Abstract
Background and Purpose
Commensal gut bacteria have a profound impact on stroke pathophysiology. Here we investigated whether modification of the microbiota influences acute and long-term outcome in mice subjected to stroke.
Methods
C57BL/6 male mice received a cocktail of antibiotics or single antibiotic. After 4 weeks, fecal bacterial density of the 16S rRNA gene was quantitated by qPCR and phylogenetic classification was obtained by 16S rRNA gene sequencing. Infarct volume and hemispheric volume loss were measured 3 days and 5 weeks after middle cerebral artery occlusion, respectively. Neurological deficits were tested by the Tape Test and the open field test.
Results
Mice treated with a cocktail of antibiotics displayed a significant reduction of the infarct volume in the acute phase of stroke. The neuroprotective effect was abolished in mice recolonized with a wild-type microbiota. Single antibiotic treatment with either ampicillin or vancomycin, but not neomycin, was sufficient to reduce the infarct volume and improved motorsensory function 3 days after stroke. This neuroprotective effect was correlated with a specific microbial population rather than the total bacterial density. In particular, random forest analysis trained for the severity of the brain damage revealed that Bacteroidetes S24.7 and the enzymatic pathway for aromatic metabolism discriminate between large versus small infarct size. Additionally, the microbiota signature in the ampicillin-treated mice was associated with a reduced gut inflammation, long-term favorable outcome shown by an amelioration of the stereotypic behavior and a reduction of brain tissue loss in comparison to control and was predictive of a regulation of short-chain fatty acids and tryptophan pathways.
Conclusions
The findings highlight the importance of the intestinal microbiota in short and long-term outcomes of ischemic stroke and raises the possibility that targeted modification of the microbiome associated with specific microbial enzymatic pathways may provide a preventive strategy in patients at high risk for stroke.
Keywords: Stroke, MCAO, neuroinflammation, gut, microbiota
Graphical Abstract

Modification of the microbiota with ampicillin or vancomycin, but not neomycin reduces the infarct volume in a mouse model of stroke. This neuroprotective effect is associated with a distinct microbiota composition, a reduced pro-inflammatory milieu in the gut, an improvement of the motorsensory function 3 days after stroke (short-term behavior) and stereotypic/stress behaviors 14 days after stroke (long-term deficits) in comparison to control mice. In addition, the “neuroprotective” microbiome is predictive of a regulation of the short-chain fatty acids and tryptophan pathways (PICRUSt2).
Introduction
Commensal bacteria that populate epithelial surfaces play a defining role in the physiology, metabolism and immunity of the host, depending on the relative abundance, the composition and function of microbial species1,2. Environmental factors including the type of diet, exercise, use of medications as well as non-modifiable factors such as the host genetics, mode of birth delivery and age influence the gut microbiota composition. In turn, changes in the microbiome may impact the host homeostasis and influence health and diseases1,3. Advances in metagenome sequencing of the microbiome have allowed the identification of non-cultivable bacteria and have revealed a close association of this complex ecosystem with multiple diseases4. Whereas human research has mostly addressed the correlative link between the microbiome and disease state, the development of animal models and fecal microbiota transplantation (FMT) have provided evidence as to showing a direct bidirectional communication between the microbiome and the brain5. In particular, recent studies have implied that the microbiome can have remarkable effects on brain diseases, including Alzheimer’s disease6, Parkinson’s disease7, multiple sclerosis8, neurodevelopmental9 and psychiatric disorders10,11 as well as stroke12–18.
Signaling between the brain and the gut occurs through neuronal pathways but also through microbial metabolites as well as hormones, and the immune system19. Importantly, the vast majority of the microorganisms reside in the gastrointestinal tract and tightly regulate immune cell function20. We and others have shown that the gut microbiome influences stroke outcome by modulating the immune response16, in turn stroke itself induces a shift of the microbial community which impacts gut motility and permeability, stress response and poststroke infection13,17,18,21. In particular, these findings highlight a direct connection along the gut-brain axis via intestinal T cells regulating the neuroinflammatory response to brain injury22.
The bacterial species underlying the protective or deleterious effect in stroke remain to be defined, as well as whether a shift of the microbiota composition has a long-lasting impact on stroke outcome. Recent findings from Spychala et al. have identified that the microbiome from aged mice is associated with a disbalance of the two main bacteria phyla in the gut in comparison to young mice and fecal transplantation of a young microbiome in aged mice improved stroke outcome23, suggesting that targeting the microbiome composition in patients with high risk of stroke, such as in elderly might be beneficial. Understanding on how modification of the gut microbial community impacts the consequences of stroke on the host has the potential for the development of new therapeutic strategy to improve recovery after stroke.
In this study, we use combinatorial and singular antibiotic treatment protocols to modify the microbiota composition. We showed that a targeted modification of the gut microbiota is associated with acute and long-term protection from ischemic stroke.
Materials and Methods
Raw sequence reads were deposited to the NIH Sequence Read Archive (SRA) with the accession No. PRJNA613289. All other data that support the findings of this study are available from the corresponding authors upon reasonable request.
Detailed experimental description of the different materials and methods described below can be found in the online-only Data Supplement.
Mice and Antibiotic treatment.
All procedures were approved by the institutional animal care and use committee of Weill Cornell Medical College (WCMC, protocol number: 2012–0051). Wild-type C57BL/6 4 weeks old male mice were purchased from Jackson Laboratories (JAX; Bar Harbor, Maine, USA) and housed under standard conditions of our WCMC animal facility. Antibiotic treatment: ampicillin, metronidazole, neomycin sulfate and vancomycin, abbreviated AMNV, was administered for 4 weeks in the drinking water. Due to the possible effect of sex hormones on the microbiota composition, experiments were performed in male mice. All animal experiments were performed in accordance with the ‘animal research: reporting of in vivo experiments’ (ARRIVE) guidelines24.
Middle cerebral artery occlusion (MCAO) and N-methyl-D-aspartate (NMDA) lesion.
Transient MCAO was induced as previously described with monitoring of body temperature (37.0±0.5) and by transcranial laser Doppler flowmetry (Supplemental Tables)16. Topical lidocaine/bupivacaine (0.25 %/ 0.1 mL, transdermal) and buprenorphine (0.5 mg/kg; sub-cutaneously) were used for pre- or post- operative analgesia, respectively. NMDA lesion was induced into the parietal cortex as described previously25. The order in which mice from different groups were subjected to surgery was randomized. Antibiotic treated mice cannot be blinded to the investigator because they have an enlarged abdomen and their stool pellets appear distinguishable from control mice.
Quantification of lesion volume and tissue loss.
Mice were euthanized 3 days or 5 weeks after MCAO for infarct volume and tissue loss quantification, respectively, or 1 day after NMDA injection for lesion volume measurement.
Neurobehavioral testing.
Sensorimotor deficit was assessed 1 day before and 3 days after MCAO using the Tape Test16. The open field test was used to assay spontaneous locomotor activity 14 d after MCAO or sham surgery.
Feces DNA extraction, 16S rRNA gene amplification and quantification.
DNA was extracted from frozen stool samples, amplified using 16S-V2 primers and quantitated by real-time polymerase chain reaction.
16S rRNA gene amplification and multiparallel sequencing, analysis and visualization.
Amplicons of the V4 16S rRNA region were amplified and sequenced using an Illumina MiSeq platform (LC Sciences, Houston, TX). Demultiplexed sequence reads and metabolic pathways from the taxonomic composition were processed with the QIIME2 (vers. 2019.4) pipeline26 implemented in PICRUSt27.
Statistical analysis.
Mouse randomization was based on the random number generator function (RANDBETWEEN) in Microsoft Excel software. Exclusion criteria are described in the individual method sections. GraphPad Prism (v. 8.0) software was used for statistical analysis. Data are expressed as mean ± SD or SEM and were analyzed by unpaired Student’s t-test (two-tailed), or one-way ANOVA and Tukey’s test, as appropriate. Significant differences are indicated by: *p≤0.05, **p≤0.01, ***p≤0.001, ****p≤0.0001 or non-significant: NS; detailed of the mean and N values/group can be found in the online-only Data Supplement.
Results
Antibiotic treatment induces neuroprotection and is reversible by passive recolonization
A cocktail of antibiotics targeting a broad-spectrum of gut bacteria was administered to mice to evaluate its effect on fecal bacterial density and stroke outcome. Mice received AMNV in the drinking water for 4 weeks. AMNV treatment was discontinued 3 days before inducing MCAO to mitigate off-target antibiotic effects. Control C57BL/6J mice (CTR) were age matched and received autoclaved water. Stool pellets were collected after 4 weeks of AMNV treatment, at the time of MCAO induction and 3 days after stroke (timeline of the treatment protocol is shown in Fig. 1A). As previously reported28, we observed that mice treated with AMNV significantly lost weight during the first 3 weeks (death rate of 2.7%) and regained their body weight similar to CTR mice after the 4th week of antibiotics (no mortality was observed at this time point). At the time we induced stroke, there was no significant difference in body weight between the two groups (Fig. 1B). Quantification of 16S rRNA copies in feces revealed a 105-fold reduction in bacterial density 4 weeks after AMNV compared to CTR mice. Bacterial density of AMNV-treated mice was largely restored to a 10-fold difference from CTR mice 6 days after antibiotic treatment was stopped (Fig. 1C). AMNV treatment for 4 weeks induced a 40% reduction of the infarct volume compared to CTR mice 3 days after MCAO induction (Fig. 1D). This shows that combinatorial antibiotics prior to inducing stroke successfully reduced the bacterial density in feces and was sufficient to induce neuroprotection. To investigate whether changes in microbiota directly influence neuronal death we used a cortical excitotoxic lesion model25. We found that AMNV-treatment had no effect on the size of the brain lesion produced by neocortical NMDA injection. This finding could suggest that the reduction of ischemic injury is not primarily mediated by the inhibition of excitotoxicity (Fig. 1D) but rather by modulation of the post-ischemic immune response as showed here (Supplementary Fig. IB,C) and published before13,16.
FIG. 1. Broad-spectrum antibiotics modifies the bacterial density in feces and induces neuroprotection after stroke.

A) Mice received broad-spectrum antibiotics (AMNV) in the drinking water for 4 weeks (w4). AMNV treatment was discontinued 3 days before inducing MCAO or NMDA injection. Control mice (CTR) were age matched and received autoclaved water. Mice were sacrificed 3 days after MCAO induction (red) or 1 day after NMDA injection (blue). Stool pellets were collected as indicated. B) Body weight progression during AMNV treatment. X indicates mice which died during the AMNV treatment. C) Fecal bacterial density at several time points after the antibiotic supplementation was discontinued. D) Left, infarct volumetry in CTR and AMNV mice 3 days after MCAO induction. Right, lesion volumetry in CTR and AMNV mice 1 day after neocortical injection of NMDA.
We then addressed whether acute antibiotic treatment is neuroprotective in comparison with long-term AMNV treatment. AMNV was given daily to naïve mice starting one day prior MCAO until sacrifice at day 3 or to mice treated with AMNV for 4 weeks (Fig. 2A). Fecal bacterial density was successfully reduced after short time AMNV treatment similarly to AMNV chronic treatment level (Fig. 2B). However, short time AMNV treatment did not induce a reduction of the infarct volume compared to long time AMNV treatment (Fig. 2B). In order to investigate the direct link between the gut microbiota and stroke outcome, we passively recolonized AMNV-treated mice by co-housing with a wild-type mouse for 2 weeks (Fig. 2C). Fecal bacterial density of the recolonized AMNV-treated mice was re-established to levels found in untreated wild-type mice (1×109 copies/mg) and the observed neuroprotection was abolished (Fig. 2D), showing the neuroprotective effect is reversible by passive recolonization of the gut microbiota.
FIG. 2. Acute AMNV-treatment is not protective from stroke and passive recolonization abolishes neuroprotection.

A) Left, mice received AMNV by gavage starting one day before MCAO surgery (d-1) until sacrifice (d+3) (“AMNV short”). Right, another group of mice received AMNV in the drinking water for 4 weeks following by the same treatment procedure as in the left panel (“AMNV long”). B) Left, bacterial density in feces before and 1 day to 3 days after AMNV treatment by gavage (AMNV short). Dash line indicates bacterial density in mice treated with AMNV in the drinking water for 4 weeks. Right, infarct volume in control mice not treated (CTR), after chronic AMNV treatment (AMNV long) and acute AMNV treatment (AMNV short) 3 days after MCAO induction. C) 4 weeks AMNV-treated mice were recolonized by co-housing for 2 weeks with a control wild-type mouse. Stool pellets were collected before and after recolonization. MCAO was induced after 2 weeks of co-housing. Mice were sacrificed 3 days after stroke and infarct volumetry was assessed. D) Left, bacterial density in feces 4 weeks after AMNV administration (black circles) and after 2 weeks of co-housing with a wild-type mouse (white circles). Dash line indicates bacterial density in wild-type mice. Right, infarct volume 3 days after MCAO in 4 weeks AMNV-treated mice and after recolonization.
Single antibiotic treatment induces a distinct bacterial signature associated with improvement of acute and long-term stroke outcome
Each antibiotic used in this study has different anti-microbial properties. Here we wanted to better characterize the effect of singular antibiotic treatment to identify the most potent strategy to alter the composition of the gut microbiota associated with an improvement of stroke outcome. Mice were treated for 4 weeks with either neomycin (N), vancomycin (V) or ampicillin (A) and feces were collected for 16S rRNA sequencing (Fig. 3). The antibiotic-treated mice had an overall reduced Shannon diversity index which its magnitude was dependent on the type of antibiotic (Fig. 3A). The reduction of the richness and evenness was more pronounced in V- and A-treated mice (Fig. 3B). Specifically, the evenness index in A-treated mice was the lowest in comparison to all groups indicating the dominance of one or few species among the other (Fig. 3B). Taxonomic relative abundance of bacterial phyla revealed a contraction of members of the Bacteroidetes in both V- and A- treated mice, as well as an expansion of the antimicrobial resistant Verrucomicrobia and Proteobacteria, respectively. Neomycin reduced slightly the diversity but did not influence the overall bacterial population in the stool in comparison to CTR mice (Fig. 3A–3C and Supplementary Fig.IA). Overall, redundancy analysis ordination at the family level showed distinct clusters, distinguishing clearly the 3 different antibiotic treatment groups and controls (Fig. 3D).
FIG. 3. Single antibiotic treatment induces a distinct microbiota signature.

A) Shannon α-diversity index and B) richness and evenness of OTUs in control mice (CTR) and in mice treated with either neomcyin (N), vancomycin (V) or ampicillin (A) for 4 weeks. C) Relative abundances of bacterial families in fecal samples 4 weeks after the indicated antibiotic treatment. Each bar represents an individual mouse. D) Redundancy analysis ordination of the family composition across the three antibiotic treatment groups and controls. RDA1 and 2 explained 39% and 13% of the variance, respectively. For better clarity, phyla are indicated on the plot. Defined bacteria phyla are associated with specific antibiotic treatment groups and are distinct from the control group.
The neuroprotection in AMNV treated mice was not due to additive effects of the different antibiotics (Fig. 4A), because treatment with V or A alone reduced infarct volume 3 days after MCAO induction, whereas N-treated mice were not protected in comparison to CTR mice (Fig. 4B). Metronidazole (M) in combination with N or V did not further influence the size of the lesion (data not shown). Body weight progression was similar in all groups tested and no mortality was recorded during the 4-weeks treatment protocol. Bacterial load was moderately reduced in V- and A- treated mice (102-fold) in comparison to control, however the neuroprotective effect in V- and A-treated mice were not correlated with the total fecal bacterial density (Fig. 4C) but was associated with distinct bacteria dependent on the antibiotic treatment used (Fig. 3D and Supplementary Fig. II). Reduction of Bacteroidetes S24–7 in both V- and A-treated mice and expansion of Verrucomicrobiaceae and Lactobacillaceae or Burkholderiaceae and Streptococcaceae families in V- and A-treated mice, respectively, was correlated with a reduction of brain infarct (Fig. 3C). We then tested whether the observed changes of the microbiota composition influenced neurological deficits in the acute phase of stroke. Sensorimotor function was tested 3 days after MCAO by the Tape Test (Fig. 4D). Mice treated with either V or A took less time on average to sense and remove the tape on their contralateral forepaw than N-treated and CTR mice in respect to the performance before MCAO induction. Altogether, whereas single antibiotic treatment induced a distinct shift of the microbiota population, V and A treatment but not N were associated with a better stroke outcome (Fig. 4) and correlated with a suppression of IL17+ γδT cells in the gut (Supplementary Fig. IB,C).
FIG. 4. Vancomycin or ampicillin alone is sufficient to improve acute stroke outcome.

A) Timeline of the single antibiotic administration. One day prior stroke mice were trained for the Tape Test. 3 days after stroke mice were tested for motor and sensory function by the Tape Test. B) Infarct volumes in antibiotic treated mice as compared to CTR mice 3 days after MCAO induction. C) Left, bacterial density in the feces 4 weeks after single antibiotic supplementation or in CTR mice. Dash line indicates bacterial density in mice treated with AMNV in the drinking water for 4 weeks. Right, correlation analysis of the fecal bacterial density with infarct volumes 3 days post MCAO after 4 weeks of single antibiotic treatment or in control mice. D) Sensorimotor function in CTR and antibiotic treated mice. Graphs show contact time (left) and time to remove the tape (right) from the contralateral forepaw 3 days after MCAO induction as relative to d-1.
We then investigated whether the neuroprotective phenotype in mice treated with single antibiotic persisted in the chronic phase of stroke (Fig. 5A). Long-term deficits were tested 14 d after stroke by measuring the mobility and exploratory behavior (Fig. 5B). Whereas, the total ambulatory distance was not different between groups (Supplementary Fig. IIA), A-treated mice tended to develop decreased stereotypic behaviors (time and counts) in comparison to all other groups as shown by a less repetitive behavior in the open field in the presence of an intruder mouse. This decrease reflects a diminution of circling behavior or repetitive back and forth motion as well as a decrease of social stress response (number of entries in the intruder zone and duration in the intruder zone, supplementary Fig. IIB, C). In contrary, N-treated mice had an increase of the time spending in the intruder zone in the open field in comparison to CTR mice, suggesting an impaired social behavior in N-treated mice (Supplementary Fig.IIC). In addition, the brain tissue loss was less pronounced in A-treated mice 5 weeks after stroke induction as shown by a significant decrease of the volume of the ipsilateral hemisphere in comparison to CTR mice (Fig. 5C).
FIG. 5. Single antibiotic treatment with vancomycin or ampicillin improves long-term stroke outcome.

A) CTR and 4-weeks antibiotic treated mice were tested for stereotypic behavior in the vicinity of a foreign mouse (intruder) by the open field test 14 days after stroke or sham surgery. Mice were sacrificed 35 days after MCAO induction for quantification of the brain tissue loss. B) Upper row shows a representative trajectory of mouse movements during the presence of the intruder mouse at the location indicated. Colored circle indicates the position of the mouse at the end of the 15 min trial. Lower row, quantification of the stereotypic behavior (time and counts) in the open field of CTR and antibiotic-treated mice in presence of the intruder 14 days after stroke and sham surgery. No statistical difference was observed between sham groups. C) Brain tissue loss was less pronounced in A-treated mice 35 days after MCAO as reflected by a significant decrease of ipsilateral volume loss compared to CTR mice.
Enzymatic pathways associated with a specific microbiota are predictive of stroke outcome
We then used PICRUSt27 to infer the functional composition of the collective metagenome for each treatment group from the taxonomic data. To identify a predictive microbial signature for stroke outcome, we performed random forest (RF) analysis on fecal OTUs at the family level (Fig. 6A) and KEGG enzymatic pathways (Fig. 6B) trained for the severity of the brain damage. We found that the Bacteroidetes S24.7 and the enzymatic pathway related to xenobiotic metabolism/aromatic biodegradation discriminate highly between large versus small infarct size, independently of the antibiotic treatment (Fig. 6A, B). We then performed a clustered heatmap of KEGG analysis to investigate the biological pathways that were predictive of the different microbiomes. V- and A-treated groups clustered away from the CTR group, whereas N-treated mice were mostly mixed with CTR mice (Fig. 6C). Although V-treated mice had only 3 pathways significantly different from the CTR group and N-treated group had none, A-treated mice, which showed the highest and reproducible level of neuroprotection in the acute and chronic phase of stroke, had 40 enzymatic pathways significantly regulated in comparison to CTR mice (Supplementary Fig. III). These included an increase of pathways associated with amino-acid metabolism (valine, leucine, isoleucine degradation) and especially the aromatic amino-acids (phenylalanine metabolism, tryptophan metabolism, histidine metabolism), aromatic compound degradation (benzoate degradation), ATP production (glyoxylate and dicarboxylate metabolism, fatty acid degradation, oxidative phosphorylation), carbohydrate metabolism (butanoate metabolism, propanoate metabolism), pyruvate and nitrogen metabolisms. These findings show that modification of the composition of the gut microbiota with ampicillin induces changes of metabolic pathways that could be predictive of stroke outcome.
FIG. 6. Association of specific bacteria and enzymatic pathways with infarct volume.

Random forest (RF) analysis showing predictive importance of A) Operational taxonomic units (OTU) at the family level (OTUs > 1% were included) and B) Enzymatic KEGG pathways trained for stroke outcome (size of the infarct volume) in all samples from the antibiotic treated- and control groups. “mse” (mean squared error) is a measure of the prediction accuracy of the RF as a function of permutating a variable. Variables associated with higher mse increase have higher predictive value. “Node purity increase” is a measure of how a split on a given variable reduces node impurity if applied to all nodes and all trees. Higher values are associated with more important variables. C) Heat-map of the significant regulated enzymatic pathways (rows) by samples (columns) after hierarchical clustering of treatment groups and KEGG pathways. Each column represents one mouse.
Discussion
In this study, we used combinatorial and singular antibiotic treatment protocols to modify the composition of the microbiota and we investigated the acute and long-term effect of gut dysbiosis on stroke outcome. Whereas broad-spectrum antibiotic treatment for 4 weeks prior inducing stroke was neuroprotective, short time AMNV treatment was inefficient in reducing the size of the ischemic lesion corroborating studies in stroke patients29. Additionally, we demonstrated that antibiotics – targeting different classes of intestinal bacteria and metabolic pathways – alter differently the acute and long-term outcome of stroke. Ampicillin-derived microbiome was the most efficient in inducing short and long-term neuroprotection from stroke and its composition clearly segregated from the other antibiotic-treated mice with no or less efficient protection from stroke. The “ampicillin neuroprotective microbiome” was associated with an expansion of Proteobacteria and Lactobacilliales and was predictive of specific metabolic pathways but was independent of fecal bacterial density. Thus, bacterial density does not necessarily correlate with stroke outcome. Indeed, short term antibiotics lack to provide neuroprotection compared to the protection with long term antibiotics despite a change in the microbiome density in both antibiotic treatment paradigm. We highlighted here that different class of antibiotics induce distinct changes of the microbiota composition and was associated with a distinct immune response in the gut. In particular, antibiotics such as ampicillin and vancomycin but not neomycin promote an anti-inflammatory milieu in the gut by reducing the number of IL-17 producing γδT cells which was associated with short- and long-term neuroprotection. We have previously shown that the alteration of the microbial composition precedes the immune changes in the intestine16. Whether an expansion of a specific bacterial species or family is responsible for this time lag should be addressed in future studies. As for instance, we observed that the bacteria family S24–7 within the phylum Bacteroidetes was highly associated with the size of the infarct. Different studies have reported the altered abundance of S24–7 family in association with brain diseases30–32. S24–7, among other genera, possess large numbers of genes involved in carbohydrate metabolism33 and have been involved in humoral response34 in the gut that could impact the availability of gut metabolites for the host and its immune response, respectively. Despite these findings, the specific role of S24–7 members on stroke outcome has not been tested yet.
In our previous study, we were able to inhibit the development of the infarct when FMT of the “modified protective microbiota” was inoculated to naive mice16. However, we could not determine whether the protective phenotype after FMT was solely due to the original microorganisms, as the phylogenetic analysis of the transplanted recipient mice was highly different from the donor mice (Benakis et al., Nat. Med. 2016). This is not surprising, considering that a) bacteria might not survive the oral gavage and passage through the acidic and aerobe conditions of the upper gastrointestinal tract, b) colonization of the gut may need empty niches to be efficient, c) the recipient immune system may not be primed to accept the transplant. However, one can assume that recapitulation of the donor microbiome in the recipient might not be necessary since different bacterial species have redundant functions. Thus, investigation of the metabolic microbial pathways might be a better approach to describe the altered microbiome after FMT. Here using PICRUSt tool as a discovery based algorithm, we highlighted that the enzymatic pathway related to xenobiotic/aromatic compound degradation discriminate highly between large versus small infarct size. Stanley and colleagues analyzed the predicted KEGG pathways from samples isolated directly from the intestinal mucosal microbiota21. In agreement with our study, they found an increasing capacity for xenobiotic biodegradation and metabolism after stroke in comparison to sham surgery. This suggest that xenobiotic/aromatic-degrading microorganisms might be regulated by stroke and involved in the development of the infarct. Interestingly, several pathways related to aromatic compound metabolism (benzoate degradation, phenylalanine, tryptophan and histidine metabolism) were associated with the microbiome composition of the ampicillin-treated mice, which induces the most potent neuroprotective effect after stroke, in comparison to control mice. Although it is not clear yet how regulation of these enzymatic pathways, predicted by PICRUSt algorithm, impact the host and stroke outcome, there is evidence from the literature showing that catabolites of the essential amino acid tryptophan that include indole metabolites can modulate intestinal immune cell function through the aryl hydrocarbon receptor AHR (first discovered as a receptor for xenobiotic ligands)35. In an animal model of multiple sclerosis, Rothhammer and colleagues showed that the brain inflammatory response to the disease was regulated by AHR through indole metabolites8,36. Thus, direct modulation of these pathways by microbial metabolite supplementation or inhibition might have an impact on outcome of stroke. Short-chain-fatty acids (SCFAs) are other group of microbial metabolites exclusively produced by bacterial fermentation of dietary fibers. Interestingly, we showed that alteration of the gut microbiota by ampicillin was also found to change the predicted functionality of SCFA metabolism, with a significant increase in pathways of butyrate and propionate metabolisms. In accordance, we have recently demonstrated that SCFAs added in the drinking water of mice for 4 weeks influenced microglia morphology towards a resting phenotype, increased neuronal spine growth and was associated with long-term recovery after stroke37, suggesting an important role of gut-derived metabolites in modulating the outcome of stroke23,37.
The microbiome is a highly complex ecosystem with dynamic interactions between the different types of bacteria. Investigating the microbiome function rather than its composition might help to understand its impact on the host and brain disease development. While an increased stroke incidence in young individuals has been recently reported38 stroke risk factors such as age, and gender where not addressed in this study. Interestingly, recent findings have demonstrated that reproductively senescent rats significantly affect gut communities under stroke conditions32 and a young microbiome is neuroprotective when transfer to aged mice23. Whereas the impact of lifestyle factors (diabetes, high blood cholesterol levels, alcohol consumption, high fat diet, lack of exercise) on the gut microbiome and stroke outcome remains to be addressed.
In conclusion, our findings highlight the importance of the intestinal microbiome in the short and long-term outcome of ischemic brain injury and raise the possibility that modulation of microbial metabolism could be a novel preventive strategy in patients at high risk for stroke
Supplementary Material
Acknowledgments
C.B. contributed to study design, performed and/or contributed to all experiments, analyzed data and wrote the manuscript. In some experiments, C.B. was assisted by C.P., J.M., M.M., G.S. and G.R. D.L. performed the open field test and analyzed the data. D.B. performed the FACS analysis. C.I. contributed to study design. J.A. formulated the original hypothesis, designed the study, analyzed the sequencing data and wrote the manuscript together with C.B. and C.I. All authors read and approved the manuscript.
Sources of Funding
The study was supported by the US National Institutes of Health (NIH) grants NS081179, NS094507 (J.A.) and NS34179 (C.I. and J.A.), the Feil Family Foundation (C.I.), and the Swiss National Science Foundation for Grants in Biology and Medicine (P3SMP3 148367; C.B.).
Footnotes
Conflict-of-Interest/Disclosures
Dr. Iadecola served on the Strategic Advisory Board and Broadview Ventures.
References
- 1.Sommer F, Bäckhed F. The gut microbiota — masters of host development and physiology. Nat Med. 2013;11:227–238. [DOI] [PubMed] [Google Scholar]
- 2.Ivanov II, Honda K. Intestinal Commensal Microbes as Immune Modulators. Cell Host Microbe. 2012;12:496–508. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Cryan JF, O’Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, et al. The Microbiota-Gut-Brain Axis. Physiol Rev. 2019;99:1877–2013. [DOI] [PubMed] [Google Scholar]
- 4.Knight R, Vrbanac A, Taylor BC, Aksenov A, Callewaert C, Debelius J, et al. Best practices for analysing microbiomes. Nat Med. 2018;16:410–422. [DOI] [PubMed] [Google Scholar]
- 5.Fung TC, Olson CA, Hsiao EY. Interactions between the microbiota, immune and nervous systems in health and disease. Nat Neurosci. 2017;20:145–155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Minter MR, Zhang C, Leone V, Ringus DL, Zhang X, Oyler-Castrillo P, et al. Antibiotic-induced perturbations in gut microbial diversity influences neuro-inflammation and amyloidosis in a murine model of Alzheimer’s disease. Sci Rep. 2016;6:30028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Sampson TR, Debelius JW, Thron T, Janssen S, Shastri GG, Ilhan ZE, et al. Gut Microbiota Regulate Motor Deficits and Neuroinflammation in a Model of Parkinson’s Disease. Cell. 2016;167:1469–1480.e12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Rothhammer V, Mascanfroni ID, Bunse L, Takenaka MC, Kenison JE, Mayo L, et al. Type I interferons and microbial metabolites of tryptophan modulate astrocyte activity and central nervous system inflammation via the aryl hydrocarbon receptor. Nat Med. 2016;22:586–597. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Buffington SA, Di Prisco GV, Auchtung TA, Ajami NJ, Petrosino JF, Costa-Mattioli M. Microbial Reconstitution Reverses Maternal Diet-Induced Social and Synaptic Deficits in Offspring. Cell. 2016;165:1762–1775. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Neufeld KM, Kang N, Bienenstock J, Foster JA. Reduced anxiety-like behavior and central neurochemical change in germ-free mice. Neurogastroenterol Motil. 2011;23:255–64–e119. [DOI] [PubMed] [Google Scholar]
- 11.van de Wouw M, Boehme M, Lyte JM, Wiley N, Strain C, O’Sullivan O, et al. Short-chain fatty acids: microbial metabolites that alleviate stress-induced brain-gut axis alterations. J Physiol. 2018;596:4923–4944. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Yin J, Liao SX, He Y, Wang S, Xia GH, Liu FT, et al. Dysbiosis of gut microbiota with reduced trimethylamine‐N‐oxide level in patients with large‐artery atherosclerotic stroke or transient ischemic Attack. J Am Heart Assoc. 2015;4:e002699–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Singh V, Roth S, Llovera G, Sadler R, Garzetti D, Stecher B, et al. Microbiota dysbiosis Controls the Neuroinflammatory Response after Stroke. J Neurosci. 2016;36:7428–7440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Singh V, Sadler R, Heindl S, Llovera G, Roth S, Benakis C, et al. The gut microbiome primes a cerebroprotective immune response after stroke. J Cereb Blood Flow Metab. 2018;38:1293–1298. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Winek K, Engel O, Koduah P, Heimesaat MM, Fischer A, Bereswill S, et al. Depletion of cultivatable gut microbiota by broad-spectrum antibiotic pretreatment worsens outcome after murine stroke. Stroke. 2016;47:1354–1363. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Benakis C, Brea D, Caballero S, Faraco G, Moore J, Murphy M, et al. Commensal microbiota affects ischemic stroke outcome by regulating intestinal γδ T cells. Nat Med. 2016;22:516–523. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Stanley D, Mason LJ, Mackin KE, Srikhanta YN, Lyras D, Prakash MD, et al. Translocation and dissemination of commensal bacteria in post-stroke infection. Nat Med. 2016;22:1277–1284. [DOI] [PubMed] [Google Scholar]
- 18.Houlden A, Goldrick M, Brough D, Vizi ES, Lénárt N, Martinecz B, et al. Brain injury induces specific changes in the caecal microbiota of mice via altered autonomic activity and mucoprotein production. Brain Behav Immun. 2016;57:10–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Schroeder BO, Bäckhed F. Signals from the gut microbiota to distant organs in physiology and disease. Nat Med. 2016;22:1079–1089. [DOI] [PubMed] [Google Scholar]
- 20.Littman DR, Pamer EG. Role of the Commensal Microbiota in Normal and Pathogenic Host Immune Responses. Cell Host Microbe. 2011;10:311–323. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Stanley D, Moore RJ, Wong CHY. An insight into intestinal mucosal microbiota disruption after stroke. Sci Rep. 2018;8:568–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Benakis C, Martin-Gallausiaux C, Trezzi J-P, Melton P, Liesz A, Wilmes P. ScienceDirect The microbiome-gut-brain axis in acute and chronic brain diseases. Curr Opin Neurobiol. 2019;61:1–9. [DOI] [PubMed] [Google Scholar]
- 23.Spychala MS, Venna VR, Jandzinski M, Doran SJ, Durgan DJ, Ganesh BP, et al. Age-related changes in the gut microbiota influence systemic inflammation and stroke outcome. Ann Neurol. 2018;84:23–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Kilkenny C, Browne W, Cuthill IC, Emerson M, Altman DG, National Centre for the Replacement, Refinement and Reduction of Amimals in Research. Animal research: reporting in vivo experiments--the ARRIVE guidelines. J Cereb Blood Flow Metab. 2011;31:991–993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Iadecola C, Niwa K, Nogawa S, Zhao X, Nagayama M, Araki E, et al. Reduced susceptibility to ischemic brain injury and N-methyl-D-aspartate-mediated neurotoxicity in cyclooxygenase-2-deficient mice. Proc Natl Acad Sci USA. 2001;98:1294–1299. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–857. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol. 2013;31:814–821. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Reikvam DH, Erofeev A, Sandvik A, Grcic V, Jahnsen FL, Gaustad P, et al. Depletion of murine intestinal microbiota: effects on gut mucosa and epithelial gene expression. PLoS One. 2011;6:e17996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.van de Beek D, Wijdicks EFM, Vermeij FH, de Haan RJ, Prins JM, Spanjaard L, et al. Preventive antibiotics for infections in acute stroke: a systematic review and meta-analysis. Arch Neurol. 2009;66:1076–1081. [DOI] [PubMed] [Google Scholar]
- 30.Chen Y, Liang J, Ouyang F, Chen X, Lu T, Jiang Z, et al. Persistence of Gut Microbiota Dysbiosis and Chronic Systemic Inflammation After Cerebral Infarction in Cynomolgus Monkeys. Front Neurol. 2019;10:41–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Minter MR, Hinterleitner R, Meisel M, Zhang C, Leone V, Zhang X, et al. Antibiotic-induced perturbations in microbial diversity during post-natal development alters amyloid pathology in an aged APPSWE/PS1ΔE9 murine model of Alzheimer’s disease. Sci Rep. 2017;7:1–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Park MJ, Pilla R, Panta A, Pandey S, Sarawichitr B, Suchodolski J, et al. Reproductive Senescence and Ischemic Stroke Remodel the Gut Microbiome and Modulate the Effects of Estrogen Treatment in Female Rats. Transl Stroke Res. 2019;7:915–19. [DOI] [PubMed] [Google Scholar]
- 33.Flint HJ, Scott KP, Duncan SH, Louis P, Forano E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes. 2014;3:289–306. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Bunker JJ, Flynn TM, Koval JC, Shaw DG, Meisel M, McDonald BD, et al. Innate and Adaptive humoral responses coat distinct commensal bacteria with immunoglobulin A. Immunity. 2015;43:541–553. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Gutiérrez-Vázquez C, Quintana FJ. Regulation of the immune response by the aryl hydrocarbon receptor. Immunity. 2018;48:19–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Rothhammer V, Borucki DM, Tjon EC, Takenaka MC, Chao C-C, Ardura-Fabregat A, et al. Microglial control of astrocytes in response to microbial metabolites. Nature. 2018;557:724–728. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Sadler R, Cramer JV, Heindl S, Kostidis S, Betz D, Zuurbier KR, et al. Short-chain fatty acids improve post-stroke recovery via immunological mechanisms. J Neurosci. 2019;40:1162–1173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Tibæk M, Dehlendorff C, Jørgensen HS, Forchhammer HB, Johnsen SP, Kammersgaard LP. Increasing incidence of hospitalization for stroke and transient ischemic attack in young adults: A registry‐based study. J Am Heart Assoc. 2016;5:27–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
