Gut microbiome-related metabolic changes in plasma of antibiotic-treated rats

Behr, Christina; Kamp, Hennicke; Fabian, Eric; Krennrich, G.; Mellert, W.; Peter, Erik; Strauss, Volker; Walk, T.; Rietjens, I.M.C.M.; Ravenzwaay, Bennard van

doi:10.1007/s00204-017-1949-2

Cited by 47 publications

(55 citation statements)

References 75 publications

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“…S2b). Because plasma metabolome is significantly affected by the gut microbiota 20,21 , we further examined whether hyperglycemia could differentiate the fecal metabolomes between GDM and the NDM controls. From the score scatter plot of PCA ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Zhao¹,

Ge²,

Li³

et al. 2020

Sci Rep

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Gestational Diabetes Mellitus (GDM), which is correlated with changes in the gut microbiota, is a risk factor for neonatal inborn errors of metabolism (ieMs). Maternal hyperglycemia exerts epigenetic effects on genes that encode IEM-associated enzymes, resulting in changes in the neonatal blood metabolome. However, the relationship between maternal gut microbiota and the neonatal blood metabolome remains poorly understood. this study aimed at understanding the connections between maternal gut microbiota and the neonatal blood metabolome in GDM. 1H-NMR-based untargeted metabolomics was performed on maternal fecal samples and targeted metabolomics on the matched neonatal dry blood spots from a cohort of 40 pregnant women, including 22 with GDM and 18 controls. Multi-omic association methods (including Co-Inertia Analysis and Procrustes Analysis) were applied to investigate the relationship between maternal fecal metabolome and the neonatal blood metabolome. Both maternal fecal metabolome and the matched neonatal blood metabolome could be separated along the vector of maternal hyperglycemia. A close relationship between the maternal and neonatal metabolomes was observed by multi-omic association approaches. Twelve out of thirty-two maternal fecal metabolites with altered abundances from 872 1H-NMR features (Bonferroni-adjusted P < 0.05) in women with GDM and the controls were identified, among which 8 metabolites contribute (P < 0.05 in a 999-step permutation test) to the close connection between maternal and the neonatal metabolomes in GDM. Four of these eight maternal fecal metabolites, including lysine, putrescine, guanidinoacetate, and hexadecanedioate, were negatively associated (Spearman rank correlation, coefficient value < −0.6, P < 0.05) with maternal hyperglycemia. Biotin metabolism was enriched (Bonferroni-adjusted P < 0.05 in the hypergeometric test) with the four-hyperglycemia associated fecal metabolites. the results of this study suggested that maternal fecal metabolites contribute to the connections between maternal fecal metabolome and the neonatal blood metabolome and may further affect the risk of IEMs. Gestational diabetes mellitus (GDM) has attracted worldwide public health concern due to its adverse maternal, fetal and neonatal outcomes. GDM is a serious pregnancy complication with various risk factors 1 , including overweight, obesity, a family history of diabetes, advanced maternal age, etc. GDM has been linked with an increased risk of inborn errors of metabolism (IEMs) in offspring 2,3. IEMs are caused by inherited genetic defects and can be influenced by environmental stimuli 4. Accumulating evidence suggests that maternal hyperglycemia is associated

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Section: Resultsmentioning

confidence: 99%

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Zhao¹,

Ge²,

Li³

et al. 2020

Sci Rep

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“…However, oligomeric and polymeric flavanols (also called procyanidins, PCs) are poorly absorbed, and the majority of the ingested dose reaches the colon. Here, they interact with the gut microbiome, which is comprised of 100 trillion cells of high inter-and intraspecies variability (Espín et al 2017;Behr et al 2017). These microbes metabolize flavanols via reactions including hydrolysis, ring cleavage, and dehydration (Selma et al 2009;Behr et al 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Here, they interact with the gut microbiome, which is comprised of 100 trillion cells of high inter-and intraspecies variability (Espín et al 2017;Behr et al 2017). These microbes metabolize flavanols via reactions including hydrolysis, ring cleavage, and dehydration (Selma et al 2009;Behr et al 2017). Flavanol metabolites (representative structures in Figure 1) are readily absorbed into circulation and are excreted in the urine (Fernandez-Millan et al 2014;.…”

Section: Introductionmentioning

confidence: 99%

Microbial metabolites of flavanols in urine are associated with enhanced anti-proliferative activity in bladder cancer cells in vitro

Griffin

Kohrt

Rathore

et al. 2020

Preprint

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Dietary flavanols and their metabolites are excreted primarily via the urine, suggesting uroepithelial cells as a site of activity due to lengthy exposure to high concentrations of these compounds. Flavanols are metabolized by the gut microbiota to numerous bioavailable metabolites. The observed effects of flavanols, including cancer chemoprevention, may be due in part to the activities of microbial metabolites. Most in vitro mechanistic work in this area relies on a limited pool of commercially available or synthesized flavanol microbial metabolites, and little work has been done in the area of bladder cancer. The impact of physiologically relevant mixtures of native flavanols and their metabolites generated in vivo remains unknown. Rats were fed various flavanols after which 48 h urine samples, approximating the total bioavailable metabolome, were collected. Urine samples were profiled by UPLC-MS/MS, and their anti-proliferative activities were assayed in vitro in four bladder cancer cell models. Significant interindividual variability was observed for chemical profiles and anti-proliferative activities. Concentrations of microbial metabolites (valerolactones, phenylalkyl acids and hippuric acids) were positively associated with reduced bladder cancer cell proliferation in vitro, while native flavanols were poorly correlated with activity. These results suggest that microbial metabolites may be the primary compounds responsible for chemoprevention in uroepithelial cell following flavanol consumption. Furthermore, this highlights the potential for exploiting knowledge about individual genetics, microbiome profiles, flavonoid metabolism profiles, tumor characteristics, etc. to design personalized dietary interventions for cancer prevention and/or adjuvant therapy to reduce bladder cancer incidence and improve outcomes.

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“…However, only Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were found in all samples [28]. In general, rats, the golden standard model in toxicological studies, are proposed to be more representative of the human gut microbiota than mice, and the gut bacterial communities of humanized rats more closely reflect the gut microbiota of human donors [28,29]. However, while many species inhabiting the human gut are well described [30,31], the majority of rodent gut bacteria remain to be cultured and characterized [20].…”

Section: Inter-and Intraspecies Variability Of the Gut Microbiomementioning

confidence: 99%

“…To use metabolomics in toxicology as a screening tool, various metabolite patterns for different toxicological targets and mode of actions (MoAs) were established in the MetaMap ® Tox database, with the aim to identify and predict the toxicological MoA of new test substances, e.g. in the liver, kidney, thyroid, testes, blood, nervous system and endocrine system [29]. In other words, this means that changes of the endogenous metabolites, derived from the organs affected by a compound, are analyzed.…”

Section: Metabolomics Key Metabolites and (Systemic) Effect Of Antibmentioning

confidence: 99%

Influence of the gut microbiome on plasma metabolite patterns

Behr¹

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General introduction Chapter 2 25 Gut microbiome-related metabolic changes in plasma of antibiotic-treated rats Chapter 3 55 Microbiome-related metabolite changes in gut tissue, cecum content and feces of rats treated with antibiotics Chapter 4 87 Impact of lincosamides antibiotics on the composition of the rat gut microbiota and the metabolite profile of plasma and feces Chapter 5 Analysis of metabolome changes in the bile acid pool in feces and plasma of antibiotic-treated rats Chapter 6 General discussion Chapter 7 Summary Appendix Acknowledgements, Curriculum Vitae, List of publications, Overview of completed training activities Although the fundamental role of the microbiome in the well-being of the host is clear, science is now dealing with a bigger challenge, i.e. understanding the mechanisms by which these processes of the tight microbial-host interaction are driven. Integrative approaches that not only assess the composition of the gut microbiome but also its functionality must be implemented to unravel the complex dynamics of these interactions [11]. There are high intra-and interspecies variabilities regarding the composition of the microbiome, however, there are also indications that the functionality in terms of gene activity and metabolic output of the microbes have a lower variability [20-22] which supports assessing functional microbial changes with metabolomics approaches. capacity of metabolites, or the first pass metabolism of xenobiotics can influence the host's metabolism or the toxicity of a compound, which may have implications for the host's health. However, since mechanistic studies are mostly performed in rodents, the results are difficult to extrapolate to humans and other species due to the interspecies differences in the composition of the microbiome. Furthermore, the microbiome is influenced by several factors such as a change in diet, the host condition, radiation, xenobiotics and genetics, which results in a high variability regarding the composition of the microbial community within species, but also between different species [14-16,61-63]. Hence, an essential first step is to identify host species-specific effects, e.g. to measure the endogenous metabolite profile, to identify key metabolites and to correlate them to bacterial species. New technologies such as the omics technologies enable a deep research of the complex interaction between microbiome and host, potentially having the power to elucidate its outstanding role in the developing organism. To understand its role in toxicology and pharmacology, it is essential to determine the microbiota's function, composition, community organization, and resulting host-microbiota interactions. Omics technologies, especially metabolomics, can be suitable tools to identify microbiome-derived orassociated metabolites and to reflect changes in the composition of the microbiota that could potentially lead to disease [18]. Analyzing the production of microbiota-derived metabolites is the first stage of a series of investigations that have th...

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Gut microbiome-related metabolic changes in plasma of antibiotic-treated rats

Cited by 47 publications

References 75 publications

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Microbial metabolites of flavanols in urine are associated with enhanced anti-proliferative activity in bladder cancer cells in vitro

Influence of the gut microbiome on plasma metabolite patterns

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