The intestinal microbiota is composed of hundreds of species of bacteria, fungi and protozoa and is critical for numerous biological processes, such as nutrient acquisition, vitamin production, and colonization resistance against bacterial pathogens. We studied the role of the intestinal microbiota on host resistance to Salmonella enterica serovar Typhimurium-induced colitis. Using multiple antibiotic treatments in 129S1/SvImJ mice, we showed that disruption of the intestinal microbiota alters host susceptibility to infection. Although all antibiotic treatments caused similar increases in pathogen colonization, the development of enterocolitis was seen only when streptomycin or vancomycin was used; no significant pathology was observed with the use of metronidazole. Interestingly, metronidazole-treated and infected C57BL/6 mice developed severe pathology. We hypothesized that the intestinal microbiota confers resistance to infectious colitis without affecting the ability of S. Typhimurium to colonize the intestine. Indeed, different antibiotic treatments caused distinct shifts in the intestinal microbiota prior to infection. Through fluorescence in situ hybridization, terminal restriction fragment length polymorphism, and real-time PCR, we showed that there is a strong correlation between the intestinal microbiota composition before infection and susceptibility to Salmonella-induced colitis. Members of the Bacteroidetes phylum were present at significantly higher levels in mice resistant to colitis. Further analysis revealed that Porphyromonadaceae levels were also increased in these mice. Conversely, there was a positive correlation between the abundance of Lactobacillus sp. and predisposition to colitis. Our data suggests that different members of the microbiota might be associated with S. Typhimurium colonization and colitis. Dissecting the mechanisms involved in resistance to infection and inflammation will be critical for the development of therapeutic and preventative measures against enteric pathogens.
The intestinal microbiota is composed of hundreds of species of bacteria, fungi and protozoa and is critical for numerous biological processes, such as nutrient acquisition, vitamin production, and colonization resistance against bacterial pathogens. We studied the role of the intestinal microbiota on host resistance to Salmonella enterica serovar Typhimurium-induced colitis. Using multiple antibiotic treatments in 129S1/SvImJ mice, we showed that disruption of the intestinal microbiota alters host susceptibility to infection. Although all antibiotic treatments caused similar increases in pathogen colonization, the development of enterocolitis was seen only when streptomycin or vancomycin was used; no significant pathology was observed with the use of metronidazole. Interestingly, metronidazole-treated and infected C57BL/6 mice developed severe pathology. We hypothesized that the intestinal microbiota confers resistance to infectious colitis without affecting the ability of S. Typhimurium to colonize the intestine. Indeed, different antibiotic treatments caused distinct shifts in the intestinal microbiota prior to infection. Through fluorescence in situ hybridization, terminal restriction fragment length polymorphism, and real-time PCR, we showed that there is a strong correlation between the intestinal microbiota composition before infection and susceptibility to Salmonella-induced colitis. Members of the Bacteroidetes phylum were present at significantly higher levels in mice resistant to colitis. Further analysis revealed that Porphyromonadaceae levels were also increased in these mice. Conversely, there was a positive correlation between the abundance of Lactobacillus sp. and predisposition to colitis. Our data suggests that different members of the microbiota might be associated with S. Typhimurium colonization and colitis. Dissecting the mechanisms involved in resistance to infection and inflammation will be critical for the development of therapeutic and preventative measures against enteric pathogens.
The mammalian intestinal microbiota is a highly complex community of microorganisms
that live in close association with its host. These microbes are important in
numerous biological processes and are essential for health. The phyla Firmicutes and
Bacteroidetes (BAC) comprise 90% of the intestinal microbiota, whereas
members of the Proteobacteria, Actinobacteria, Verrucomicrobia and Cyanobacteria are
present in low amounts [1]. The importance of the intestinal microbiota in human
health is increasingly acknowledged and a surge in the number of research papers on
the subject have been published in recent years. Imbalances of the intestinal
microbiota composition have been linked to several diseases such as diabetes,
inflammatory bowel disease, colorectal cancer and atopic diseases [2], [3], [4], [5].Salmonella enterica serovar Typhimurium are Gram-negative,
facultative intracellular pathogens that cause a wide range of human illnesses, from
typhoid fever to gastroenteritis. In mice, S. Typhimurium normally
causes a disease that resembles systemic typhoid fever. However, streptomycin
treatment prior to S. Typhimuriuminfection in mice leads to a
disease similar to salmonellosis in humans. Salmonellosis is marked by increased
S. Typhimurium colonization of the intestines and a strong
inflammatory response leading to colitis [6]. Recent work in our lab
described that treatments with low doses of streptomycin, a broad-spectrum
antibiotic, and vancomycin, an antibiotic targeting Gram-positive bacteria, altered
the intestinal microbiota composition of C57BL/6 mice and increased susceptibility
to S. Typhimuriuminfection and intestinal pathology, without
changing overall numbers of intestinal microbiota [7].In this study, we used several antibiotics to modify the intestinal microbiota
composition of 129S1/SvImJ mice, which are more resistant to S.
Typhimurium infection than C57BL/6 mice. We showed that there is a strong
correlation between distinct subsets of the intestinal microbiota and protection
against S. Typhimurium colonization and associated colitis in this
model. While treatments with streptomycin and vancomycin increased both
S. Typhimurium colonization and intestinal inflammation, we
found that metronidazole treatment significantly increased colonization by
S. Typhimurium without inducing colitis. However, metronidazole
treatment in C57BL/6 mice increased both colonization and colitis, similar to the
effects of streptomycin treatment in both mouse strains. Differences in the
intestinal microbiota composition of these murine strains following metronidazole
treatment and similarities between streptomycin-treated 129S1/SvImJ and
metronidazole-treated C57BL/6 mice suggest that specific members of the microbiota
are associated with the development of colitis. A better understanding of the role
of specific members of the microbiota in resistance to infection will help
facilitate the development of mechanisms to manipulate the intestinal microbiota for
human benefit.
Results
Streptomycin, vancomycin and metronidazole treatments increase intestinal
colonization by S. Typhimurium
In order to study the impact of antibiotic treatment on host susceptibility to
infection, we treated 129S1/SvImJ mice with antibiotics in their drinking water
before oral infection with S. Typhimurium. Four days
post-infection, mice were sacrificed and samples from caecum, spleen and feces
were analyzed. S. Typhimurium caecal colonization was increased
over ten-fold in streptomycin-, vancomycin- and metronidazole-treated mice
compared to control-infected mice (Figure 1A). S. Typhimurium counts were similar
between mice treated with each of the different antibiotics. Colonization levels
in feces were comparable to the counts obtained in caecal samples (Figure 1B). At the systemic
level (spleen), S. Typhimurium counts did not significantly
change after antibiotic treatment compared to the infected control mice (data
not shown).
Figure 1
Different antibiotic treatments lead to different degrees of
intestinal pathology in 129S1/SvImJ mice.
A. S. Typhimurium levels in caeca of 129S1/SvImJ mice
after 4 days of infection with or without antibiotic treatment. B.
S. Typhimurium levels in feces of 129S1/SvImJ mice
after 4 days of infection with or without antibiotic treatment. C.
H&E staining of caeca of 129S1/SvImJ mice. (a). infected 129S1/SvImJ
mice; (b). metronidazole-treated and infected 129S1/SvImJ mice; (c).
streptomycin-treated and infected 129S1/SvImJ mice; (d).
vancomycin-treated and infected 129S1/SvImJ mice. D. Pathology scores of
caeca of 129S1/SvImJ mice after 4 days of infection with or without
antibiotic treatment. E. Levels of IL6 in caecal samples measured by
ELISA. F. Levels of IL8 in caecal samples measured by ELISA. G. Levels
of IFNγ in caecal samples measured by ELISA. Met: metronidazole (750
mg/L), Strep: streptomycin (450 mg/L) and Vanco: vancomycin (50 mg/L).
Black bars represent pathology scores of the intestinal lumen, white
bars represent scores of the surface epithelia, dark grey bars represent
scores of the mucosa and light grey bars represent scores of the
submucosa of the tissue. ns: not significant; *:
p<0.05; **: p<0.01; ***: p≤0.001.
Experiments were performed three times with at least 4 mice in each
group.
Different antibiotic treatments lead to different degrees of
intestinal pathology in 129S1/SvImJ mice.
A. S. Typhimurium levels in caeca of 129S1/SvImJ mice
after 4 days of infection with or without antibiotic treatment. B.
S. Typhimurium levels in feces of 129S1/SvImJ mice
after 4 days of infection with or without antibiotic treatment. C.
H&E staining of caeca of 129S1/SvImJ mice. (a). infected 129S1/SvImJ
mice; (b). metronidazole-treated and infected 129S1/SvImJ mice; (c).
streptomycin-treated and infected 129S1/SvImJ mice; (d).
vancomycin-treated and infected 129S1/SvImJ mice. D. Pathology scores of
caeca of 129S1/SvImJ mice after 4 days of infection with or without
antibiotic treatment. E. Levels of IL6 in caecal samples measured by
ELISA. F. Levels of IL8 in caecal samples measured by ELISA. G. Levels
of IFNγ in caecal samples measured by ELISA. Met: metronidazole (750
mg/L), Strep: streptomycin (450 mg/L) and Vanco: vancomycin (50 mg/L).
Black bars represent pathology scores of the intestinal lumen, white
bars represent scores of the surface epithelia, dark grey bars represent
scores of the mucosa and light grey bars represent scores of the
submucosa of the tissue. ns: not significant; *:
p<0.05; **: p<0.01; ***: p≤0.001.
Experiments were performed three times with at least 4 mice in each
group.
Metronidazole treatment does not increase intestinal pathology of
Salmonella-infected 129S1/SvImJ mice
After S. Typhimuriuminfection, we observed that the intestines
of infected-only and metronidazole-treated infected mice had a similar
appearance, suggesting that treatment with this antibiotic did not increase
inflammation following infection. However, the intestines of streptomycin- and
vancomycin-treated mice appeared shorter and lacked fecal matter, classical
macroscopic signs of S. Typhimurium-induced colitis (data not
shown). In agreement with our macroscopic observations, histological evaluation
of haematoxilin-eosin stained caecal tissues from metronidazole-treated and
infected mice showed limited signs of inflammation (Figure 1C). On the other hand, tissues from
streptomycin- and vancomycin-treated infected mice displayed markers of
significant inflammation, with severe edema of the submucosa, necrotic cells and
neutrophils in the lumen and widespread presence of polymorphonuclear leukocytes
(PMNs) in the epithelium. The degree of tissue inflammation was further analyzed
through pathological scoring of caecal samples (Figure 1D). Pathology scores were
significantly different between metronidazole-treated infected mice and
streptomycin and vancomycin-treated infected mice, with the latter two showing
significantly stronger intestinal pathology. These results indicate that even
though S. Typhimurium colonization levels were similar after
each antibiotic treatment, the intestinal pathology observed was strikingly
different. Unlike streptomycin and vancomycin, metronidazole pre-treatment does
not exacerbate S. Typhimurium-induced colitis. In order to gain
insights into the inflammation invoked by S. Typhimuriuminfection after antibiotic pre-treatment, caecal cytokine levels of 129S1/SvImJ
were analyzed by ELISAs (Figure 1E,
1F and 1G). Metronidazole treatment prior to S.
Typhimurium infection in 129S1/SvImJ mice did not significantly change IL6, IL8
or IFNγ production. However, streptomycin-treated and infected 129S1/SvImJ
mice showed increased levels of the cytokines tested. These data are in
agreement with the severe caecal pathology observed in these mice, as these
cytokines are involved in pro-inflammatory responses.
Metronidazole treatment increases intestinal pathology in
Salmonella-infected C57BL/6 mice
In order to further characterize the phenotype seen with metronidazole treatment,
we investigated the effects of this antibiotic in C57BL/6 mice prior to
infection and compared the results with those seen with 129S1/SvImJ mice.
Consistent with what was observed with 129S1/SvImJ mice, metronidazole treatment
of C57BL/6 animals significantly increased S. Typhimurium
colonization of caecum and feces by over 10-fold (Figure 2A and 2B). However, contrary to our
observations of metronidazole-treated 129S1/SvImJ, treatment of C57BL/6 mice
with this antibiotic significantly increased intestinal pathology (Figure 2C and 2D). Cytokine
levels in the ceacum of C57BL/6 mice were also analyzed (Fig 2E, 2F and 2G). Metronidazole-treated and
infected mice showed increased levels of IL6, IL8 and IFNγ compared to
control mice, in agreement with the pathology observed in these mice. Altogether
these data indicate that the same antibiotic can have opposite effects on
different strains of mice, presumably due to differences in microbiota and/or
host genetic background.
Figure 2
Metronidazole treatment prior to S. Typhimurium infection
induces colitis in C57BL/6 mice.
A. S. Typhimurium levels in caeca of C57BL/6 mice after
4 days of infection with or without antibiotic treatment. B.
S. Typhimurium levels in feces of C57BL/6 mice
after 4 days of infection with or without antibiotic treatment. C.
H&E staining of caeca of C57BL/6 mice. (a). infected C57BL/6 mice;
(b). metronidazole-treated and infected C57BL/6 mice. D. Pathology
scores of caeca of C57BL/6 mice after 4 days of infection with or
without metronidazole treatment. E. Levels of IL6 in caecal samples
measured by ELISA. F. Levels of IL8 in caecal samples measured by ELISA.
G. Levels of IFNγ in caecal samples measured by ELISA. Met:
metronidazole (750 mg/L). Black bars represent pathology scores of the
intestinal lumen, white bars represent scores of the surface epithelia,
dark grey bars represent scores of the mucosa and light grey bars
represent scores of the submucosa of the tissue. *: p<0.05;
**: p<0.01. Experiments were performed three times with at
least 4 mice in each group.
Metronidazole treatment prior to S. Typhimurium infection
induces colitis in C57BL/6 mice.
A. S. Typhimurium levels in caeca of C57BL/6 mice after
4 days of infection with or without antibiotic treatment. B.
S. Typhimurium levels in feces of C57BL/6 mice
after 4 days of infection with or without antibiotic treatment. C.
H&E staining of caeca of C57BL/6 mice. (a). infected C57BL/6 mice;
(b). metronidazole-treated and infected C57BL/6 mice. D. Pathology
scores of caeca of C57BL/6 mice after 4 days of infection with or
without metronidazole treatment. E. Levels of IL6 in caecal samples
measured by ELISA. F. Levels of IL8 in caecal samples measured by ELISA.
G. Levels of IFNγ in caecal samples measured by ELISA. Met:
metronidazole (750 mg/L). Black bars represent pathology scores of the
intestinal lumen, white bars represent scores of the surface epithelia,
dark grey bars represent scores of the mucosa and light grey bars
represent scores of the submucosa of the tissue. *: p<0.05;
**: p<0.01. Experiments were performed three times with at
least 4 mice in each group.
The difference in susceptibility to colitis displayed by
metronidazole-treated C57BL/6 and 129S1/SvImJ mice is not due to Nramp1
One of the major differences between 129S1/SvImJ and C57BL/6 mice is their Nramp1
(Natural resistance-associated macrophage protein 1, also called Slc11a1)
status, which represents a critical host defense mechanism against
S. Typhimurium [8]. C57BL/6 mice are Nramp1
−/− and, therefore, highly susceptible to S.
Typhimurium, succumbing to the disease within 5 days of infection. 129S1/SvImJ
mice are Nramp1 +/+ and, as such, are more resistant to and generally
able to control the infection. Therefore, we investigated whether the difference
in susceptibility to colitis between metronidazole-treated C57BL/6 and
129S1/SvImJ mice was due to their Nramp1 status. To do so, both 129S1/SvImJ
Nramp1 −/− and +/+ mice were treated with metronidazole
prior to infection. Our results showed that metronidazole treatment increased
S. Typhimurium colonization without increasing caecal
inflammation in both Nramp1 −/− and +/+ mice (Figure S1).
Therefore, the differences between metronidazole treated 129S1/SvImJ and C57BL/6
mice are not a result of differences in their Nramp1 status.
The susceptibility to colitis caused by antibiotic treatment correlates with
differences in the composition of the intestinal microbiota
Initially, we investigated if bacterial abundance was affected by the antibiotic
treatments through SYBR green staining of fecal samples. Total intestinal
bacterial numbers did not significantly change after any of the antibiotic
treatments (Figure 3A),
suggesting that the changes observed are not simply due to a decrease in total
commensal numbers. We also analyzed the total number of viable bacteria in fecal
samples under aerobic and anaerobic conditions. No significant changes were
observed when the total number of colonies grown under both conditions was
combined. However, a significant change was observed in the total number of
colonies grown under aerobiosis in streptomycin-treated 129S1/SvImJ mice (Figure S2).
Terminal-restriction fragment length polymorphism (TRFLP) was used to assess the
bacterial 16S rRNA composition of the feces of antibiotic-treated uninfected
mice. The use of fecal samples allowed us to collect multiple samples from the
same mouse at different points of the treatment without having to euthanize the
animal. However, to ensure that the results obtained with these samples were
representative of what occurred in the caecum, caecal microbiota was also
analyzed by TRFLP. No significant differences between the fecal and caecal
samples of mice from the same treatment were observed (data not shown). The
composition of each fecal sample was plotted using non-metric multidimensional
scaling (NMS) ordination based on Sorensen distance measure to assess overall
changes in microbial community composition between treatment groups [9]. Both
metronidazole and streptomycin treatment in 129S1/SvImJ mice resulted in changes
in microbial composition (p<0.05, p<0.005, respectively) (Figure 3B and 3C). However,
streptomycin and metronidazole had distinct effects on the fecal microbial
composition (p<0.001) , causing changes in the microbiota
that were positively and negatively correlated with caecal pathology upon
infection, respectively. The effect of metronidazole treatment on the fecal
microbiota of C57BL/6 mice was also compared to metronidazole-treated
129S1/SvlmJ mice (Figure 3D and
3E). Despite the fact that the fecal microbiota of the two mouse
strains was relatively similar before antibiotic treatment, metronidazole had a
more marked effect on the microbiota of C57BL/6 mice (p<0.005). Again, these
changes correlate well with the pathology observed after S.
Typhimurium infection, as streptomycin-treated 129S1/SvImJ and
metronidazole-treated C57BL/6 mice exhibited stronger colitis compared to
metronidazole-treated 129S1/SvImJ mice. The microbial diversity, as assessed by
Simpson's index of diversity [10], indicate that streptomycin
treatment decreased diversity (p<0.05) in 129S1/SvImJ mice, whereas
metronidazole did not (Figure
3F). Interestingly, metronidazole treatment of C57BL/6 mice did not
significantly alter the microbial diversity. Although this may seem
contradictory to our hypothesis that these parameters of microbiota structure
are responsible for susceptibility to colitis, it is important to note that the
diversity of C57BL/6 mice was much lower than that observed in 129S1/SvImJ mice.
It is possible that this is an important determinant that may be predisposing
C57BL/6 mice to antibiotic-induced colitis.
Figure 3
Different antibiotics have distinct effects on the composition of the
intestinal microbiota.
A. Total bacterial counts of fecal samples of 129S1/SvImJ and C57BL/6
uninfected mice before and after antibiotic treatments, as determined by
SYBR Green staining. B. Non-metrical multidimentional scaling (NMS)
ordination of Terminal restriction fragment length polymorphism (TRFLP)
data of 129S1/SvImJ uninfected mice before and after streptomycin or
metronidazole treatment. Black triangles: naïve 129S1/SvImJ; green
circles: metronidazole-treated 129S1/SvImJ; blue squares:
streptomycin-treated 129S1/SvImJ. C. Dendrogram of TRFLP data of
129S1/SvImJ mice before and after streptomycin or metronidazole
treatment. D. NMS ordination of TRFLP data of 129S1/SvImJ and C57BL/6
mice before and after metronidazole treatment. Black triangles:
naïve 129S1/SvImJ; green circles: naïve C57BL/6; blue squares:
metronidazole-treated 129S1/SvImJ; pink inverted triangles:
metronidazole-treated C57BL/6. E. Dendrogram of TRFLP data of
129S1/SvImJ and C57BL/6 mice before and after metronidazole treatment F.
Microbial diversity in feces (Simpson's diversity index) before and
after the antibiotic treatments. Met: metronidazole (750 mg/ L) and
Strep: streptomycin (450 mg/ L). ns: not significant;
*: p<0.05; **: p<0.01; ***: p≤0.001.
Experiments were performed three times with at least 4 mice in each
group.
Different antibiotics have distinct effects on the composition of the
intestinal microbiota.
A. Total bacterial counts of fecal samples of 129S1/SvImJ and C57BL/6
uninfected mice before and after antibiotic treatments, as determined by
SYBR Green staining. B. Non-metrical multidimentional scaling (NMS)
ordination of Terminal restriction fragment length polymorphism (TRFLP)
data of 129S1/SvImJ uninfected mice before and after streptomycin or
metronidazole treatment. Black triangles: naïve 129S1/SvImJ; green
circles: metronidazole-treated 129S1/SvImJ; blue squares:
streptomycin-treated 129S1/SvImJ. C. Dendrogram of TRFLP data of
129S1/SvImJ mice before and after streptomycin or metronidazole
treatment. D. NMS ordination of TRFLP data of 129S1/SvImJ and C57BL/6
mice before and after metronidazole treatment. Black triangles:
naïve 129S1/SvImJ; green circles: naïve C57BL/6; blue squares:
metronidazole-treated 129S1/SvImJ; pink inverted triangles:
metronidazole-treated C57BL/6. E. Dendrogram of TRFLP data of
129S1/SvImJ and C57BL/6 mice before and after metronidazole treatment F.
Microbial diversity in feces (Simpson's diversity index) before and
after the antibiotic treatments. Met: metronidazole (750 mg/ L) and
Strep: streptomycin (450 mg/ L). ns: not significant;
*: p<0.05; **: p<0.01; ***: p≤0.001.
Experiments were performed three times with at least 4 mice in each
group.
Specific subsets of the intestinal microbiota can be correlated with
protection against colitis
By comparing the abundance of individual terminal restriction fragment (TRF)
lengths in protective versus non-protective conditions it was possible to
identify a small subset of TRFs that were negatively and positively correlated
with susceptibility to colitis. Clone libraries of 16S rRNA genes were generated
and screened with restriction digestion to allow for phylogenetic assignment of
TRFs of interest. TRFs in the range of 83 to 87 bp remained abundant after
metronidazole treatment of 129S1/SvImJ mice, but were significantly decreased in
colitis-susceptible mice, thus representing potentially protective organisms
(Figure 4A). Clones
corresponding to these TRFs were all classified within the family
Porphyromonadaceae from the Bacteroidetes phylum. Conversely, TRF188, identified
as Lactobacillus, was present at increased levels in
streptomycin-treated 129S1/SvImJ and metronidazole-treated C57BL/6, but was not
detectable after metronidazole treatment of 129S1/SvImJ, and was thus positively
correlated with colitis susceptibility (Figure 4C). We also found that TRF154 was
present at significantly higher levels in metronizadole-treated 129S1/SvImJ, but
was unaffected by other treatments (Figure 4B). Clones corresponding to this TRF were classified within
the family Lachnospiraceae. It is important to note that an attempt to grow
viable bacteria from the fecal microbiota of the different groups in selective
media showed no correlation with the phenotypes observed in mice (data not
shown). This highlights the importance of DNA-based methodologies to thoroughly
analyze the composition of the intestinal microbiota.
Figure 4
Specific members of the microbiota are involved in predisposition to
colitis.
The contribution of individual peaks to the total peak intensity of each
sample was determined through TRFLP analyses. A. Porphyromonadaceae (TFR
83–87). B. Lachnospiraceae (TRF 154). C.
Lactobacillus sp. (TRF 187–188).
ns: not significant; *: p<0.05; **:
p<0.01; ***: p≤0.001. Experiments were performed three
times with at least 4 mice in each group.
Specific members of the microbiota are involved in predisposition to
colitis.
The contribution of individual peaks to the total peak intensity of each
sample was determined through TRFLP analyses. A. Porphyromonadaceae (TFR
83–87). B. Lachnospiraceae (TRF 154). C.
Lactobacillus sp. (TRF 187–188).
ns: not significant; *: p<0.05; **:
p<0.01; ***: p≤0.001. Experiments were performed three
times with at least 4 mice in each group.Fluorescent in situ hybridization (FISH) was also performed to
further analyze the microbial composition of the intestinal microbiota at the
phylum level. For this purpose, we used specific probes to calculate the
percentages of Bacteroidetes (BAC), Gammaproteobacteria (GAM) and Firmicutes and
others (FIM) in the intestinal microbiota. Consistent with the TRFLP data,
metronidazole treatment caused an increase in the BAC numbers in 129S1/SvImJ
mice (Figure 5) whereas a
depletion of this microbial group was seen in streptomycin-treated 129S1/SvImJ
and metronidazole-treated C57BL/6 mice. Therefore, BAC abundance could correlate
with resistance to colitis. On the other hand, increased GAM numbers were
observed in colitis-susceptible mice prior to infection and seemed to correlate
with increased susceptibility to colitis.
Figure 5
Predisposition to colitis can be associated with phylum-level changes
in the composition of the intestinal microbiota caused by antibiotic
treatments.
Fluorescent in situ hybridization (FISH) of fecal
samples of 129S1/SvImJ and C57BL/6 mice before and after antibiotic
treatment. Met: metronidazole (750 mg/ L) and Strep: streptomycin (450
mg/ L). Black bars represent the percentage of bacteria belonging to the
BAC phyla. White bars represent the percentage of bacteria belonging to
the GAM phyla and gray bars represent the percentage of Firmicutes and
other groups. Experiments were performed three times with at least 4
mice in each group.
Predisposition to colitis can be associated with phylum-level changes
in the composition of the intestinal microbiota caused by antibiotic
treatments.
Fluorescent in situ hybridization (FISH) of fecal
samples of 129S1/SvImJ and C57BL/6 mice before and after antibiotic
treatment. Met: metronidazole (750 mg/ L) and Strep: streptomycin (450
mg/ L). Black bars represent the percentage of bacteria belonging to the
BAC phyla. White bars represent the percentage of bacteria belonging to
the GAM phyla and gray bars represent the percentage of Firmicutes and
other groups. Experiments were performed three times with at least 4
mice in each group.Real-time PCR was used to confirm the results of TRFLP and clone-library data,
and to further characterize the abundance of specific bacterial subsets that
were below detection levels of community profiling techniques. Because of the
differences in the Bacteroidetes numbers between the groups predisposed or
resistant to colitis, we investigated the levels of Mouse Intestinal Bacteria
(MIB) [11], a
subset of Porphyromonadaceae, in these mice. We also confirmed the results
obtained by TRFLP, which showed a prevalence of TRF188, identified as
Lactobacillus sp., in samples of mice predisposed to
colitis. We observed that MIB levels did not significantly change after
streptomycin treatment of 129S1/SvImJ or metronidazole treatment of C57BL/6
mice, both models that are predisposed to colitis. In contrast, MIB levels were
significantly increased after metronidazole treatment of 129S1/SvImJ (Figure 6A). The opposite was
seen when we analyzed Lactobacillus numbers, which increased
after streptomycin (colitis-inducing) but not metronidazole (colitis
non-inducing) treatment of 129S1/SvImJ (Figure 6B).
Figure 6
MIB and Lactobacillus sp. levels are associated to
predisposition to S. Typhimurium-induced
colitis.
A. Levels of MIB on fecal samples of 129S1/SvImJ and C57BL/6 mice before
and after antibiotic treatment, as determined by RT-PCR. B. Levels of
Lactobacillus on fecal samples of 129S1/SvImJ and
C57BL/6 mice before and after antibiotic treatment, as determined by
RT-PCR. ns: not significant; *: p<0.05;
**: p<0.01; ***: p≤0.001. Experiments were
performed three times with at least 4 mice in each group.
MIB and Lactobacillus sp. levels are associated to
predisposition to S. Typhimurium-induced
colitis.
A. Levels of MIB on fecal samples of 129S1/SvImJ and C57BL/6 mice before
and after antibiotic treatment, as determined by RT-PCR. B. Levels of
Lactobacillus on fecal samples of 129S1/SvImJ and
C57BL/6 mice before and after antibiotic treatment, as determined by
RT-PCR. ns: not significant; *: p<0.05;
**: p<0.01; ***: p≤0.001. Experiments were
performed three times with at least 4 mice in each group.Because of the recent data on metronidazole treatment increasing
Bifidobacteria presence in the colon of rats [12], the
presence of Bifidobacteria was also determined in our models.
Bifidobacteria were below detection levels in 129S1/SvImJ
mice, but significantly increased after metronidazole treatment of C57BL/6 (data
not shown). Additionally, segmented filamentous bacteria (SFB) have also been
shown to be an important component of the intestinal microbiota, increasing
resistance to the mouse pathogen Citrobacter rodentium
[13], [14].
In our models, the presence of SFB could not be detected in any of the samples
analyzed (data not shown), suggesting that these bacteria are not involved in
the development of colitis described here.
Discussion
Changes in the intestinal microbiota have been described as important players in a
vast number of both intestinal and extra-intestinal diseases [15], [16]. It has been shown that the
composition of the intestinal microbiota protects mice from S.
Typhimurium colonization in the gut [7]. In the present study, we
describe that the inflammatory process elicited during S.
Typhimurium-induced colitis is not due only to high levels of S.
Typhimurium encountered in the intestine after antibiotic treatment. Although
129S1/SvImJ mice treated with metronidazole prior to infection had high levels of
S. Typhimurium intestinal colonization, they did not develop
severe caecal pathology and did not show increased levels of pro-inflammatory
cytokines. On the other hand, mice treated with streptomycin had high levels of
S. Typhimurium as well as marked signs of infectious colitis.
We also showed that metronidazole induces distinct caecal pathologies and
inflammatory responses in 129S1/SvImJ and C57BL/6 mice, which coincided with
differences in microbiota populations. This indicates that differences in host
microbiota might explain the differences in the outcome of infection observed in our
study. The results obtained herein reflect the effect of the specific antibiotic
treatments described. Different antibiotic doses and different treatment regimens
may have had different outcomes in the intestinal pathologies and host responses
observed. Metronidazole is a nitroimidazole antibiotic effective against anaerobes
that is routinely used in the treatment of inflammatory bowel diseases (IBD) and has
been shown to decrease postoperative recurrence in Crohn's disease (CD)
patients [17],
diseases linked to uncontrolled immune responses to the intestinal microbiota.
However, the effectiveness of the use of metronidazole in the treatment of CD is
still under debate [18]. Some studies have shown a positive effect of this drug
on CD treatment [17], [19], [20], whereas others show no significant difference between
metronidazole treatment and the placebo [21], [22].The two strains of mice used in our models, 129S1/SvImJ and C57BL/6, are commonly
used as resistant and susceptible typhoid infection models, respectively [23], [24]. One difference
in these mice is that C57BL/6 mice possess a point mutation in the gene encoding
Nramp1, leading to a non-functional protein. As a result, these mice are susceptible
to S. Typhimurium, and succumb to uncontrolled bacterial
replication [23].
129S1/SvImJ, on the other hand, express Nramp1 and are able to survive
S. Typhimuriuminfection [23]. Therefore, we investigated
whether Nramp1 status was the determining factor in the differences in
susceptibility to colitis upon metronidazole treatment displayed by these two mouse
strains. The intestinal pathology of infected 129S1/SvImJ and an isogenic mutant of
Nramp1 −/− after metronidazole treatment was analyzed and no differences
were observed, indicating that Nramp1 is not involved in this phenomenon. Although
one of the major differences between 129S1/SvImJ and C57BL/6 mouse strains is Nramp1
expression, there are other genetic differences with known impacts on inflammatory
responses, such as C5 deficiency and Vnn haplotype differences that may be playing a
role in these phenotypic differences [25], [26], [27], [28]. We hypothesize that differences
in the intestinal microbiota between these two models may be one of the important
factors in determining susceptibility to colitis.In this work, we explored the intestinal microbiota composition as a player in the
development of S. Typhimurium-induced colitis in mice. We
demonstrated that significant differences in the composition of the intestinal
microbiota during antibiotic treatment of the two different mouse strains are
strongly associated with predisposition to colitis. By comparing streptomycin versus
metronidazole treatment of 129S1/SvImJ and metronidazole treatment of C57BL/6 versus
129S1/SvImJ, we were able to circumvent issues related to host genetics and
potential direct effects of antibiotics on the host, thus substantiating the role of
the microbiota in infection. Our data suggests that specific members of the
microbiota are linked to protection against inflammation but do not affect
S. Typhimurium colonization. These members are overrepresented
when 129S1/SvImJ mice are treated with metronidazole, but they decrease or are
unchanged after streptomycin treatment in these mice or metronidazole treatment in
C57BL/6 mice. Our data indicates that they belong to the Bacteroidetes (BAC) phylum,
particularly to the Porphyromonadaceae family, which is represented here by Mouse
Intestinal Bacteria (MIB). MIB are part of a recently discovered operational
taxonomic unit (OTU), which is very closely related to Bacteroides.
It is present in all parts of the intestinal tract of mice [11] and is also found in lower
numbers in human feces [29]. In addition to the increased numbers of MIB in mice
resistant to S. Typhimurium-induced colitis, we also found
bacterial groups that seem correlated with susceptibility to colitis. These include
Lactobacillus sp., which belong to the Firmicutes phylum and
are present in the intestinal tract of many animals [11]. Several studies have shown a
positive effect of different species of Lactobacillus on protecting
against intestinal pathophysiology [30]. However, most clinical
trials showed that these bacteria were not able to induce remission in IBDpatients
[31], [32], [33]. Our data
indicates that Lactobacillus sp. levels are significantly increased
in streptomycin-treated 129S1/SvImJ and metronidazole-treated C57BL/6 mice, both
predisposed to infectious colitis. In agreement with this finding, a recent study
revealed that certain prebiotics, which stimulate the growth of
Lactobacillus sp., among other bacteria, increase the severity
of S. Typhimuriuminfection in mice [34]. The increase of
Lactobacillus sp. occurred only in instance of reduced
Bacteroidetes, and therefore it is not possible to determine which one of these
events is responsible for the control of the inflammatory response to
Salmonella infection observed herein. Furthermore, the fact
that Lactobacillus sp. levels in control C57BL/6 mice (resistant to
colitis) are higher than in streptomycin-treated 129S1/SvImJ mice (susceptible to
colitis) (Figure 4C) indicates
an indirect effect of these species on susceptibility to colitis. Although a strong
correlation is shown here, further studies are necessary to prove a definitive
causal link between these bacteria and S. Typhimurium-induced
colitis.Recently, it was shown that metronidazole alters the gut microbiota of rats and
reduces basal oxidative stress to proteins in colonic tissue. It has also been
demonstrated that this antibiotic increases the thickness of the mucus layer and the
presence of Bifidobacteria, which would decrease intestinal
inflammation in IBDpatients [12]. In our model, metronidazole treatment induces protection
against S. Typhimurium-induced intestinal inflammation only in one
of the mouse strains tested. It is important to note that treatment with this
antibiotic did not increase the presence of Bifidobacteria in these
mice, suggesting that the potentially protective role of
Bifidobacteria in rats is distinct from the phenotype observed
in our study.Our data strongly support the notion that specific microbial components of the
intestinal microbiota determine predisposition to colitis. Since it has been known
for several decades that the intestinal microbiota protects against
S. Typhimurium colonization, it has been generally assumed that
the protection against colitis was a consequence of reduced levels of
S. Typhimurium in the intestines of untreated mice. However,
our study adds another layer of complexity to the role of the microbiota in
protection against infectious agents. We now know that the protection against
colonization and inflammation are two independent events, and that different subsets
of the microbiota are responsible for each aspect of disease resistance. It has been
know that certain commensals produce molecules that can affect the host immune
system and protect against intestinal inflammation [35], [36] and this might be the case in
our study. Dissecting the potentially numerous unidentified roles of microbial
members of the intestinal biota will be fundamental in our quest towards
understanding the complexities of the human body and its relationship with our
microbe partners.
Materials and Methods
Ethics Statement
All animal experiments were performed in strict accordance with the guidelines of
the University of British Columbia Animal Care Committee and the Canadian
Council on the Use of Laboratory Animals. The protocol was approved by the UBC
Animal Care Committee (Certificate number: A09-0168). The mice were euthanized
by CO2 asphyxiation and all efforts were made to minimize
suffering.
Mice
Female, age-matched (6–8 weeks old) C57BL/6 and 129Sv/ImJ Nramp1
−/− and Nramp1 +/+ [8], [37] mice were obtained from
Jackson Laboratory (Bar Harbor, ME) or from a breeding colony maintained at the
Wesbrook Animal Unit at The University of British Columbia. Nramp1
−/− mice have a null allele at the Nramp1 locus (the Nramp1 gene was
interrupted by an inserted neomycin cassette), and thus, mRNA transcripts are
absent. Mice were fed a standard sterile chow diet (Laboratory Rodent Diet 5001,
Purina Mills, St. Louis, Missouri) ad libitum throughout the
experiments.
Bacterial Strains
Salmonella enterica serovar Typhimurium strain SL1344 [38] was grown
overnight at 37°C with shaking (200 rpm) in Luria-Bertani (LB) broth. This
strain is resistant to streptomycin, metronidazole and vancomycin.
Antibiotic treatments and S. Typhimurium infection
Mice were treated with 450 mg/L of streptomycin (Sigma) or 50 mg/L vancomycin
(Sigma) in drinking water for 2 days or 750 mg/L of metronidazole (Sigma) in
drinking water for 7 days. Antibiotics were dissolved in filter-sterilized
water; control mice were given water without antibiotics. After the antibiotic
treatment period, regular drinking water was returned and mice were infected
with ∼2.7×108
S. Typhimurium in LB broth by oral gavage. Uninfected control
mice were given 100 µL of sterile LB broth. At 4 days post-infection, mice
were euthanized by CO2 asphyxiation and samples were harvested
aseptically for further analysis. Antibiotic-treated, uninfected mice were
euthanized by CO2 asphyxiation after the treatment period.
Sample collection and assessment of S. Typhimurium
colonization
Caeca, spleen and feces were collected in 1 mL of sterile phosphate-buffered
saline (PBS). The samples were kept on ice and homogenized with an MM 301 Mixer
Mill (Retsch, Newton, PA). Serial dilutions of the homogenates were plated on LB
agar plates supplemented with 100 µg/mL of streptomycin to enumerate
S. Typhimurium. Plates were incubated overnight at 37°C
and colonies were counted after incubation. Fecal samples were also collected
throughout the experiments and kept at −80°C for further microbiota
analysis.
Histopathology
Caecal samples were collected and fixed in 10% neutral buffered formalin
overnight and then placed into 75% ethanol. Fixed tissues were embedded
in paraffin and cut into 5 µm sections. Tissues were stained with
hematoxylin and eosin (H&E) using standard techniques by Wax-it Histology
Services (Vancouver, BC, Canada) and UBC Histology Laboratory. Pathological
scores were assigned as previously described [39]. Briefly, the scoring
system was performed as follows: for lumen, sum of empty (score 0), necrotic
cells (scant 1, moderate 2, dense 3) and PMNs (scant 2, moderate 2, severe 3);
for surface epithelium, sum of no pathological change (score 0), regenerative
changes (mild 1, moderate 2, severe 3), desquamation (patchy 1, diffuse 2), PMNs
(score 1), ulceration (score 1); for mucosa, sum of no pathological change
(score 0), crypt abscesses (rare 1, moderate 2, abundant 3), presence of
mucinous plugs (score 1) and granulation tissue (score 1); for submucosa, sum of
no pathological changes (score 0), mononuclear cell infiltrate (one small
aggregate 0, more than one 1, large aggregates plus increase single cells 1),
PMN infiltrate (single 1, aggregates 2) and edema (moderate 1, severe 2).
Pathology Images were taken using a Zeiss Axioskop 2 microscope.
Microbiota analysis
Total bacterial counts from fecal samples were performed using SYBR Green
staining as described previously [40]. Briefly, a 1∶10 dilution of the homogenized
fecal samples were fixed and stored in 3.7% formalin at 4°C. Two
µL were stained with 0.25 µL of SYBR Green (Invitrogen) and viewed
with an Olympus 1x81 microscope. Cells were counted from three randomly chosen
fields and the numbers averaged. Counts were corrected based on volume used,
dilution and the known diameter of the microscope field. Fluorescent in
situ hybridization (FISH) was performed as previously described
[7]. Five
to 100 µL of sample was hybridized to 250 ng of the general EUB338 probe
(5′-GCT GCC TCC CGT AGG
AGT-3′), fluorescently labeled with Texas Red [41] and 250 ng
of either the CFB286 (5′-TCC TCT CAG
AAC CCC TAC-3′) or GAM42a (5′-GCC TTC CCA CAT
CGT TT-3′) probes [42] labeled with fluorescein, then viewed and counted as
described for SYBR staining. The percentage compositions of Bacteroidetes and
Gammaproteobacteria were calculated by dividing the numbers obtained for each
phylum by the total number of Eubacteria. The remaining bacteria were defined as
Firmicutes and others, as previously described [7].
Enumeration of viable bacteria from the fecal microbiota
Fecal samples were collected in 1 mL of PBS with 0.5% cysteine,
homogenized with an MM 301 Mixer Mill and immediately taken to an anaerobic
chamber. Serial dilutions were performed in PBS containing 0.5% cysteine
and plated in Tryptose blood agar base, Reinforced clostridial agar, Rogosa and
Anaerobe basal agar (Oxoid). Tryptose blood agar base and Anaerobe basal agar
were supplemented with 7% sheep blood (Cedarlane). Plates were incubated
under aerobic (Tryptose blood agar base) or anaerobic conditions (all the media)
for 48h at 37°C and colonies were counted after incubation.
Terminal-Restriction Fragment Length Polymorphism (TRFLP)
Total DNA was isolated from fecal and caecal samples using the QIAamp DNA stool
kit (Qiagen) according to the manufacturer's instructions with the addition
of a bead-beating step. Polymerase Chain Reaction (PCR) was performed to amplify
bacterial 16S rDNA present in fecal samples using broad-range bacterial primers
Bact8F(FAM) (5′-AGA GTT TGA TCM TGG CTC AG-3′) [43] labeled with
6-carboxyfluorescein on the 5′-end and 926R (5′-CCG TCA ATT CCT TTR
AGT TT-3′) [44]. The PCR products were digested with MspI (New
England Biolabs, Ipswich, MA) and sent to analysis at NAPS (Michael Smith
Laboratories, Vancouver, BC). Electropherograms were processed using Gene Marker
v.1.75 software (State College, PA) and relative peak areas of terminal
restriction fragments corresponding to sizes between 50–600 bp were
analyzed. Data were plotted using PC-ORD5 software (MjM Software, Gleneden
Beach, OR).
Cloning and Sequencing
Clone libraries were generated for the phylogenetic classification of TRFs of
interest. PCR amplified 16S rRNA genes from DNA isolated from feces were cloned
into the TA pCR® 4 TOPO vector and inserted into Escherichia
coli chemically competent cells (Invitrogen). Transformants were
screened by TRFLP as previously described, and those coinciding with peaks of
interest were sequenced. Sequences were classified using the naïve Bayesian
rRNA classifier in RDP [45].
Quantitative Real-Time PCR (RT-PCR)
The abundance of specific intestinal bacterial groups in DNA extracted from fecal
samples was measured by RT-PCR on a 7500 Fast Real-Time System (Applied
Biosystems, Foster City, CA). The reactions were performed using Quantitec SYBR
Green mastermix (Qiagen) with the following group-specific 16S rDNA primers
(IDT, Coralville, IA). Eubacteria (all bacteria): UniF340 ACT CCT ACG GGA GGC AGC AGT and UniR514
ATT ACC GCG GCT GCT GGC
(60°C) [46]; Mouse Intestinal Bacteria (MIB): UNI516F
CCA GCA GCC GCG GTA ATA
and ambMIBR677 CGG CAT TCC GCR TAC TTC TC (60°C) ([46] and this study);
Lactobacillus/Lactococcus: LabF362
ACG AGT AGG GAA ATC TTC
CA and LabR677 CAC CGC
TAC ACA TGG AG (56°C) [46]; Segmented Filamentous
Bacteria (SFB): SFB736F GAC GCT GAG GCA TGA
GAG CAT and SFB844R GAC
GGC ACG GAT TGT TAT TCA (58°C) [46];
Bifidobacterium BIF164 GGG TGG TAA TGC CGG ATG and BIF662 CCA CCG TTA CAC CGG GAA (62°C) [47].
Eubacteria primers were used to amplify a segment of the 16S rDNA to determine
the total amount of bacteria in each sample. The RT-PCR program started with two
steps of 50°C for 2 minutes and 95°C for 10 minutes, followed by 40
cycles of 95°C for 30 seconds and 60°C for 1 minute, when data was
acquired. The same DNA sample was amplified using the group-specific primers
described above observing their different annealing temperatures at the final
step. Group-specific bacterial numbers were determined as a percentage of the
numbers obtained with the Eubacteria primers.
ELISAs
Caecum homogenates were centrifuged twice at 16,000 g, and the supernatants were
stored at −80°C. The levels of interleukin-8 (IL8), interleukin-6
(IL6), interferon gamma (IFNγ), tumornecrosis factor alpha (TNFα)
(R&D System, Minneapolis, MN) and interleukin-22 (IL22) (eBioscience, San
Diego, CA) were measured by enzyme–linked immunosorbent assays (ELISAs)
according to the manufacturers' instructions.
Statistical Analysis
Statistical significance was calculated using the Mann-Whitney test with a
95% confidence interval. All analyses were performed using GraphPad Prism
version 4.0 (GraphPad Software, San Diego, CA). The results were expressed as
mean values with standard errors of the means. Microbial community composition
was plotted using non-metric multidimensional scaling (NMS) ordination based on
Sorensen distance measure, and significance between treatments was tested using
the multiple response permutation procedure (MRPP) in PC-ORD5 software (Gleneden
Beach, OR).Nramp1 is not responsible for the differences in intestinal pathology
between 129S1/SvImJ and C57BL/6 mice observed following metronidazole
treatment and infection. A. S. Typhimurium
levels in the caeca of Nramp1 +/+ and Nramp1 −/−
129S1/SvImJ mice after 4 days of infection with or without antibiotic
treatment. B. S. Typhimurium levels in feces of Nramp1
+/+ and Nramp1 −/− 129S1/SvImJ mice after 4 days of
infection with or without antibiotic treatment. C. H&E staining of caeca
of Nramp1 +/+ and Nramp1 −/− 129S1/SvImJ mice. (a).
infected Nramp1 +/+ 129S1/SvImJ mice; (b). metronidazole-treated
and infected Nramp1 +/+ 129S1/SvImJ mice; (c). infected Nramp1
−/− 129S1/SvImJ mice; (d). metronidazole-treated and infected
Nramp1 −/− 129S1/SvImJ mice. D. Pathology scores of caeca of
Nramp1 +/+ and Nramp1 −/− 129S1/SvImJ mice after 4
days of infection with or without antibiotic treatment. Met: metronidazole
(750 mg/L). Black bars represent pathology scores of the intestinal lumen,
white bars represent scores of the surface epithelia, dark grey bars
represent scores of the mucosa and light grey bars represent scores of the
submucosa of the tissue. ns: not significant; *:
p<0.05; **: p<0.01. Experiments were performed three times
with at least 4 mice in each group.(EPS)Click here for additional data file.Determination of viable bacteria in fecal samples incubated in
aerobiosis and anaerobiosis in Tryptose blood agar base. Total
bacterial counts in control, metronidazole-treated or streptomycin-treated
uninfected 129S1/SvImJ mice and control and metronidazole-treated uninfected
C57BL/6 mice. Aerobiosis (black bars) and Anaerobiosis (white bars).(EPS)Click here for additional data file.
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