Bioaccumulation of therapeutic drugs by human gut bacteria

Abstract

Bacteria in the gut can modulate the availability and efficacy of therapeutic drugs. However, the systematic mapping of the interactions between drugs and bacteria has only started recently¹ and the main underlying mechanism proposed is the chemical transformation of drugs by microorganisms (biotransformation). Here we investigated the depletion of 15 structurally diverse drugs by 25 representative strains of gut bacteria. This revealed 70 bacteria-drug interactions, 29 of which had not to our knowledge been reported before. Over half of the new interactions can be ascribed to bioaccumulation; that is, bacteria storing the drug intracellularly without chemically modifying it, and in most cases without the growth of the bacteria being affected. As a case in point, we studied the molecular basis of bioaccumulation of the widely used antidepressant duloxetine by using click chemistry, thermal proteome profiling and metabolomics. We find that duloxetine binds to several metabolic enzymes and changes the metabolite secretion of the respective bacteria. When tested in a defined microbial community of accumulators and non-accumulators, duloxetine markedly altered the composition of the community through metabolic cross-feeding. We further validated our findings in an animal model, showing that bioaccumulating bacteria attenuate the behavioural response of Caenorhabditis elegans to duloxetine. Together, our results show that bioaccumulation by gut bacteria may be a common mechanism that alters drug availability and bacterial metabolism, with implications for microbiota composition, pharmacokinetics, side effects and drug responses, probably in an individual manner.

Fig 1. Gut bacteria accumulate therapeutic drugs without altering them.

Bacteria-drug interaction network identified in our study (see main text). Left network: Biotransformation or bioaccumulation of drugs by gut bacteria. Shown are the interactions significant in two independent screens, and validated in a follow-up assay (Wilcoxon’s rank sum test, FDR corrected p < 0.05). Also included are previously reported interactions that were detected in the screen but not tested in the validation assay. Right network: Growth impact of drugs on gut bacteria as detected in at least two independent screens. (Student’s t-test, alpha=0.05).

Fig 2. Bioaccumulation of duloxetine impacts bacterial physiology.

a) NMR analysis showing bioaccumulation of duloxetine by S. salivarius. Drug measurements in cell-free supernatant. Differential spectrum contrasts the drug-treated and untreated cells. b) NMR quantification of duloxetine in the supernatants of three gut bacterial strains treated with 50 μM duloxetine. n=4 biologically independent replicates for drug treatment, n=2 technical replicates for drug-free controls, n=7 biologically independent replicates for bacteria-free controls. n.d. = no peak detected. Bioaccumulation assays in (a, b) performed in PBS buffer. c) LC-MS quantification of duloxetine in C. saccharolyticum bioaccumulation assays in GMM at different initial drug concentrations (n=4 biologically independent replicates). Boxplots in (b, c) show the interquartile range (IQR), the median, and whiskers extending to 1.5 × IQR from the 1st or 3rd quartile. d) C. saccharolyticum nucleotide biosynthetic pathway marking the duloxetine-binding or responding enzymes (EC numbers shown) and the differentially secreted metabolites (underlined). e) E. coli IAI1 (bioaccumulating in GMM) and E. coli ED1a (non-bioaccumulating in GMM) strains respond differentially to duloxetine in thermal proteome profiling (TPP) analysis. Each dot represents the summed log2 fold-changes across all temperatures for an identified protein. Main panel: duloxetine added to intact cells prior to TPP (1437 proteins in total); inset: TPP results when drug added to the cell lysates (1694 proteins in total). The black line marks the diagonal, and the blue line shows the linear regression fit. Error bands around the blue lines show 95% confidence interval. Data for both intact cells and lysate TPP is based on n=5 independent experiments for each strain (4 different drug concentrations and a vehicle control). f) Impact of duloxetine treatment on the exo-metabolome (untargeted HILIC-MS, Methods) of six gut bacterial strains. The numbers in parentheses mark the explained variance for the corresponding principal components. The dotted arrow marks the duloxetine induced shift in the exo-metabolome of C. saccharolyticum. g) Duloxetine induced changes in the C. saccharolyticum exo-metabolome are concentration dependent.

Fig 3. Duloxetine bioaccumulation alters community assembly and host response.

a) Community assembly is impacted by duloxetine. A starting mixture of five bacteria was transferred to fresh medium with or without duloxetine every 48 hours (Methods). Shown is the profile of mean relative abundances estimated using 16S rRNA amplicon sequencing (biological triplicates). Apparent initial uneven distribution is due to interspecies differences in cell lysis and gene amplification efficiency. The trend of E. rectale normalized to the inoculum signal in Supplementary Fig. 9b. b) Mono-culture duloxetine sensitivity of the five species used in (a). For each concentration-strain combination, n=3 independent growth curves. Error bars depict standard deviation, central circles mark the mean. c) OD578 of E. rectale grown on spent medium of S salivarius. Medium was supplemented with duloxetine either before (drug conditioned) or after (spent control) S. salivarius growth. n=9, three biological and three technical replicates. Boxplots show the interquartile range (IQR), the median, and whiskers extending to 1.5 × IQR from the 1st or 3rd quartile. d) Metabolite profiles (956 in total, untargeted HILIC-MS analysis, Methods) that increased during S. salivarius growth in GMM and decreased during E. rectale growth in the cell-free conditioned medium of S. salivarius, implying cross-feeding. Thicker lines mark 5 metabolites putatively assigned using HILIC-MS/MS, two of which (linolenic acid and glycocholic acid) were confirmed against analytical standards. Mean intensities from three biological replicates are shown. e) Percentage of worms displaying movement in spent LB media pre-incubated with 0.5 mM duloxetine in the absence or presence of E. coli IAI1 (bioaccumulating) or E. coli ED1a (non-bioaccumulating). n = 8 (column 3 and 5; 4 biological X 2 technical replicates) or 12 (all other columns; 6 biological X 2 technical replicates). Bar heights mark mean, error bars = standard deviation. P-values estimated using one-way ANOVA followed by correction for multiple pair-wise comparisons (Tukey’s test). Duloxetine measurements in Supplementary Fig. 9f.