Comparative secretome metabolic dysregulation by six engineered dietary nanoparticles (EDNs) on the simulated gut microbiota

The potential use of engineered dietary nanoparticles (EDNs) in diet has been increasing and poses a risk of exposure. The effect of EDNs on gut bacterial metabolism remains largely unknown. In this study, liquid chromatography-mass spectrometry (LC-MS) based metabolomics was used to reveal significantly altered metabolites and metabolic pathways in the secretome of simulated gut microbiome exposed to six different types of EDNs (Chitosan, cellulose nanocrystals (CNC), cellulose nanofibrils (CNF) and polylactic-co-glycolic acid (PLGA); two inorganic EDNs including TiO2 and SiO2) at two dietary doses. We demonstrated that all six EDNs can alter the composition in the secretome with distinct patterns. Chitosan, followed by PLGA and SiO2, has shown the highest potency in inducing the secretome change with major pathways in tryptophan and indole metabolism, bile acid metabolism, tyrosine and phenol metabolism. Metabolomic alterations with clear dose response were observed in most EDNs. Overall, phenylalanine has been shown as the most sensitive metabolites, followed by bile acids such as chenodeoxycholic acid and cholic acid. Those metabolites might be served as the representative metabolites for the EDNs-gut bacteria interaction. Collectively, our studies have demonstrated the sensitivity and feasibility of using metabolomic signatures to understand and predict EDNs-gut microbiome interaction.

Feeding state greatly modulates the effect of xenobiotics on gut microbiome metabolism: A case study of tetracycline

The human gut microbiome is crucial in modulating host health mostly through bacterial metabolites. Chemical exposure is typical external stress which alters its composition and functionality. To date, very few studies have investigated the effect of feeding state on chemical-induced gut microbial metabolic dysregulations. Here, we set up an in vitro human gut microbiome and incorporated a metabolomics approach to investigate the effect of tetracycline (TET) at multiple doses (i.e., 10, 1, and 0.01 mg/L) on gut microbiome under the fed and fasted states. Overall, the metabolome was highly responsive at the fed state with 62 metabolites dysregulated while only 14 were altered at the fasted state under 10 mg/L (clinical TET dose). As expected, nutrient consumption was significantly inhibited under clinical TET dose at the fed state accumulating nutrients such as glutamate and leucine. Interestingly, at the fed state, TET could increase the synthesis of indole and phenyl derivatives including indole-3-aldehyde and hydrocinnamate, while inhibiting indoxyl, tryptamine, and vitamin B production, all of which have host health implications. Furthermore, metabolites like indoxyl and xanthurenic acid were still responsive at 0.01 mg/L (dietary TET dose). Collectively, results demonstrated that the feeding state greatly modulates the chemical-induced gut microbial metabolic alterations.

Risk-Based Chemical Ranking and Generating a Prioritized Human Exposome Database

BACKGROUND

Due to the ubiquitous use of chemicals in modern society, humans are increasingly exposed to thousands of chemicals that contribute to a major portion of the human exposome. Should a comprehensive and risk-based human exposome database be created, it would be conducive to the rapid progress of human exposomics research. In addition, once a xenobiotic is biotransformed with distinct half-lives upon exposure, monitoring the parent compounds alone may not reflect the actual human exposure. To address these questions, a comprehensive and risk-prioritized human exposome database is needed.

OBJECTIVES

Our objective was to set up a comprehensive risk-prioritized human exposome database including physicochemical properties as well as risk prediction and develop a graphical user interface (GUI) that has the ability to conduct searches for content associated with chemicals in our database.

METHODS

We built a comprehensive risk-prioritized human exposome database by text mining and database fusion. Subsequently, chemicals were prioritized by integrating exposure level obtained from the Systematic Empirical Evaluation of Models with toxicity data predicted by the Toxicity Estimation Software Tool and the Toxicological Priority Index calculated from the ToxCast database. The biotransformation half-lives (HLBs) of all the chemicals were assessed using the Iterative Fragment Selection approach and biotransformation products were predicted using the previously developed BioTransformer machine-learning method.

RESULTS

We compiled a human exposome database of >20,000 chemicals, prioritized 13,441 chemicals based on probabilistic hazard quotient and 7,770 chemicals based on risk index, and provided a predicted biotransformation metabolite database of >95,000 metabolites. In addition, a user-interactive Java software (Oracle)-based search GUI was generated to enable open access to this new resource.

DISCUSSION

Our database can be used to guide chemical management and enhance scientific understanding to rapidly and effectively prioritize chemicals for comprehensive biomonitoring in epidemiological investigations. https://doi.org/10.1289/EHP7722.

A high-throughput method to characterize the gut bacteria growth upon engineered nanomaterial treatment

Human are increasingly exposed to various types of engineered nanomaterials (ENMs) via dietary ingestion of nano-enabled food products, but these ENMs' impact on the gut bacteria health is still poorly understood. Current efforts in understanding the impact of these ENMs are hampered by their optical interferences in conventional quantification and viability assays, such as optical density and whole cell fluorescence staining assays. Therefore, there is a need to develop a more reliable bacteria quantification method in the presence of ENMs to effectively screen the potential adverse effects arising from the exposure of increasing ENMs on human gut microbiome. In this study, we developed a DNA-based quantification (DBQ) method in a 96-well plate format. Post-spiking method was used to correct the interference from ENMs on the reading. We showed the applicability of this method for several types of ENMs, i.e., cellulose nanofiber (CNF), graphene oxide (GO), silicon dioxide (SiO2), and chitosan, both in pure bacterial culture and in vitro human gut microbiome community. The detection limit for the highest dosing of CNF, GO, SiO2, and chitosan ENMs was approximately 0.18, 0.19, 0.05, and 0.24 as OD600, respectively. The method was also validated by a dose response experiment of E. coli with chitosan in the course of 8 hr. We believe that this method has great potential to be used in screening the effect of ENMs on the growth of gut bacteria or any other in vitro models and normalization for metabolites or proteins analysis.

Long-term exposure to TET increases body weight of juvenile zebrafish as indicated in host metabolism and gut microbiome

The application of tetracycline (TET) is very common in medical treatment, fisheries, and animal husbandry, resulting in its frequent detection with abundant concentrations in the aquatic environment. Though the effects of TET on zebrafish (Danio rerio) at embryonic and larval stages have been reported, there is very limited information on the possible long-term effect on aquatic fishes at the juvenile stage, especially at environmentally relevant levels. In this study, we have exposed juvenile zebrafish to two levels of TET at 1 and 100 µg/L for one month until their adulthood. The result showed that both levels of TET can significantly increase the body weight of the zebrafish, while there is no change in the body length. TET exposure also affected the liver microstructure by lipid vacuoles generation and global lipidomics analysis revealed a significant upregulation in hepatic triglyceride (TAG) levels. The metabolomics analysis showed great dysregulations in hepatic metabolic pathways including linoleic acid metabolism, tyrosine metabolism, and methionine metabolism, which are known to be linked with increased body weight gain through hepatic lipid accumulation. The hepatic gene expression involved in lipid transport (e.g., apoa4 and fabp11) and lipogenic factors (e.g., ppar) have been significantly upregulated in the livers of TET exposed zebrafish. Interestingly, the 16 rRNA gene sequence-based zebrafish gut microbial community analysis revealed an enhanced community diversity and altered microbial community composition upon TET exposure. To our knowledge, this is the first study showing that TET exposure can increase the body weight in juvenile zebrafish and the study on the ecotoxicity of antibiotic occurrences in the aquatic system can be further warranted.

"Cocktail" of Xenobiotics at Human Relevant Levels Reshapes the Gut Bacterial Metabolome in a Species-Specific Manner

The human gut microbiome experiences long-term exposure to numerous organic contaminants (e.g., xenobiotics) in the digestive tract, and the possible consequences have rarely been characterized. To date, very few studies have investigated the metabolic variation from different species of gut bacteria in response to xenobiotic mixtures. In this study, we applied liquid chromatography mass spectrometry-based global metabolomics, coupled with targeted metabolomics, to characterize the model gut bacterial responses toward the xenobiotic mixture, covering diverse classes of compounds at human relevant concentrations. The xenobiotic "cocktail" will not likely affect the growth or morphological properties of model bacteria at human relevant concentrations. However, the metabolic results were distinct between four model bacteria and dose levels, showing species-specific and dose-dependent responsive patterns among different commensal gut bacteria. The key metabolites responsive to xenobiotic exposure are mainly involved in amino acid metabolism and central carbon metabolism, including sulfur-containing amino acids, aromatic amino acids, amino sugars, neurotransmitters, and energy-related metabolic pathways. Many of those metabolites also play an important role in the host's health. In summary, our results show that the gut microbiome can be significantly perturbed by exposure to xenobiotic mixtures at human relevant levels, providing key information on susceptibilities of individuals with diverse gut microbial structures.