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1.
mBio ; 13(4): e0118322, 2022 08 30.
Article in English | MEDLINE | ID: mdl-35856563

ABSTRACT

The severity of Clostridioides difficile infections (CDI) has increased over the last few decades. Patient age, white blood cell count, and creatinine levels as well as C. difficile ribotype and toxin genes have been associated with disease severity. However, it is unclear whether specific members of the gut microbiota are associated with variations in disease severity. The gut microbiota is known to interact with C. difficile during infection. Perturbations to the gut microbiota are necessary for C. difficile to colonize the gut. The gut microbiota can inhibit C. difficile colonization through bile acid metabolism, nutrient consumption, and bacteriocin production. Here, we sought to demonstrate that members of the gut bacterial communities can also contribute to disease severity. We derived diverse gut communities by colonizing germfree mice with different human fecal communities. The mice were then infected with a single C. difficile ribotype 027 clinical isolate, which resulted in moribundity and histopathologic differences. The variation in severity was associated with the human fecal community that the mice received. Generally, bacterial populations with pathogenic potential, such as Enterococcus, Helicobacter, and Klebsiella, were associated with more-severe outcomes. Bacterial groups associated with fiber degradation and bile acid metabolism, such as Anaerotignum, Blautia, Lactonifactor, and Monoglobus, were associated with less-severe outcomes. These data indicate that, in addition to the host and C. difficile subtype, populations of gut bacteria can influence CDI disease severity. IMPORTANCE Clostridioides difficile colonization can be asymptomatic or develop into an infection ranging in severity from mild diarrhea to toxic megacolon, sepsis, and death. Models that predict severity and guide treatment decisions are based on clinical factors and C. difficile characteristics. Although the gut microbiome plays a role in protecting against CDI, its effect on CDI disease severity is unclear and has not been incorporated into disease severity models. We demonstrated that variation in the microbiome of mice colonized with human feces yielded a range of disease outcomes. These results revealed groups of bacteria associated with both severe and mild C. difficile infection outcomes. Gut bacterial community data from patients with CDI could improve our ability to identify patients at risk of developing more severe disease and improve interventions that target C. difficile and the gut bacteria to reduce host damage.


Subject(s)
Clostridioides difficile , Clostridium Infections , Gastrointestinal Microbiome , Animals , Bacteria/genetics , Bile Acids and Salts , Clostridium Infections/microbiology , Feces/microbiology , Humans , Mice
2.
mSphere ; 6(3)2021 05 05.
Article in English | MEDLINE | ID: mdl-33952668

ABSTRACT

The gut bacterial community prevents many pathogens from colonizing the intestine. Previous studies have associated specific bacteria with clearing Clostridioides difficile colonization across different community perturbations. However, those bacteria alone have been unable to clear C. difficile colonization. To elucidate the changes necessary to clear colonization, we compared differences in bacterial abundance between communities able and unable to clear C. difficile colonization. We treated mice with titrated doses of antibiotics prior to C. difficile challenge, resulting in no colonization, colonization and clearance, or persistent colonization. Previously, we observed that clindamycin-treated mice were susceptible to colonization but spontaneously cleared C. difficile Therefore, we investigated whether other antibiotics would show the same result. We found that reduced doses of cefoperazone and streptomycin permitted colonization and clearance of C. difficile Mice that cleared colonization had antibiotic-specific community changes and predicted interactions with C. difficile Clindamycin treatment led to a bloom in populations related to Enterobacteriaceae Clearance of C. difficile was concurrent with the reduction of those blooming populations and the restoration of community members related to the Porphyromonadaceae and Bacteroides Cefoperazone created a susceptible community characterized by drastic reductions in the community diversity and interactions and a sustained increase in the abundance of many facultative anaerobes. Lastly, clearance in streptomycin-treated mice was associated with the recovery of multiple members of the Porphyromonadaceae, with little overlap in the specific Porphyromonadaceae observed in the clindamycin treatment. Further elucidation of how C. difficile colonization is cleared from different gut bacterial communities will improve C. difficile infection treatments.IMPORTANCE The community of microorganisms, or microbiota, in our intestines prevents pathogens like C. difficile from colonizing and causing infection. However, antibiotics can disturb the gut microbiota, which allows C. difficile to colonize. C. difficile infections (CDI) are primarily treated with antibiotics, which frequently leads to recurrent infections because the microbiota has not yet returned to a resistant state. The recurrent infection cycle often ends when the fecal microbiota from a presumed resistant person is transplanted into the susceptible person. Although this treatment is highly effective, we do not understand the mechanism. We hope to improve the treatment of CDI through elucidating how the bacterial community eliminates CDI. We found that C. difficile colonized susceptible mice but was spontaneously eliminated in an antibiotic treatment-specific manner. These data indicate that each community had different requirements for clearing colonization. Understanding how different communities clear colonization will reveal targets to improve CDI treatments.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Bacteria/metabolism , Clostridioides difficile/drug effects , Clostridioides difficile/physiology , Clostridium Infections/drug therapy , Gastrointestinal Microbiome/drug effects , Animals , Anti-Bacterial Agents/administration & dosage , Anti-Bacterial Agents/classification , Bacteria/drug effects , Cefoperazone/therapeutic use , Clindamycin/therapeutic use , Clostridium Infections/microbiology , Clostridium Infections/prevention & control , Disease Susceptibility , Feces/microbiology , Gastrointestinal Microbiome/physiology , Mice , Streptomycin/therapeutic use
4.
mSphere ; 4(1)2019 02 06.
Article in English | MEDLINE | ID: mdl-30728281

ABSTRACT

Acarbose is a safe and effective medication for type 2 diabetes that inhibits host glucoamylases to prevent starch digestion in the small intestines and thus decrease postprandial blood glucose levels. This results in an increase in dietary starch in the distal intestine, where it becomes food for the gut bacterial community. Here, we examined the effect of acarbose therapy on the gut community structure in mice fed either a high-starch (HS) or high-fiber diet rich in plant polysaccharides (PP). The fecal microbiota of animals consuming a low dose of acarbose (25 ppm) was not significantly different from that of control animals that did not receive acarbose. However, a high dose of acarbose (400 ppm) with the HS diet resulted in a substantial change to the microbiota structure. Most notably, the HS diet with a high dose of acarbose lead to an expansion of the Bacteroidaceae and Bifidobacteriaceae and a decrease in the Verrucomicrobiaceae (such as Akkermansia muciniphila) and the Bacteroidales S24-7. Once acarbose treatment ceased, the community composition quickly reverted to mirror that of the control group, suggesting that acarbose does not irreversibly alter the gut community. The high dose of acarbose in the PP diet resulted in a distinct community structure with increased representation of Bifidobacteriaceae and Lachnospiraceae Short-chain fatty acids (SCFAs) measured from stool samples were increased, especially butyrate, as a result of acarbose treatment in both diets. These data demonstrate the potential of acarbose to change the gut community structure and increase beneficial SCFA output in a diet-dependent manner.IMPORTANCE The gut microbial community has a profound influence on host physiology in both health and disease. In diabetic individuals, the gut microbiota can affect the course of disease, and some medications for diabetes, including metformin, seem to elicit some of their benefits via an interaction with the microbiota. Here, we report that acarbose, a glucoamylase inhibitor for type 2 diabetes, changes the murine gut bacterial community structure in a reversible and diet-dependent manner. In both high-starch and high-fiber diet backgrounds, acarbose treatment results in increased short-chain fatty acids, particularly butyrate, as measured in stool samples. As we learn more about how human disease is affected by the intestinal bacterial community, the interplay between medications such as acarbose and the diet will become increasingly important to evaluate.


Subject(s)
Acarbose/administration & dosage , Bacteria/drug effects , Diet , Gastrointestinal Microbiome/drug effects , Glycoside Hydrolase Inhibitors/administration & dosage , Animals , Bacteria/genetics , Bacteroidaceae/drug effects , Butyrates/analysis , Dietary Fiber/metabolism , Fatty Acids, Volatile/analysis , Feces/chemistry , Feces/microbiology , Male , Mice , Mice, Inbred C57BL , RNA, Ribosomal, 16S , Starch/metabolism
5.
mBio ; 6(4): e00974, 2015 Jul 14.
Article in English | MEDLINE | ID: mdl-26173701

ABSTRACT

UNLABELLED: Perturbations to the gut microbiota can result in a loss of colonization resistance against gastrointestinal pathogens such as Clostridium difficile. Although C. difficile infection is commonly associated with antibiotic use, the precise alterations to the microbiota associated with this loss in function are unknown. We used a variety of antibiotic perturbations to generate a diverse array of gut microbiota structures, which were then challenged with C. difficile spores. Across these treatments we observed that C. difficile resistance was never attributable to a single organism, but rather it was the result of multiple microbiota members interacting in a context-dependent manner. Using relative abundance data, we built a machine learning regression model to predict the levels of C. difficile that were found 24 h after challenging the perturbed communities. This model was able to explain 77.2% of the variation in the observed number of C. difficile per gram of feces. This model revealed important bacterial populations within the microbiota, which correlation analysis alone did not detect. Specifically, we observed that populations associated with the Porphyromonadaceae, Lachnospiraceae, Lactobacillus, and Alistipes were protective and populations associated with Escherichia and Streptococcus were associated with high levels of colonization. In addition, a population affiliated with the Akkermansia indicated a strong context dependency on other members of the microbiota. Together, these results indicate that individual bacterial populations do not drive colonization resistance to C. difficile. Rather, multiple diverse assemblages act in concert to mediate colonization resistance. IMPORTANCE: The gastrointestinal tract harbors a complex community of bacteria, known as the microbiota, which plays an integral role preventing its colonization by gut pathogens. This resistance has been shown to be crucial for protection against Clostridium difficile infections (CDI), which are the leading source of hospital-acquired infections in the United States. Antibiotics are a major risk factor for acquiring CDI due to their effect on the normal structure of the indigenous gut microbiota. We found that diverse antibiotic perturbations gave rise to altered communities that varied in their susceptibility to C. difficile colonization. We found that multiple coexisting populations, not one specific population of bacteria, conferred resistance. By understanding the relationships between C. difficile and members of the microbiota, it will be possible to better manage this important infection.


Subject(s)
Anti-Bacterial Agents/administration & dosage , Clostridioides difficile/growth & development , Feces/microbiology , Gastrointestinal Microbiome/drug effects , Animals , Bacterial Load , Clostridioides difficile/isolation & purification , Computer Simulation , Mice , Supervised Machine Learning
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