Skin Microbiome Research in the Omics Era
The most commonly applied high-throughput technologies for microbiota composition profiling target the highly conserved 16S rRNA gene sequence. The continuously expanding and improving bioinformatic tools, which allow the effective assessment of microbial diversity and taxonomic composition (genus or OTU), places this field within reach of clinical investigators. The microbiota data generated by these methods are very well suited for multivariate statistical modelling to assess the impact of environmental and external variables on microbiota composition, enabling the selective identification of microbial biomarkers of disease, which may allow the assessment of disease status in individuals, or the tracing of therapy efficacy. Apart from addressing bacterial populations, molecular methods can also be adapted to characterize yeast, fungal, and viral communities associated with skin. Moreover, upcoming advances in sequencing technology will increase throughput (more samples), sequencing depth (more reads per sample), and phylogenetic resolution (longer reads). Nevertheless, rRNA targeting methodologies are restricted to assessment of ecosystem composition, and do not provide direct information of the functionality of the microbiota. Metagenomic approaches, in which the total DNA of an ecosystem is sequenced, offer great potential for the generation of untargeted inventories of ecosystem inhabitants and provide direct access to the functional composition of the skin microbiome. A major hurdle in these approaches is that they require a substantial quantity of DNA, which is currently limiting the applicability of metagenomics in (dry) skin sites that are colonized by low-density communities. Nevertheless, the potential of this technology has been illustrated recently for two skin sites, namely, the anterior nares (moist) and retroauricular crease (sebaceous) sites, revealing that these ecosystems are more similar in terms of functional composition as compared with their phylogenetic composition. A compelling advantage of metagenomic function profiling is the high phylogenetic resolution that goes beyond the species level. Importantly, functional adaptations of the microbiome were associated with changes at the strain level, which was reflected in host-specific structural variant enrichment that illustrates the genomic plasticity of a microbial community in response to its environmental conditions. The potential power of metagenomic technologies in unravelling the functional adaptations of the skin microbiome to the diseased skin still has to be evaluated, but strain level analyses of the major skin commensal Propionibacterium acnes found in both acne and healthy skin provided insight into specific phylogenetic lineages typically associated with acne and unhealthy skin versus healthy skin controls. Moreover, the potential role of acne-associated lineages in the pathophysiology was further addressed by whole genome comparison of representative strains, enabling the identification of genes with a role in adherence, virulence, and pathogenic immune response in P. acnes lineages derived from unhealthy skin. Apart from these genetic differences, several studies also addressed the functional differences of P. acnes communities in the skin of healthy and acne patients, demonstrating that the anaerobic compartment of the sebaceous follicles of acne-skin biopsies was more frequently colonized with P. acnes, which were mostly present as microbial biofilms. It remains unknown how this relates to lineage or strain-specific genetics of the S. aureus genus representatives that are found to dominate the atopic dermatitis-affected skin microbiota, but comparative genomics in cutaneous infections already revealed specific phylotypes to be associated with distinct clinical properties. Increasing our understanding of the compartmentalized behaviour of skin microorganisms in relation to skin diseases might be a crucial step towards unravelling their role in pathophysiology.
The determination of the collective pool of messenger RNAs that are expressed in situ, a technology known as metatranscriptomics, enables the characterization of the activity of specific metabolic functions. These approaches also have the capacity to reveal functions expressed at high level by low-abundance members of the skin microbiota. High resolution functional activity profiles of the skin microbiota in relation to clinical entities of the skin such as inflammation, infection, and disease hold great promises to refine our understanding of the molecular interplay between the skin and the microbial community it hosts. Metatranscriptome approaches have not yet been reported for the skin, most likely because of the limited amount of sample material that can be collected. However, emerging advances in sample preparation, material enrichment, RNA amplification, or sequencing technologies may solve these problems in the future.
Overall, skin microbiome research will be able to harness the emerging technological possibilities that are being developed for other microbial communities that inhabit human niches such as the oral and gastrointestinal tract. The combination of different omics-based technologies and their integration will enable the deciphering of microbiome functionalities related to pathophysiologic host–microbe interactions, which may open avenues for novel prophylactic or therapeutic approaches for skin diseases, which may include microbiome manipulation strategies.