Fig. 1

Driven by major advances in sequencing, metabolomics, proteomics and bioinformatics, an increasing number of microbiome-wide association studies (MWAS) aim to take complex and large data set analyses of the microbiome with longitudinal sampling and multiple molecular perspectives, and associate these with markers for health and disease. As discussed in the keynote debate led by Jack Gilbert and moderated by Colin Hill, it is time to cease merely measuring. It is crucial that the microbiome field moves towards more detailed functional and mechanistic studies. Various examples presented at the Wellcome Trust meeting have shown that the field is ready for the next steps in the translation of microbiome knowledge; indeed, one could assert that microbiome research is as beautiful (and as complex) as modern art. (a) and (b) show typical Principal Component Analyses (PCAs), which are often used to visualize complex, multidimensional microbiome data. (c) represents a typical heat map-based way of visualizing complex microbiome correlation data, with different colors representing correlation coefficients, microbiome operational taxonomic units (OTUs) and groups of subjects. More details can be found in the original paper (figure taken from Fig. 1, Claesson et al., Nature 488, 178-184)