Scientific possibilities in associating microbiome to specific diseases and its bioinformatic and experimental challenges

Microbes play important roles in human health and disease either as individual species or as a consortium. While medical microbiology has traditionally associated a single species with a specific disease, recent knowledge of the diversity of microbes present at different sites of the body has opened our eyes to the dynamic interactions between species, and how community interactions amongst microbes could potentiate disease. More importantly, clinical manifestations of disease symptoms have been hypothesized to arise from cross-interactions between metabolites and signalling molecules secreted by microbes not in direct communication with each other. Such myriad and entangled interactions raise important questions on clinicians and researchers’ quest to understand the aetiologies of disease and underpinnings of their progression. Doing so require profiling the microbes present and their community structure, to which mass spectrometry metabolomics could lend a lens. Nevertheless, how do we associate specific diseases to one or two microbiome which may be at different body sites? Do we have the analytical and bioinformatic toolkit to do so? A review paper in Nature (“Microbiome-wide association studies link dynamic microbial consortia to disease”) seek to illuminate this question. But from the clinical perspective, is associating a microbiome to a specific disease useful, particularly for multifactorial diseases such as metabolic syndrome? To a limited extent, the answer is yes, for it provides an initial direction towards understanding the molecular mechanisms at play in disease manifestations as well as the complex interplay between microbe and host in pathological processes. At a deeper level, however, dynamic changes in microbiome community composition and structure with changing environmental conditions and host physiology meant that tracing the specific steps important to disease processes might be more fruitfully accomplished through the bottom-up approach rather than the top-down methodology inherent in microbiome profiling. Specifically, sets of molecular processes are likely impacted in complex diseases which translate to dysfunctional enzymes, or metabolic pathways and signalling cascades in overdrive. Teasing the complex web of metabolic cum signalling pathways apart in seeking to understand the specific molecular effectors important in disease necessitates a combination of molecular biology and biochemistry techniques coupled with contemporary discovery tools in omics. Such information would provide downstream leads for therapeutic development, which microbiome-wide association studies lend a first pointer. Collectively, associating a microbiome to specific disease states provide a list of candidate microbes that could be aetiological agents of disease, from which further biochemical and molecular biology investigations would uncover the underlying disease mechanisms.