I have read the journal’s policy and the authors of this manuscript have the following competing interests: Edward D. Karoly is employed by Metabolon Inc. At the time of the study Lauren N. Bell was also employed by Metabolon Inc. Metabolon did not fund the study but performed the metabolomic analysis described in the manuscript on a fee for service basis. This does not alter our adherence to PLOS ONE policies on sharing data and materials
Ozone is an asthma trigger. In mice, the gut microbiome contributes to ozone-induced airway hyperresponsiveness, a defining feature of asthma, but the mechanistic basis for the role of the gut microbiome has not been established. Gut bacteria can affect the function of distal organs by generating metabolites that enter the blood and circulate systemically. We hypothesized that global metabolomic profiling of serum collected from ozone exposed mice could be used to identify metabolites contributing to the role of the microbiome in ozone-induced airway hyperresponsiveness. Mice were treated for two weeks with a cocktail of antibiotics (ampicillin, neomycin, metronidazole, and vancomycin) in the drinking water or with control water and then exposed to air or ozone (2 ppm for 3 hours). Twenty four hours later, blood was harvested and serum analyzed via liquid-chromatography or gas-chromatography coupled to mass spectrometry. Antibiotic treatment significantly affected 228 of the 562 biochemicals identified, including reductions in the known bacterially-derived metabolites, equol, indole propionate, 3-indoxyl sulfate, and 3-(4-hydroxyphenyl)propionate, confirming the efficacy of the antibiotic treatment. Ozone exposure caused significant changes in 334 metabolites. Importantly, ozone-induced changes in many of these metabolites were different in control and antibiotic-treated mice. For example, most medium and long chain fatty acids declined by 20–50% with ozone exposure in antibiotic-treated but not control mice. Most taurine-conjugated bile acids increased with ozone exposure in antibiotic-treated but not control mice. Ozone also caused marked (9-fold and 5-fold) increases in the polyamines, spermine and spermidine, respectively, in control but not antibiotic-treated mice. Each of these metabolites has the capacity to alter airway responsiveness and may account for the role of the microbiome in pulmonary responses to ozone.
Ozone (O3) is an air pollutant produced by interactions between sunlight and automobile exhaust. O3 causes injury to the airway epithelium leading to an inflammatory response that includes production of numerous cytokines and chemokine and recruitment of neutrophils to the lungs [
In male C57BL/6 mice, the gut microbiome contributes to the ability of O3 to induce AHR and recruit neutrophils to the lungs [
Gut bacteria can affect the function of distal organs by generating metabolites from dietary factors and by modifying host-derived metabolites [
In rats, acute exposure to O3 causes profound changes in the serum metabolome including increases in sugars, free fatty acids, branched chain amino acids (BCAAs), and urea, indicating impaired glycemic control, lipolysis, and proteolysis [
We hypothesized that global metabolomic profiling of serum collected from O3-exposed mice could be used to identify metabolites contributing to the role of the microbiome in pulmonary responses to O3 [
Male C57BL/6 mice aged 6–7 weeks were purchased from Taconic Farms (New York) and held in the Harvard T.H. Chan School of Public Health vivarium for one week prior to the initiation of antibiotic (or regular water) treatment. The study was approved by the Harvard Medical Area Standing Committee on Animals (protocol 03753). We chose to examine C67BL/6 male mice because we have established the gut microbiome is required for O3-induced AHR in this sex and strain [
Mice (n = 8 per group) were treated with a cocktail of antibiotics in the drinking water for 2 weeks, as previously described [
Mice were exposed to O3 (2 ppm for 3 hours) or to room air. During O3 exposure, mice were placed in individual wire mesh cages inside a 145 L stainless steel chamber with a plexiglass door without food or water. Air-exposed mice were placed in a separate but identical chamber. Immediately after exposure, mice were returned to their home cages and provided with food and control or antibiotic-containing water ad libitum. O3 was generated by passing oxygen through ultraviolet (UV) light. This gas was mixed with room air in the chamber. A sample of the chamber atmosphere was continuously drawn through a sampling port, the O3 concentration within the chamber monitored by a UV photometric O3 analyzer (model 49; Thermo Electron Instruments, Hopkinton, MA).
Twenty four hours after exposure, mice were euthanized with an overdose of sodium pentobarbital. Blood was obtained by cardiac puncture for the preparation of serum. Serum was stored at -80°C until shipped on dry ice to Metabolon Inc. (Durham, NC). Upon receipt, the serum was again frozen at -80°C until analysis.
Samples were shipped to Metabolon for processing and prepared for metabolomics as previously described [
The LC/MS portion of the platform was based on a Waters ACQUITY ultra-performance liquid chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. Each sample extract was first dried, then reconstituted in acidic or basic LC-compatible solvents. To ensure injection and chromatographic consistency, these solvents each contained 8 or more injection standards at fixed concentrations. One aliquot was analyzed using acidic positive ion optimized conditions and the other using basic negative ion optimized conditions in two independent injections using separate dedicated columns (Waters UPLC BEH C18-2.1x100 mm, 1.7 μm). Extracts reconstituted in acidic conditions were gradient eluted from a C18 column using water and methanol containing 0.1% formic acid. The basic extracts were similarly eluted from C18 using methanol and water, however with 6.5mM Ammonium Bicarbonate. The third aliquot was analyzed via negative ionization following elution from a HILIC column (Waters UPLC BEH Amide 2.1x150 mm, 1.7 μm) using a gradient consisting of water and acetonitrile with 10mM Ammonium Formate. The MS analysis alternated between MS and data-dependent MS2 scans using dynamic exclusion, and the scan range was from 80–1000 m/z.
For GC-MS analysis, samples were dried under vacuum for at least 18 h prior to derivatization under dried nitrogen using bistrimethyl-silyltrifluoroacetamide. Derivatized samples were separated on a 5% diphenyl / 95% dimethyl polysiloxane fused silica column (20 m x 0.18 mm ID; 0.18 um film thickness) with helium as carrier gas and a temperature ramp from 60° to 340°C over a 17.5 min period. Samples were analyzed on a Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer using electron impact ionization (EI) and operated at unit mass resolving power. The scan range was from 50–750 m/z.
Raw data were extracted, peak-identified and QC processed using Metabolon’s proprietary hardware and software. Compounds were identified by comparison to library entries of purified standards or recurrent unknown entities. This library is based on authenticated standards and contains the retention time/index (RI), mass to charge ratio (
Livers were excised from another cohort of male mice treated and exposed in an identical manner [
To assess the significance of differences in mRNA abundances, factorial ANOVA with treatment and exposure as main effects was used with LSD Fisher post-hoc analysis (Statistica Software, Tulsa, OK). For metabolomics data analysis, for each metabolite, raw peak area counts were rescaled to set the median across all samples to 1. A two way ANOVA using the factors, treatment and exposure, was then performed on log transformed data. Follow-up pairwise contrasts were performed using F-tests. Storey’s q-values were calculated to estimate the proportion of false positives.
To determine whether there were metabolic pathways that were enriched for significantly affected metabolites, we calculated an enrichment factor (EF) as follows:
Antibiotic treatment and O3 exposure each had profound effects on the metabolome of serum. Among the 562 named biochemicals identified in serum, two-way ANOVA identified 228 that were significantly (p<0.05 and q<0.10) affected by antibiotic treatment, 334 that were affected by O3 exposure, and 185 for which there was an interaction between antibiotic treatment and O3. Differences between individual experimental groups are shown in
Air | Ozone | Water | Antibiotics | |
---|---|---|---|---|
Total biochemicals p≤0.05and q≤0.10 | 244 | 144 | 257 | 291 |
Biochemicals |
146/98 | 46/98 | 92/165 | 54/237 |
Serum metabolites from male C57BL/6 mice treated with regular drinking water or with a cocktail of antibiotics were analyzed. Treatment continued for 2 weeks at which time mice were exposed to air or ozone (2 ppm for 3 h) and studied 24 h after exposure. n = 8 per group.
In air-exposed mice, antibiotic treatment caused significant changes in serum biochemicals within multiple metabolic pathways (
For each metabolite, peaks were quantified using area-under-the-curve. Then, the median area-under-the-curve for that metabolite across all mice in all groups was calculated. Then, a scaled intensity for each metabolite was calculated by dividing the raw area counts for each mouse by this median so that the median across all mice in all groups was now equal to 1. This scaled intensity is presented on the y axis. For each group, the + indicates the mean value and the line in the center of bar indicates the median. The upper and lower limits of the bar are the upper and lower quartile and the top and bottom of the error bars are the maximum and minimum of the distribution. Extreme data points are indicated by symbols outside of the maximum and minimum of the distribution. # p<0.05 and q<0.10 versus water-treated mice with the same exposure; * p<0.05 and q<0.10 versus air exposed mice with same treatment. n = 8 per group.
Treatment with antibiotics also caused a significant, 18% reduction in serum glucose (
Lipid | Ozone/Air |
Ozone/Air |
Antibiotics/Water |
Antibiotics/Water |
---|---|---|---|---|
caproate (6:0) | 1.22 |
1.11 | 1.36 |
1.24 |
heptanoate (7:0) | 1.16 |
0.75 |
1.52 |
0.98 |
caprylate (8:0) | 1.24 |
0.88 | 1.24 |
0.88 |
pelargonate (9:0) | 1.21 | 0.79 | 1.18 | 0.77 |
caprate (10:0) | 1.24 |
0.83 | 1.19 | 0.80 |
undecanoate (11:0) | 1.17 | 0.74 |
1.46 |
0.92 |
10-undecenoate (11:1n1) | 1.53 |
0.48 |
4.10 |
1.29 |
Laurate | 1.32 |
0.77 |
1.43 |
0.83 |
myristate (14:0) | 1.06 | 0.59 |
1.30 | 0.73 |
myristoleate (14:1n5) | 1.74 |
0.64 |
1.72 |
0.63 |
pentadecanoate (15:0) | 0.92 | 0.63 |
1.12 | 0.77 |
palmitate (16:0) | 0.87 | 0.61 |
1.11 | 0.77 |
palmitoleate (16:1n7) | 1.23 | 0.62 | 1.15 | 0.58 |
margarate (17:0) | 0.95 | 0.46 |
1.67 |
0.81 |
10-heptadecenoate (17:1n7) | 1.03 | 0.54 |
1.28 | 0.67 |
stearate (18:0) | 0.83 | 0.56 |
1.35 | 0.91 |
oleate (18:1n9) | 0.89 | 0.64 |
1.18 | 0.85 |
cis-vaccenate (18:1n7) | 0.84 | 0.74 | 1.10 | 0.97 |
nonadecanoate (19:0) | 0.57 |
0.46 |
1.10 | 0.88 |
10-nonadecenoate (19:1n9) | 1.07 | 0.49 |
1.55 | 0.71 |
arachidate (20:0) | 0.34 |
0.36 |
0.77 | 0.83 |
eicosenoate (20:1) | 0.65 | 0.41 |
1.05 | 0.67 |
erucate (22:1n9) | 0.35 |
0.31 |
0.81 | 0.72 |
stearidonate (18:4n3) | 0.71 | 0.33 |
1.49 |
0.68 |
eicosapentaenoate (EPA; 20:5n3) | 1.27 | 0.64 |
1.85 |
0.93 |
docosapentaenoate (n3 DPA; 22:5n3) | 1.07 | 0.50 |
1.44 | 0.68 |
docosahexaenoate (DHA; 22:6n3) | 1.16 | 0.58 |
1.67 |
0.83 |
linoleate (18:2n6) | 1.25 | 0.58 |
1.46 |
0.67 |
linolenate [alpha or gamma; (18:3n3 or 6)] | 1.07 | 0.41 |
1.54 |
0.59 |
dihomo-linolenate (20:3n3 or n6) | 0.82 | 0.63 |
1.14 | 0.87 |
arachidonate (20:4n6) | 1.27 | 1.11 | 1.53 |
1.33 |
adrenate (22:4n6) | 0.81 | 0.49 |
1.49 | 0.90 |
docosapentaenoate (n6 DPA; 22:5n6) | 0.68 |
0.47 |
1.39 |
0.96 |
docosadienoate (22:2n6) | 0.40 |
0.39 |
0.71 | 0.69 |
dihomo-linoleate (20:2n6) | 0.87 | 0.42 |
1.42 | 0.68 |
mead acid (20:3n9) | 0.78 | 0.71 | 1.16 | 1.06 |
1-pentadecanoylglycerol (15:0) | 0.55 |
0.42 |
1.25 | 0.97 |
1-palmitoylglycerol (16:0) | 0.59 |
0.31 |
2.02 |
1.06 |
2-palmitoylglycerol (16:0) | 0.79 | 0.30 |
2.49 |
0.96 |
1-stearoylglycerol (18:0) | 0.83 | 0.79 | 1.17 | 1.12 |
1-oleoylglycerol (18:1) | 0.46 |
0.42 |
1.13 | 1.02 |
2-oleoylglycerol (18:1) | 0.56 |
0.36 |
1.57 |
0.99 |
1-linoleoylglycerol (18:2) | 0.81 | 0.37 |
1.85 |
0.85 |
2-linoleoylglycerol (18:2) | 0.65 |
0.37 |
1.48 |
0.83 |
1-linolenoylglycerol (18:3) | 0.43 |
0.31 |
1.09 | 0.79 |
1-arachidonylglycerol (20:4) | 1.42 |
0.49 |
3.05 |
1.05 |
2-arachidonoylglycerol (20:4) | 0.98 | 0.65 |
1.98 |
1.31 |
1-docosahexaenoylglycerol (22:6) | 0.77 | 0.48 |
1.56 |
0.97 |
1-dihomo-linolenylglycerol (alpha, gamma) | 0.81 | 0.39 |
1.93 |
0.92 |
2-docosahexaenoylglcyerol | 1.07 | 0.50 |
2.07 |
0.97 |
palmitoyl-arachidonoyl-glycerophosphocholine (1) | 1.17 |
1.05 | 1.12 | 1.01 |
palmitoyl-arachidonoyl-glycerophosphocholine (2) | 1.19 |
1.17 |
1.03 | 1.01 |
palmitoyl-linoleoyl-glycerophosphocholine (1) | 0.85 |
0.84 |
1.03 | 1.01 |
palmitoyl-linoleoyl-glycerophosphocholine (2) | 0.85 |
0.88 |
0.98 | 1.01 |
palmitoyl-oleoyl-glycerophosphocholine (1) | 0.74 |
0.89 | 0.81 |
0.97 |
stearoyl-arachidonoyl-glycerophosphocholine (1) | 1.60 |
1.03 | 1.66 |
1.08 |
stearoyl-arachidonoyl-glycerophosphocholine (2) | 1.57 |
1.21 |
1.38 |
1.06 |
oleoyl-linoleoyl-glycerophosphocholine (1) | 0.89 |
0.93 | 1.12 |
1.16 |
oleoyl-linoleoyl-glycerophosphocholine (2) | 0.89 | 0.83 |
1.21 |
1.13 |
palmitoyl-palmitoyl-glycerophosphocholine (1) | 1.01 | 0.93 | 1.08 | 1.00 |
palmitoyl-palmitoyl-glycerophosphocholine (2) | 1.14 |
1.02 | 1.15 |
1.03 |
stearoyl-linoleoyl-glycerophosphocholine (1) | 0.78 |
0.73 |
1.26 |
1.19 |
stearoyl-linoleoyl-glycerophosphocholine (2) | 0.76 |
0.66 |
1.37 |
1.19 |
For each metabolite, peaks were quantified using area-under-the-curve. Then, the median area-under-the-curve for that metabolite across all mice in all groups was calculated. Then, a scaled intensity for each metabolite was calculated by dividing the raw area counts for each mouse by this median so that the median across all mice in all groups was now equal to 1. A two way ANOVA using the factors, treatment and exposure, was then performed on log transformed data. Follow-up pairwise contrasts were performed using F-tests. Storey’s q-values were calculated to estimate the proportion of false positives. Results here are the ratio of mean lipid metabolite scaled intensity in O3 versus air exposed mice treated with regular drinking water (column 2) or in O3 versus air exposed mice treated with antibiotic-supplemented drinking water (column 3). Also shown are the mean lipid metabolite scaled intensity in antibiotic versus water treated mice exposed to air (column 4) or O3 (column 5). For example, a ratio of 1.5 for a metabolite indicates a 50% increase in that metabolite. Green and red highlighted areas indicate a significant (p<0.05 and q<0.10) decrease or increase in that metabolite.
*p<0.05 and q<0.10 versus air exposed mice with the same treatment;
# p<0.05 and q<0.10 versus water-treated mice with the same exposure.
In mice exposed to air, there were also effects of antibiotics on serum bile acids (
Bile acid | Ozone/Air |
Ozone/Air |
Antibiotics/Water |
Antibiotics/Water |
---|---|---|---|---|
cholate | 0.10 |
5.29 |
0.03 |
1.85 |
glycocholate | 0.79 | 5.70 |
0.68 | 4.92 |
taurocholate | 0.77 | 11.43 |
2.31 | 34.14 |
chenodeoxycholate | 0.73 | 1.66 | 0.99 | 2.27 |
taurochenodeoxycholate | 1.24 | 10.99 | 5.18 |
45.98 |
beta muricholate | 0.26 | 19.05 |
0.08 |
5.97 |
tauro-beta-muricholate | 0.54 | 22.72 |
3.58 |
150.95 |
deoxycholate | 1.12 | 10.91 |
0.07 |
0.66 |
taurodeoxycholate | 2.44 | 17.12 |
1.06 | 7.42 |
ursodeoxycholate | 0.09 |
4.53 |
0.05 |
2.45 |
tauroursodeoxycholate | 0.62 | 36.50 |
2.37 | 138.75 |
hyodeoxycholate | 0.63 | 1.62 | 0.18 |
0.46 |
taurohyodeoxycholate | 1.57 | 22.74 |
0.64 | 9.25 |
cholesterol | 0.82 |
0.94 | 1.00 | 1.15 |
Results are the ratio of mean bile acid scaled peak area in mice treated with regular drinking water or antibiotic-supplemented drinking water and exposed to air or ozone. See figure legend for
*p<0.05 and q<0.10 versus air exposed mice with the same treatment;
# p<0.05 and q<0.10 versus water treated mice with the same exposure.
Green indicates a significant decrease and red indicates a significant increase. n = 8/group
Bacterial processes that modify bile acids are indicated by the dashed blue boxes. The primary bile acids cholic acid, chenodeoxyholic acid, and β muricholic acid are produced from cholesterol, conjugated with taurine or glycine in the host liver, and secreted into the bile. In the intestinal lumen, bacteria convert primary bile acids to secondary bile acids by dehydroxylation and also deconjugate bile acids. Bile acids are absorbed across enterocytes into the enterohepatic circulation and returned to the liver. A portion (about 5%) remain in the blood and are delivered to the systemic circulation. Liver expression of the enzymes indicated in red text were assayed.
There was a marked effect of antibiotic treatment on serum γ-glutamyl amino acids: all 12 of the12 γ-glutamyl amino acids identified in serum were decreased in antibiotic-treated versus control mice exposed to air (
γ-glutamyl amino acids | Ozone/Air |
Ozone/Air |
Antibiotics/Water |
Antibiotics/Water |
---|---|---|---|---|
γ -glutamylalanine | 0.60 |
0.84 | 0.65 |
0.91 |
γ -glutamylglutamate | 0.26 |
0.40 |
0.48 |
0.73 |
γ -glutamylglutamine | 0.62 |
1.16 | 0.40 |
0.76 |
γ -glutamylisoleucine | 0.52 |
0.57 |
0.70 |
0.76 |
γ -glutamylleucine | 0.50 |
0.63 |
0.61 |
0.77 |
γ -glutamyl-epsilon-lysine | 0.51 |
0.58 |
0.70 |
0.80 |
γ -glutamylmethionine | 0.46 |
0.93 | 0.54 |
1.09 |
γ -glutamylphenylalanine | 0.70 |
0.73 |
0.77 |
0.80 |
γ -glutamylthreonine | 0.65 |
0.82 |
0.66 |
0.84 |
γ -glutamyltryptophan | 0.60 |
0.65 |
0.79 |
0.85 |
γ -glutamyltyrosine | 0.54 |
0.63 |
0.67 |
0.78 |
γ -glutamylvaline | 0.53 |
0.59 |
0.64 |
0.72 |
Results are the ratio of mean γ-glutamyl amino acid scaled peak area in mice treated with regular drinking water or antibiotic-supplemented drinking water and exposed to air or ozone. See figure legend for
*p<0.05 and q<0.10 versus air exposed mice with the same treatment;
# p<0.05 and q<0.10 versus water treated mice with the same exposure.
Green indicates a significant decrease. n = 8/group
Gamma glutamyl transferase (GGT) metabolizes glutathione, in the presence of an amino acid, to form a γ-glutamyl amino acid and cysteinylglycine. γ-glutamyl amino acids are then metabolized to oxoproline and an amino acid and oxoproline is converted back to glutathione. Metabolites in red were significantly affected either by O3 or antibiotics or both.
To determine whether there were metabolic pathways that were enriched among those metabolites significantly affected by O3 exposure, we calculated an enrichment factor (
Superpathway | Pathway | n | Water-treated | Antibiotic-treated | ||
---|---|---|---|---|---|---|
EF | p value | EF | p value | |||
Amino acids | 163 | 1.11 | 0.24 | 0.90 | 0.12 | |
Peptides | 20 | 0.033 | 1.16 | 0.454 | ||
γ-glutamyl amino acids | 12 | 0.0002 | 1.45 | 0.104 | ||
Carbohydrates | 27 | 0.73 | 0.206 | 0.86 | 0.434 | |
Energy | 8 | 0.55 | 0.24 | 0.97 | 0.919 | |
Lipids | 217 | 0.97 | 0.708 | 0.0003 | ||
Medium chain fatty acid | 8 | 1.64 | 0.099 | 0.97 | 0.919 | |
Long chain fatty acid | 15 | 0.58 | 0.133 | 0.0061 | ||
Polyunsaturated fatty acid | 13 | 0.030 | 0.0165 | |||
Fatty acid, dicarboxylate | 16 | 0.032 | 1.45 | 0.0593 | ||
Monohydroxy fatty acid | 17 | 0.022 | 1.25 | 0.279 | ||
Phospholipid metabolism | 6 | 0.36 | 0.155 | 0.97 | 0.930 | |
Lysolipid | 30 | 1.38 | 0.060 | 1.03 | 0.861 | |
Phosphatidylcholine | 13 | 0.0055 | 1.04 | 0.880 | ||
Other phospholipids (PE, PI, and glycerolipid metabolism) | 9 | 1.70 | 0.056 | 1.07 | 0.819 | |
Monoacylglyceride | 14 | 1.09 | 0.75 | 0.0018 | ||
Sphingolipid metabolism | 9 | 1.46 | 0.21 | 1.29 | 0.368 | |
Bile acid metabolism | 13 | 0.030 | 1.49 | 0.0664 | ||
Nucleotides | 41 | 0.040 | 0.85 | 0.295 | ||
Cofactors and vitamins | 23 | 1.14 | 0.54 | 0.76 | 0.215 | |
Xenobiotics | 63 | 1.07 | 0.60 | 0.80 | 0.077 |
n: number of metabolites in pathway; Enrichment factor (EF) was computed as follows: (# of metabolites in pathway significantly affected by ozone exposure/ total # of detected metabolites in pathway)/ (total # of metabolites affected by ozone/total # of detected metabolites). Individual metabolites were considered to have been significantly affected if p<0.05 and q<0.10. p values in the table indicate the significance of enrichment of the metabolite group compared to the total number of significantly affected metabolites and were computed by Chi square test. Pathways with significant enrichment of significantly altered metabolites are indicated in bold text.
Results are expressed as described in
As indicated in
There were also changes in other metabolites following O3 exposure. O3 changed many serum amino acids and their metabolites, consistent with data reported in rats [
Serum (A) spermidine and (B) spermine in mice treated with water or antibiotics prior to air or ozone. (C) Schematic representation of the metabolism of polyamines. Arg1: arginase 1; ODC: ornithine decarboxylase; SAM: S-Adenosinemethionine; SAM-dc: Decarboxy-S-adenosinemethionine; MTA: 5-methylthioadenosine (MTA). In C, metabolites that were affected by antibiotics, ozone, or the combination of antibiotics and ozone are shown in red. Results are expressed as described in
As discussed above, γ-glutamyl amino acids and phosphatidylcholine species were significantly enriched among the metabolites affected by O3 in water-treated mice (
Many tyrosine and tryptophan metabolites were also differentially affected by O3 exposure in control and antibiotic treated mice, likely because many of these metabolites are derivatives of bacterial metabolism of these amino acids (
O3-induced changes in serum bile acid metabolites also differed substantially in water- versus antibiotic-treated mice (
Results are expressed relative to expression in air-exposed water-treated mice and are shown as mean +/- SE of data from n = 6-7/mice per group * p<0.05 versus air exposed mice with the same treatment. # p<0.05 versus water-treated mice with the same exposure.
In rodents, acute exposure to O3 reduces thyroxine and increases corticosterone [
Results are expressed as described in
The purpose of this study was to identify metabolites affected by the gut microbiome that may mediate the role of the microbiome in pulmonary responses to O3 [
Even in air-exposed mice, antibiotic treatment had a substantial effect on the serum metabolome. Nearly 45% of the metabolites identified were significantly different in control versus antibiotic-treated mice exposed to air (
In antibiotic-treated mice, O3 caused significant decreases in most long chain fatty acids (
The reductions in serum long chain fatty acids, PUFAs, and monoglycerides observed after O3 exposure in antibiotic-treated mice (Tables
O3 increased serum concentrations of many bile acids, especially taurine-conjugated bile acids, in antibiotic-treated but not water-treated mice (
We do not know the mechanistic basis for the increases in bile acids observed in antibiotic-treated mice exposed to O3 (
We observed marked increases in the polyamines, spermine and spermidine, in serum of water- but not antibiotic-treated mice after O3 exposure (
There are several limitations to this study. First, we studied only male mice. There are sex differences in the effects of O3 on AHR [
It is interesting to note that while antibiotics appropriately attenuated many known bacterial-derived metabolites, O3 had similar effects on many of the same metabolites (
In summary, we observed marked effects of O3 exposure on the serum metabolome that differed in control mice and mice in which the gut microbiome had been depleted with antibiotics. In particular, O3-induced changes in serum lipids were markedly different in control and antibiotic-treated mice. Microbial-dependent changes in some of these lipids, notably bile acids and long chain fatty acids, as well as changes in the polyamines, spermine and spermidine, may account for the role of the microbiome in pulmonary responses to O3, since each of these metabolites has the capacity to alter airway responsiveness and neutrophil recruitment.
The blue shaded areas indicate significant (p<0.05, q<0.10) effects on two-way ANOVA. Fold change results are the ratio of mean lipid metabolite scaled peak area in mice treated with regular drinking water or antibiotic-supplemented drinking water and exposed to air or ozone, as described in
(XLSX)
A scaled intensity for each metabolite was calculated by dividing the raw area counts for each mouse by this median so that the median across all mice in all groups was now equal to 1, as described in
(XLSX)