Epithelial hypoxia maintains colonization resistance against Candida albicans

Hannah P Savage; Derek J Bays; Connor R Tiffany; Mariela A F Gonzalez; Eli J Bejarano; Thaynara P Carvalho; Zheng Luo; Hugo L P Masson; Henry Nguyen; Renato L Santos; Krystle L Reagan; George R Thompson; Andreas J Bäumler

doi:10.1016/j.chom.2024.05.008

. Author manuscript; available in PMC: 2025 Jul 10.

Published in final edited form as: Cell Host Microbe. 2024 Jun 4;32(7):1103–1113.e6. doi: 10.1016/j.chom.2024.05.008

Epithelial hypoxia maintains colonization resistance against Candida albicans

Hannah P Savage ^1,^2,^*, Derek J Bays ^3,^*, Connor R Tiffany ^1,^*, Mariela A F Gonzalez ¹, Eli J Bejarano ¹, Thaynara P Carvalho ^1,⁴, Zheng Luo ², Hugo L P Masson ¹, Henry Nguyen ¹, Renato L Santos ^1,⁴, Krystle L Reagan ⁵, George R Thompson ³, Andreas J Bäumler ^1,^6,^$

PMCID: PMC11239274 NIHMSID: NIHMS2001240 PMID: 38838675

SUMMARY

Antibiotic treatment promotes the outgrowth of intestinal Candida albicans, but the mechanisms driving this fungal bloom remain incompletely understood. We identify oxygen as a resource required for post-antibiotic C. albicans expansion. C. albicans depleted simple sugars in ceca of gnotobiotic mice but required oxygen to grow on these resources in vitro, pointing to anaerobiosis as a potential factor limiting growth in the gut. Clostridia species limit oxygen availability in the large intestine by producing butyrate, which activates PPAR-γ signaling to maintain epithelial hypoxia. Streptomycin treatment depleted Clostridia-derived butyrate to increase epithelial oxygenation, but the PPAR-γ agonist 5-aminosalicylic acid (5-ASA) functionally replaced Clostridia species to restore epithelial hypoxia and colonization resistance against C. albicans. Additionally, probiotic Escherichia coli required oxygen respiration to prevent a post-antibiotic bloom of C. albicans, further supporting the role of oxygen in colonization resistance. We conclude that limited access to oxygen maintains colonization resistance against C. albicans.

Graphical Abstract

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In Brief

Savage et al. show that anaerobiosis limits growth of Candida albicans in the healthy gut. Antibiotic-mediated disruption of anaerobiosis drives an intestinal C. albicans bloom, which can be prevented by inoculation with probiotic bacteria that respire oxygen or by pharmacological restoration of anaerobiosis using drugs that stimulate epithelial oxygen consumption.

INTRODUCTION

The human colon is host to a large microbial community, the gut microbiota, which is dominated by bacteria belonging to the classes Clostridia and Bacteroidia¹. Fungi are minority species within the gut microbiota, which includes the opportunistic pathogen Candida albicans in approximately 60% of individuals². A non-specific defense mechanism, termed colonization resistance, limits growth of C. albicans in the large intestine during homeostasis, resulting in a low abundance of the opportunist in the feces. However, a disruption of the gut microbiota, particularly through administration of broad-spectrum antibiotics with anaerobic activity, ablates colonization resistance and leads to intestinal dominance by C. albicans^2,3. A bloom of C. albicans in the gastrointestinal tract during antibiotic therapy is the most common etiology of invasive disease (candidemia) in patients with hematologic malignancies⁴. Candidemia is a leading cause of nosocomial infections in the United States^5,6 and carries a high mortality rate (up to 49%)^6–9. In cases of invasive candidiasis originating from the gut^3,4, preventing intestinal domination of intestinal C. albicans during receipt of antibiotics could be an approach to reducing invasive disease in patients with hematologic malignancy. The development of this prophylactic strategy requires an improved understanding of the factors conferring colonization resistance against C. albicans.

The importance of an intact microbiota in preventing an expansion of C. albicans in the gastrointestinal tract can be modeled in mice^10–13. Antibiotic treatment depletes microbiota-derived short-chain fatty acids and increases levels of carbohydrates and sugar alcohols, which correlates with increased gastrointestinal colonization of C. albicans in mice^14,15. Carbohydrates and sugar alcohols promote growth of C. albicans in vitro¹⁵ but are depleted from intestinal contents by Clostridia species in antibiotic naïve mice¹⁶. Clostridia species are also the main producers of the short-chain fatty acid butyrate^17,18, which inhibits growth of C. albicans in vitro¹⁹. An antibiotic-induced depletion of Clostridia species correlates with decreased colonization resistance against C. albicans in rodent models and has been shown to increase the risk for fungal infections in preterm infants²⁰. This correlative evidence supports the premise that an antibiotic-mediated depletion of Clostridia species paves the way for intestinal domination by C. albicans. However, probiotic Clostridia species that are susceptible to antibiotics cannot restore colonization resistance against C. albicans during antibiotic therapy, which is a necessary treatment for many patients with hematologic malignancies²¹. Since patients often develop invasive candidiasis while they are receiving antibiotic prophylaxis, alternative approaches for restoring colonization resistance are needed to prevent intestinal domination by C. albicans in these individuals.

Here we used a mouse model to study which resources drive intestinal domination of C. albicans in antibiotic-treated mice. We then investigated whether limiting access to these resources in vivo would curb growth of C. albicans and restore colonization resistance following antibiotic treatment.

RESULTS

Metabolic footprinting reveals that C. albicans catabolizes carbohydrates and sugar alcohols in the gut

To identify potential resources C. albicans uses to support its growth in the gastrointestinal tract of mice, we developed a generalizable framework, termed metabolic footprinting (Fig. 1A), which consists of the following steps. First, germ-free mice are inoculated under sterile conditions with the microbe of interest. An un-targeted metabolomics screen is conducted on cecal contents to identify metabolites which are decreased in the cecal metabolome of mice that received the microbe relative to mice that remained germ-free, as these metabolites are potential carbon sources utilized by the microbe of interest. In vitro growth assays on minimal media are then performed to confirm consumption of a decreased metabolite when it is added as a carbon source.

Figure 1: — (A) Schematic of steps involved in metabolic footprinting. (B) Workflow of metabolomics data analysis with the reactive web application omuShiny. (C-E) Comparative analysis of the cecal metabolome of germ-free mice (n = 6), and gnotobiotic mice three days after engraftment with *C. albicans* (strain ATCC28367) (n = 4). (C) Principal component analysis of the cecal metabolome in the indicated groups of mice. Ovals indicate the 95% confidence interval. (D) Volcano plot of metabolites colored by class. The Y-axis shows the decadic logarithm of the false discovery rate (FDR)-corrected P value. The dashed line is set at an FDR corrected P value of 0.05. Metabolites with a negative fold-change value decreased in mice engrafted with *C. albicans* compared to germ-free mice, while metabolites with a positive fold-change value increased. (E) The graphs show the abundance of the indicated sugars in mice engrafted with *C. albicans* compared to germ-free mice. (C and E) Each dot represents data from one animal. (F) *In vitro* growth of *C. albicans* (strain ATCC28367) in yeast nitrogen broth supplemented with cysteine and the indicated sugars under aerobic (left panels) or anaerobic (right panels) growth conditions. Data are represented as mean ± SEM. GC-MS, gas chromatography time-of-flight mass spectrometry; KEGG, Kyoto Encyclopedia of Genes and Genomes; **, P < 0.005. See also Figure S1 and Table S1.

To perform metabolomic footprinting for C. albicans (ATCC28367), germ-free (Swiss Webster) mice were mock-inoculated or inoculated with the opportunistic pathogen and cecal contents collected three days later. The soluble fraction of the cecal contents was then analyzed by un-targeted gas chromatography time-of-flight mass spectrometry (metabolite profiling). For the downstream analysis of un-targeted metabolomics data, we developed a reactive web application called omuShiny (Fig. 1B). This reactive web application is an extension of the existing R package omu²² with a graphical user interface, which leverages Kyoto Encyclopedia of Genes and Genomes (KEGG)²³ metadata to improve data analysis, visualization, and interpretation. Principal component analysis of the samples showed a distinct clustering of mice by treatment group, indicating that colonization with C. albicans changes the composition of the murine cecal metabolome (Fig. 1C). The metabolic footprint of C. albicans revealed that many of the known metabolites that exhibited a reduced concentration during colonization with the opportunistic pathogen were simple carbohydrates, including fructo-oligosaccharides (e.g., 1-kestose), disaccharides (e.g., β-gentiobiose), sugar acids (eg., mucic acid and gluconolactone), and alcoholic sugars (e.g., sorbitol, ribitol and galactinol) (Fig 1D). The finding that C. albicans depleted carbohydrates and alcoholic sugars in the murine cecum was of interest because previous studies show that the abundance of these carbon sources increases during antibiotic treatment^15,16.

Next, we determined whether sorbitol, 1-kestose, or β-gentiobiose, which were each reduced in the ceca of mice colonized with C. albicans (Fig. 1E), served as carbon sources to support in vitro growth of the opportunistic pathogen. Sorbitol, 1-kestose, or β-gentiobiose promoted aerobic growth of C. albicans (strain ATCC28367) in yeast nitrogen broth supplemented with cysteine (Fig. 1F). However, aerobic in vitro batch culture is not considered a good mimic of growth conditions encountered in the healthy cecum, where oxygen levels are low. Notably, when we repeated the experiment under anaerobic growth conditions, neither sorbitol, 1-kestose, nor β-gentiobiose promoted growth of C. albicans (Fig. 1F). Similar results were obtained with a different C. albicans isolate (strain SC5314) grown aerobically or anaerobically on sorbitol (Fig. S1A). Although additional experiments are required to determine if C. albicans consumes simple sugars in mice with a complex microbiota, depletion of sorbitol by C. albicans in gnotobiotic mice was informative, because humans and mice lack a specific sorbitol transporter. We recently showed that sorbitol depletion in the murine cecum is attributable solely to its breakdown by the gut microbiota²⁴. Our in vitro growth assays (Fig. 1F and S1A) along with the finding that C. albicans depleted sorbitol in gnotobiotic mice (Fig. 1D and 1E) thus suggested that the opportunistic pathogen had access to oxygen to fuel its growth in the gnotobiotic gut environment. Importantly, oxygen levels in the large intestine become elevated during antibiotic treatment²⁵. We thus hypothesized that an antibiotic-induced increase in luminal oxygen levels enables C. albicans to take advantage of antibiotic-induced metabolome alterations¹⁵ in the large intestine to promote an intestinal expansion.

Escherichia coli respires oxygen to limit growth of C. albicans in the antibiotic-treated gut

To test our hypothesis, we first established a mouse model in which antibiotic-mediated gut microbiota disruption increases susceptibility to Candida albicans colonization. Oral streptomycin was chosen because it is not systemically absorbed, which limits effects on the host, but induces changes in the microbiota composition that include a depletion of Clostridia species^25,26, and an increase in the levels of carbohydrates and sugar alcohols in the cecal metabolome¹⁶. Consistent with these reports, treating mice with a single dose of streptomycin caused a prominent reduction in the absolute Clostridia abundance (Fig. 2A) and a striking depletion of the short-chain fatty acids acetate (Fig. 2B), propionate (Fig. 2C), and butyrate (Fig. 2D). Specific pathogen-free C57BL/6J mice pre-treated with a single dose of streptomycin became colonized after challenge with 10⁴ colony-forming units (CFU) of C. albicans (strain ATCC28367), whereas antibiotic-naïve mice had to be challenge with a 10,000-fold higher dose to achieve colonization with the opportunistic pathogen (Fig. 3A). Similarly, in mice pre-colonized with C. albicans, treatment with a single dose of streptomycin triggered a fecal bloom of the opportunistic pathogen (Fig. 3B). These data suggested that treatment of mice with streptomycin disrupts colonization resistance against C. albicans.

Figure 2: — Groups (n = 8) of special pathogen-free C57BL/6J mice were started on chow supplemented with 5-aminosalicylic acid (5-ASA: +) or control chow (5-ASA: −) and four days later mice received a single dose of streptomycin by oral gavage (Strep: +) or were mock-treated (Strep: −). Feces were collected for analysis one day after streptomycin treatment. (A) The absolute abundance of *Clostridia* in fecal samples was determined by real-time PCR using class specific primers. (B-D) Concentrations of acetate (B), propionate (C) or butyrate (D) in fecal contents were determined by gas chromatography-mass spectrometry. Data are represented as mean ± SEM. ***, P < 0.0005. See also Table S2

Figure 3: — (A) Groups (n = 4) of special pathogen-free C57BL/6J mice were either given a single dose of streptomycin (20 mg/animal) by oral gavage (Strep: +) or were mock treated (Strep: −) and were challenged 48 hours later with the indicated doses of *C. albicans* (strain ATCC28367). Shown are geometric means (bars) +/− geometric standard deviation (error bars) of *C. albicans* colony-forming units (CFU) recovered per gram (g) of cecal contents. (B) Special pathogen-free C57BL/6J mice were infected with the indicated dose of *C. albicans* (strain ATCC28367) and were either mock-treated (n = 4) or given a single dose of streptomycin (20 mg/animal) by oral gavage five days after *C. albicans* infection (n = 8). Shown are geometric means (symbols) +/− geometric standard deviation (error bars) of *C. albicans* CFU recovered per gram of feces at the indicated time points. (C-E) Special pathogen-free C57BL/6J mice were either mock treated (−) or given a single dose of streptomycin (20 mg/animal) by oral gavage (+). The next day, mice were either mock inoculated, inoculated with 10⁹ CFU of *E. coli* Nissle 1917 (WT) or 10⁹ CFU of an *E. coli* Nissle 1917 *cydA* mutant (*cydA*). One day later, mice were challenged with 10⁵ CFU of *C. albicans* (strain ATCC28367) and organs were collected two days later. (C and D) Shown are geometric means (bars) +/− geometric standard deviation (error bars) of *C. albicans* CFU recovered one day after challenge from feces (C) or two days after challenge from cecal contents (D). (E) Shown are geometric means (bars) +/− geometric standard deviation (error bars) of *E. coli* CFU recovered from feces or cecal contents at the indicated time points relative to *C. albicans* challenge. (A and C-E) Each symbol represents data from one animal. NS, P > 0.05; *, P < 0.05; **, P < 0.005; ***, P < 0.0005. See also Figure S1.

Our hypothesis predicted that inoculation with a probiotic that consumes oxygen would restore colonization resistance in streptomycin-treated mice. Mice were mock-treated or pre-treated with a single dose of streptomycin. The next day, mice were mock-inoculated or inoculated with 10⁹ CFU of the probiotic Escherichia coli Nissle 1917 (family Enterobacteriaceae)²⁷, a facultative anaerobic bacterium that respires available oxygen in the murine large intestine²⁵. Mice were challenged the next day with 10⁵ CFU C. albicans (strain ATCC28367) and colonization levels in the cecum were determined two days later. Streptomycin pre-treatment increased recovery of C. albicans by 3–4 orders of magnitude compared to antibiotic-naïve mice. Inoculation of streptomycin-pretreated mice with E. coli Nissle 1917 markedly lowered the numbers of C. albicans that were recovered from feces and cecal contents (Fig. 3C and 3D), suggesting the probiotic improved colonization resistance against the opportunistic pathogen. Clostridia and Bacteroidia species can confer colonization resistance against C. albicans by inducing colonic expression of the Cramp gene, which encodes an antimicrobial peptide²⁸. However, inoculation of streptomycin pre-treated mice with E. coli did not increase colonic Cramp expression (Fig. S1B), suggesting that increased levels of the encoded antimicrobial peptide did not account for colonization resistance against C. albicans in this setting. To test whether colonization resistance conferred by E. coli was linked to oxygen respiration, streptomycin pre-treated mice were inoculated with an aerobic respiration-deficient E. coli Nissle 1917 derivative (cydA mutant), which lacks cytochrome bd oxidase, an enzyme required for respiring oxygen under microaerophilic conditions²⁹. Notably, C. albicans was recovered in markedly higher numbers from streptomycin pre-treated mice inoculated with an aerobic respiration-deficient E. coli Nissle 1917 strain (cydA mutant) compared to mice inoculated with the aerobic respiration-proficient wild-type E. coli Nissle 1917 (wild-type) (Fig. 3C and 3D), although both wild-type and cydA mutant were recovered in similar numbers from fecal contents at the time of C. albicans challenge (Fig. 3E). Similar results were obtained when the experiment was repeated with a different C. albicans isolate (strain SC5314) (Fig. S1C–S1E). These data suggested that the ability to respire oxygen was essential for probiotic E. coli to confer colonization resistance against C. albicans after streptomycin treatment.

The drug 5-aminosalicylic acid restores epithelial hypoxia and improves colonization resistance after streptomycin

With evidence pointing to oxygen as a potential resource required for the bloom of C. albicans in the antibiotic-treated gut, we next wanted to test whether limiting oxygen availability would restore colonization resistance. Short-chain fatty acids reduce C. albicans growth^14,19 and hyphal formation³⁰ in vitro, which is thought to help control the opportunist during homeostasis. Disruption of the microbiota by streptomycin treatment depletes short-chain fatty acids³¹, thereby relieving growth inhibition. However, the Clostridia-derived short-chain fatty acid butyrate^17,18 also stimulates epithelial peroxisome proliferator-activated receptor gamma (PPAR-γ) signaling to maintain the epithelial surface in a state of physiological hypoxia^25,32,33. We thus reasoned that an increase in the luminal oxygen bioavailability might be a second mechanism by which depletion of short-chain fatty acids stimulates growth of C. albicans in the large intestine. We have shown previously that the PPAR-γ agonist 5-aminosalicylic acid (5-ASA) restores an anaerobic environment in the colon of mice with chemically induced colitis by activating PPAR-γ signaling specifically in the intestinal epithelium²⁹. We thus hypothesized that reducing oxygen bioavailability in the antibiotic treated gut by treatment with 5-ASA might be sufficient to restore colonization resistance against C. albicans.

To test our hypothesis, we first determined whether 5-ASA treatment would improve colonization resistance against C. albicans when mice were colonized with the opportunistic pathogen prior to streptomycin exposure. C57BL/6J mice were pre-colonized with C. albicans (strain ATCC28367) and subsequently treatment with a single dose of streptomycin to disrupt colonization resistance. Notably, streptomycin treatment triggered a fecal C. albicans bloom, but this bloom was blunted by 5-ASA supplementation (Fig. 4A).

Figure 4: — (A) Mice maintained on control chow or chow supplemented with 5-aminosalicylic acid (5-ASA) were challenged with 10⁶ colony-forming units (CFU) of *C. albicans* (strain ATCC28367). Three days later, mice were mock-treated or received a single dose of streptomycin (Strep) by oral gavage. Shown are geometric mean +/− geometric standard deviation of *C. albicans* CFU recovered from feces in each group (n = 6 for strep + 5-ASA, n = 3 for remaining groups) at the indicated time points. (B-E) Mice were started on chow supplemented with 5-aminosalicylic acid (5-ASA: +) or control chow (5-ASA: −) and two days later mice received a single dose of streptomycin by oral gavage (Strep: +) or were mock-treated (Strep: −). Each symbol represents data from one animal (i.e., n for each group is provided by the number of symbols). (B, D, and E) Mice were challenged with 10⁵ *C. albicans* CFU (strain ATCC28367) one day after streptomycin treatment and samples were collected the next day. (C) Mice were challenged with 10⁶ *C. albicans* CFU (strain ATCC28367) two days after streptomycin treatment and *C. albicans* CFU in cecal contents were determined seven days later. (B and C) Shown are geometric means (bars) +/− geometric standard deviation (error bars) of *C. albicans* CFU recovered from cecal contents. (D) Sections from the cecum were blinded and scored by a veterinary pathologist. (E) RNA was extracted from preparations of colonic epithelia cells. Transcript levels of *Lcn2*, *Tnfa*, *Il17a*, and *Ifng* were determined by quantitative real-time PCR. Shown are geometric means (bars) +/− geometric standard deviation (error bars) of fold-changes in transcript levels of *Lcn2*, *Tnfa*, *Il17a*, or *Ifng* compared to transcript levels in mock-treated mice on control chow. NS, P > 0.05; *, P < 0.05; **, P < 0.005. See also Figure S2 and Table S4

Next, we determined whether 5-ASA would improve colonization resistance when streptomycin pre-treated mice were challenged with C. albicans. C57BL/6J mice received normal chow or chow supplemented with 5-ASA and were mock-treated or pre-treated with a single dose of streptomycin to decrease colonization resistance. Mice were challenged the next day with C. albicans (strain ATCC28367). Remarkably, 5-ASA supplementation restored colonization resistance in streptomycin pre-treated mice, as indicated by reduced recovery of C. albicans from cecal contents at one (Fig. 4B) or seven (Fig. 4C) days after challenge. Similar results were obtained when the experiment was repeated with a different C. albicans isolate (strain SC5314) (Fig. S1F). Collectively, these data suggested that 5-ASA improves colonization resistance against C. albicans after streptomycin treatment.

5-ASA has anti-inflammatory properties³⁴, and improves barrier function in mouse models of acute intestinal inflammation^35,36. Furthermore, inflammation can alter the gut microbial composition by inducing a bloom of facultatively anaerobic bacteria³⁷. To investigate whether reduced colonization by C. albicans was attributable to reduced inflammation in mice treated with 5-ASA, we investigated whether streptomycin pre-treatment or C. albicans challenge triggered inflammatory responses in the gut by scoring histopathological changes (Fig. 4D) and measuring transcript levels of genes encoding lipocalin-2, tumor necrosis factor alpha (TNF-α), interleukin (IL)-17A, or gamma interferon (IFN-γ) one day after challenge with C. albicans (Fig. 4E). No overt signs of inflammation were detected by examining histopathological changes (Fig. 4D). Although a small increase in transcript levels of Lcn2 and Il17a was observed in streptomycin pre-treated mice after challenge with C. albicans, these increases were not reversed by 5-ASA supplementation and thus did not correlate with the reduced C. albicans colonization levels observed in these animals (Fig. 4B). These data did not support the idea that 5-ASA improved colonization resistance against C. albicans by reducing intestinal inflammation.

Pharmacologic activation of colonic Cramp expression can restore colonization resistance against C. albicans in antibiotic-treated mice²⁸. We thus investigated whether 5-ASA treatment increases colonic expression of genes encoding antimicrobial peptides. Although 5-ASA treatment caused a marked reduction in C. albicans CFU seven days after challenge (Fig. 4C), no increase in colonic antimicrobial peptide expression was observed to explain restoration of colonization resistance by this drug (Fig. S2).

To test whether 5-ASA changes the intestinal environment by restoring epithelial hypoxia, we visualized epithelial oxygenation using pimonidazole, a 2-nitroimidazole that is reductively activated to specifically bind to hypoxic (< 1% oxygen) cells³⁸. Detection of pimonidazole binding using a monoclonal antibody revealed that in antibiotic-naïve mice, the epithelial surface in the cecum was hypoxic. Streptomycin pre-treatment reduced epithelial hypoxia, but 5-ASA supplementation restored epithelial hypoxia in streptomycin pre-treated C57BL/6J mice (Fig. 5A–C). 5-ASA supplementation did not restore a normal absolute abundance of Clostridia (Fig. 2A) or increase the fecal concentrations of short-chain fatty acids (Fig. 2B–2D and Fig. 5D), thus ruling out the possibility that 5-ASA restores hypoxia indirectly by restoring Clostridia and butyrate levels. Collectively, these data suggested that 5-ASA changes the intestinal environment by restoring epithelial hypoxia after antibiotic treatment, thereby limiting the growth of C. albicans in the lumen of the large intestine.

Figure 5: — Mice were started on chow supplemented with 5-aminosalicylic acid (5-ASA: +) or control chow (5-ASA: −) and two days later mice received a single dose of streptomycin by oral gavage (Strep: +) or were mock-treated (Strep: −). Mice were challenged with 10⁵ *C. albicans* CFU (strain ATCC28367) one day after streptomycin treatment. One day after challenge, mice were injected with pimonidazole HCl (PMDZ) and the cecum was collected one hour later. (A-C) Binding of pimonidazole was detected using hypoxyprobe-1 primary antibody and a Cy-3 conjugated goat anti-mouse secondary antibody (red fluorescence) in histological sections from the cecum that were counterstained with DAPI nuclear stain (blue fluorescence). (A) Representative images are shown. Scale bar is 50 μm. (B) Pimonidazole staining was quantified by measuring mean PMDZ intensities from the lumen (distance of 0.0 arbitrary units) to the border of the colonocytes (distance of 0.1), and into the tissue. (C) The graph shows the peak PMDZ intensity for each mouse (symbols) and the mean peak intensity for each group (lines) (n = 7–8). (D) Butyrate concentrations in cecal contents were determined by gas chromatography-mass spectrometry (n = 4). Data are represented as mean ± SEM. NS, P > 0.05; **, P < 0.005. See also Table S2

5-aminosalicylic acid restores colonization resistance by functionally replacing Clostridia species

A single dose of streptomycin disrupts the microbiota, but acquisition of microbes from the environment leads to a gradual restoration of colonization resistance over time as the microbiota recovers^39,40. In contrast, when germ-free mice are engrafted with microbiota from antibiotic-treated mice, the sterile housing conditions prevent acquisition of environmental bacteria, which hinders microbiota recovery. We thus reasoned that a gnotobiotic model would enable us to study whether 5-ASA limits growth of C. albicans in mice when microbiota recovery is inhibited. C57BL/6J donor mice were mock-treated or received a single dose of streptomycin and cecal contents were collected 48 hours later. These cecal contents were then used to inoculate germ-free Swiss Webster recipient mice by oral gavage (cecal microbiota transfer). Two weeks later, gnotobiotic recipient mice were challenged with C. albicans and cecal contents were collected one week later (Fig. 6A). Gnotobiotic recipient mice engrafted with microbiota from mock-treated donor mice carried a significantly lower C. albicans burden in their ceca than gnotobiotic recipient mice engrafted with microbiota from streptomycin-treated donor mice (Fig 6B), indicating that loss of colonization resistance was not attributable to direct effects of streptomycin on C. albicans or on host cells. To mimic microbiota recovery, gnotobiotic mice were engrafted with microbiota from streptomycin-treated donor mice and were inoculated one week later with microbiota from a mock-treated donor mouse. The following week, mice were challenged with C. albicans, and the opportunistic pathogen was enumerated in cecal contents collected one week after challenge (Fig. 6A). Mimicking microbiota recovery by engrafting mice carrying microbiota from streptomycin-treated donors with microbiota from mock-treated donors restored colonization resistance against C. albicans (Fig 6B). Blinded scoring of histological sections from the cecum revealed that C. albicans challenge did not trigger overt inflammation in gnotobiotic mice engrafted with microbiota from streptomycin-treated or mock-treated donors (Fig 6C and 6D).

Figure 6: — Germ-free Swiss Webster mice received a cecal microbiota transplant from streptomycin-treated C57BL/6J mice (Strep) or from mock-treated C57BL/6J mice (Mock). Seven days later, some mice were inoculated with a community of human *Clostridia* isolates (C17), received a second cecal microbiota transplant from mock-treated C57BL/6J mice (Mock), or were switched to chow supplemented with 5-aminosalicylic acid (5-ASA: +). Seven days later, all mice were challenged with 10⁵ *C. albicans* CFU (strain ATCC28367) and organs were collected one week later. (A) Schematic of the experimental timeline. (B) Shown are *C. albicans* CFU recovered 7 days after challenge from cecal contents of each animal (symbols; n = 3 for Strep + Mock, n = 6 for Strep + Mock and Strep + C17, n = 8–9 for remaining groups) and geometric means (bars) +/− geometric standard deviation (error bars). (C and D) Blinded sections from the cecum of each animal were scored by a veterinary pathologist. (C) Representative images of colonic sections for each group are shown. Scale bar is 100 μm. (D) Average histopathology score for each group. (E-G) Mice were injected with pimonidazole HCl (PMDZ) and the cecum was collected one hour later. Binding of pimonidazole was detected using hypoxyprobe-1 primary antibody and a Cy-3 conjugated goat anti-mouse secondary antibody (red fluorescence) in histological sections from the cecum that were counterstained with DAPI nuclear stain (blue fluorescence). (E) The graph shows the peak PMDZ intensity for each mouse (symbols) and the mean peak intensity for each group (lines). (F) Pimonidazole staining was quantified by measuring mean PMDZ intensities from the lumen (distance of 0.0 arbitrary units) to the border of the colonocytes (distance of 0.1), and into the tissue. (G) Representative images are shown. Scale bar is 50 μm. NS, P > 0.05; ***, P < 0.0005; ****, P < 0.00005. See also Table S3

To determine whether loss of epithelial hypoxia induced by streptomycin treatment in donor mice (Fig 5A–C) was recapitulated when cecal microbiota was transferred into gnotobiotic recipient mice, we visualized epithelial oxygenation with pimonidazole. Pimonidazole staining revealed that epithelial hypoxia was reduced in gnotobiotic recipient mice engrafted with microbiota from streptomycin-treated donor mice compared to gnotobiotic recipient mice engrafted with microbiota from mock-treated donor mice (Fig. 6E–G). Consistent with the idea that loss of epithelial hypoxia during streptomycin treatment is due to a depletion of Clostridia species^25,40, epithelial hypoxia was restored when gnotobiotic recipient mice engrafted with microbiota from streptomycin-treated donors were inoculated with a community of 17 human Clostridia isolates⁴¹(Fig. 6E–G). Inoculation with a consortium of 17 human Clostridia isolates also restored colonization resistance against C. albicans (Fig. 6B), which was consistent with previous work implicating Clostridia species in colonization resistance against the yeast²⁰. Notably, when gnotobiotic recipient mice engrafted with microbiota from streptomycin-treated donors received chow containing 5-ASA (Fig. 6A), both epithelial hypoxia (Fig. 6E–G) and colonization resistance against C. albicans (Fig. 6B) were restored. These data demonstrated that 5-ASA can functionally replace Clostridia species to promote epithelial hypoxia and limit intestinal growth of C. albicans.

DISCUSSION

Fecal carriage of C. albicans is detected in approximately 60% of individuals, but this opportunistic pathogen is typically a minority species within the gut microbiota². Factors that limit growth of C. albicans in the large intestine include inhibitory concentrations of short-chain fatty acids¹⁴, such as butyrate, which can limit growth of C. albicans in vitro¹⁹. Growth of C. albicans in the gut is further controlled by a limited availability of critical resources, such as simple sugars¹⁵. Our results show that oxygen limitation, a characteristic feature of the large intestinal environment, can prevent in vitro growth of C. albicans on simple sugars, such as sorbitol. A disruption of the gut microbiota by antibiotic treatment results in a depletion of microbiota-derived short-chain fatty acids and increases the availability of simple sugars in the lumen of the large intestine^14–16,31. An antibiotic-induced microbiota depletion also triggers changes in the host, including an altered ratio of T helper 17 (T_h17) cells to regulatory T cells (T_regs) in the colonic mucosa^42–46, which is associated with invasive candidiasis in patients⁴⁷. Furthermore, antibiotic treatment can reduce colonic expression of genes encoding antimicrobial peptides that limit growth of C. albicans in mice²⁸. It is thought that these changes in the intestinal environment drive intestinal domination by C. albicans, which is a common cause of candidemia in patients with hematologic malignancies who receive antibiotic prophylaxis⁴.

The body of work discussed above suggests that oral antibiotics weaken multiple factors contributing to colonization resistance simultaneously. However, not all these factors need to be normalized to restore colonization resistance. For example, pharmacological induction of Cramp expression alone is sufficient for restoring colonization resistance against C. albicans in antibiotic-treated mice, even when short-chain fatty acids remain depleted²⁸. Here we identify oxygen as a critical resource that limits intestinal growth of C. albicans and demonstrate that pharmacological reduction of oxygen availability in the gut can restore colonization resistance against C. albicans, even when short-chain fatty acid levels remain low and no increase in the colonic expression of genes encoding antimicrobial peptides is detected.

During homeostasis, the host limits diffusion of oxygen into the intestinal lumen by maintaining the colonic epithelium in a state of physiological hypoxia^48,49. An antibiotic-mediated depletion of short-chain fatty acids increases epithelial oxygenation³³, which disrupts anaerobiosis in the lumen of the large intestine²⁵. Here we show that an antibiotic-mediated disruption of the microbiota can be mitigated by inoculation with Clostridia species, which restores epithelial hypoxia and reconstitutes colonization resistance against C. albicans. Clostridia species belonging to the families Lachnospiraceae and Ruminococcaceae are the main producers of the short-chain fatty acid butyrate^17,18, which activates epithelial PPAR-γ signaling to maintain epithelial hypoxia²⁵. However, using a probiotic therapy to restore colonization resistance by inoculation with Clostridia species raises health concerns in immunocompromised patients, such as those with hematologic malignancies, who are at risk for developing invasive candidiasis⁵⁰. Furthermore, patients with hematologic malignancies can develop candidiasis while receiving antibiotic prophylaxis, which would likely clear any antibiotic-susceptible probiotic bacteria.

Treatment with 5-ASA restored colonization resistance against C. albicans by targeting the host to restore epithelial hypoxia. The activity of 5-ASA was thus similar to Clostridia-derived butyrate, which maintains epithelial hypoxia during homeostasis^25,33. These observations suggest that 5-ASA functionally replaced Clostridia species to restore epithelial hypoxia and reinstate colonization resistance against C. albicans by limiting oxygen availability. To describe this mechanism of action, we propose the term “faux-biotics” for chemical microbiota substitutes (e.g., 5-ASA) that replace probiotics (e.g., Clostridia species) functionally. Whereas antibiotic prophylaxis interferes with engraftment of probiotics or fecal microbiota transplants, treatment with a faux-biotic offers the benefit that it is not inhibited or eliminated by antibiotics. Furthermore, by restoring epithelial hypoxia in the antibiotic-treated gut using 5-ASA, growth of C. albicans is restricted by the same mechanism the host uses to maintain a low abundance of the yeast during homeostasis. Since low-level fecal carriage of C. albicans is a constellation that has likely existed for a long time, it is unlikely that the opportunistic pathogen can develop resistance against growth restriction imposed by epithelial hypoxia. Thus, reinstating colonization resistance by restoring host functions, such as epithelial hypoxia, could be a therapeutic strategy to end the antimicrobial arms race with opportunistic fungal pathogens.

STAR METHODS

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Prof. Andreas Bäumler ajbaumler@ucdavis.edu

Materials availability

Reagents generated in this study are available, upon reasonable requests, with a completed material transfer agreement.

Data and Code Availability

Normalized metabolomics spectra data are available as supplementary material with this manuscript (Supplementary Table 1). Raw Spectra data can be found at the NIH metabolomics (database www.metabolomicsworkbench.org) using the values in the file id row of Supplementary Table 1.
Source code for omuShiny can be found at https://github.com/connor-reid-tiffany/omuShiny, while the web app can be found at https://clostridia-enjoyer.shinyapps.io/omuShiny/.
Any additional information required to reanalyze the data reported in this work paper is available from the Lead Contact upon request

Experimental model and subject details

Mice

For experiments using specific pathogen-free (SPF) mice, 7–8 week-old female C57BL/6J mice were obtained from The Jackson Laboratory. Mice were maintained under SPF conditions throughout the duration of the experiment. For gnotobiotic experiments, age-, sex-, and strain-matched male and female C57BL/6J and Swiss-Webster mice, ages 6–10 weeks old, were bred in-house and were housed in Tecniplast Isocages throughout the duration of the experiments. Mice were fed autoclaved water and irradiated Teklad 2018 (2918) mouse chow. For the colonization resistance experiment with Escherichia coli Nissle 1917, mice were fed a defined, irradiated Teklad chow (#TD110675).

To colonize specific pathogen free mice with the probiotic Escherichia coli Nissle 1917 strain or the isogenic mutant Escherichia coli 1917 strain deficient in oxygen respiration (cydA mutant), mice were given 20 mg of streptomycin one day prior to E. coli inoculation. The E. coli inoculums were produced as follows. Both E. coli strains were grown anaerobically in Luria-Bertani broth (LB) at 37°C for 24 hours. Cell concentration was then determined by OD600 measurements. The E. coli cultures were then centrifuged to produce a pellet which was resuspended in sterile PBS to achieve a desired concentration of 10⁹ CFU/100 μL. Mice were then given 100 μL of inoculum by oral gavage. To collect feces, mice were placed in 70% ethanol-cleaned beakers cleaned until they produced a fecal pellet, which was then collected in 1 mL PBS, weighed, vortexed, and plated at 10-fold dilutions on either MacConkey agar, or LB agar with either carbenicillin or kanamycin for the competitive index experiment. Cecal contents collected at necropsy were similarly placed in PBS and plated. Plates were incubated at 37°C for 18 hours prior to counting colony forming units.

To colonize the gnotobiotic mice with a cecal microbiota transfer (CMT) from either control or antibiotic-treated SPF mice, SPF mice were treated with 20 mg streptomycin vs. mock treatment and two days later cecal contents were collected, diluted at 1 g/10 ml PBS, and stored in 25 % glycerol at −80°C until use. Gnotobiotic mice were administered 200 μL of stored mock- or streptomycin-treated CMT by oral gavage. The CMT was given 1 week to colonize prior to further treatment. For the mice receiving first streptomyc-intreated CMT followed by mock-treated CMT, mice were gavaged after 1 week with 200 μL of stored mock-treated CMT. For the C17 treatment group, mice were colonized with a mix of 17 human Clostridia isolates⁴¹ known to produce SCFAs. Strains were grown individually for 4 days in Eggerth-Gagnon broth, then equal volumes of broth from each strain were combined and 200 μL were administered by oral gavage to each mouse. For the 5-ASA treatment group, gnotobiotic mice were then placed on a diet containing 0.25 % 5-ASA added to a base diet of Teklad 2018 mouse chow (Envigo). One week after the diet change or administration of C17, mice were infected with C. albicans.

At necropsy, mice were euthanized by overexposure to carbon dioxide followed by cervical dislocation. All procedures were approved by the UC Davis Animal Care and Use Committee.

Strains and culture conditions

Candida albicans strains ATCC 28367 and SC5314 were streaked from a glycerol stock onto agar with 1% yeast extract, 2% peptone, 2% dextrose (YPD) + chloramphenicol at 100 ug/mL four days prior to infection, and re-streaked at two days prior to infection. To prepare the inoculum, colonies from the agar were resuspended in PBS, concentration was determined by OD600, and samples were diluted to the desired final concentration. Inocula were vortexed immediately prior to infection. Gnotobiotic mice were administered 10⁵ colony forming units (CFU) C. albicans in 100 μL phosphate buffered saline (PBS) by oral gavage. Specific pathogen free mice were given 10⁵ CFU or 10⁶ CFU C. albicans in 100 μL PBS by oral gavage, unless otherwise indicated. Inoculum CFUs were confirmed by plating on YPD agar + chloramphenicol to determine concentration.

One-2 days prior to or 1–5 days after infection with C. albicans, as indicated for each experiment, mice were randomized to receive 20 mg streptomycin in 100 μL sterile water by oral gavage or no treatment. For mice colonized with C. albicans prior to streptomycin treatment, colonization was confirmed, via measuring CFU/g feces, to be comparable between groups at the time of antibiotic administration.

C. albicans burden after infection was determined in feces and cecal contents by enumerating CFU on YPD agar + chloramphenicol. Prior to infection, mice were not colonized with any fungal organisms that grow on YPD agar. To collect feces, mice were placed in 70% ethanol-cleaned beakers cleaned until they produced a fecal pellet, which was then collected in 1 mL PBS, weighed, vortexed, and plated at 10-fold dilutions on YPD agar + chloramphenicol. Cecal contents collected at necropsy were similarly placed in PBS and plated. Plates were counted approximately 24 hours later. A presumptive identification of C. albicans was made for white, glistening, circular, smooth colonies growing on YPD agar containing chloramphenicol. Any colony growing on YPD agar + chloramphenicol with an atypical appearance was confirmed to be Candida spp. by Gram stain.

For in vitro growth on different carbon sources, C. albicans strains ATCC 28367 and SC5314 were cultured on yeast peptone dextrose agar plates for 48 hours at 30°C. Culture from the agar plate was then resuspended in sterile PBS. OD₆₀₀ measurements were taken to dilute the PBS solution to a final concentration of 10⁸ cells/mL of PBS. Minimal media for the candida growth assays was created using yeast nitrogen base (YNB) medium without amino acids, supplemented with a 50 μM concentration of cysteine. For the different growth conditions, we added either no sugar, 0.5 % sorbitol, 5 % 1-kestose, or 5 % beta-gentiobiose to the YNB media. 198 μL of media was added to 96 well maxisorb plates for each growth condition in triplicate, and 2 μL of the 10⁸ cells/mL candida inoculum was added to each well for a final concentration of 10⁶ cells/mL. Plates were then inoculated in a victor nivo plate reader under either aerobic, or anaerobic conditions in a hypoxia chamber for 48 hours at 30°C, with OD₆₀₀ measurements taken every 2 hours after 30 seconds of shaking.

Method details

Development of omuShiny

A shiny app extension of the existing R package omu designed for untargeted metabolomics data analysis, termed omuShiny, was developed using the following packages: Shiny, devtools, and roxygen2. These additional packages are dependencies for omuShiny: rstatix, shinyFeedback, shinyWidgets, omu, tidyverse, openxlsx, DT, officer, thematic, colourpicker, e1071, car, magick, spsComps, ggpubr, ggrepel, and gridExtra.

GC-TOF mass spectrometry

Cecal contents from gnotobiotic mice which were either kept germ-free or infected with 10⁶ CFU of Candida albicans ATCC 28367 were collected 3 days following infection, flash frozen in liquid nitrogen, then stored at −80°C until further processing. Data were acquired using the following chromatographic parameters. Column: Restek corporation Rtx-5Sil MS (30 m length × 0.25 mm internal diameter with 0.25 μm film made of 95% dimethyl/5%diphenylpolysiloxane). Mobile phase: Helium. Column temperature: 50–330 °C. Flow rate: 1 mL min⁻¹. Injection volume: 0.5 μL. Injection: 25 splitless time into a multi-baffled glass liner. Injection temperature: 50 °C ramped to 250 °C by 12 °C s⁻¹. Oven temperature program: 50 °C for 1 min, then ramped at 20 °C min⁻¹ to 330 °C, held constant for 5 min. The analytical GC column is protected by a 10 m long empty guard column which is cut by 20 cm intervals whenever the reference mixture QC samples indicate problems caused by column contaminations. We have validated that at this sequence of column cuts, no detrimental effects are detected with respect to peak shapes, absolute or relative metabolite retention times or reproducibility of quantifications. We use automatic liner exchanges after each set of 10 injections which we could show to reduce sample carryover for highly lipophilic compounds such as free fatty acids. Mass spectrometry parameters are used as follows: a Leco Pegasus IV mass spectrometer is used with unit mass resolution at 17 spectra s⁻¹ from 80–500 Da at − 70 eV ionization energy and 1800 V detector voltage with a 230 °C transfer line and a 250 °C ion source.

Metabolomics data processing

Raw data files are preprocessed directly after data acquisition and stored as ChromaTOF-specific *.peg files, as generic *.txt result files and additionally as generic ANDI MS *.cdf files. ChromaTOF vs. 2.32 is used for data preprocessing without smoothing, 3 s peak width, baseline subtraction just above the noise level, and automatic mass spectral deconvolution and peak detection at signal/noise levels of 5:1 throughout the chromatogram. Apex masses are reported for use in the BinBase algorithm. Result *.txt files are exported to a data server with absolute spectra intensities and further processed by a filtering algorithm implemented in the metabolomics BinBase database. The BinBase algorithm (rtx5) used the settings: validity of chromatogram (< 10 peaks with intensity > 107 counts s−1), unbiased retention index marker detection (MS similarity > 800, validity of intensity range for high m/z marker ions), and retention index calculation by 5th order polynomial regression. Spectra are cut to 5% base peak abundance and matched to database entries from most to least abundant spectra using the following matching filters: retention index window ± 2000 units (equivalent to about ± 2 s retention time), validation of unique ions and apex masses (unique ion must be included in apexing masses and present at > 3 % of base peak abundance), mass spectrum similarity must fit criteria dependent on peak purity and signal/noise ratios and a final isomer filter. Failed spectra are automatically entered as new database entries if s/n > 25, purity < 1.0, and presence in the biological study design class was > 80 %. All thresholds reflect settings for ChromaTOF v. 2.32. Quantification is reported as peak height using the unique ion as default, unless a different quantification ion is manually set in the BinBase administration software BinView. A quantification report table is produced for all database entries that are positively detected in more than 10 % of the samples of a study design class (as defined in the miniX database) for unidentified metabolites. A subsequent post-processing module is employed to automatically replace missing values from the *.cdf files. Replaced values are labeled as ‘low confidence’ by color coding, and for each metabolite, the number of high-confidence peak detections is recorded as well as the ratio of the average height of replaced values to high-confidence peak detections. These ratios and numbers are used for manual curation of automatic report data sets to data sets released for submission. These data were then normalized to the mTIC value (sum of the peak heights of the known metabolites).

SCFA analysis

Two fecal pellets per mouse were collected in 200 μL PBS. Samples were vortexed to disrupt particulate matter and then centrifuged at 6,000 rpm for 10 min to pellet any remaining debris. For each sample, 100 μL of supernatant was combined with 10 μL of a solution containing deuterated acetate, propionate, and butyrate so that each deuterated metabolite was at a final concentration of 100 μM. Samples were dried without heat in a vacuum dryer and then stored at −80°C until use.

Dried extracts were then solubilized by sonication in 0.1 mL anhydrous pyridine and then incubated for 20 min at 80°C. An equal amount of N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide with 1 % tert-butyldimethylchlorosilate (Sigma-Aldrich) was added, and the samples were incubated for 1 h at 80°C. Samples were centrifuged at 20,000 g for 1 min to remove leftover particles. One hundred microliters of the supernatant were transferred to an autosampler vial and analyzed by gas chromatography-mass spectrometry (Agilent 8890 Gas Chromatograph and Agilent 7000D Mass spectrometer). 1 μL of the sample was injected with a 1:50 split ratio at an injection temperature of 250°C on an HP 5ms Ultra Inert (2×15 m-length, 0.25 mm diameter, 0.25 μm film thickness) fused silica capillary column. Helium was used as the carrier gas with a constant flow of 1.2 mL/min. The gas chromatograph (GC) oven temperature started at 50°C for 5 min, rising to 110°C at 10°C/min and holding for 2 min, then raised to 310°C at 40°C/min with a final hold for 4 min. The interface was heated to 300°C. The ion source was used in electron ionization (EI) mode (70 V, 150 μA, 200°C). The dwell time for selected ion monitoring (SIM) events was 50ms. Both acetate, propionate and butyrate were quantified using SIM, with the monitored m/z, and experimentally determined retention times detailed in Supplementary Table 2. Efficient recovery of target metabolites was determined using deuterated compounds as internal standards. Quantification was based on external standards comprised of a series of dilutions of pure compounds, derivatized as described above at the same time as the samples.

Histopathology

At necropsy, cecal tips were collected in individual histology cassettes and immediately placed in 10 % phosphate-buffered formalin. After approximately 24 hours, cassettes were moved to 70 % ethanol until processing. Samples were embedded in paraffin, mounted on slides, and stained with hematoxylin and eosin (H&E) by the UC Davis VMTH Pathology Lab. Slides were scored in a blinded manner by a board-certified Veterinary Pathologist using standard scoring criteria (Supplemental Table 3)⁵².

Colonocyte isolation and Real Time-PCR

Ceca and colons were opened and placed in PBS on ice after feces were gently removed. Tissues were swirled in D-PBS until clean of fecal material, placed in DPBS with 0.03 M EDTA and 1.5 mM DTT on ice for 20 mins, then transferred to D-PBS with 0.03 M EDTA in 37°C for 10 min. Samples were shaken vigorously until colonocytes were released, remaining tissues were removed, and DPBS tubes containing colonocytes were spun at 800g for 5 min. at 4°C. After supernatant was removed, the colonocyte pellet was transferred to a cryovial and stored at −80°C.

For mRNA isolation, colonocytes were thawed, TRI Reagent (Molecular Research Center) was added and incubated for 5 min., 200 μL chloroform was added, cells were spun at max speed, 4°C, for 15 min., and the aqueous phase was collected. An equal volume of 95% ethanol was added and samples were loaded onto Econo-Spin Columns (Epoch Life Science). Samples were washed with 3M sodium acetate, treated with PureLink DNase (Invitrogen), washed with 3× 70 % ethanol+1 % HEPES, and eluted with RNase-free water. RNA was quantified using the NanoDrop ND-1000 Spectrophotometer (Thermo Scientific). Complementary DNA was generated from 1 μg of RNA using MultiScribe reverse transcriptase (Applied Biosystems) with 10X RT PCR buffer (Applied Biosystems), 25 mM MgCl₂ (Applied Biosystems), dNTPs (Applied Biosystems), random hexamers (Applied Biosystems), and RNase inhibitor (Applied Biosystems). Samples were run on a PTC-200 Peltier Thermal Cycler (MJ Research) for 25°C (10 min.), 48°C (30 min.), 95°C (5 min.), then 4°C. Real-time PCR was performed with SYBR green (Applied Biosystems) and then primers listed in Supplemental Table 4 on a ViiA 7 real-time PCR system (Applied Biosystems) with the following cycling parameters: 50°C (2 min), 95°C (10 min), 40 cycles of 95°C (15 s) and 60°C (1 min). Results were analyzed using QuantiStudio Real-Time PCR software v1.3 (Applied Biosystems), and ΔΔC_T was calculated with beta-actin as the control gene.

Hypoxia staining and imaging

30–90 minutes prior to necropsy, mice were injected intraperitoneally with 100 mg/kg of pimonidazole (PMDZ) HCl (Hypoxyprobe) in PBS. Staining with the Hypoxyprobe kit was done as previously described^25,29. Briefly, paraffin-embedded tissues mounted on slides and prepared for staining with xylene (2× 10 min.) and ethanol (3 min. each in 95 %, 80 %, and 70 %). Samples were treated with Proteinase K 20 mg/mL in TE buffer for 15 min. at 37°C, nonspecific binding was blocked with serum at room temperature for 1 hour, and slides were stained overnight at 4°C with the mouse IgG1 anti-PMDZ monoclonal antibody 4.3.11.3 (Hypoxyprobe). Slides were then stained with Cyanine3-labeled goat anti-mouse IgG (Jackson ImmunoResearch) for 90 min. at room temperature. Between each staining step, slides were washed 3× 5 min. in PBS. Slides were briefly dried and mounted with Shandon Immu-Mount (Thermo Scientific).

Image numbers were randomized, blinded, and three representative images were collected on a Carl Zeiss AxioVision microcope with AxioVision 4.8.1 software (Zeiss) at 20X for scoring and 63X for image samples. Using ImageJ (NIH), the Texas Red channel (Cyanine3) was isolated, 3 representative slices of equal size containing the epithelial-lumen border were saved, and the Plot Profile for each was acquired. After unblinding, PMDZ peaks (epithelial-lumen borders) were aligned for each image and Profiles for the 9 slices associated with each mouse were averaged to obtain an average PMDZ Plot Profile and average PMDZ Peak for each mouse.

Method details Quantification and Statistical Analysis

Statistical analysis

Statistics were performed using GraphPad Prism 9.4.0 (GraphPad). An unpaired Student t test was performed on log-transformed CFU results, fold change in mRNA expression, and on short chain fatty acid levels. To compare peak pimonidazole staining intensities, a Mann-Whitney U test was performed. For mouse experiments, n refers to the number of animals. Unless indicated otherwise, bars represent geometric means +/− geometric standard deviation (error bars). Throughout all figures, * = p<0.05, ** = p<0.005, *** = p<0.0005, and **** = p<0.00005.

Metabolomics data analysis

Following processing, metabolomics data were analyzed using our recently developed shiny application, omuShiny. Principal component analysis was performed on natural logarithm transformed metabolite abundances and ellipses denote a 95 % confidence interval on a multivariate t distribution. Univariate statistics were performed using a welch-corrected two-sided t-test on natural logarithm transformed metabolite abundances. P values were adjusted using the Benjamini-Hochberg method to correct for the false discovery rate. Volcano plots and dot plots were derived from data generated by the welch t test in omuShiny. Error bars on the dot plot were calculated using the standard error of the mean.

Supplementary Material

Download video file^{(3.7MB, mp4)}

NIHMS2001240-supplement-2.pdf^{(374.9KB, pdf)}

Supplemental Table 1: Normalized metabolomics spectra data (related to figure 1) Figure 360: Anaerobiosis maintains colonization resistance against Candida (related to Figures 1 and 6).

NIHMS2001240-supplement-3.xlsx^{(809.1KB, xlsx)}

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Mouse anti-pimonidazole monoclonal antibody MAb1	Hypoxyprobe	Hypoxyprobe^™-1 Kit, HP1-1000, RRID: AB_2801307
Cyanine3-labeled goat anti-mouse IgG	Jackson ImmunoResearch	Cat# 115-165-003 RRID: AB_2338680
Bacterial and fungal strains
Candida albicans strain ATCC28367	ATCC	ATCC28367
Candida albicans strain SC5314	Gillum et al.⁵¹	SC5314
Escherichia coli Nissle 1917	DSMZ	DSM 6601
Escherichia coli Nissle 1917 cydA	Byndloss et al.²⁵	YL219
Erysipelatoclostridium saccharogumia	Atarashi et al.⁴¹	C1
Flavonifractor plautii	Atarashi et al.⁴¹	C3
Hungatella hathewayi	Atarashi et al.⁴¹	C4
Blautia producta	Atarashi et al.⁴¹	C6
Enterocloster bolteae	Atarashi et al.⁴¹	C7
Dielma fastidiosa	Atarashi et al.⁴¹	C8
Anaerostipes caccae	Atarashi et al.⁴¹	C9
Anaerotruncus colihominis	Atarashi et al.⁴¹	C13
Unclassified Lachnospiraceae	Atarashi et al.⁴¹	C14
Enterocloster asparagiformis	Atarashi et al.⁴¹	C15
Lachnoclostridium symbiosum	Atarashi et al.⁴¹	C16
Erysipelatoclostridium ramosum	Atarashi et al.⁴¹	C18
Faecalicatena fissicatena	Atarashi et al.⁴¹	C21
Lachnoclostridium scindens	Atarashi et al.⁴¹	C26
Eisenbergiella massiliensis	Atarashi et al.⁴¹	C27
Enterocloster spp.	Atarashi et al.⁴¹	C28
Eisenbergiella tayi	Atarashi et al.⁴¹	C29
Chemicals, peptides, and recombinant proteins
Streptomycin	Sigma	Cat#59137
Chloramphenicol	ThermoFisher	Cat#BP904
Sorbitol	Sigma	Cat#53889
1-Kestose	Sigma	Cat#72555
β-Gentiobiose	Sigma	Cat#G3000
N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide	Sigma	Cat#00942
Critical commercial assays
DNAeasy Powersoil Kit	QIAGEN	Cat#:12888-100
TRI Reagent	Molecular Research Center	Cat#TR118
PureLink DNAse	Invitrogen	Cat#18068015
MultiScribe Reverse Transcriptase	ThermoFisher	Cat#4311235
GeneAmp^™ 10X PCR Gold Buffer & MgCl₂	ThermoFisher	Cat#4306898
Applied Biosystems^™ Random Hexamers (50 μM)	ThermoFisher	Cat#N8080127
Applied Biosystems^™ RNase Inhibitor	ThermoFisher	Cat#N8080119
Applied Biosystems^™ PowerUp^™ SYBR^™ Green Master Mix for qPCR	ThermoFisher	Cat#A25742
Applied Biosystems^™ GeneAmp^™ dNTP Blend (100 mM)	ThermoFisher	Cat# N8080261
Experimental models: Organisms/strains
Candida albicans	ATCC	ATCC 28367
Mus musculus C57BL/6J	The Jackson Laboratory	Cat#000664
Mus musculus Germ-Free Swiss Webster	Bred in house; originally acquired from Taconic	N/A
Mus musculus Germ-Free C57BL/6J	Bred in house; originally acquired from UNC National Gnotobiotic Rodent Resource Center https://www.med.unc.edu/ngrrc/products-services/	N/A
Oligonucleotides
See supplementary table 3	See supplementary table 3	See supplementary table 3
Software and algorithms
omu	Tiffany et al.²²	https://cran.r-project.org/web/packages/omu/index.html
omuShiny	Connor Tiffany, This study	https://clostridia-enjoyer.shinyapps.io/omuShiny/
KEGG	M Kanehisa, S Goto	https://www.genome.jp/kegg/
Prism	Graph Pad	https://www.graphpad.com/features
R	R project	https://www.r-project.org/
RStudio	Posit	https://posit.co/products/open-source/rstudio/
Tidyverse	Posit	https://www.tidyverse.org/
Shiny	Posit	https://shiny.posit.co/
gridExtra	Baptiste Auguie, Anton Antonov	https://cran.r-project.org/web/packages/gridExtra/index.html
officer	David Gohel et al.	https://cran.r-project.org/web/packages/officer/index.html
openxlsx	Philipp Schauberger et al.	https://cran.r-project.org/web/packages/openxlsx/index.html
shinyFeedback	Andy Merlino, Patrick Howard	https://cran.r-studio.com/web/packages/shinyFeedback/index.html
DT	Yihui Xie et al.	https://cran.r-project.org/web/packages/DT/index.html
shinyWidgets	Victor Perrier et al.	https://cran.r-project.org/web/packages/shinyWidgets/index.html
magick	Jeroen Ooms	https://cran.r-project.org/web/packages/magick/index.html
spsComps	Le Zhang	https://cran.r-project.org/web/packages/spsComps/index.html
thematic	Posit.	https://cran.r-project.org/web/packages/thematic/index.html
ggpubr	Alboukadel Kassambara	https://cran.r-project.org/web/packages/ggpubr/index.html
car	Fox J, Weisberg S	https://cran.r-project.org/web/packages/car/index.html
e1071	David Meyer et al.	https://cran.r-project.org/web/packages/e1071/index.html
colourpicker	Dean Attali, David Griswold	https://cran.r-project.org/web/packages/colourpicker/index.html
ggrepel	Kamil Slowikowski et al.	https://cran.r-project.org/web/packages/ggrepel/index.html
Microsoft Excel	Microsoft	https://www.microsoft.com/en-us/microsoft-365
Other
Mouse 10% Fat Diet	Teklad Diet	#TD110675
0.25% 5-ASA added to base teklad diet	Teklad Diet	N/A

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Highlights.

C. albicans depletes sorbitol in gnotobiotic mice and needs oxygen to catabolize it E. coli requires oxygen respiration to limit a post-antibiotic C. albicans bloom Depletion of Clostridia by antibiotics disrupts anaerobiosis to boost Candida growth 5-ASA restores epithelial hypoxia to curb post-antibiotic C. albicans growth

ACKNOWLEDGEMENTS

We would like to thank K. Honda for kindly providing 17 human fecal Clostridia isolates. We would like to thank Ardeypharm GmbH for kindly providing E. coli strain Nissle 1917 and Suzanne Noble for supplying C. albicans strain SC5314. Metabolomics sample prep, GC-TOF mass spectrometry, and data processing were performed by the West Coast Metabolomics Center at the University of California, Davis.

This work was supported by Microbiome Tri-institutional Partnership in Microbiome Research (TrIP) Seed funding award number 000582. Work in A.J.B.’s laboratory was supported by award 650976 from the Crohn’s and Colitis Foundation of America and by Public Health Service Grants AI044170, AI096528, AI112949, AI146432 and AI153069. This project was also supported by F32 AI161850 (H.P.S.). The project described was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant number UL1 TR000002 and linked award TL1 TR000133 (H.P.S.). The project described was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant number UL1 TR001860 (D.J.B.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Declarations of Interest

Dr. George Thompson is consulting for Astellas, Cidara, F2G, Immy, Mayne, Melinta, Mundipharma, Scynexis, and Pfizer on projects that are not related to this publication. Dr. George Thompson receives research support from Astellas, Cidara, F2G, Mayne, Melinta, Merck, Mundipharma, Scynexis, and Pfizer for projects that are not related to this publication.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Download video file^{(3.7MB, mp4)}

NIHMS2001240-supplement-2.pdf^{(374.9KB, pdf)}

Supplemental Table 1: Normalized metabolomics spectra data (related to figure 1) Figure 360: Anaerobiosis maintains colonization resistance against Candida (related to Figures 1 and 6).

NIHMS2001240-supplement-3.xlsx^{(809.1KB, xlsx)}

Data Availability Statement

Normalized metabolomics spectra data are available as supplementary material with this manuscript (Supplementary Table 1). Raw Spectra data can be found at the NIH metabolomics (database www.metabolomicsworkbench.org) using the values in the file id row of Supplementary Table 1.
Source code for omuShiny can be found at https://github.com/connor-reid-tiffany/omuShiny, while the web app can be found at https://clostridia-enjoyer.shinyapps.io/omuShiny/.
Any additional information required to reanalyze the data reported in this work paper is available from the Lead Contact upon request

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[R11] 11.Samonis G, Anastassiadou H, Dassiou M, Tselentis Y, and Bodey GP (1994). Effects of broad-spectrum antibiotics on colonization of gastrointestinal tracts of mice by Candida albicans. Antimicrob Agents Chemother 38, 602–603. 10.1128/AAC.38.3.602. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] 12.Clark JD (1971). Influence of antibiotics or certain intestinal bacteria on orally administered Candida albicans in germ-free and conventional mice. Infect Immun 4, 731–737. 10.1128/iai.4.6.731-737.1971. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] 13.Mason KL, Erb Downward JR, Mason KD, Falkowski NR, Eaton KA, Kao JY, Young VB, and Huffnagle GB (2012). Candida albicans and bacterial microbiota interactions in the cecum during recolonization following broad-spectrum antibiotic therapy. Infect Immun 80, 3371–3380. 10.1128/IAI.00449-12. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Guinan J, Wang S, Hazbun TR, Yadav H, and Thangamani S (2019). Antibiotic-induced decreases in the levels of microbial-derived short-chain fatty acids correlate with increased gastrointestinal colonization of Candida albicans. Sci Rep 9, 8872. 10.1038/s41598-019-45467-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R15] 15.Gutierrez D, Weinstock A, Antharam VC, Gu H, Jasbi P, Shi X, Dirks B, Krajmalnik-Brown R, Maldonado J, Guinan J, and Thangamani S (2020). Antibiotic-induced gut metabolome and microbiome alterations increase the susceptibility to Candida albicans colonization in the gastrointestinal tract. FEMS Microbiol Ecol 96. 10.1093/femsec/fiz187. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R16] 16.Tiffany CR, Lee JY, Rogers AWL, Olsan EE, Morales P, Faber F, and Baumler AJ (2021). The metabolic footprint of Clostridia and Erysipelotrichia reveals their role in depleting sugar alcohols in the cecum. Microbiome 9, 174. 10.1186/s40168-021-01123-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] 17.Vital M, Howe AC, and Tiedje JM (2014). Revealing the bacterial butyrate synthesis pathways by analyzing (meta)genomic data. MBio 5, e00889. 10.1128/mBio.00889-14. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R18] 18.Louis P, and Flint HJ (2009). Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine. FEMS Microbiol Lett 294, 1–8. 10.1111/j.1574-6968.2009.01514.x. [DOI] [PubMed] [Google Scholar]

[R19] 19.Nguyen LN, Lopes LCL, Cordero RJB, and Nosanchuk JD (2011). Sodium butyrate inhibits pathogenic yeast growth and enhances the functions of macrophages. J Antimicrob Chemoth 66, 2573–2580. 10.1093/jac/dkr358. [DOI] [PubMed] [Google Scholar]

[R20] 20.Huang D, Li H, Lin Y, Lin J, Li C, Kuang Y, Zhou W, Huang B, and Wang P (2022). Antibiotic-induced depletion of Clostridium species increases the risk of secondary fungal infections in preterm infants. Front Cell Infect Microbiol 12, 981823. 10.3389/fcimb.2022.981823. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R21] 21.Moreno-Sanchez F, and Gomez-Gomez B (2022). Antibiotic Management of Patients with Hematologic Malignancies: From Prophylaxis to Unusual Infections. Curr Oncol Rep 24, 835–842. 10.1007/s11912-022-01226-y. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R22] 22.Tiffany CR, and Baumler AJ (2019). omu, a Metabolomics Count Data Analysis Tool for Intuitive Figures and Convenient Metadata Collection. Microbiol Resour Announc 8. 10.1128/MRA.00129-19. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R23] 23.Kanehisa M, and Goto S (2000). KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28, 27–30. 10.1093/nar/28.1.27. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R24] 24.Lee JY, Tiffany CR, Mahan SP, Kellom M, Rogers AWL, Nguyen H, Stevens ET, Masson HLP, Yamazaki K, Marco ML, et al. (2024). High fat intake sustains sorbitol intolerance after antibiotic-mediated Clostridia depletion from the gut microbiota. Cell 187, 1191–1205 e1115. 10.1016/j.cell.2024.01.029. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R25] 25.Byndloss MX, Olsan EE, Rivera-Chávez F, Tiffany CR, Cevallos SA, Lokken KL, Torres TP, Byndloss AJ, Faber F, Gao Y, et al. (2017). Microbiota-activated PPAR-g signaling inhibits dysbiotic Enterobacteriaceae expansion. Science 357, 570–575. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R26] 26.Sekirov I, Tam NM, Jogova M, Robertson ML, Li Y, Lupp C, and Finlay BB (2008). Antibiotic-induced perturbations of the intestinal microbiota alter host susceptibility to enteric infection. Infect Immun 76, 4726–4736. 10.1128/IAI.00319-08. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R27] 27.Nissle A (1925). Weiteres über grundlagen und praxis der mutaflorbehandlung. DMW-Deutsche Medizinische Wochenschrift 51, 1809–1813. [Google Scholar]

[R28] 28.Fan D, Coughlin LA, Neubauer MM, Kim J, Kim MS, Zhan X, Simms-Waldrip TR, Xie Y, Hooper LV, and Koh AY (2015). Activation of HIF-1alpha and LL-37 by commensal bacteria inhibits Candida albicans colonization. Nat Med 21, 808–814. 10.1038/nm.3871. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R29] 29.Cevallos SA, Lee JY, Velazquez EM, Foegeding NJ, Shelton CD, Tiffany CR, Parry BH, Stull-Lane AR, Olsan EE, Savage HP, et al. (2021). 5-Aminosalicylic Acid Ameliorates Colitis and Checks Dysbiotic Escherichia coli Expansion by Activating PPAR-gamma Signaling in the Intestinal Epithelium. mBio 12. 10.1128/mBio.03227-20. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Epithelial hypoxia maintains colonization resistance against Candida albicans

Hannah P Savage

Derek J Bays

Connor R Tiffany

Mariela A F Gonzalez

Eli J Bejarano

Thaynara P Carvalho

Zheng Luo

Hugo L P Masson

Henry Nguyen

Renato L Santos

Krystle L Reagan

George R Thompson

Andreas J Bäumler

SUMMARY

Graphical Abstract

In Brief

INTRODUCTION

RESULTS

Metabolic footprinting reveals that C. albicans catabolizes carbohydrates and sugar alcohols in the gut

Figure 1: Metabolic footprinting identifies resources that support C. albincans growth in the gastrointestinal tract of mice.

Escherichia coli respires oxygen to limit growth of C. albicans in the antibiotic-treated gut

Figure 2: Treatment with streptomycin depletes Clostridia and short-chain fatty acids.

Figure 3: E. coli requires aerobic respiration to restore colonization resistance against C. albincans after streptomycin treatment.

The drug 5-aminosalicylic acid restores epithelial hypoxia and improves colonization resistance after streptomycin

Figure 4: 5-ASA restores colonization resistance against C. albicans after streptomycin treatment.

Figure 5: 5-ASA restores epithelial hypoxia in the large intestine after streptomycin treatment.

5-aminosalicylic acid restores colonization resistance by functionally replacing Clostridia species

Figure 6: 5-ASA can functionally replace Clostridia species to restore colonization resistance against C. albicans after streptomycin treatment.

DISCUSSION

STAR METHODS

Resource availability

Lead contact

Materials availability

Data and Code Availability

Experimental model and subject details

Mice

Strains and culture conditions

Method details

Development of omuShiny

GC-TOF mass spectrometry

Metabolomics data processing

SCFA analysis

Histopathology

Colonocyte isolation and Real Time-PCR

Hypoxia staining and imaging

Method details Quantification and Statistical Analysis

Statistical analysis

Metabolomics data analysis

Supplementary Material

Highlights.

ACKNOWLEDGEMENTS

Footnotes

REFERENCES

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases