intestinal colonization mouse model the colonization ability of E1504∆iolD mutant was not affected relative to the wild-type E1504 strain. In conclusion, we describe and functionally characterise a gene cluster involved in MI catabolism that is associated with the ICEEfm1 island in hospital-associated E. faecium isolates. We were unable to show that this gene cluster provides a competitive advantage during gut colonisation in a mouse model. Therefore, to what extent this gene cluster contributes to the spread and ecological specialisation of ICEEfm1-carrying hospital-associated isolates remains to be investigated.

Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study

BACKGROUND

Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD.

METHODS

To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns.

RESULTS

Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%-100%) and 71.7% (range, 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%-26%; ibuprofen, 10%-18%).

CONCLUSIONS

This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.

Dysregulated metabolism and behaviors by disrupting gut microbiota in prenatal and neonatal mice

The live microbiota ecosystem in the intestine plays a critical role in maintaining the normal physiological and psychological functions in both animals and human beings. However, the chronic effect of microbiota disturbances during prenatal and neonatal developing periods on animal's health remains less studied. In the current study, pregnant ICR mice were fed with an antibiotic diet (7-g nebacitin [bacitracin-neomycin sulphate 2:1]/kg standard diet) from day 14 of conception, and their offspring were provided with the same diet till the termination of the experiments. Dams treated with antibiotics showed increased body weight along with enlarged gut. Antibiotic-treated offspring revealed decreased bodyweight, increased food, water, and sucrose intake. Administration of antibiotics affected corticosterone responsivity to acute 20 min restraint challenge in male pups. In behavior tests, female pups showed decreased movement in open field while male pups revealed decreased latency to open arms in elevated plus maze test and immobility time in tail suspension test. Together, these results suggested that early antibiotic exposure may impact on the food intake, body weight gain, and emotional behavior regulation in mice.

Gut microbiome variation modulates the effects of dietary fiber on host metabolism

BACKGROUND

There is general consensus that consumption of dietary fermentable fiber improves cardiometabolic health, in part by promoting mutualistic microbes and by increasing production of beneficial metabolites in the distal gut. However, human studies have reported variations in the observed benefits among individuals consuming the same fiber. Several factors likely contribute to this variation, including host genetic and gut microbial differences. We hypothesized that gut microbial metabolism of dietary fiber represents an important and differential factor that modulates how dietary fiber impacts the host.

RESULTS

We examined genetically identical gnotobiotic mice harboring two distinct complex gut microbial communities and exposed to four isocaloric diets, each containing different fibers: (i) cellulose, (ii) inulin, (iii) pectin, (iv) a mix of 5 fermentable fibers (assorted fiber). Gut microbiome analysis showed that each transplanted community preserved a core of common taxa across diets that differentiated it from the other community, but there were variations in richness and bacterial taxa abundance within each community among the different diet treatments. Host epigenetic, transcriptional, and metabolomic analyses revealed diet-directed differences between animals colonized with the two communities, including variation in amino acids and lipid pathways that were associated with divergent health outcomes.

CONCLUSION

This study demonstrates that interindividual variation in the gut microbiome is causally linked to differential effects of dietary fiber on host metabolic phenotypes and suggests that a one-fits-all fiber supplementation approach to promote health is unlikely to elicit consistent effects across individuals. Overall, the presented results underscore the importance of microbe-diet interactions on host metabolism and suggest that gut microbes modulate dietary fiber efficacy. Video abstract.

The Multiomics Analyses of Fecal Matrix and Its Significance to Coeliac Disease Gut Profiling

Gastrointestinal (GIT) diseases have risen globally in recent years, and early detection of the host’s gut microbiota, typically through fecal material, has become a crucial component for rapid diagnosis of such diseases. Human fecal material is a complex substance composed of undigested macromolecules and particles, and the processing of such matter is a challenge due to the unstable nature of its products and the complexity of the matrix. The identification of these products can be used as an indication for present and future diseases; however, many researchers focus on one variable or marker looking for specific biomarkers of disease. Therefore, the combination of genomics, transcriptomics, proteomics and metabonomics can give a detailed and complete insight into the gut environment. The proper sample collection, sample preparation and accurate analytical methods play a crucial role in generating precise microbial data and hypotheses in gut microbiome research, as well as multivariate data analysis in determining the gut microbiome functionality in regard to diseases. This review summarizes fecal sample protocols involved in profiling coeliac disease.

Changes in the Serum Metabolome of Patients Treated With Broad-Spectrum Antibiotics

Background:

The gut microbiome (GMB) generates numerous small chemicals that can be absorbed by the host and variously biotransformed, incorporated, or excreted. The resulting metabolome can provide information about the state of the GMB, of the host, and of their relationship. Exploiting this information in the service of biomarker development is contingent on knowing the GMB-sensitivity of the individual chemicals comprising the metabolome. In this regard, human studies have lagged far behind animal studies. Accordingly, we tested the hypothesis that serum levels of chemicals unequivocally demonstrated to be GMB-sensitive in rodent models would also be affected in a clinical patient sample treated with broad spectrum antibiotics.

Methods:

We collected serum samples from 20 hospitalized patients before, during, and after treatment with broad-spectrum antibiotics. We also collected samples from 5 control patients admitted to the hospital but not prescribed antibiotics. We submitted the samples for a non-targeted metabolomic analysis and then focused on chemicals known to be affected both by germ-free status and by antibiotic treatment in the mouse and/or rat.

Results:

Putative identification was obtained for 499 chemicals in human serum. An aggregate analysis did not show any time x treatment interactions. However, our literature search identified 10 serum chemicals affected both by germ-free status and antibiotic treatment in the mouse or rat. Six of those chemicals were measured in our patient samples and additionally met criteria for inclusion in a focused analysis. Serum levels of 5 chemicals (p-cresol sulfate, phenol sulfate, hippurate, indole propionate, and indoxyl sulfate) declined significantly in our group of antibiotic-treated patients but did not change in our patient control group.

Conclusions:

Broad-spectrum antibiotic treatment in patients lowered serum levels of selected chemicals previously demonstrated to be GMB-sensitive in rodent models. Interestingly, all those chemicals are known to be uremic solutes that can be derived from aromatic amino acids (L-phenylalanine, L-tyrosine, or L-tryptophan) by anaerobic bacteria, particularly Clostridial species. We conclude that judiciously selected serum chemicals can reliably detect antibiotic-induced suppression of the GMB in man and thus facilitate further metabolome-based biomarker development.

The Initial Gut Microbiota and Response to Antibiotic Perturbation Influence Clostridioides difficile Clearance in Mice

Clostridioides difficile is a leading nosocomial infection. Although perturbation to the gut microbiota is an established risk, there is variation in who becomes asymptomatically colonized, develops an infection, or has adverse infection outcomes. Mouse models of C. difficile infection (CDI) are widely used to answer a variety of C. difficile pathogenesis questions. However, the interindividual variation between mice from the same breeding facility is less than what is observed in humans. Therefore, we challenged mice from 6 different breeding colonies with C. difficile. We found that the starting microbial community structures and C. difficile persistence varied by the source of mice. Interestingly, a subset of the bacteria that varied across sources were associated with how long C. difficile was able to colonize. By increasing the interindividual diversity of the starting communities, we were able to better model human diversity. This provided a more nuanced perspective of C. difficile pathogenesis.

The gut microbiota has a key role in determining susceptibility to Clostridioides difficile infections (CDIs). However, much of the mechanistic work examining CDIs in mouse models uses animals obtained from a single source. We treated mice from 6 sources (2 University of Michigan colonies and 4 commercial vendors) with clindamycin, followed by a C. difficile challenge, and then measured C. difficile colonization levels throughout the infection. The microbiota were profiled via 16S rRNA gene sequencing to examine the variation across sources and alterations due to clindamycin treatment and C. difficile challenge. While all mice were colonized 1 day postinfection, variation emerged from days 3 to 7 postinfection with animals from some sources colonized with C. difficile for longer and at higher levels. We identified bacteria that varied in relative abundance across sources and throughout the experiment. Some bacteria were consistently impacted by clindamycin treatment in all sources of mice, including Lachnospiraceae, Ruminococcaceae, and Enterobacteriaceae. To identify bacteria that were most important to colonization regardless of the source, we created logistic regression models that successfully classified mice based on whether they cleared C. difficile by 7 days postinfection using community composition data at baseline, post-clindamycin treatment, and 1 day postinfection. With these models, we identified 4 bacterial taxa that were predictive of whether C. difficile cleared. They varied across sources (Bacteroides) or were altered by clindamycin (Porphyromonadaceae) or both (Enterobacteriaceae and Enterococcus). Allowing for microbiota variation across sources better emulates human interindividual variation and can help identify bacterial drivers of phenotypic variation in the context of CDIs.

IMPORTANCEClostridioides difficile is a leading nosocomial infection. Although perturbation to the gut microbiota is an established risk, there is variation in who becomes asymptomatically colonized, develops an infection, or has adverse infection outcomes. Mouse models of C. difficile infection (CDI) are widely used to answer a variety of C. difficile pathogenesis questions. However, the interindividual variation between mice from the same breeding facility is less than what is observed in humans. Therefore, we challenged mice from 6 different breeding colonies with C. difficile. We found that the starting microbial community structures and C. difficile persistence varied by the source of mice. Interestingly, a subset of the bacteria that varied across sources were associated with how long C. difficile was able to colonize. By increasing the interindividual diversity of the starting communities, we were able to better model human diversity. This provided a more nuanced perspective of C. difficile pathogenesis.

Evaluating Organism-Wide Changes in the Metabolome and Microbiome following a Single Dose of Antibiotic

We are just beginning to understand the unintended effects of antibiotics on our microbiomes and health. In this study, we aimed to define an approach by which one could obtain a comprehensive picture of (i) how antibiotics spatiotemporally impact commensal microbes throughout the gut and (ii) how these changes influence host chemistry throughout the body. We found that just a single dose of antibiotic altered host chemistry in a variety of organs and that microbiome alterations were not uniform throughout the gut. As technological advances increase the feasibility of whole-organism studies, we argue that using these approaches can provide further insight on both the wide-ranging effects of antibiotics on health and how to restore microbial communities to mitigate these effects.

Antibiotics are a mainstay of modern medicine, but as they kill their target pathogen(s), they often affect the commensal microbiota. Antibiotic-induced microbiome dysbiosis is a growing research focus and health concern, often assessed via analysis of fecal samples. However, such analysis does not inform how antibiotics influence the microbiome across the whole host or how such changes subsequently alter host chemistry. In this study, we investigated the acute (1 day postadministration) and delayed (6 days postadministration) effects of a single parenteral dose of two common antibiotics, ampicillin or vancomycin, on the global metabolome and microbiome of mice across 77 different body sites from 25 different organs. The broader-spectrum agent ampicillin had the greatest impact on the microbiota in the lower gastrointestinal tract (cecum and colon), where microbial diversity is highest. In the metabolome, the greatest effects were seen 1 day posttreatment, and changes in metabolite abundances were not confined to the gut. The local abundance of ampicillin and its metabolites correlated with increased metabolome effect size and a loss of alpha diversity versus control mice. Additionally, small peptides were elevated in the lower gastrointestinal tract of mice 1 day after antibiotic treatment. While a single parenteral dose of antibiotic did not drastically alter the microbiome, nevertheless, changes in the metabolome were observed both within and outside the gut. This study provides a framework for how whole-organism -omics approaches can be employed to understand the impact of antibiotics on the entire host.

IMPORTANCE We are just beginning to understand the unintended effects of antibiotics on our microbiomes and health. In this study, we aimed to define an approach by which one could obtain a comprehensive picture of (i) how antibiotics spatiotemporally impact commensal microbes throughout the gut and (ii) how these changes influence host chemistry throughout the body. We found that just a single dose of antibiotic altered host chemistry in a variety of organs and that microbiome alterations were not uniform throughout the gut. As technological advances increase the feasibility of whole-organism studies, we argue that using these approaches can provide further insight on both the wide-ranging effects of antibiotics on health and how to restore microbial communities to mitigate these effects.

Antibiotics Effects on the Fecal Metabolome in Preterm Infants

Within a randomized prospective pilot study of preterm infants born at less than 33 weeks' gestation, weekly fecal samples from 19 infants were collected and metabolomic analysis was performed. The objective was to evaluate for differences in fecal metabolites in infants exposed to antibiotics vs. not exposed to antibiotics in the first 48 h after birth. Metabolomics analysis was performed on 123 stool samples. Significant differences were seen in the antibiotics vs. no antibiotics groups, including pathways related to vitamin biosynthesis, bile acids, amino acid metabolism, and neurotransmitters. Early antibiotic exposure in preterm infants may alter metabolites in the intestinal tract of preterm infants. Broader multi-omic studies that address mechanisms will guide more prudent antibiotic use in this population.

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.

Commensal-derived metabolites govern Vibrio cholerae pathogenesis in host intestine

BACKGROUND

Recent evidence suggests that the commensal microbes act as a barrier against invading pathogens and enteric infections are the consequences of multi-layered interactions among commensals, pathogens, and the host intestinal tissue. However, it remains unclear how perturbations of the gut microbiota compromise host infection resistance, especially through changes at species and metabolite levels.

RESULTS

Here, we illustrate how Bacteroides vulgatus, a dominant species of the Bacteroidetes phylum in mouse intestine, suppresses infection by Vibrio cholerae, an important human pathogen. Clindamycin (CL) is an antibiotic that selectively kills anaerobic bacteria, and accordingly Bacteroidetes are completely eradicated from CL-treated mouse intestines. The Bacteroidetes-depleted adult mice developed severe cholera-like symptoms, when infected with V. cholerae. Germ-free mice mono-associated with B. vulgatus became resistant to V. cholerae infection. Levels of V. cholerae growth-inhibitory metabolites including short-chain fatty acids plummeted upon CL treatment, while levels of compounds that enhance V. cholerae proliferation were elevated. Furthermore, the intestinal colonization process of V. cholerae was well-simulated in CL-treated adult mice.

CONCLUSIONS

Overall, we provide insights into how a symbiotic microbe and a pathogenic intruder interact inside host intestine. We identified B. vulgatus as an indigenous microbial species that can suppress intestinal infection. Our results also demonstrate that commensal-derived metabolites are a critical determinant for host resistance against V. cholerae infection, and that CL pretreatment of adult mice generates a simple yet useful model of cholera infection.

Ozone-induced changes in the serum metabolome: Role of the microbiome

Ozone is an asthma trigger. In mice, the gut microbiome contributes to ozone-induced airway hyperresponsiveness, a defining feature of asthma, but the mechanistic basis for the role of the gut microbiome has not been established. Gut bacteria can affect the function of distal organs by generating metabolites that enter the blood and circulate systemically. We hypothesized that global metabolomic profiling of serum collected from ozone exposed mice could be used to identify metabolites contributing to the role of the microbiome in ozone-induced airway hyperresponsiveness. Mice were treated for two weeks with a cocktail of antibiotics (ampicillin, neomycin, metronidazole, and vancomycin) in the drinking water or with control water and then exposed to air or ozone (2 ppm for 3 hours). Twenty four hours later, blood was harvested and serum analyzed via liquid-chromatography or gas-chromatography coupled to mass spectrometry. Antibiotic treatment significantly affected 228 of the 562 biochemicals identified, including reductions in the known bacterially-derived metabolites, equol, indole propionate, 3-indoxyl sulfate, and 3-(4-hydroxyphenyl)propionate, confirming the efficacy of the antibiotic treatment. Ozone exposure caused significant changes in 334 metabolites. Importantly, ozone-induced changes in many of these metabolites were different in control and antibiotic-treated mice. For example, most medium and long chain fatty acids declined by 20-50% with ozone exposure in antibiotic-treated but not control mice. Most taurine-conjugated bile acids increased with ozone exposure in antibiotic-treated but not control mice. Ozone also caused marked (9-fold and 5-fold) increases in the polyamines, spermine and spermidine, respectively, in control but not antibiotic-treated mice. Each of these metabolites has the capacity to alter airway responsiveness and may account for the role of the microbiome in pulmonary responses to ozone.

Clostridium difficile Infection Risk with Important Antibiotic Classes: An Analysis of the FDA Adverse Event Reporting System

Introduction: Antibiotic use is an important risk factor for Clostridium difficile infection (CDI). Prior meta-analyses have identified antibiotics and antibiotic classes that pose the greatest risk for CDI; however, CDI epidemiology is constantly changing and contemporary analyses are needed. Objectives: The objective of this study was to evaluate the association between CDI and important antibiotic classes in recent years using the FDA Adverse Event Report System (FAERS). Methods: FAERS reports from January 1, 2015 to December 31, 2017 were analyzed. The Medical Dictionary for Regulatory Activities (MedDRA) was used to identify CDI cases. We computed the Reporting Odds Ratios (RORs) and corresponding 95% confidence intervals (95%CI) for the association between antibiotics and CDI. An association was considered statistically significant when the lower limit of the 95%CI was greater than 1. Results: A total of 2,042,801 reports (including 5,187 CDI reports) were considered, after inclusion criteria were applied. Lincosamides (e.g., clindamycin) had the greatest proportion of CDI reports, representing 10.4% of all lincosamide reports. CDI RORs (95%CI) for the antibiotic classes were (in descending order): lincosamides 46.95 (39.49-55.82), monobactams 29.97 (14.60-61.54), penicillin combinations 20.05 (17.39-23.12), carbapenems 19.16 (15.52-23.67), cephalosporins/ monobactams/carbapenems 17.28 (14.95-19.97), cephalosporins 15.33 (12.60-18.65), tetracyclines 7.54 (5.42-10.50), macrolides 5.80 (4.48-7.51), fluoroquinolones 4.94 (4.20-5.81), and trimethoprim-sulfonamides 3.32 (2.03-5.43). Conclusion: All antibiotic classes included in the study were significantly associated with CDI. Lincosamides (e.g., clindamycin) had the highest CDI ROR among the antibiotics evaluated in this study.

A non-targeted LC-HRMS approach for detecting exposure to illegal veterinary treatments: The case of cephalosporins in commercial laying Hens

Cephalosporins are of particular importance in human medicine and should be reserved for second-line curative treatment in the veterinary field to avoid any emerging antimicrobial resistance. Due to misuse of ceftiofur in the poultry sector in France, it is now recommended to completely stop using cephalosporins in this sector. Methods currently used for the control of veterinary practices are mostly based on liquid chromatography coupled to mass spectrometry in a targeted mode, including parent compounds and any major metabolites. The aim of the present study was to evaluate the relevance of untargeted metabolomic approaches to highlight a possible exposure of laying hens to cephalosporins using a predictive model including selected treatment biomarkers. An experimentation carried out on living animals involved the administration of cefquinome and ceftiofur. Three biological matrices-droppings, eggs and liver-were investigated. Metabolites were extracted and analysed by liquid chromatography coupled to high resolution mass spectrometry in a full scan mode. Metabolites impacted by the treatment were selected by using univariate and multivariate statistical analyses. Predictive models built from the potential biomarkers selected in the "droppings" matrix were validated and able to classify "treated" and "control" hens. PLS-DA and logistic regression models were compared and both models gave satisfactory results in terms of prediction. Results were of less interest for other matrices in which only biomarkers of exposure to cefquinome were detected.

Targeted UPLC-MS Metabolic Analysis of Human Faeces Reveals Novel Low-Invasive Candidate Markers for Colorectal Cancer

Low invasive tests with high sensitivity for colorectal cancer and advanced precancerous lesions will increase adherence rates, and improve clinical outcomes. We have performed an ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-(TOF) MS)-based metabolomics study to identify faecal biomarkers for the detection of patients with advanced neoplasia. A cohort of 80 patients with advanced neoplasia (40 advanced adenomas and 40 colorectal cancers) and 49 healthy subjects were analysed in the study. We evaluated the faecal levels of 105 metabolites including glycerolipids, glycerophospholipids, sterol lipids and sphingolipids. We found 18 metabolites that were significantly altered in patients with advanced neoplasia compared to controls. The combinations of seven metabolites including ChoE(18:1), ChoE(18:2), ChoE(20:4), PE(16:0/18:1), SM(d18:1/23:0), SM(42:3) and TG(54:1), discriminated advanced neoplasia patients from healthy controls. These seven metabolites were employed to construct a predictive model that provides an area under the curve (AUC) median value of 0.821. The inclusion of faecal haemoglobin concentration in the metabolomics signature improved the predictive model to an AUC of 0.885. In silico gene expression analysis of tumour tissue supports our results and puts the differentially expressed metabolites into biological context, showing that glycerolipids and sphingolipids metabolism and GPI-anchor biosynthesis pathways may play a role in tumour progression.

Clostridium difficile Alters the Structure and Metabolism of Distinct Cecal Microbiomes during Initial Infection To Promote Sustained Colonization

Susceptibility to Clostridium difficile infection (CDI) is primarily associated with previous exposure to antibiotics, which compromise the structure and function of the gut bacterial community. Specific antibiotic classes correlate more strongly with recurrent or persistent C. difficile infection. As such, we utilized a mouse model of infection to explore the effect of distinct antibiotic classes on the impact that infection has on community-level transcription and metabolic signatures shortly following pathogen colonization and how those changes may associate with persistence of C. difficile Untargeted metabolomic analysis revealed that C. difficile infection had significantly larger impacts on the metabolic environment across cefoperazone- and streptomycin-pretreated mice, which became persistently colonized compared to clindamycin-pretreated mice, where infection quickly became undetectable. Through metagenome-enabled metatranscriptomics, we observed that transcripts for genes associated with carbon and energy acquisition were greatly reduced in infected animals, suggesting that those niches were instead occupied by C. difficile Furthermore, the largest changes in transcription were seen in the least abundant species, indicating that C. difficile may "attack the loser" in gut environments where sustained infection occurs more readily. Overall, our results suggest that C. difficile is able to restructure the nutrient-niche landscape in the gut to promote persistent infection.IMPORTANCEClostridium difficile has become the most common single cause of hospital-acquired infection over the last decade in the United States. Colonization resistance to the nosocomial pathogen is primarily provided by the gut microbiota, which is also involved in clearing the infection as the community recovers from perturbation. As distinct antibiotics are associated with different risk levels for CDI, we utilized a mouse model of infection with 3 separate antibiotic pretreatment regimens to generate alternative gut microbiomes that each allowed for C. difficile colonization but varied in clearance rate. To assess community-level dynamics, we implemented an integrative multi-omics approach that revealed that infection significantly changed many aspects of the gut community. The degree to which the community changed was inversely correlated with clearance during the first 6 days of infection, suggesting that C. difficile differentially modifies the gut environment to promote persistence. This is the first time that metagenome-enabled metatranscriptomics have been employed to study the behavior of a host-associated microbiota in response to an infection. Our results allow for a previously unseen understanding of the ecology associated with C. difficile infection and provide the groundwork for identification of context-specific probiotic therapies.

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.

Anaerobic 4-hydroxyproline utilization: Discovery of a new glycyl radical enzyme in the human gut microbiome uncovers a widespread microbial metabolic activity

The discovery of enzymes responsible for previously unappreciated microbial metabolic pathways furthers our understanding of host-microbe and microbe-microbe interactions. We recently identified and characterized a new gut microbial glycyl radical enzyme (GRE) responsible for anaerobic metabolism of trans-4-hydroxy-l-proline (Hyp). Hyp dehydratase (HypD) catalyzes the removal of water from Hyp to generate Δ¹-pyrroline-5-carboxylate (P5C). This enzyme is encoded in the genomes of a diverse set of gut anaerobes and is prevalent and abundant in healthy human stool metagenomes. Here, we discuss the roles HypD may play in different microbial metabolic pathways as well as the potential implications of this activity for colonization resistance and pathogenesis within the human gut. Finally, we present evidence of anaerobic Hyp metabolism in sediments through enrichment culturing of Hyp-degrading bacteria, highlighting the wide distribution of this pathway in anoxic environments beyond the human gut.

Engineering chemical interactions in microbial communities

Microbes living within host-associated microbial communities (microbiotas) rely on chemical communication to interact with surrounding organisms. These interactions serve many purposes, from supplying the multicellular host with nutrients to antagonizing invading pathogens, and breakdown of chemical signaling has potentially negative consequences for both the host and microbiota. Efforts to engineer microbes to take part in chemical interactions represent a promising strategy for modulating chemical signaling within these complex communities. In this review, we discuss prominent examples of chemical interactions found within host-associated microbial communities, with an emphasis on the plant-root microbiota and the intestinal microbiota of animals. We then highlight how an understanding of such interactions has guided efforts to engineer microbes to participate in chemical signaling in these habitats. We discuss engineering efforts in the context of chemical interactions that enable host colonization, promote host health, and exclude pathogens. Finally, we describe prominent challenges facing this field and propose new directions for future engineering efforts.

Shifts in the Gut Metabolome and Clostridium difficile Transcriptome throughout Colonization and Infection in a Mouse Model

Clostridium difficile is a bacterial pathogen of global significance that is a major cause of antibiotic-associated diarrhea. Antibiotics deplete the indigenous gut microbiota and change the metabolic environment in the gut to one favoring C. difficile growth. Here we used metabolomics and transcriptomics to define the gut environment after antibiotics and during the initial stages of C. difficile colonization and infection. We show that amino acids, in particular, proline and branched-chain amino acids, and carbohydrates decrease in abundance over time and that C. difficile gene expression is consistent with their utilization by the bacterium in vivo. We employed an integrated approach to analyze the metabolome and transcriptome to identify associations between metabolites and transcripts. This highlighted the importance of key nutrients in the early stages of colonization, and the data provide a rationale for the development of therapies based on the use of bacteria that specifically compete for nutrients that are essential for C. difficile colonization and disease.

Antibiotics alter the gut microbiota and decrease resistance to Clostridium difficile colonization; however, the mechanisms driving colonization resistance are not well understood. Loss of resistance to C. difficile colonization due to antibiotic treatment is associated with alterations in the gut metabolome, specifically, with increases in levels of nutrients that C. difficile can utilize for growth in vitro. To define the nutrients that C. difficile requires for colonization and pathogenesis in vivo, we used a combination of mass spectrometry and RNA sequencing (RNA Seq) to model the gut metabolome and C. difficile transcriptome throughout an acute infection in a mouse model at the following time points: 0, 12, 24, and 30 h. We also performed multivariate-based integration of the omics data to define the signatures that were most important throughout colonization and infection. Here we show that amino acids, in particular, proline and branched-chain amino acids, and carbohydrates decrease in abundance over time in the mouse cecum and that C. difficile gene expression is consistent with their utilization in vivo. This was also reinforced by the multivariate-based integration of the omics data where we were able to discriminate the metabolites and transcripts that support C. difficile physiology between the different time points throughout colonization and infection. This report illustrates how important the availability of amino acids and other nutrients is for the initial stages of C. difficile colonization and progression of disease. Future studies identifying the source of the nutrients and engineering bacteria capable of outcompeting C. difficile in the gut will be important for developing new targeted bacterial therapeutics.

IMPORTANCEClostridium difficile is a bacterial pathogen of global significance that is a major cause of antibiotic-associated diarrhea. Antibiotics deplete the indigenous gut microbiota and change the metabolic environment in the gut to one favoring C. difficile growth. Here we used metabolomics and transcriptomics to define the gut environment after antibiotics and during the initial stages of C. difficile colonization and infection. We show that amino acids, in particular, proline and branched-chain amino acids, and carbohydrates decrease in abundance over time and that C. difficile gene expression is consistent with their utilization by the bacterium in vivo. We employed an integrated approach to analyze the metabolome and transcriptome to identify associations between metabolites and transcripts. This highlighted the importance of key nutrients in the early stages of colonization, and the data provide a rationale for the development of therapies based on the use of bacteria that specifically compete for nutrients that are essential for C. difficile colonization and disease.

Lactobacillus paracasei CNCM I-3689 reduces vancomycin-resistant Enterococcus persistence and promotes Bacteroidetes resilience in the gut following antibiotic challenge

Enterococci, in particular vancomycin-resistant enterococci (VRE), are a leading cause of hospital-acquired infections. Promoting intestinal resistance against enterococci could reduce the risk of VRE infections. We investigated the effects of two Lactobacillus strains to prevent intestinal VRE. We used an intestinal colonisation mouse model based on an antibiotic-induced microbiota dysbiosis to mimic enterococci overgrowth and VRE persistence. Each Lactobacillus spp. was administered daily to mice starting one week before antibiotic treatment until two weeks after antibiotic and VRE inoculation. Of the two strains, Lactobacillus paracasei CNCM I-3689 decreased significantly VRE numbers in the feces demonstrating an improvement of the reduction of VRE. Longitudinal microbiota analysis showed that supplementation with L. paracasei CNCM I-3689 was associated with a better recovery of members of the phylum Bacteroidetes. Bile salt analysis and expression analysis of selected host genes revealed increased level of lithocholate and of ileal expression of camp (human LL-37) upon L. paracasei CNCM I-3689 supplementation. Although a direct effect of L. paracasei CNCM I-3689 on the VRE reduction was not ruled out, our data provide clues to possible anti-VRE mechanisms supporting an indirect anti-VRE effect through the gut microbiota. This work sustains non-antibiotic strategies against opportunistic enterococci after antibiotic-induced dysbiosis.

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.

BURRITO: An Interactive Multi-Omic Tool for Visualizing Taxa-Function Relationships in Microbiome Data

The abundance of both taxonomic groups and gene categories in microbiome samples can now be easily assayed via various sequencing technologies, and visualized using a variety of software tools. However, the assemblage of taxa in the microbiome and its gene content are clearly linked, and tools for visualizing the relationship between these two facets of microbiome composition and for facilitating exploratory analysis of their co-variation are lacking. Here we introduce BURRITO, a web tool for interactive visualization of microbiome multi-omic data with paired taxonomic and functional information. BURRITO simultaneously visualizes the taxonomic and functional compositions of multiple samples and dynamically highlights relationships between taxa and functions to capture the underlying structure of these data. Users can browse for taxa and functions of interest and interactively explore the share of each function attributed to each taxon across samples. BURRITO supports multiple input formats for taxonomic and metagenomic data, allows adjustment of data granularity, and can export generated visualizations as static publication-ready formatted figures. In this paper, we describe the functionality of BURRITO, and provide illustrative examples of its utility for visualizing various trends in the relationship between the composition of taxa and functions in complex microbiomes.

The Gut Microbiota and Ageing

Understanding how the human gut microbiota might influence ageing is challenging. The gut microbiota is a hugely complex ecology of organisms that varies greatly with individuals and time, making age-related changes difficult to measure. However, elderly and younger populations do show differences in gut microbe composition. The key question is whether these differences only reflect age-related changes in host physiology and diet, or if microbes can drive host ageing? Model organisms allow this question to be addressed. Longitudinal analyses in the fruit fly Drosophila melanogaster show that changes in microbial composition precedes intestinal and host ageing, and antibiotic treatment increases lifespan, implicating microbes in accelerating ageing. Antibiotics also extend the lifespan of middle-aged killifish but additional transplantation of gut microbes from young killifish extends lifespan further, suggesting a positive effect of microbes associated with young animals. Microbes from old, but not young, mice induce inflammation when added to germ-free mice suggesting that microbes become more harmful to the host with age. These studies implicate broad classes of bacteria, particularly members of the phylum Proteobacteria, as drivers of ageing in a feed-forward loop with intestinal degradation and inflammation. The nematode Caenorhabditis elegans can be associated with single strains of genetically-tractable bacteria, and this simplified system has revealed specific interventions in bacterial metabolism, such as inhibition of bacterial folate synthesis, that extend animal lifespan. Transferring this understanding to the human microbiota is challenging but promises to reveal how manipulation of the gut microbiota might be a route to maintain health in old age.

Gleaning Insights from Fecal Microbiota Transplantation and Probiotic Studies for the Rational Design of Combination Microbial Therapies

Beneficial microorganisms hold promise for the treatment of numerous gastrointestinal diseases. The transfer of whole microbiota via fecal transplantation has already been shown to ameliorate the severity of diseases such as Clostridium difficile infection, inflammatory bowel disease, and others. However, the exact mechanisms of fecal microbiota transplant efficacy and the particular strains conferring this benefit are still unclear. Rationally designed combinations of microbial preparations may enable more efficient and effective treatment approaches tailored to particular diseases. Here we use an infectious disease, C. difficile infection, and an inflammatory disorder, the inflammatory bowel disease ulcerative colitis, as examples to facilitate the discussion of how microbial therapy might be rationally designed for specific gastrointestinal diseases. Fecal microbiota transplantation has already shown some efficacy in the treatment of both these disorders; detailed comparisons of studies evaluating commensal and probiotic organisms in the context of these disparate gastrointestinal diseases may shed light on potential protective mechanisms and elucidate how future microbial therapies can be tailored to particular diseases.

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

Antibiotics excreted into the intestinal tract may disrupt the microbiota that provide colonization resistance against enteric pathogens and alter normal metabolic functions of the microbiota. Many of the bacterial metabolites produced in the intestinal tract are absorbed systemically and excreted in urine. Here, we used a mouse model to test the hypothesis that alterations in levels of targeted bacterial metabolites in urine specimens could provide useful biomarkers indicating disrupted or intact colonization resistance. To assess in vivo colonization resistance, mice were challenged with Clostridium difficile spores orally 3, 6, and 11 days after the completion of 2 days of treatment with piperacillin-tazobactam, aztreonam, or saline. For concurrent groups of antibiotic-treated mice, urine samples were analyzed by using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify the concentrations of 11 compounds targeted as potential biomarkers of colonization resistance. Aztreonam did not affect colonization resistance, whereas piperacillin-tazobactam disrupted colonization resistance 3 days after piperacillin-tazobactam treatment, with complete recovery by 11 days after treatment. Three of the 11 compounds exhibited a statistically significant and >10-fold increase (the tryptophan metabolite N-acetyltryptophan) or decrease (the plant polyphenyl derivatives cinnamoylglycine and enterodiol) in concentrations in urine 3 days after piperacillin-tazobactam treatment, followed by recovery to baseline that coincided with the restoration of in vivo colonization resistance. These urinary metabolites could provide useful and easily accessible biomarkers indicating intact or disrupted colonization resistance during and after antibiotic treatment.

Clostridium difficile Colonizes Alternative Nutrient Niches during Infection across Distinct Murine Gut Microbiomes

Clostridium difficile is the largest single cause of hospital-acquired infection in the United States. A major risk factor for Clostridium difficile infection (CDI) is prior exposure to antibiotics, as they disrupt the gut bacterial community which protects from C. difficile colonization. Multiple antibiotic classes have been associated with CDI susceptibility, many leading to distinct community structures stemming from variation in bacterial targets of action. These community structures present separate metabolic challenges to C. difficile. Therefore, we hypothesized that the pathogen adapts its physiology to the nutrients within different gut environments. Utilizing an in vivo CDI model, we demonstrated that C. difficile highly colonized ceca of mice pretreated with any of three antibiotics from distinct classes. Levels of C. difficile spore formation and toxin activity varied between animals based on the antibiotic pretreatment. These physiologic processes in C. difficile are partially regulated by environmental nutrient concentrations. To investigate metabolic responses of the bacterium in vivo, we performed transcriptomic analysis of C. difficile from ceca of infected mice across pretreatments. This revealed heterogeneous expression in numerous catabolic pathways for diverse growth substrates. To assess which resources C. difficile exploited, we developed a genome-scale metabolic model with a transcriptome-enabled metabolite scoring algorithm integrating network architecture. This platform identified nutrients that C. difficile used preferentially between pretreatments, which were validated through untargeted mass spectrometry of each microbiome. Our results supported the hypothesis that C. difficile inhabits alternative nutrient niches across cecal microbiomes with increased preference for nitrogen-containing carbon sources, particularly Stickland fermentation substrates and host-derived glycans. IMPORTANCE Infection by the bacterium Clostridium difficile causes an inflammatory diarrheal disease which can become life threatening and has grown to be the most prevalent nosocomial infection. Susceptibility to C. difficile infection is strongly associated with previous antibiotic treatment, which disrupts the gut microbiota and reduces its ability to prevent colonization. In this study, we demonstrated that C. difficile altered pathogenesis between hosts pretreated with antibiotics from separate classes and exploited different nutrient sources across these environments. Our metabolite score calculation also provides a platform to study nutrient requirements of pathogens during an infection. Our results suggest that C. difficile colonization resistance is mediated by multiple groups of bacteria competing for several subsets of nutrients and could explain why total reintroduction of competitors through fecal microbial transplant currently is the most effective treatment for recurrent CDI. This work could ultimately contribute to the identification of targeted, context-dependent measures that prevent or reduce C. difficile colonization, including pre- and probiotic therapies.

Microbiota-Based Therapies for Clostridium difficile and Antibiotic-Resistant Enteric Infections

Bacterial pathogens are increasingly antibiotic resistant, and development of clinically effective antibiotics is lagging. Curing infections increasingly requires antimicrobials that are broader spectrum, more toxic, and more expensive, and mortality attributable to antibiotic-resistant pathogens is rising. The commensal microbiota, comprising microbes that colonize the mammalian gastrointestinal tract, can provide high levels of resistance to infection, and the contributions of specific bacterial species to resistance are being discovered and characterized. Microbiota-mediated mechanisms of colonization resistance and pathogen clearance include bactericidal activity, nutrient depletion, immune activation, and manipulation of the gut's chemical environment. Current research is focusing on development of microbiota-based therapies to reduce intestinal colonization with antibiotic-resistant pathogens, with the goal of reducing pathogen transmission and systemic dissemination.

Divergent Relationships between Fecal Microbiota and Metabolome following Distinct Antibiotic-Induced Disruptions

Despite the fundamental importance of antibiotic therapies to human health, their functional impact on the intestinal microbiome and its subsequent ability to recover are poorly understood. Much research in this area has focused on changes in microbiota composition, despite the interdependency and overlapping functions of many members of the microbial community. These relationships make prediction of the functional impact of microbiota-level changes difficult, while analyses based on the metabolome alone provide relatively little insight into the taxon-level changes that underpin changes in metabolite levels. Here, we used combined microbiota and metabolome profiling to characterize changes associated with clinically important antibiotic combinations with distinct effects on the gut. Correlation analysis of changes in the metabolome and microbiota indicate that a combined approach will be essential for a mechanistic understanding of the functional impact of distinct antibiotic classes.

The intestinal microbiome plays an essential role in regulating many aspects of host physiology, and its disruption through antibiotic exposure has been implicated in the development of a range of serious pathologies. The complex metabolic relationships that exist between members of the intestinal microbiota and the potential redundancy in functional pathways mean that an integrative analysis of changes in both structure and function are needed to understand the impact of antibiotic exposure. We used a combination of next-generation sequencing and nuclear magnetic resonance (NMR) metabolomics to characterize the effects of two clinically important antibiotic treatments, ciprofloxacin and vancomycin-imipenem, on the intestinal microbiomes of female C57BL/6 mice. This assessment was performed longitudinally and encompassed both antibiotic challenge and subsequent microbiome reestablishment. Both antibiotic treatments significantly altered the microbiota and metabolite compositions of fecal pellets during challenge and recovery. Spearman’s correlation analysis of microbiota and NMR data revealed that, while some metabolites could be correlated with individual operational taxonomic units (OTUs), frequently multiple OTUs were associated with a significant change in a given metabolite. Furthermore, one metabolite, arginine, can be associated with increases/decreases in different sets of OTUs under differing conditions. Taken together, these findings indicate that reliance on shifts in one data set alone will generate an incomplete picture of the functional effect of antibiotic intervention. A full mechanistic understanding will require knowledge of the baseline microbiota composition, combined with both a comparison and an integration of microbiota, metabolomics, and phenotypic data.

IMPORTANCE Despite the fundamental importance of antibiotic therapies to human health, their functional impact on the intestinal microbiome and its subsequent ability to recover are poorly understood. Much research in this area has focused on changes in microbiota composition, despite the interdependency and overlapping functions of many members of the microbial community. These relationships make prediction of the functional impact of microbiota-level changes difficult, while analyses based on the metabolome alone provide relatively little insight into the taxon-level changes that underpin changes in metabolite levels. Here, we used combined microbiota and metabolome profiling to characterize changes associated with clinically important antibiotic combinations with distinct effects on the gut. Correlation analysis of changes in the metabolome and microbiota indicate that a combined approach will be essential for a mechanistic understanding of the functional impact of distinct antibiotic classes.

IMPACT OF TIGECYCLINE VERSUS OTHER ANTIBIOTICS ON THE FECAL METABOLOME AND ON COLONIZATION RESISTANCE TO CLOSTRIDIUM DIFFICILE IN MICE

Background:

The glycylcycline antibiotic tigecycline may have a relatively low propensity to promote Clostridium difficile infection in part because it causes less disruption of the indigenous intestinal microbiota than other broad-spectrum antibiotics. We used a mouse model to compare the effects of tigecycline versus other commonly used antibiotics on colonization resistance to C. difficile and on the metabolic functions of the intestinal microbiota.

Methods:

To assess in vivo colonization resistance to C. difficile, mice were challenged with oral C. difficile spores 1, 7, or 12 days after completion of 3 days of treatment with subcutaneous saline, tigecycline, ceftriaxone, piperacillin-tazobactam, or linezolid. Levels of bacterial metabolites in fecal specimens of mice treated with the same antibiotics were analyzed using non-targeted metabolic profiling by gas chromatograph (GC)/mass spectrometry (MS) and ultra-high performance liquid chromatography-tandem MS (UPLC-MS/MS).

Results:

All of the antibiotics disrupted colonization resistance to C. difficile when challenge occurred 2 days after treatment. Only piperacillin/tazobactam mice had disturbed colonization resistance at 7 days after treatment. All of the antibiotics altered fecal metabolites in comparison to controls, but tigecycline caused significantly less alteration than the other antibiotics, including less suppression of multiple amino acids, bile acids, and lipid metabolites.

Conclusions:

Tigecycline, linezolid, and ceftriaxone caused transient disruption of colonization resistance to C. difficile, whereas piperacillin/tazobactam caused disruption that persisted for 7 days post-treatment. Tigecycline caused less profound alteration of fecal bacterial metabolites than the other antibiotics, suggesting that the relatively short period of disruption of colonization resistance might be related in part to reduced alteration of the metabolic functions of the micro-biota.

Fecal Microbiota and Metabolome in a Mouse Model of Spontaneous Chronic Colitis: Relevance to Human Inflammatory Bowel Disease

BACKGROUND

Dysbiosis of the gut microbiota may be involved in the pathogenesis of inflammatory bowel disease (IBD). However, the mechanisms underlying the role of the intestinal microbiome and metabolome in IBD onset and its alteration during active treatment and recovery remain unknown. Animal models of chronic intestinal inflammation with similar microbial and metabolomic profiles would enable investigation of these mechanisms and development of more effective treatments. Recently, the Winnie mouse model of colitis closely representing the clinical symptoms and characteristics of human IBD has been developed. In this study, we have analyzed fecal microbial and metabolomic profiles in Winnie mice and discussed their relevance to human IBD.

METHODS

The 16S rRNA gene was sequenced from fecal DNA of Winnie and C57BL/6 mice to define operational taxonomic units at ≥97% similarity threshold. Metabolomic profiling of the same fecal samples was performed by gas chromatography-mass spectrometry.

RESULTS

Composition of the dominant microbiota was disturbed, and prominent differences were evident at all levels of the intestinal microbiome in fecal samples from Winnie mice, similar to observations in patients with IBD. Metabolomic profiling revealed that chronic colitis in Winnie mice upregulated production of metabolites and altered several metabolic pathways, mostly affecting amino acid synthesis and breakdown of monosaccharides to short chain fatty acids.

CONCLUSIONS

Significant dysbiosis in the Winnie mouse gut replicates many changes observed in patients with IBD. These results provide justification for the suitability of this model to investigate mechanisms underlying the role of intestinal microbiota and metabolome in the pathophysiology of IBD.

Doses Lactobacillus reuteri depend on adhesive ability to modulate the intestinal immune response and metabolism in mice challenged with lipopolysaccharide

The objective of this study was to evaluate the modulatory effects of Lactobacillus reuteri ZJ617 and ZJ615, which have high and low adhesive abilities, respectively, and Lactobacillus rhamnosus GG (LGG) on immune responses and metabolism in mice stimulated with lipopolysaccharide (LPS). Six C57BL/6 mice per group were orally inoculated with ZJ617, ZJ615 or LGG for one week (1 × 10(8) CFU/mouse) and i.p. injected with LPS (10 mg/kg) for 24 h. Compared with the LPS stimulation group, ZJ615, ZJ617 and LGG significantly decreased TNF-α levels in the sera of mice stimulated by LPS. ZJ615 and LGG significantly down-regulated mRNA levels of cytokines and Toll-like receptors, and suppressed activation of MAPK and NF-κB signaling, while ZJ617 up-regulated anti-inflammatory cytokine IL-10 mRNA levels in the ilea of mice stimulated by LPS. Correlation analysis confirmed that adhesive ability is relative with the immunomodulation in the ilea of mice. There were 24, 7 and 10 metabolites and 10, 9 and 8 major metabolic pathways with significant differences (VIP > 1, P < 0.05) between the LPS and ZJ617 + LPS groups, the LPS and ZJ615 + LPS groups, and the ZJ617 + LPS and ZJ615 + LPS groups, respectively. The results indicated that both ZJ617 and ZJ615 could modulate the intestinal immune responses and metabolism in LPS-stimulated mice.

Effect of Surotomycin, a Novel Cyclic Lipopeptide Antibiotic, on Intestinal Colonization with Vancomycin-Resistant Enterococci and Klebsiella pneumoniae in Mice

Surotomycin (formerly called CB-183,315) is a novel, orally administered cyclic lipopeptide antibacterial in development for the treatment of Clostridium difficile infection (CDI) that has potent activity against vancomycin-resistant enterococci (VRE) but limited activity against Gram-negative bacilli, including Bacteroides spp. We used a mouse model to investigate the impact of surotomycin exposure on the microbiome, and to test the consequences of the disruption on colonization by vancomycin-resistant enterococci (VRE) and extended-spectrum β-lactamase-producing Klebsiella pneumoniae (ESBL-KP), in comparison with the effects of oral vancomycin and metronidazole. Mice (8 per group) received saline, vancomycin, metronidazole, or surotomycin through an orogastric tube daily for 5 days and were challenged with 10(5) CFU of VRE or ESBL-KP administered through an orogastric tube on day 2 of treatment. The concentrations of the pathogens in stool were determined during and after treatment by plating on selective media. A second experiment was conducted to determine if the antibiotics would inhibit established VRE colonization. In comparison to controls, oral vancomycin promoted VRE and ESBL-KP overgrowth in stool (8 log10 to 10 log10 CFU/g; P < 0.001), whereas metronidazole did not (<4 log10 CFU/g; P > 0.5). Surotomycin promoted ESBL-KP overgrowth (>8 log10 CFU/g; P, <0.001 for comparison with saline controls) but not VRE overgrowth. Surotomycin suppressed preexisting VRE colonization, whereas metronidazole and vancomycin did not. These results suggest that treatment of CDI with surotomycin could reduce levels of VRE acquisition and overgrowth from those with agents such as vancomycin and metronidazole. However, surotomycin and vancomycin may promote colonization by antibiotic-resistant Gram-negative bacilli.

Structural and functional changes within the gut microbiota and susceptibility to Clostridium difficile infection

Alteration of the gut microbial community structure and function through antibiotic use increases susceptibility to colonization by Clostridium difficile and other enteric pathogens. However, the mechanisms that mediate colonization resistance remain elusive. As the leading definable cause of infectious diarrhea, toxigenic C. difficile represents a burden for patients and health care systems, underscoring the need for better diagnostics and treatment strategies. Next-generation sequence data has increased our understanding of how the gut microbiota is influenced by many factors including diet, disease, aging and drugs. However, a microbial-based biomarker differentiating C. difficile infection from antibiotic-associated diarrhea has not been identified. Metabolomics profiling, which is highly responsive to changes in physiological conditions, have shown promise in differentiating subtle disease phenotypes that exhibit a nearly identical microbiome community structure, suggesting metabolite-based biomarkers may be an ideal diagnostic for identifying patients with CDI. This review focuses on the current understanding of structural and functional changes to the gut microbiota during C. difficile infection obtained from studies assessing the microbiome and metabolome of samples from patients and murine models.

The effects of antibiotics on the microbiome throughout development and alternative approaches for therapeutic modulation

The widespread use of antibiotics in the past 80 years has saved millions of human lives, facilitated technological progress and killed incalculable numbers of microbes, both pathogenic and commensal. Human-associated microbes perform an array of important functions, and we are now just beginning to understand the ways in which antibiotics have reshaped their ecology and the functional consequences of these changes. Mounting evidence shows that antibiotics influence the function of the immune system, our ability to resist infection, and our capacity for processing food. Therefore, it is now more important than ever to revisit how we use antibiotics. This review summarizes current research on the short-term and long-term consequences of antibiotic use on the human microbiome, from early life to adulthood, and its effect on diseases such as malnutrition, obesity, diabetes, and Clostridium difficile infection. Motivated by the consequences of inappropriate antibiotic use, we explore recent progress in the development of antivirulence approaches for resisting infection while minimizing resistance to therapy. We close the article by discussing probiotics and fecal microbiota transplants, which promise to restore the microbiota after damage of the microbiome. Together, the results of studies in this field emphasize the importance of developing a mechanistic understanding of gut ecology to enable the development of new therapeutic strategies and to rationally limit the use of antibiotic compounds.

Composition of fecal microbiota of laboratory mice derived from Japanese commercial breeders using 16S rRNA gene clone libraries

The fecal microbiota of six mice derived from three Japanese commercial breeders was analyzed by using 16S rRNA gene clone libraries to construct a database for analyzing the gut microbiota of laboratory mice. The 566 clones were obtained from the clone libraries generated from the fecal DNA samples derived from BALB/c, C57BL/6N, DBA/2 and ICR mice. Among these 566 clones, there were 446 unique 16S rRNA gene sequences. When grouped at the 98% similarity level, the 446 unique sequences consisted of 103 Clostridiales, 43 Bacteroidales, 5 Lactobacillus and 3 Erysipelotricaceae, as well as sequences from 11 other phyla.

Gastrointestinal dysbiosis and the use of fecal microbial transplantation in Clostridium difficile infection

The impact of antibiotics on the human gut microbiota is a significant concern. Antibiotic-associated diarrhea has been on the rise for the past few decades with the increasing usage of antibiotics. Clostridium difficile infections (CDI) have become one of the most prominent types of infectious diarrheal disease, with dramatically increased incidence in both the hospital and community setting worldwide. Studies show that variability in the innate host response may in part impact upon CDI severity in patients. That being said, CDI is a disease that shows the most prominent links to alterations to the gut microbiota, in both cause and treatment. With recurrence rates still relatively high, it is important to explore alternative therapies to CDI. Fecal microbiota transplantation (FMT) and other types of bacteriotherapy have become exciting avenues of treatment for CDI. Recent clinical trials have generated excitement for the use of FMT as a therapeutic option for CDI; however, the exact components of the human gut microbiota needed for protection against CDI have remained elusive. Additional investigations on the effects of antibiotics on the human gut microbiota and subsequent CDI will help reduce the socioeconomic burden of CDI and potentially lead to new therapeutic modalities.