This post is by MSU grad student Connie Rojas
Microbes colonize every surface of their hosts. Once established, they do not live in isolated patches, but instead form highly regulated, structurally and functionally organized communities, termed ‘microbiota’. Due to the interplay of the host’s immune system with its microbiota, many members are commensals or mutualists, performing functions critical for host health and physiology. In the human mouth, resident microbiota secrete antimicrobials and enzymes that contribute to oral health. In the mammalian gastrointestinal tract, microbiota synthesize vitamins, and supply the host with energy released from the fermentation of indigestible carbohydrates. In the human vagina, members of the microbiota produce lactic acid, which maintains a low pH environment thought to protect against infection. However, despite the explosion in microbiome research, we know very little about the additional functions microbes are performing within their hosts. We also do not know whether or how they have affected the behavior and evolution of their hosts.
The host generally maintains a stable microbiota. Stability ensures that beneficial symbionts and their associated functions persist over time. Host regulatory mechanisms like physical barriers, mucosal antibodies, and immune systems work to promote the growth of certain microbes, exclude others, and keep the microbiota in check. Furthermore, because some microbes are functionally redundant and can substitute for one another, community function can be retained despite shifts in composition. In fact, alterations to the function of these naturally occurring communities have been implicated in diseases like inflammatory bowel syndrome, type 2 diabetes, bacterial vaginosis, and colorectal cancer. Nevertheless, it is unknown the extent to which fluctuations in host and microbial environments, and resultant variation in the microbiota, can be afforded before these changes become detrimental. Years of research show that microbiota are often host species- and niche-specific, and across hosts, the microbiota varies with a myriad of factors like diet, age, antibiotic use, habitat, season, and environmental stressors. However, it is very likely that numerous other factors are driving variation in microbiota composition and function among hosts, and determining how this variation affects host phenotype is a key line of inquiry.
I study the gut microbiome of spotted hyenas! Photo Credit: Lily Johnson-Ulrich
My research seeks to understand the stability, composition, and function of the microbiota at various body-sites and elucidate the socio-ecological traits of hosts influencing its structure. While most microbiome research is conducted in humans and mice, typically within the context of host health and disease; I study these questions in wild spotted-hyenas (Crocuta crocuta). Due to their complex social behavior, hyenas are an excellent model system to explore how microbiota both influence host behavior and respond to host ecology.
Spotted-hyenas are large, social carnivores inhabiting much of Sub-Saharan Africa. They live in large groups, called ‘clans’, which are structured by linear dominance hierarchies, where an individual’s position determines its priority of access to resources. Their societies are also characterized by female dominance, male-biased dispersal, and a high degree of fission-fusion dynamics, such that individuals move freely among subgroups several times per day. Hyenas are reared in communal dens for the first 9mo of life, are weaned at 12-18mo old, and reach reproductive maturity at 24mo, although most females do not bear young until they are at least 36mo. In my current research, I am investigating how host factors like social dominance rank, group membership, and patterns of association affect hyena microbiota structure and function. Do individuals of varying social ranks differ in the stability and functional potential of their microbial communities? Are certain microbial genetic pathways lacking in one group vs. another? How similar are the communities, in terms of composition and function, of hyenas that associate very closely? Once again, can this variation have implications for host phenotype?
About to collect body-swabs and other biological samples from a hyena, after darting
We use next-generation sequencing technologies, mainly 16Sr RNA sequencing to profile the taxonomic composition of the microbiota, and metagenomic sequencing to characterize its function. From shotgun metagenomic data, it is also possible to infer microbial community dynamics. Populations of microbes, like members of any ecological community, cooperate and compete with each other, break-down and synthesize metabolites, and adapt rapidly to ever-changing environmental conditions. A recently developed mathematical framework by Sung and colleagues (2017) reconstructs community metabolic networks from metagenomic and available metabolic data. In these networks, the nodes represent major taxa, and the edges, which are color-coded, represent interactions (gray: cooperative; red: competitive; see Figure below). Metabolites that are imported and degraded by a species are shown in purple, and those that are synthesized and exported are in blue. I hope to use this framework to identify, for example, the molecules that are important for hyena gut community function, and evaluate whether the microbial community is dominated by competitive or cooperative interactions. Changes in community function and dynamics in response to extreme fluctuations in prey abundance (e.g. arrival of migratory wildebeest) will also be assessed this way.
The human gut microbiota metabolic community-level network constructed by Sung and colleagues (2017). Also, Connie’s dream figure.
Despite the interesting questions being asked, and the multitude of research on diverse host-microbiome systems being conducted, we still have a long way to go as a field. The things we do not know are too many to list. But I hope that revival of innovative culture-based techniques, advances in single-cell genomics, and development of more encompassing bioinformatics tools can help address the many existing gaps in our knowledge.
Reference
Sung et al. (2017). Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis. Nature Communications 8: 1-12.
