The commensal skin microbiota plays an active role in maintaining skin health and function. Several clinical phenotypes are associated with an imbalance in the relative proportions of these microbiota including, atopic dermatitis, psoriasis, and dandruff. For example, dandruff, a scalp disorder that is characterized by abnormal flaking and irritation, is correlated with a higher incidence of Malassezia restricta and Staphylococcus epidermidis, and a lower incidence of Cutiibacterium acnes, as compared to normal scalp. It is not clear how the relative proportions of the microbial populations are either kept in balance (disease-free state), or lead to an imbalanced state, resulting in conditions such as in dandruff and atopic dermatitis. Understanding the mechanisms of interactions between members of the skin microbiome and their impact on skin health will lead to novel intervention strategies that would modulate the skin microbiome in favor of health.
To study the mechanisms by which skin microbes maintain stable communities, a robust and reproducible microbial community model was developed with three major skin microbial species: S. epidermidis, C. acnes, and M. restricta. Growth conditions were established to allow co-cultivation of all three microbes that form a mixed-species biofilm, and standardized methods were developed to label, quantify, and track their relative abundances within this community. Intriguingly, the mixed-species community produces significantly higher biofilm biomass than the mono-species biofilms. Further investigation revealed both cooperative and antagonistic interactions between different members of this community. Our data suggest that the relative proportions of each member may modulate the growth of the others and that such interactions dictate the microbiome balance/imbalance on the skin. Based on our in vitro model, we have defined the interaction network and gained a detailed understanding of the community dynamics of skin microbes. This in vitro model system forms the basis for the development of a fully characterized skin microbiota model, which could be further extended to mimic complex skin disease phenotypes and could help develop potential microbiota-targeted strategies.