"...it would appear to be a pointless and doubtful exercise to examine and disentangle the apparently random appearing bacteria in normal feces and the intestinal tract, a situation that seems controlled by a thousand coincidences... Yet I have nevertheless devoted myself now for a year virtually exclusively to this special study, it was with the conviction that the accurate knowledge of these conditions is essential, for the understanding of not only the physiology of digestion..., but also the pathology and therapy of microbial intestinal diseases."
-Theodore Escherich, 1885
Nearly 130 years ago, the pioneer of the modern movement to understand the microbiome operated in ignorance of evolutionary theory, genomics, ecology, statistics, or the knowledge that most bacteria cannot be cultured in the laboratory. Today, even with amazing advances in all of these fields microbiologists are still grappling with the questions that motivated Escherich to understand why some of his pediatric patients developed diarrhea and others did not. In many ways it is amazing how far the field has developed since Escherich isolated Communialis coli, yet it is also distressing that in spite of these advances we are still struggling to address fundamental questions about the interplay between humans and the microbes that reside on and within us - the human microbiome. The Schloss lab is motivated by the opportunities presented by combining the tools of microbiology, ecology, and bioinformatics to address many of these fundamental and applied questions.
The human microbiome is more than ten-time larger than the number of human cells and represents a collective genome that is at least 100-times more complex than our genome. Although many people are interested in pathogens, until recently, there has been little emphasis placed on "the good guys" or determining how our microbiome keeps us healthy. Numerous lines of evidence indicate that our genetics, diet, behavior, and life experiences affect the structure of our microbiome and make us each unique. Yet, because of this daunting intra- and inter-personal complexity, it is difficult to make statements about the precise interactions between specific bacterial groups within our microbiome and their interaction with overall human health.
My lab is specifically interested in understanding the temporal stability of the microbiome and how perturbations in the microbiome (i.e. dysbiosis) relate to changes in health and disease. The overall hypothesis of the lab is that each individual is their own indication of "normal" and deviations from this state will tell us a lot about our state of health. To this end we are pursuing two projects, which simulate a personal medicine strategy using the murine microbiome. First, we are taking a classical ecology approach to study the effect of various perturbations on community stability. Through this approach we can determine the relationship between diversity and stability and the resistance and resilience of the microbiome to antibiotic treatments. Second, we are using mouse models of tumor formation in the colon to investigate the antagonistic or potentiating role that the microbiome has in tumor formation. These models will enable us to determine whether there are specific microbial populations or interactions that have a causal role or serve as biomarkers of tumorigenesis. To address these questions we use a variety of culture-independent techniques focused on DNA sequencing of the 16S rRNA gene as well as bulk bacterial DNA (aka metagenomics). These tools enable us to address our biological questions from a taxonomic and functional perspective. Furthermore, through the use of mathematical modeling we hope to improve our understanding of the mechanistic underpinnings of the microbiome as well as predict the effects of perturbations on the microbiome.
Because we are at the forefront of applying modern sequence-based tools to biological questions, we are also developing software to describe and compare microbial communities. This software enables the scientific community to reach conclusions regarding host-microbiome interactions with statistical confidence and has effectively enabled the field to transition from discover-based to hypothesis-driven research. As part of this effort, we provide workshops to train microbial ecologists on the theory and practice of analyzing their data. Our program, mothur (http://www.mothur.org), is being widely used by microbial ecologists that have generated Sanger sequence data and pyrosequence tag sequences. We also collaborate with other investigators to conduct studies in murine, human, and "environmental" samples to help design experiments and analyze data related to studying microbial ecology.
I am always on the lookout for excellent students and postdoctoral fellows. My goal is to train scientists to straddle the fields of microbiology, ecology, and bioinformatics. Attempting to study host-microbiome interactions without this approach is limiting and so I believe that although this course of training is demanding, it will prepare people for the next generation of science.