Gut microbiome and antibiotic resistance effects during travelers' diarrhea treatment and prevention

Abstract

The travelers' gut microbiome is potentially assaulted by acute and chronic perturbations (e.g., diarrhea, antibiotic use, and different environments). Prior studies of the impact of travel and travelers' diarrhea (TD) on the microbiome have not directly compared antibiotic regimens, and studies of different antibiotic regimens have not considered travelers' microbiomes. This gap is important to be addressed as the use of antibiotics to treat or prevent TD-even in moderate to severe cases or in regions with high infectious disease burden-is controversial based on the concerns for unintended consequences to the gut microbiome and antimicrobial resistance (AMR) emergence. Our study addresses this by evaluating the impact of defined antibiotic regimens (single-dose treatment or daily prophylaxis) on the gut microbiome and resistomes of deployed servicemembers, using samples collected during clinical trials. Our findings indicate that the antibiotic treatment regimens that were studied generally do not lead to adverse effects on the gut microbiome and resistome and identify the relative risks associated with prophylaxis. These results can be used to inform therapeutic guidelines for the prevention and treatment of TD and make progress toward using microbiome information in personalized medical care.

Keywords: antibiotic resistance; human microbiome; international travel; travelers' diarrhea.

Fig 1

Gut microbiome dynamics based on treatment or prophylactic usage of antibiotics. (A–C) Shannon diversity, richness, and phylum-level relative abundance for the TrEAT TD trial (n = 108). (D–F) Shannon diversity, richness, and phylum-level relative abundance for the PREVENT TD trial (n = 232). Data points are individual fecal samples. The horizontal lines represent the median, and the upper and lower hinges represent the 25th to 75th percentiles (interquartile range). The coloring represents the treatment regimen for Shannon diversity and richness plots. For the relative abundance of phyla, the coloring represents the specified phyla. Subjects who had acute dysentery in TrEAT TD and who did not complete the prophylaxis regimen in PREVENT TD were excluded from the analysis.

Fig 2

Genus-level dynamics and cytokine differences link to Escherichia abundance. (A and B) Microbial genera significantly associated with diarrheal samples detected using MaAsLin2 where subjects were used as random effects and treatment and time (PREVENT TD) or time (TrEAT TD) as fixed effects. The error bars extend to the values within the 95% CI. The colors represent the timepoint for TrEAT TD and treatment and time for PREVENT TD. (C) Radar plot of significantly different cytokines [(pg cytokine/μg protein)/mg feces] between timepoints in TrEAT TD. Using LME models with treatment and time as fixed effects and subject ID as random effects, the cytokines with P < 0.05 for time are presented. Values are depicted using a logarithmic scale. The color of the line represents the timepoint. (D) Circos plot using DIABLO demonstrating correlations between gut microbiome genus abundance and fecal cytokine concentration. The color of the connecting line represents the directionality of correlation. Subjects who had acute dysentery in TrEAT TD and who did not complete the prophylaxis regimen in PREVENT TD were excluded from the analysis.

Fig 3

Resistome dynamics based on treatment or prophylactic usage of antibiotics. (A and B) The reads per kilobase per million (RPKM) sum and counts of resistomes for the TrEAT TD trial (n = 108). (C and D) The RPKM sum and counts of resistomes for the PREVENT TD trial (n = 232). The points are individual fecal samples with a horizontal line at the median, and the upper and lower hinges represent the 25th to 75th percentiles. The coloring represents the treatment regimen for each trial. Subjects who had acute dysentery in TrEAT TD and who did not complete the prophylaxis regimen in PREVENT TD were excluded from the analysis.

Fig 4

Diarrheagenic E. coli isolates are phylogenetically diverse and encode many ARGs and virulence factors (VFs). The phylogenetic tree inferred from the core-genome alignment of 54 E. coli isolates from the TrEAT TD cohort (red), 189 published DEC genomes from the Cusco TD study (blue), and 35 E. coli reference genomes (gray). Annotations from the inner to the outer ring: cohort, phylogroup, barplot denoting ARG count, E. coli pathotype (assigned by the presence/absence of specific VFs), and barplot denoting VF count.

Fig 5

ARG content of E. coli isolates. (A) Boxplot of ARG counts of E. coli isolates. Each point represents an isolate. Isolates are binned by those collected from diarrheal samples (timepoint 0) and then from stool samples collected 7 and 21 days later. The boxes show median and quartiles; the error bars extend to the values within the 1.5 interquartile range. (B) Boxplot of ARG counts of E. coli isolates. Each point represents an isolate. The isolates are binned by E. coli pathotype (assigned by the presence/absence of specific VFs) or as no pathotype determined (NPD). The boxes show the median and quartiles; the error bars extend to the values within the 1.5 interquartile range. (C) Linkage of isolates between subjects. High-resolution single nucleotide polymorphism (SNP) comparisons between isolates belonging to the same strain collected from different subjects and timepoints. The points represent the individual isolates, the type of line indicates the number of SNPs in the comparison, and the coloring of points/lines indicates the isolates’ multi-locus sequence type (MLST). Open reading frames (ORF) are colored as follows: ARGs (red), mobile elements (yellow), hypothetical proteins (dark gray), and other genes (light gray). (D) Arrangements of ARGs and mobile elements identified on the same contig and shared between multiple samples. Labeled by the isolate the contig belongs to. The bars connecting the contig regions indicate the regions of similarity with a minimum comparison length of 500 bp, and shading indicates nucleotide identity.