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Published in final edited form as: Metabolomics. 2013 Jun 1;10(1):8–20. doi: 10.1007/s11306-013-0546-5

Prolonged antibiotic use induces intestinal injury in mice that is repaired after removing antibiotic pressure: implications for empiric antibiotic therapy

Lindsey E Romick-Rosendale 1, Anne Legomarcino 2, Neil B Patel 3, Ardythe L Morrow 4,5, Michael A Kennedy 6,✉
PMCID: PMC4532301  NIHMSID: NIHMS711671  PMID: 26273236

Abstract

Metabolic profiling of urine and fecal extracts, histological investigation of intestinal ilea, and fecal metagenomics analyses were used to investigate effects of prolonged antibiotic use in mice. The study provides insight into the effects of extended empiric antibiotic therapy in humans. Mice were administered a broad-spectrum antibiotic for four consecutive days followed by oral gavage with Clostridium butyricum, an opportunistic gram-positive pathogenic bacteria commonly isolated in fecal and blood cultures of necrotizing enterocolitis patients. Metagenomics data indicated loss of bacterial diversity after 4 days on antibiotics that was restored after removing antibiotic pressure. Histological analyses indicated damage to ileal villi after antibiotic treatment that underwent repair after lifting antibiotic pressure. Metabolic profiling confirmed intestinal injury in antibiotic-treated mice indicated by increased urinary trans-4-hydroxy-l-proline, a breakdown product of collagen present in connective tissue of ileal villi that may serve as a biomarker for antibiotic-induced injury in at risk populations.

Keywords: Antibiotic, Metabolomics, Mouse model, Necrotizing enterocolitis, NMR, PCA

1 Introduction

Empiric antibiotic therapy is prescribed for many human conditions including urinary tract infections (Aypak et al. 2009), inflammatory bowel disease (Balfour Sartor 2004; Shanahan and Bernstein 2004; Perencevich and Burafkoff 2006; Hammer 2011) organ transplants (Hamandi et al. 2009), lyme disease (Klempner et al. 2001; Marques 2008; Wright et al. 2012), cancer patients with febrile neutropenia caused by chemotherapy Kern et al. 2013) and nursing home acquired infections in elderly patients (Xie et al. 2012). Prolonged broad-spectrum empiric antibiotics are also prescribed for serious bacterial infections such as bacteremia, sepsis and pneumonia (Kollef 2008; Iapichino et al. 2008; Siddiqui and Razzak 2012). While antibiotics offer obvious benefits for treating human bacterial infections, even short regimens can have long-lasting impacts on the human gut microbial population (Jernberg et al. 2007; Dethlefsen et al. 2008; Jakobsson et al. 2010) and prolonged broad spectrum antibiotic therapy can significantly alter the normal balance of beneficial microbiota (Jernberg et al. 2007; Dethlefsen et al. 2008; Willing et al. 2011) essential to innate and adaptive immunity, relative infection susceptibilities, immune tolerance, bioavailability of nutrients, and intestinal barrier function (Preidis and Versalovic 2009; Neish 2009; MacDonald and Monteleone 2005). Antibiotic therapy can also give rise to emergent antibiotic-resistant pathogenic bacteria precipitating severe health consequences as in antibiotic associated diarrhea (Doron et al. 2008; Hempel et al. 2012) caused by Clostridium difficile leading to pseudomembraneous colitis (Faris et al. 2010).

Judicial use of empiric antibiotics is crucial in fragile populations such as neonates and preterm infants. Recent studies have demonstrated a strong correlation between empiric antibiotic treatment of extremely low birth weight (ELBW) preterm infants and higher rates of neonatal necrotizing enterocolitis (NEC) (Kuppala et al. 2011; Cotton et al. 2009), early onset sepsis (Stoll et al. 2002; Cordero and Ayers 2003; Clark et al. 2006), and death (Kuppala et al. 2011; Clark et al. 2006). Nearly all ELBW neonates receive empiric antibiotics in the first days following birth (Cotton et al. 2009) even though many are not actually infected (Clark et al. 2006; Stoll et al. 2005). Empiric antibiotic therapy continues to be standard in neonatal intensive care units for preterm infants considered at risk of sepsis as the benefits are widely perceived to outweigh the risks (McGuire et al. 2004) although there is growing concern about this practice (Tripathi et al. 2012; Tzialla et al. 2012).

The gastrointestinal tract of preterm infants is often colonized initially with relatively few beneficial bacteria compared to full-term newborn infants due to empiric antibiotic therapy. Preterm infants also experience delayed gut colonization with protective bacterial species, such as Bifidobacteria, while high levels of Enterobacteria and Clostridia are commonly found in these same infants with C. butyricum and C. perfringens most common among Clostridial species (Gewolb et al. 1999). This early gut microbiota imbalance may contribute to NEC onset since minor microflora species inhabiting intestines under normal circumstances have the potential to become pathogenic when present in high numbers (Lawrence et al. 1982; Kosloske 1994) and C. butyricum, suggested as a potential contributing factor in NEC (Sturm et al. 1980; Howard et al. 1977), is thought to be such an opportunistic pathogen.

Here, in BALB/c mice, we examined the gut microbial community, urine and fecal metabolic profiles, and ileum of the small intestine under extended broad-spectrum antibiotics and following removal of antibiotic pressure and exposure to C. butyricum. Fecal metagenomics data, histological analyses of intestinal ilea, and proton (1H) nuclear magnetic resonance (NMR) spectroscopy-based metabolic profiling of urine and fecal extracts indicated decreased gut microbial diversity and injury to distal intestinal ileal villi under antibiotic pressure that reversed after stopping antibiotic administration indicating an important host/gut microbial symbiosis required for normal gut structure and function. Metabolic profiling data revealed urinary trans-4-hydroxy-l-proline, a breakdown product of collagen present in connective tissue of ileal villi, as a potentially useful biomarker of antibiotic-induced injury in at risk populations receiving empiric or prolonged broad-spectrum antibiotics.

2 Materials and methods

2.1 Animals and treatment

All animal studies were approved by the Miami University Institutional Animal Care and Use Committee. Mice were 4 weeks old at the start of the study, which corresponded to 1 week post weaning. Mice were fed a common rodent liquid diet that comes in powder form was prepared each day. Samples were collected from 24 BALB/c mice (Harlan Laboratories, Indianapolis, IN) held in custom-built metabolism cages (Romick-Rosendale 2011). Modifications were made to cages to limit cross contamination between the urine and feces. Mice were administered 50 ml of PMI micro-stabilized rodent liquid diet LD101 (Test-Diet, Richmond, IN) once daily for four consecutive days. On the fourth day, four mice were sacrificed for histological studies. Beginning on the fifth day, all remaining mice were given the same liquid diet supplemented with 0.4 µl per gram of body mass of enrofloxacin 10 % oral solution (Oxford Veterinary Hospital, Oxford, Ohio) for four consecutive days. Similar dosages of enrofloxacin were previously administered to rodents and shown to eliminate both gram-negative and gram-positive microflora. On the eighth day, four additional mice were sacrificed for histological studies. On the ninth day, mice were administered C. butyricum LMG 1217 (Belgian Co-Ordinated Collections of Micro-Organisms, Belgium) by intragastric gavage. All remaining mice were sacrificed on the thirtieth day and subjected to histological analyses. Animal experiments were conducted according to federal and local guidelines and the animal handling protocols were approved by Miami University Institutional Animal Care and Use Committee.

2.2 Metagenomics analysis of bacterial species in feces

Frozen fecal samples were pooled from six mice in each of the four groups and shipped to the Research and Testing Laboratory, LLC (Lubbock, Texas) for metagenomics data collection. The 16sRNA samples were extracted on site by Research and Testing Laborotory, LLC and subjected to tag-encoded FLX amplicon pyrosequencing (Sun et al. 2011) at a 3 K average coverage. Raw metagenomics data was analyzed using Qiime (Caporaso et al. 2010) (http://www.qiime.org). The resulting data were subjected to a two-way cluster analysis using Ward’s clustering method and the Jaccard similarity coefficient in R (R Development Core Team 2008).

2.3 Intestinal histology

Intestinal ileum biopsies from control mice, antibiotic-treated mice, and Clostridial-treated mice were fixed in neutral buffered formalin solution overnight, dehydrated, embedded in paraffin and sectioned at 5 µm. Staining of intestinal ileum sections was carried out with hematoxylin and eosin. Results are based on assessment of four or more mice per group examined.

2.4 Biofluid sample collection

Control urine and fecal samples were collected for 4 days prior to treatment. Urine and fecal samples were collected once daily during the 4 days that enrofloxacin (Baytril) was given. Once C. butyricum was introduced by intragastric gavage, urine and fecal samples were collected ever other day for the remainder of the study. All mice were maintained in separate animal cages and transferred to individual metabolic cages for all sample collection. Mice were transferred to the metabolic cages at 6 p.m. and urine and fecal samples were collected at 9 a.m. the following day. All samples were kept at −80 °C after collection and prior to NMR analysis.

2.5 Preparation of biological fluids for NMR analysis

Samples were thawed on ice prior to preparation for NMR analysis. A 1-ml aliquot of each urine sample was centrifuged for 10 min at 2,500×g, and then 350 µl of clear urine was pipette into a 1.5 ml microcentrifuge tube. A volume of 350 µl of buffer (300 mM KH2PO4, 2 mM NaN3, 0.01 % Trimethylsilyl propionate (TSP) in 100 %D2O, pH 7.4) was added to each urine sample. A volume of 600 µl of the urine/buffer mixture was then pipette into a 5 mm NMR tube (Norell ST500-7). Aqueous fecal extract was prepared by adding a known amount of thawed feces (~0.5 g) to two volumes (w/v) of sterile phosphate buffered saline (1.0 mM Na2HPO4, 8.1 mM NaH2PO4, 150 mM NaCl, pH 7.4). The fecal/buffer mixture was then homogenized by vortexing for 1 min per sample. The samples were then centrifuged at 4 °C for 1 h at 18,000×g. A volume of 350 µl of the fecal extract was then added to 350 µl of water containing 20 % D2O, and 0.02 % TSP in a 1.5 ml microcentrifuge tube. The mixture was then vortexed for 1 min and then centrifuged for 10 min at 10,000×g. A volume of 550 µl of the clear supernatant was pipette into a 5 mm NMR tube (Norell ST500-7).

2.6 NMR data collection and processing

All data were collected as described in Romick-Rosendale et al. (Romick-Rosendale et al. 2009) at 850 MHz 1H frequency using a Bruker Avance III NMR spectrometer.

2.7 Multivariate statistical analysis of NMR spectra

Principal component analysis (PCA) and statistical analysis were performed using AMIX (Bruker Biospin, Billerica, MA). NMR spectra were binned into 0.03 ppm wide buckets over the region δ 10.0–0.5 ppm. The region of δ 4.75–4.875 was removed from the analysis to avoid effects of imperfect water suppression. All spectra were normalized and PCA analysis was conducted as described in Watanabe et al. (2011). The Bonferroni-corrected α-values were determined as described by Goodpaster et al. (Goodpaster et al. 2010) for each urine and fecal comparison: Urine Control/Antibiotic-treated: 5.07 × 10−5, Urine Antibiotic-treated/Clostridium-treated: 7.94 × 10−5, Urine Control/Clostridium-treated: 8.01 × 10−5, Feces Control/Antibiotic-treated: 9.82 × 10−5, Feces Antibiotic-treated/Clostridium-treated: 9.09 × 10−5, and comparison between Feces Control/Clostridium-treated: 9.03 × 10−5. Changes in bucket intensities and metabolite concentrations, with p values less than the Bonferroni-corrected α-values were considered to be statistically significant. The loadings plot data points were color-coded according to bucket p-values: black (>α-value, i.e., not statistically significant), blue (α-value > 10−5), green (10−5–10−6), yellow (10−6–10−7), red (10−7–0). Fold-changes were calculated by dividing the antibiotic-treated bucket means by the control bucket means, the Clostridium-treated bucket means by the control bucket means, and the clostridium-treated bucket means by the antibiotic-treated bucket means. For fold changes less than 1.0, the negative inverse of the above ratios were calculated and the resulting values were expressed as “negative” fold changes.

2.8 Mahalanobis distance and F value calculations

Mahalanobis distance calculations were performed in MatLab using a method to quantitatively and statistically analyze group separation of NMR data developed by Goodpaster et al. (Goodpaster and Kennedy 2011) Critical F values were calculated using http://www.danielsoper.com/statcalc/calc04.aspx.

2.9 Identification of metabolites

Statistical significance analysis was used to identify the bucket frequencies that showed significant changes in the various treatment groups compared to the control, or changes between treatment groups (Goodpaster et al. 2010). Next, a list of tentatively assigned metabolites was generated for further validation. The chemical shifts for each tentatively assigned metabolite were compared against the chemical shifts of candidate metabolites using the ChenomX NMR Suite (ChenomX Inc., Edmonton, Alberta, Canada) and other published data (Bundy et al. 2007). A summary of NMR spectral assignments of metabolites is given in Table S1.

3 Results

3.1 Metagenomics analysis of fecal bacteria

Metagenomics analysis of feces (1) prior to antibiotics, (2) 4 days after continuous antibiotics, (3) 3 weeks after stopping antibiotics and administration of oral gavage with C. butyricum, and (4) 6 weeks after stopping antibiotics and 3 weeks after oral gavage with B. infantis indicated 76 operational taxonomic units (OTUs) with 18 OTUs present in all four samples, 13 OTUs present in three samples, 16 OTUs present in two samples and 29 OTUs present in one sample (Fig. S1). A redistribution of bacterial taxa occurred under antibiotic pressure that largely reversed after removing antibiotics, however, differences in the bacterial taxa profile remained even after 6 weeks. Examination of the twenty most abundant bacterial taxa in each group (Fig. 1a) revealed changes in relative abundance of bacterial taxa. Prior to antibiotics, the most abundant bacterial taxa had comparable relative abundance, whereas Akkermansia muciniphila dominated under antibiotic pressure. Among Clostridial species (Fig. 1b) C. tepidiprofundum dominated Clostridial species prior to antibiotics, diminished relative to other Clostridial species under antibiotic pressure, and again dominated Clostridial species after removing antibiotics.

Fig. 1.

Fig. 1

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Metagenomics analysis of fecal extracts of mice. a Analysis of the relative abundance of the 20 most abundant bacterial taxa found across the four groups of mice. b Analysis of the relative abundance of Clostridial species across the four groups of mice

3.2 Metabolic profiling of mice urine and fecal extracts indicated similarity between control mice and mice exposed to C. butyricum after removal of antibiotic pressure

NMR data were collected on samples from control mice (C), under antibiotic pressure (A), and following removal of antibiotics and exposure to C. butyricum (CB). Representative urine and fecal extract NMR spectra from each group are shown in Fig. S2. Spectral differences between groups were evident from visual inspection and validated by statistical significance analysis. Unsupervised principal components analysis (PCA) was carried out on spectra from all three groups. PCA scores plots of urine samples (Fig. 2a) revealed that all groups formed distinct clusters indicating unique urinary metabolic profiles. Magnitudes and statistical significance of cluster separations were evaluated by calculating the Mahalanobis distance (DM) between cluster centroids and comparing F-scores to critical F values (Fig. 2a, Supplementary Table S2). The DM between C and A group centroids was 2.063 (F value of >20) indicating statistically significant separation of these groups. Antibiotic-treated mice clustered separately from CB mice, with a DM of 3.103 (F value of >44). Surprisingly, urine spectra of CB mice appeared to cluster with C mice, however the small DM of 1.579 (F-score of >11), indicated the group separation remained statistically significant. Similar cluster patterns were observed in fecal sample PCA scores plots (Fig. 2b), however, cluster separations were larger. For example, the DM was 4.152 between the cluster centroids of C and A groups (F value > 60). Likewise, DM was 4.938 between cluster centroids of A and CB groups, whereas DM was 1.276 between C and CB group clusters.

Fig. 2.

Fig. 2

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PCA of mice urine and fecal extracts before and during antibiotic treatment. PC1 versus PC2 scores plot of mouse urine (a) and fecal (b) samples for control (black), antibiotic-treated (red), and after stopping antibiotic treatment and administration of C. butyricum (green). The 95 % confidence interval for the three clusters of data points were indicated with dotted oval lines (Color figure online)

PCA scores plots of pair-wise comparisons of Control/Antibiotic-treated (C vs A), Antibiotic-treated/C. butyricum-treated (A vs CB), Control/C. butyricum-treated (C vs CB) urine and fecal samples are shown in Fig. 3 and the DM values and F values are given in Table S2. The PCA indicated all groups separated into statistically significant distinct clusters. The PCA loadings plots for each pair-wise comparison are shown in Fig. S3. Eight metabolites (trans-4-hydroxy-l-proline, betaine, taurine, ornithine, hippurate, 3-indoxylsulfate, allantoin, and 2-oxobutyrate) differed in urines of C and A groups (Table S3) whereas 12 metabolites (creatinine, creatine, β-alanine, succinate, 3-hydroxyisovalerate, 3-methyl-2-oxovalerate, formate, fumarate, trans-4-hydroxy-l-proline, glycolate, betaine, and sarcosine) differed between CB and A groups (Table S4). Only two metabolites (methionine and uracil) differed between C and CB groups (Table S5). More metabolite changes occurred in comparisons of fecal samples than urine samples. Five metabolites (galactose, glucose, choline, glutamine, and propionate) differed between fecal extracts of C and A groups (Table S6) whereas nine metabolites (succinate, propionate, β-alanine, valine, isoleucine, galactose, glucose, glutamine, and choline) differed between fecal extracts from CB and A groups (Table S7). Twelve metabolites (phenylalanine, tyrosine, creatinine, creatine, aspartate, methionine, β-alanine, isoleucine, valine, leucine, propionate, and butyrate) changed between C and CB groups (Table S8).

Fig. 3.

Fig. 3

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Pairwise PCA of mice urine and fecal extracts. PC1 versus PC2 scores plot are shown for comparisons of urine (a–c) and fecal (d–f) samples of control versus antibiotic-treated (a, d), antibiotic-treated versus C. butyricum-treated (b, e), and control versus C. butyricum-treated (c, f). Control (black), antibiotic-treated (red), and C. butyricum-treated (green) spectra are represented (Color figure online)

3.3 Histological analyses of mice distal intestinal ilea revealed villi damage under antibiotic pressure that was repaired after removal of antibiotic pressure

Histological cross-sections of distal intestinal ilea from C, A and CB mice are shown in Fig. 4. Characteristic features in C mice (Fig. 4a–c) included well-shaped, elongated villi lined with columnar epithelia having regularly-spaced dark-staining nuclei and evenly distributed dark-staining nuclei in lamina propia defining the villi core, composed of arteries, veins, capillaries, lymphatic vessels, and connective tissue. Figure 4d–f show cross-sections of distal intestinal ilea from A mice, revealing loss of regular villi structure, lack of regularly distributed columnar epithelial cell nuclei lining villi, shortened and irregular villi, in one case ruptured villi (Fig. 4e), and concentration of dark-staining nuclei near the villi base (Fig. 4d–f). These data revealed damage to distal ileal villi associated with prolonged antibiotic treatment. Moreover, two mice died following antibiotic treatment and the histological investigation showed bowel perforation in these mice. Sections of distal intestinal ilea of mice sacrificed 2 weeks after C. butyricum administration are shown in Fig. 4g–i revealing villi resembling those of C mice. These data indicated removal of antibiotic pressure and restored gut bacterial colonization resulted in repair of antibiotic-associated damage to ileal villi.

Fig. 4.

Fig. 4

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Histological sections of distal ilea of control mice, antibiotic-treated mice and mice after stopping antibiotic treatment and administration of C. butyricum. The 5-micron H & E stained sections show typical ileal villi of control mice (a–c), mice after 4 days of continuous antibiotics (d–f), and 3 weeks after stopping antibiotics and administration of C. butyricum

3.4 Metabolic evidence of collagen breakdown in distal ileal villi in antibiotic-treated mice and repair following removal of antibiotic pressure

Trans-4-hydroxy-l-proline (T4HP) was absent in urines of C and CB mice but present in large amounts in A mice. Moreover, T4HP experienced the largest change in the C versus A group comparison exhibiting an average +2.1 fold change for the 15 T4HP-associated buckets, i.e. an average >100 % increase in peak intensity in the A Group compared to the C group. Correspondingly, the p-value for 14 out of the 15 T4HP-associated buckets were 10−4 or smaller. T4HP is a breakdown product of collagen (Näntö-Salonen et al. 1984) found largely in connective tissue (Udenfriend 1966). The villi lamina propia core is mainly composed of connective tissue (Udenfriend 1966); therefore damage to ileal villi and its connective tissue could result in collagen leakage into ileal lumina and degradation into constituent components like T4HP. Breakdown of collagen would explain T4HP in urine of A mice consistent with rat and human studies reporting increased urinary T4HP in collagen breakdown from other causes (Näntö-Salonen et al. 1984, Prockop and Sjoerdsma 1961; Anasuya and Rao 1970). T4HP may serve as a useful marker of intestinal necrosis in NEC in preterm infants and in other childhood inflammatory bowel diseases.

3.5 Further metabolic evidence of intestinal and kidney injury in antibiotic-treated mice

Creatinine, creatine and 3-indoxysulfate decreased and taurine and ornithine increased in A mice urines. Excretion of creatinine and creatine into urine is regulated by kidneys and glomerular filtration rate (Luft et al. 1978). Decreased glomerular filtration associated with kidney injury could lead to decreased excretion of these metabolites. Removal of antibiotic pressure and exposure to C. butyricum restored these metabolites to levels observed in C mice urines. Gut flora can also regulate urine levels of creatinine and creatine since their degradation is enzymatically driven in bacteria unlike in vertebrates (Wyss and Kaddurah-Daouk 2000). Lower urinary levels of 3-indoxysulfate in A mice compared to CB mice were likely associated with reduced excretion, since individuals suffering kidney disease often experience uremia in which metabolites such as 3-indoxysulfate accumulate in blood and are not excreted as waste products in urine (Zgoda-Pols et al. 2011).

Increased urinary levels of taurine, ornithine and betaine in A mice indicated reduced reabsorption in renal proximal tubules as observed in cases of renal damage (Merheb et al. 2007). Taurine has protective properties (Kerai et al. 2001) and hosts may increase taurine production to counteract negative renal and intestinal effects associated with antibiotic treatment. Increased excretion of ornithine occurs in kidney damage and other diseases, such as cystinuria (Fjellstedt et al. 2003). Betaine, increased in urine of A mice compared to C and CB groups, is synthesized from choline in vertebrates (Craig 2004) and may be increased in urine of A mice due to increased urinary choline. Researchers have suggested that betaine is synthesized by renal tubular cells to protect kidney cells against osmotic stress (Chambers and Kunin 1985).

Fecal butyrate and glutamine changed in mice with suspected intestinal injury. Butyrate is a major fermentation product of many bacterial species (Miller and Wolin 1996), especially C. butyricum; however, butyrate produced after colonization of mice with Clostridial species was likely consumed during ileal villi epithelia repair. Butyrate is a chief energy source for intestinal epithelial cells (Roediger 1980), which could explain its decrease in feces of CB mice compared to C mice since ileal epithelial cells would consume butyrate to repair damage associated with antibiotic treatment. Elevated glutamine in A mice feces was correlated with ileal villi damage. Glutamine is metabolized in the small intestine as key respiratory fuel for enterocytes (Hartmann and Plauth 1989); however, intestinal injury caused by antibiotics likely hindered uptake resulting in increased fecal excretion.

3.6 Changes in gut bacteria metabolism

Urinary fumarate, sarcosine, and glycolate decreased in CB mice compared to A mice likely due to loss of microbial enzymes. Succinate is normally converted to fumarate (King et al. 2006), however, absent certain bacterial enzymes the reaction does not take place in the gut. Consequently, succinate accumulation in CB mice indicated absence of key bacterial enzymes for conversion to fumarate. Sarcosine and glycolate are in the creatine/creatinine pathway and creatine is converted to sarcosine by microflora. However, loss of these microbial enzymes could cause elevated creatine in CB mice compared to A mice (Wyss and Kaddurah-Daouk 2000). Glycolate is a bacterial degradation product of creatinine (Wyss and Kaddurah-Daouk 2000) and without key bacterial enzymes for degradation, creatinine would be higher in CB mice urines.

Hippurate, allantoin, 2-oxobutyrate and β-alanine decreased in urine of A mice compared to C mice. Hippurate is produced from benzoate (Beliveau and Brusilow 1987); however, altered gut metabolism could lead to reduced benzoate production and ultimately hippurate synthesis (Williams et al. 2010; Liu et al. 2011). Allantoin decreased in A mice urine due to reduced protein break-down into purine and pyrimidine bases by gut microflora, reduced absorption through the intestinal wall, and reduced allantoin end product excreted in urine (Chen et al.1992; Condon and Hatfield 1970). A similar scenario could explain decreased urinary 2-oxobutyrate in A mice since it is produced from metabolism of amino acids such as threonine and methionine (Paxton et al. 1986) and loss of microbial species would reduce these breakdown products. β-alanine is produced from incomplete oxidation of pantothenate (Gojković et al. 2001) and from digestion of proteins by gut microbial species (West 2011). Decreased β-alanine in A mice indicated reduced microbial species to perform these metabolic processes. Similar findings for β-alanine were found in fecal extracts.

Uracil decreased in urine of CB mice compared to C mice. Uracil catabolism is performed by bacteria using a reductive pathway to convert uracil to β-alanine (West 2011). Here, removing antibiotic pressure and treatment with C. butyricum resulted in gut microflora more efficient at catabolizing pyrimidine bases such as uracil, resulting in higher urinary uracil levels in C mice. Methionine increased in urine of CB mice compared to C mice due to more efficient conversion of homocysteine to methionine by CB mouse gut microbes (Shapiro et al. 1964). S-adenosylmethionine is needed for homocysteine conversion; normal gut flora apparently generate an abundance of this metabolite (Salem and Foster 1972) and methionine increased in fecal extracts of CB mice compared to C mice.

Tyrosine, creatinine, creatine and aspartate increased in fecal extracts of CB mice compared to C mice. Intestinal microflora metabolize these metabolites; consequently, their accumulation in feces would result from reduced catabolism by re-colonized gut flora compared to C mice gut bacteria (Wyss and Kaddurah-Daouk 2000; Sparnins and Chapman 1976). Branched-chain amino acids (BCAAs) isoleucine, leucine and valine increased in feces of CB mice compared to C and A groups. BCAAs are Krebs cycle intermediates produced from breakdown of proteins by microbial enzymes (Salter and Fulford 1974; Freundlich et al. 1962). Reduced gut microbial enzymes in A mice and less efficient breakdown of proteins in C mice compared to CB mice may explain these findings.

3.7 Changes in gut bacteria fermentation

Urinary alanine, succinate and 3-hydroxyisovalerate increased in CB mice compared to A mice, potentially due to fermentation by Clostridial species. Alanine and succinate are common products of sugar (Ravot et al. 1996) and carbohydrate fermentation (Scheifinger and Wolin 1973), respectively. 3-hydroxyisovalerate is produced by leucine and valine fermentation (Freundlich et al. 1962).

Phenylalanine increased in CB mice feces compared to C mice, likely due to higher tyrosine fermentation in C mice (Smith and Macfarlane 1997). Propionate increased in C and CB mice feces compared to A mice. Propionate, like succinate, is derived from carbohydrate fermentation (Scheifinger and Wolin 1973; Stams et al. 1984) using transcarboxylase (Stams et al. 1984). Loss of this microbial enzyme in A mice would result in decreased propionate production. Galactose and glucose increased in A mice feces compared to C and CB mice. Fermentation of sugars by microbial species is well documented (Schaub and Lentze 1973; Koser and Saunders 1933) and sugars are an ideal carbon source for many bacterial strains (Brückner and Titgemeyer 2002). Glucose, catabolized by the Embden-Meyerhof-Parnas pathway, may be diminished in antibiotic-treated mice because of loss of important microbial enzymes (Macy et al. 1978).

3.8 Changes in bacterial growth factors

Formate decreased in CB mice urine compared to A mice. Formate is consumed by many bacteria including methanogens (Kosaka et al. 2008; Cselovszky et al. 1992). Formate is a growth substrate consumed by intestinal bacteria (Kosaka et al. 2008). Increased urinary formate in A mice indicated reduced gut microbial growth.

Choline, increased in feces of A mice compared to C and CB mice, is converted to trimethylamine by intestinal microflora (De La Huerga and Popper 1952); however, reduced gut microbes in A mice resulted in accumulation of choline in feces. Decreased choline in feces of CB compared to A mice was correlated with increased gut microbial colonization resulting in increased choline utilization in cell membrane synthesis, phospholipid metabolism and cholesterol integration (Martin et al. 2008; Mosser and Tomasz 1970).

4 Conclusions

Empiric antibiotic treatment of preterm infants has been implicated as a potential causative factor of NEC, late onset sepsis, and even death and there is growing debate as to whether prolonged administration of prophylactic empirical antibiotic therapy for preterm infants at risk to infection causes more harm than benefit (Kuppala et al. 2011). Our mouse study indicated distal intestinal ileal villi injury associated with prolonged antibiotic pressure. Metagenomics analysis indicated a significant reduction of gut bacteria diversity under antibiotic pressure and increased abundance of the commensal bacterium, A. muciniphila. Overcolonization of mucin-degrading bacteria may be a causative factor in development of NEC-like symptoms and associated intestinal injury, since intestinal mucosa is not only utilized as an energy source by, but also is an important habitat for, intestinal flora (Hooper et al. 2002; Derrien et al. 2004).

Prolonged and empiric antibiotics has potentially far reaching consequences for diseases other than NEC. For example, disruption of the mucosal barrier has been implicated in the inflammatory bowel disorders Crohn’s disease and ulcerative colitis (UC). More specifically, the mucosal layer in the inflamed region of the intestine in UC patients was found to be thinner (Pullan et al. 1994), leading to the hypothesis that reduced mucus may correlated with elevated abundance of mucin-degrading bacteria, as observed here. In our case, once antibiotic pressure was removed, metagenomics analysis indicated that the diversity of gut bacterial species returned to pre-antibiotic-treatment levels, however, the composition changed significantly upon re-colonization. These observations indicated that prolonged empirical antibiotic therapy could have potentially negative effects on the immature gut of the premature human infant and potentially contribute to NEC incidence in human preterm infants.

Rupturing of intestinal villi can lead to decreased intestinal surface area and reduced nutrient absorption into the blood stream through the intestinal wall. Consistent with our histological findings, the most striking change in the metabolic profiles of urine samples from mice under antibiotic pressure was the appearance of T4HP. If prolonged antibiotic administration also leads to ileal villi damage in human preterm infants, then urinary T4HP could serve as a potential early marker for ileal damage preceding localized gut perforation in preterm infant patients receiving empiric antibiotic therapy.

Although NEC etiology remains unknown, gut colonization with specific microbial organisms has been observed and suggested as potential causative factors in NEC initiation and progression. Our results indicated antibiotic-associated damage to distal intestinal ileal villi that repaired after re-colonization of the gut with diverse microflora suggesting a symbiotic benefit of bacterial colonization and diversity of the ileal villi that outweighed any pathogenic effect of Clostridial species detected in the gut microflora of control mice. Consequently, gut microflora may provide ileal villi with an important proximal source of nutrients from bacterial metabolism that is depleted under antibiotic pressure.

Supplementary Material

supplemental

Acknowledgments

The authors would like to acknowledge support of Miami University and the Ohio Board of Regents for funding to establish the Ohio Eminent Scholar Laboratory where the work was performed. MAK acknowledges Miami University start-up funds that, in part, supported this study. The authors would also like to acknowledge support from Bruker Biospin, Inc that enabled development of the statistical significance analysis software used in the analysis of the data reported in this paper. ALM was supported by R01 HD 059140/HD/NICHD. MAK was supported by a grant from the NIH/NCI (1R15CA152985).

Abbreviations

BCAAs

Branched-chain amino acids

DM

Mahalanobis distance

ELBW

Extremely low birth weight

NEC

Neonatal necrotizing enterocolitis

NMR

Nuclear magnetic resonance

OTU

Operational taxonomic units

PCA

Principal components analysis

T4HP

Trans-4-hydroxy-l-proline

TSP

Trimethylsilyl propionate

UC

Ulcerative colitis

Footnotes

Electronic supplementary material The online version of this article (doi:10.1007/s11306-013-0546-5) contains supplementary material, which is available to authorized users.

Competing Interests The authors have declared that no competing interests exist. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Contributor Information

Lindsey E. Romick-Rosendale, Department of Chemistry & Biochemistry, Miami University, 701 East High Street, Oxford, OH 45056, USA

Anne Legomarcino, Perinatal Institute, Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH 45218, USA.

Neil B. Patel, Department of Chemistry & Biochemistry, Miami University, 701 East High Street, Oxford, OH 45056, USA

Ardythe L. Morrow, Perinatal Institute, Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH 45218, USA Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, USA.

Michael A. Kennedy, Email: kennedm4@miamioh.edu, Department of Chemistry & Biochemistry, Miami University, 701 East High Street, Oxford, OH 45056, USA.

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