Effect of antibiotic pre-treatment and pathogen challenge on the intestinal microbiota in mice
© The Author(s) 2016
Received: 14 October 2016
Accepted: 14 November 2016
Published: 18 November 2016
More than 50 years after the discovery of antibiotics, bacterial infections have decreased substantially; however, antibiotics also may have negative effects such as increasing susceptibility to pathogens. An intact microbiome is an important line of defense against pathogens. We sought to determine the effect of orally administered antibiotics both on susceptibility to pathogens and on impact to the microbiome. We studied Campylobacter jejuni, one of the most common causes of human diarrhea, and Acinetobacter baumannii, which causes wound infections. We examined the effects of antibiotic treatment on the susceptibility of mice to those pathogens as well as their influence on the mouse gut microbiome.
In C57/BL6 mice models, we explored the effects of pathogen challenge, and antibiotic treatment on the intestinal microbiota. Mice were treated with either ciprofloxacin, penicillin, or water (control) for a 5-day period followed by a 5-day washout period prior to oral challenge with C. jejuni or A. baumannii to assess antibiotic effects on colonization susceptibility. Mice were successfully colonized with C. jejuni more than 118 days, but only transiently with A. baumannii. These challenges did not lead to any major effects on the composition of the gut microbiota. Although antibiotic pre-treatment did not modify pathogen colonization, it affected richness and community structure of the gut microbiome. However, the antibiotic dysbiosis was significantly reduced by pathogen challenge.
We conclude that despite gut microbiota disturbance, susceptibility to gut colonization by these pathogens was unchanged. The major gut microbiome disturbance produced by antibiotic treatment may be reduced by colonization with specific microbial taxa.
KeywordsMicrobiome Antibiotic treatment Pathogen challenge Penicillin Ciprofloxacin Campylobacter jejuni Acinetobacter baumannii High-throughput sequencing Next-generation sequencing
The mammalian intestine hosts a complex and diverse microbial community [1, 2]. This ecosystem interacts extensively with its host, with substantial physiological and pathological effects . For example, the gut microbiota is crucial to the host’s ability to resist colonization by pathogens [4, 5], although the mechanisms involved are incompletely characterized .
The clinical use of antibiotics has become massive in recent decades . Their use increases susceptibility to acquired pathogen, although the underlying mechanisms are not well-understood . Antibiotics change the composition of microbiota in the GI tract , affecting metabolic, hormonal, and immunological interactions between community and host, as well as intra-community interactions [10–12]. Separately, or together, these effects may increase host susceptibility to infection by introduced pathogens.
Campylobacter jejuni are Gram-negative, microaerophilic, curved rods, that commonly cause diarrheal illnesses, and can affect previously healthy hosts [13–15]. Acinetobacter baumannii, non-fermentative Gram-negative cocobacilli, have become increasingly common nosocomial pathogens, especially in intensive care units (ICUs) [16, 17]. The high prevalence of intestinal A. baumannii colonization in ICU patients suggests that the colon may be an important reservoir .
In this study, we developed mouse models involving colonization with these human pathogens to address three questions germane to colonization resistance; (1) what is the extent to which pathogens such as C. jejuni or A. baumannii colonize the GI tract of mice; (2) how does such colonization affect the gut microbiota; and (3) does pre-treatment with antibiotics change microbiota compositions and affect susceptibility to colonization by these pathogens?
Three related experiments were conducted in which control (untreated) mice were compared to experimental mice that were challenged by a pathogen, either alone, or in conjunction with antibiotic pre-treatment. In experiment #1, 7 week-old mice were challenged with either A. baumannii or C. jejuni (Additional file 1: Figure S1, panel A). In experiment #2, 6 week-old mice were challenged with one of three strains of C. jejuni that varied based on their mouse-passage histories (Additional file 1: Figure S1, panel B). In experiment #3, mice were exposed first to an antibiotic regime of either penicillin or ciprofloxacin or neither (control), and then were challenged with either A. baumannii or C. jejuni, or remained unchallenged (Additional file 1: Figure S2).
Female C57BL/6NJ mice were obtained from Jackson Laboratories at ~5 to 6 weeks of age and allowed to adjust to the NYU animal facility for 1 week. The animals then were used in experiment #1 (Additional file 1: Figure S1, panel A). In addition, animals originally received from Jackson Laboratories were used for breeding at the NYU animal facility, and the offspring females were used for experiments #2 and 3 (Additional file 1: Figure S1, panel B). In experiment #3, 10 days prior to bacterial challenge, mice were given water containing penicillin VK (0.167 mg/ml; Sigma Aldrich, St Louis MO, USA), or ciprofloxacin (0.13 mg/ml; Acros Organics, Geel, Belgium), or no antibiotic (control) for 5 days. Water containers were changed twice during these 5 days to supply fresh antibiotics. The protocols for the mouse experiments included in this study were approved by the New York University School of Medicine Institutional Animal Care and Use Committee (IACUC).
Bacterial strains used for mice inoculation
Campylobacter jejuni strain 81-176, that was originally isolated from a milkborne outbreak of human campylobacteriosis , and has been used in human volunteer studies , was used in all three experiments. For experiment #2, we used two additional C. jejuni strains that were recovered from mice experimentally inoculated with strain 81-176 in experiment #1. Campylobacter jejuni strain MP-10 was isolated from mouse stool 42 days after colonization, and C. jejuni strain Cecum J1 was isolated from the cecum of a mouse 119 days after colonization. All C. jejuni strains were cultured for 48 h on Skirrow agar (Becton–Dickinson, Franklin Lakes NJ, USA) under microaerobic conditions at 37 °C. Cultures then were resuspended in phosphate-buffered saline (PBS; pH 7.2) and adjusted to a concentration of 108 CFU (by OD600) in 400 µl, which was introduced via oral gavage to test mice. Control mice received an oral gavage of 400 µl of PBS.
Acinetobacter baumannii strain 11-1, used in experiments #1 and 3, was a recent clinical isolate obtained from the New York University Langone Medical Center (NYULMC) Clinical Microbiology Laboratory. Acinetobacter baumannii was cultured for 24 h using Columbia sheep blood agar (BD) and CHROM agar Acinetobacter Base (DRG International, Springfield NJ, USA) under aerobic conditions at 37 °C. Acinetobacter baumannii was resuspended in PBS and adjusted to a concentration of 1.3 × 1011 CFU (by OD600) per 400 µl to create the oral gavage inoculum.
Fecal specimen collection, culture and DNA extraction
In all experiments, fecal specimens were collected from mice before and after pathogen challenge (Additional file 1: Figures S1, S2), and were either immediately cultured or frozen at −20 °C. About 20 mg of feces were resuspended in 1 ml of PBS and vortex-mixed for 30 s at room temperature. From this stock suspension, tenfold dilutions were made in PBS. Aliquots (100 µl) of the 100, 10−2, and 10−3 dilutions were plated on CHROM agar for A. baumannii and on Skirrow agar for C. jejuni. Plates were incubated under the conditions indicated above and colony counts were reported as CFU/mg stool. Fecal DNA also was extracted from a 20 mg aliquot of mouse feces using the PowerSoil DNA Isolation Kit (MOBIO, West Carlsbad CA, USA), according to the manufacturer’s protocol. The concentration of extracted DNA was determined by Nanodrop 1000 (Thermo Scientific, Watham MA, USA), and DNA was stored at −20 °C until used.
Primers used for PCR in this study
Library preparation for high-throughput sequencing (HTS)
All samples were amplified and barcoded for multiplex pyrosequencing using primers targeted to the V4 region of the bacterial 16S rRNA gene under uniform PCR conditions that included 3 min at 94 °C and 45 cycles of 45 s at 94 °C, 60 s at 50 °C, and 90 s at 72 °C with final extension for 10 min at 72 °C . We used forward primer (AAT GAT ACG GCG ACC ACC GAG ATC TAC ACT ATG GTA ATT GTG TGC CAG CMG CCG CGG TAA) that includes a 5′ Illumina adaptor, forward primer pad, 2 bp linker and the 515F 16S rRNA primer, and reverse primer (CAA GCA GAA GAC GGC ATA CGA GAT NNNNNNNNNNNN—AGT CAG TCA G-CC-GGA CTA CHV GGG TWT CTA AT) that includes the Illumina 3′ adapter with 12-nt error-correcting Golay barcode, reverse primer pad, 2 bp linker and the 806R 16S rRNA primer. We ran PCR in triplicate using 0.2 µM of the primers, 1 µl of template and 1X HotMasterMix (5 PRIME, Gaithersburg MD, USA), and cleaned the products using a PCR Purification Kit (Qiagen) after pooling. Cleaned PCR products were quantified using the Qubit dsDNA HS Assay Kit (Invitrogen™, Eugene OR, USA), then adjusted to an optimal molarity as described. Sequencing was performed using the Illumina MiSeq platform in the NYULMC Genome Technology Core.
Taxonomic and ecological analyses
We analyzed all sequence data using the QIIME software (version Mac Qiime 1.8.0) . After filtering procedures, similar sequences were clustered into operational taxonomic units (OTUs) using an open reference approach with UCLUST  against the Greengenes Core set. A representative sequence was then aligned using PyNAST, and FastTree created phylogenetic trees. Rarefaction analysis used Chao-1 and whole PD to measure α-diversity. Unweighted UniFrac distances were calculated to assess β-diversity; the Unweighted paired group method with arithmetic mean (UPGMA) was performed for UniFrac-based jackknifed hierarchical clustering. Principal coordinates analysis (PCoA) of UniFrac distance matrices provided graphical representation using a KiNG, ANOVA was used to compare OTU and genus-level abundances, and Linear discriminant analysis (LDA) effect size (LEfSe), a tool that can compare differences of relative abundance between ≥2 biological conditions , also was used for analysis.
Quantifying bacteria in fecal DNA
Assessing total DNA concentrations using Nanodrop and total bacterial log10 copy number/ng DNA by qPCR, we found that they were similar between the control animals and those treated with either after antibiotic or pathogen challenge (Additional file 1: Figure S3, panels a–j). Thus, neither the antibiotic treatments nor the pathogen challenge affected the overall population size of the intestinal microbiota.
Assessment of mouse intestinal colonization after challenge
Assessment of gut microbiome changes associated with C. jejuni challenge and cage effects
Quantitative differences in specific taxa
We next analyzed the HTS results using LEfSe, identifying specific taxa that showed significant differences between mice at the beginning (6.5 weeks of life) and end (23.9 weeks) of the experiment (Additional file 1: Figure S4). Multiple taxa within Firmicutes, Bacilli, and Tenericutes were significantly increased at the early time point in the three groups of mice with only cage-related minor variations. In contrast, taxa within Bacteroides and Verrucomicrobia were significantly higher at the later time point in all groups. Animals in cage 2 showed significantly increased Proteobacteria, consistent with our finding of persistent C. jejuni colonization. Proteobacteria were not increased in cage 1 (control) as expected, nor in cage 3 after C. jejuni colonization had spontaneously ceased.
Detection of C. jejuni after mouse passage
Next, we investigated whether three C. jejuni strains with different passage histories varied in their abilities to colonize the mouse gastrointestinal tract after oral challenge (Additional file 1: Figure S5). All three C. jejuni strains showed similar kinetics; culture (panel A) and qPCR results (panel B) were consistent. Despite some variations in the kinetics of colonization, all three C. jejuni strains colonized the mouse gut to similar degrees.
Effect of antibiotic treatment on mouse intestinal colonization
Assessment of gut microbiota changes associated with bacterial challenge and antibiotic pre-treatment
We next performed analysis of β-diversity of the gut microbiota in relation to antibiotic treatment and pathogen challenge. As before, mice with no antibiotic treatment had nearly identical community structure, regardless of pathogen challenge. In the group of mice receiving ciprofloxacin, the no challenge group had minor changes in β-diversity compared to either the A. baumannii or C. jejuni challenged groups. As above, mice treated with penicillin showed dramatic changes in community structure. However, mice treated with penicillin and challenged with C. jejuni changed in β-diversity and then recovered immediately. Similar but less dramatic effects were observed in mice treated with penicillin and challenged with A. baumannii (Fig. 4, panel B).
Analysis of longitudinal inter-group phylogenic distances associated with bacterial challenge and antibiotic treatment
We observed minor β-diversity differences of the gut microbiota in the different mouse groups at time 1 (4.3 week) which was before antibiotic treatment and pathogen challenge. As such, we considered that the difference may be related to cage effects at that time point (Additional file 1: Figure S6, panel A). Next, we analyzed the intergroup variability at different time points in relation to antibiotic treatment and pathogen challenge, using the PERMANOVA metric. We did not observe significant differences in community structure in the mice challenged with either A. baumannii or C. jejuni without antibiotic pre-treatment (control groups) at any time point. In contrast, community structure in the mice treated with antibiotics and challenged with A. baumannii were significantly different from community structure before challenge. Furthermore, community structure of antibiotic-treated mice that were challenged with C. jejuni also were significantly different than pre-challenge (Data not shown). The community structure differences in the mice treated with penicillin and challenged with C. jejuni were significantly greater than before challenge (Additional file 1: Figure S7). Interestingly, these data suggest that the presence of C. jejuni minimized microbiome susceptibility to penicillin effects.
In mice without antibiotic pre-treatment, α-diversity was highest in the C. jejuni-challenged group; due to the short follow-up of the A. baumannii group, we could not assess changes. We consistently observed that in animals treated with penicillin, α-diversity was significantly increased in those challenged with C. jejuni; ciprofloxacin did not affect richness (Additional file 1: Figure S6, panel B).
In these studies, persistent colonization was achieved with C. jejuni, an intestinal pathogen, but not with A. baumannii, consistent with prior reports [28, 29]. We assessed the health status of the mice challenged with the pathogens and with or without antibiotic treatment and we did not notice any significant change in behavior or signs of disturbances in the health of mice that confirmed previous information that mice do not express disease after colonization with C. jejuni [30, 31].
Longitudinal assessment of bacterial gut community structure indicates that at early time points, essentially all mice were identical at the phylum level. However, as the experiments progressed, community structures varied, due to cage effects, and independently in relation to antibiotic treatment, or C. jejuni challenge.
However, the community richness in the gut microbiome was relatively constant, unaffected by cage, or antibiotic effects. Nevertheless, C. jejuni challenge increased richness, which was affected by penicillin pre-treatment. Mouse-adapted strains of C. jejuni were not better than a parental strain in mouse gut colonization. One hypothesis for the mechanism for the increased richness is that C. jejuni competes with dominant strains, permitting the more minor taxa to bloom. An alternative hypothesis is that C. jejuni infection stimulates production of anti-microbial peptides, as has been reported , and these select against the dominant taxa.
Antibiotic pre-treatment showed no effect on the capabilities of C. jejuni and A. baumannii to colonize the mice, which for A. baumannii was only transient. We recognized that variation in antibiotic concentration may cause different effects. However, in this study we used antibiotics equivalent of therapeutic doses used in humans to reach maximum antibiotic concentration in mice. Stable community structure was observed in mice for nearly 10 weeks whether challenged or not. Ciprofloxacin induced minor community-wide disturbances but penicillin induced major disturbances (Fig. 5).
In the absence of antibiotic pre-treatment, pathogen introduction did not affect relative abundances of the colonizing taxa either at the phyla (Fig. 5) or genus level (Data not shown). In contrast, antibiotic pre-treatment with ciprofloxacin produced minor disturbance of the gut microbiota when compare to penicillin. One explanation may be the lower activity of ciprofloxacin against anaerobes , in contrast to the known anti anaerobic activity of penicillin [34, 35]. Surprisingly, the introduction of A. baumannii or C. jejuni ameliorated the disturbances in the community structure, and facilitated the recovery to normality. We speculate that pathogen introduction affected either host responses that led to stereotypic changes, or to altered competition dynamics in the gut, favoring the status quo ante.
In conclusion, the susceptibility to gut colonization by A. baumannii and C. jejuni did not change despite the disruption of the gut microbiota of mice treated with antibiotics. The distruption of the gut mictobiota may be reduced by C. jejuni colonization but the mechanism is still unknown.
ribosomal ribonucleic acid
operational taxonomic units
principal coordinates analysis
linear discriminant analysis (LAD) effect size
TI, TT, WY, ZG, and GV performed the experiments. TI and AVA conducted the bioinformatics analysis. GPP and MJB conceived the project. TI, GPP, and MJB wrote the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
The data will be shared upon personal request.
Ethics approval and consent to participate
IACUC protocol #110504 was approved by New York University School of Medicine.
This work was supported in part by the US Army contract # W81XWH-11-1-0739, by the Diane Belfer Program in Human Microbial Ecology, the Ziff Family Fund, and the C & D Fund. The funders had no role in this study.
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