Clostridium difficile infection (CDI) is the primary cause of antibiotic associated diarrhea and the most common nosocomial infection. Due to frequent infection, potential for serious complications, and high (up to 30%) chance of recurrence, CDI treatment costs are estimated at $1-5 billion per year. Once CDI recurs, many patients get into a vicious cycle of antibiotic therapy and relapse. Although Fecal Microbiota Transplants (FMT) have demonstrated effectiveness in treating CDI (~90% success rate), there are also potential risks. The ability of the microbiota to contribute to chronic diseases such as obesity, diabetes, cancer, and cardiovascular disease in animal models demands that the long-term effects of transplanted communities on human health be better understood. This is especially true in children and young adults, where FMT is increasingly being used not only for CDI but also other ailments including inflammatory bowel disease. Treatment of CDI with defined, minimal communities of pure strains is one alternative to FMT that could negate these risks. Thus far, treatment cocktails of 10, 12 or 33 strains have proven effective in limited human trials. Although promising, these studies were limited by their lack of rigorous pre-clinical testig to demonstrate the effectiveness/necessity of all strains and to probe their long-term impacts on human health. The overall goal of this research is to identify human derived, defined microbial communities that are safe and effective for the treatment of recurrent CDI. To this end, we have developed two pre-clinical models of CDI, a human fecal Mini BioReactor Array (MBRA) and humanized microbiota mouse (HMbmouse) model of recurrent disease. The unique strengths of these models are that human-derived strains can be tested against human- derived microbial communities, either in medium-throughput MBRAs or in the context of a host.
Aim 1. Develop defined communities to suppress C. difficile invasion in human fecal MBRAs and the HMbmouse model of recurrent C. difficile disease. In the R21 phase, our MBRA model will be used to rapidly screen many combinations of strains to identify minimal communities capable of combatting CDI. Successful communities will be tested in HMbmice to identify those with the highest likelihood for success.
Aim 2. Optimization of communities for efficacy against CDI.
Aim 3. Assess the safety and long-term effects of defined community transplantation. In the R33 phase, communities will be optimized for effectiveness, safety, and capability of being produced in industrial settings. The potential hazards of strains will be evaluated through genome sequencing/annotation, antibiotic resistance profiling, and long-term association studies with murine models to determine the impact on host health and physiology. Specific impacts on human tissue will be evaluated with human enteroid models. The final products of this research will be one or more defined cocktails of strains with proven effectiveness in treating CDI, acceptable safety profiles, and proven protocols for industrial-scale production.

Public Health Relevance

Clostridium difficile infection is the leading cause of antibiotic associated diarrhea and has been deemed an urgent threat pathogen by the Centers for Disease Control. Due to increasing morbidity and mortality associated with this pathogen, we seek to identify a novel, non-antibiotic based strategy for suppressing C. difficile infection.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21AI121522-02
Application #
9186979
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Ranallo, Ryan
Project Start
2015-12-01
Project End
2017-11-30
Budget Start
2016-12-01
Budget End
2017-11-30
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030
Collins, James; Auchtung, Jennifer M (2017) Control of Clostridium difficile Infection by Defined Microbial Communities. Microbiol Spectr 5: