The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to ...drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations.
As interest in the therapeutic and biotechnological potentials of bacteriophages has grown, so has value in understanding their basic biology. However, detailed knowledge of infection cycles has been ...limited to a small number of model bacteriophages, mostly infecting Escherichia coli. We present here the first analysis coupling data obtained from global next-generation approaches, RNA-Sequencing and metabolomics, to characterize interactions between the virulent bacteriophage PAK_P3 and its host Pseudomonas aeruginosa. We detected a dramatic global depletion of bacterial transcripts coupled with their replacement by viral RNAs over the course of infection, eventually leading to drastic changes in pyrimidine metabolism. This process relies on host machinery hijacking as suggested by the strong up-regulation of one bacterial operon involved in RNA processing. Moreover, we found that RNA-based regulation plays a central role in PAK_P3 lifecycle as antisense transcripts are produced mainly during the early stage of infection and viral small non coding RNAs are massively expressed at the end of infection. This work highlights the prominent role of RNA metabolism in the infection strategy of a bacteriophage belonging to a new characterized sub-family of viruses with promising therapeutic potential.
Phage-mediated metabolic changes in bacteria are hypothesized to markedly alter global nutrient and biogeochemical cycles. Despite their theoretic importance, experimental data on the net metabolic ...impact of phage infection on the bacterial metabolism remains scarce. In this study, we tracked the dynamics of intracellular metabolites using untargeted high coverage metabolomics in Pseudomonas aeruginosa cells infected with lytic bacteriophages from six distinct phage genera. Analysis of the metabolomics data indicates an active interference in the host metabolism. In general, phages elicit an increase in pyrimidine and nucleotide sugar metabolism. Furthermore, clear phage-specific and infection stage-specific responses are observed, ranging from extreme metabolite depletion (for example, phage YuA) to complete reorganization of the metabolism (for example, phage phiKZ). As expected, pathways targeted by the phage-encoded auxiliary metabolic genes (AMGs) were enriched among the metabolites changing during infection. The effect on pyrimidine metabolism of phages encoding AMGs capable of host genome degradation (for example, YuA and LUZ19) was distinct from those lacking nuclease-encoding genes (for example, phiKZ), which demonstrates the link between the encoded set of AMGs of a phage and its impact on host physiology. However, a large fraction of the profound effect on host metabolism could not be attributed to the phage-encoded AMGs. We suggest a potentially crucial role for small, 'non-enzymatic' peptides in metabolism take-over and hypothesize on potential biotechnical applications for such peptides. The highly phage-specific nature of the metabolic impact emphasizes the potential importance of the 'phage diversity' parameter when studying metabolic interactions in complex communities.
Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data ...type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.
Increasing evidence suggests a role of the gut microbiota in patients' response to medicinal drugs. In our recent study, we combined genomics of human gut commensals and gnotobiotic animal ...experiments to quantify microbiota and host contributions to drug metabolism. Informed by experimental data, we built a physiology-based pharmacokinetic model of drug metabolism that includes intestinal compartments with microbiome drug-metabolizing activity. This model successfully predicted serum levels of metabolites of three different drugs, quantified microbial contribution to systemic drug metabolite exposure, and simulated the effect of different parameters on host and microbiota drug metabolism. In this addendum, we expand these simulations to assess the effect of microbiota on the systemic drug and metabolite levels under conditions of altered host physiology, microbiota drug-metabolizing activity or physico-chemical properties of drugs. This work illustrates how and under which circumstances the gut microbiome may influence drug pharmacokinetics, and discusses broader implications of expanded pharmacokinetic models.
Quantifying host-microbiota interactions Zimmermann-Kogadeeva, Maria
Science (American Association for the Advancement of Science),
07/2021, Letnik:
373, Številka:
6551
Journal Article
Recenzirano
Modeling the microbiome increases understanding of its role in drug metabolism
The human microbiota is a complex microbial community living on and in our bodies. Its impact on a host's health is ...immense, affecting digestion (
1
), the immune system (
2
), behavior (
3
), metabolic diseases (
4
), and responses to drugs (
5
–
7
). Rapid advances in experimental and computational methods have moved the human microbiome field from identifying associations between microbiota composition and host health to unraveling the underlying molecular mechanisms (
8
–
10
). However, exactly how much the microbiota contributes to host health is a very difficult question to answer.
Individuals vary widely in their responses to medicinal drugs, which can be dangerous and expensive owing to treatment delays and adverse effects. Although increasing evidence implicates the gut ...microbiome in this variability, the molecular mechanisms involved remain largely unknown. Here we show, by measuring the ability of 76 human gut bacteria from diverse clades to metabolize 271 orally administered drugs, that many drugs are chemically modified by microorganisms. We combined high-throughput genetic analyses with mass spectrometry to systematically identify microbial gene products that metabolize drugs. These microbiome-encoded enzymes can directly and substantially affect intestinal and systemic drug metabolism in mice, and can explain the drug-metabolizing activities of human gut bacteria and communities on the basis of their genomic contents. These causal links between the gene content and metabolic activities of the microbiota connect interpersonal variability in microbiomes to interpersonal differences in drug metabolism, which has implications for medical therapy and drug development across multiple disease indications.
Nutrient acquisition from the host environment is crucial for the survival of intracellular pathogens, but conceptual and technical challenges limit our knowledge of pathogen diets. To overcome some ...of these technical roadblocks, we exploited an experimentally accessible model for early infection of human macrophages by
, the etiological agent of tuberculosis, to study host-pathogen interactions with a multi-omics approach. We collected metabolomics and complete transcriptome RNA sequencing (dual RNA-seq) data of the infected macrophages, integrated them in a genome-wide reaction pair network, and identified metabolic subnetworks in host cells and
that are modularly regulated during infection. Up- and downregulation of these metabolic subnetworks suggested that the pathogen utilizes a wide range of host-derived compounds, concomitant with the measured metabolic and transcriptional changes in both bacteria and host. To quantify metabolic interactions between the host and intracellular pathogen, we used a combined genome-scale model of macrophage and
metabolism constrained by the dual RNA-seq data. Metabolic flux balance analysis predicted coutilization of a total of 33 different carbon sources and enabled us to distinguish between the pathogen's substrates directly used as biomass precursors and the ones further metabolized to gain energy or to synthesize building blocks. This multiple-substrate fueling confers high robustness to interventions with the pathogen's metabolism. The presented approach combining multi-omics data as a starting point to simulate system-wide host-pathogen metabolic interactions is a useful tool to better understand the intracellular lifestyle of pathogens and their metabolic robustness and resistance to metabolic interventions.
The nutrients consumed by intracellular pathogens are mostly unknown. This is mainly due to the challenge of disentangling host and pathogen metabolism sharing the majority of metabolic pathways and hence metabolites. Here, we investigated the metabolic changes of
, the causative agent of tuberculosis, and its human host cell during early infection. To this aim, we combined gene expression data of both organisms and metabolite changes during the course of infection through integration into a genome-wide metabolic network. This led to the identification of infection-specific metabolic alterations, which we further exploited to model host-pathogen interactions quantitatively by flux balance analysis. These
data suggested that tubercle bacilli consume up to 33 different nutrients during early macrophage infection, which the bacteria utilize to generate energy and biomass to establish intracellular growth. Such multisubstrate fueling strategy renders the pathogen's metabolism robust toward perturbations, such as innate immune responses or antibiotic treatments.
The gut microbiota contributes to diverse aspects of host physiology, ranging from immunomodulation to drug metabolism. Changes in the gut microbiota composition are associated with various diseases ...as well as with the response to medications. It is therefore important to understand how different lifestyle and environmental factors shape gut microbiota composition. Beyond the commonly considered factor of diet, small-molecule drugs have recently been identified as major effectors of the microbiota composition. Other xenobiotics, such as environmental or chemical pollutants, can also impact gut bacterial communities. Here, we review the mechanisms of interactions between gut bacteria and antibiotics, host-targeted drugs, natural food compounds, food additives and environmental pollutants. While xenobiotics can impact bacterial growth and metabolism, bacteria in turn can bioaccumulate or chemically modify these compounds. These reciprocal interactions can manifest in complex xenobiotic-microbiota-host relationships. Our Review highlights the need to study mechanisms underlying interactions with pollutants and food additives towards deciphering the dynamics and evolution of the gut microbiota.
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