Moving beyond descriptions of diversity: clinical and research implications of bacterial imbalance in chronic rhinosinusitis

Abstract

Chronic rhinosinusitis (CRS) is a debilitating disease which affects 5-16% of the general population and involves long-term inflammation of the sinonasal cavity. While microbial involvement in the pathogenesis of CRS has long been suspected, the exact role of microbes remains unclear. Recent application of cultivation-independent, molecular methods has provided much new information, taking advantage of developments in both laboratory- and bioinformatics-based analyses. The aim of this mini-review is to present a variety of available bioinformatics approaches, such as data classification techniques and network analyses, with proven applications in other aspects of human microbiome health and disease research. The uses of molecular techniques in the clinical setting are still in its infancy, but these tools can further our understanding of microbial imbalance during chronic disease and help guide effective patient treatment. The mini-review emphasises ways in which CRS bacterial gene-targeted sequencing data can progress beyond descriptive summaries and toward unlocking the mechanisms by which bacterial communities can be markers for sinus health.