A research team working at Brigham and Women’s Hospital (BWH) and the University of Massachusetts has created a set of computational programs that are able to predict the behavior of the human microbiome with accuracy. The microbiome is the rich and diverse population of microbes that reside on and inside the human body. The scientists have published a paper
in Genome Biology describing how the algorithms they’ve written and made publicly available can be applied to develop new treatments for serious diarrheal infections, such as inflammatory bowel disease and Clostridium difficile. The investigators also outline how to identify the bacteria that are most critical for a stable and healthy microbial community. That may be helpful in the development of probiotics and other therapies for treating problems in the microbiome, now linked to a growing number of diseases.
The open source software suite the scientists have written and called the Microbial Dynamical Systems INference Engine (MDSINE), utilizes advanced machine learning techniques to accurately model how microbial communities in the gut will interact and develop over time. Not only can it read data files, it can also generate figures. The software enables a user to select from multiple analysis options to aid in both exploratory and more focused investigation.
Image from Genome Biology via Genome Biology/BioMed Central
To validate MDSINE, the researchers performed extensive computational simulations. They also applied the software to experiments that evaluated the dynamics of a C. difficile infection. C.difficile is the most common cause of infection in hospitals and is capable of causing serious illness and even fatalities in patients. Interestingly, their results showed that a group of three organisms has the ability to establish colonization resistance against C. difficile, showing that the software provides unique predictive powers.
The team also looked at the effects of a probiotic, a cocktail of various strains of bacteria that is being developed as a treatment for inflammatory diseases. Since these probiotics cocktails are often given to patients with a huge range of dietary intake, MDSINE predicted how each strain in the probiotic cocktail contributed to the maintenance of the stability of the bacterial community when diet was altered. Their results suggested that diet had an impact on the roles various bacterial strains played, highlighting the intricacy of probiotic design and the potential of MDSINE to evaluate the efficacy and composition of probiotics.
"Every person has their own bacterial ecosystem living within them. There's a lot of exciting new evidence that giving patients bacteriotherapies, or cocktails of bacteria, may be effective in treating or preventing a variety of major diseases including infections, arthritis, inflammatory bowel disease, and cancer. MDSINE is the first tool we've developed under the new BWH Precision Medicine Initiative, and we're releasing it as open source software in that hope that it will help to advance the bacteriotherapy field," explains senior author Georg Gerber, MD, PhD, MPH, an Assistant Professor in Computational Pathology at BWH and the Co-Director of the Massachusetts Host-Microbiome Center at BWH.
"Advanced computational methods like MDSINE are essential for understanding how to design and evaluate bacteriotherapies or `bugs as drugs,' and to tailor them to individual patients since everyone's microbiome is different. Our results have given us insights into new bacteriotherapies for C. difficile infection and inflammatory bowel disease, and moreover suggest general strategies for developing these therapies for many other diseases," said Vanni Bucci, the first author of the study and an Assistant Professor at the University of Massachusetts at Dartmouth.
Downloads of the software are available from bitbucket here
and from zenodo here
, Genome Biology
via BioMed Central