Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

AbstractDespite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.</jats:p

Pharmacogenetics of the g protein-coupled receptors

Pharmacogenetics investigates the influence of genetic variants on physiological phenotypes related to drug response and disease, while pharmacogenomics takes a genome-wide approach to advancing this knowledge. Both play an important role in identifying responders and nonresponders to medication, avoiding adverse drug reactions, and optimizing drug dose for the individual. G protein-coupled receptors (GPCRs) are the primary target of therapeutic drugs and have been the focus of these studies. With the advance of genomic technologies, there has been a substantial increase in the inventory of naturally occurring rare and common GPCR variants. These variants include single-nucleotide polymorphisms and insertion or deletions that have potential to alter GPCR expression of function. In vivo and in vitro studies have determined functional roles for many GPCR variants, but genetic association studies that define the physiological impact of the majority of these common variants are still limited. Despite the breadth of pharmacogenetic data available, GPCR variants have not been included in drug labeling and are only occasionally considered in optimizing clinical use of GPCR-targeted agents. In this chapter, pharmacogenetic and genomic studies on GPCR variants are reviewed with respect to a subset of GPCR systems, including the adrenergic, calcium sensing, cysteinyl leukotriene, cannabinoid CB1 and CB2 receptors, and the de-orphanized receptors such as GPR55. The nature of the disruption to receptor function is discussed with respect to regulation of gene expression, expression on the cell surface (affected by receptor trafficking, dimerization, desensitization/downregulation), or perturbation of receptor function (altered ligand binding, G protein coupling, constitutive activity). The large body of experimental data generated on structure and function relationships and receptor-ligand interactions are being harnessed for the in silico functional prediction of naturally occurring GPCR variants. We provide information on online resources dedicated to GPCRs and present applications of publically available computational tools for pharmacogenetic studies of GPCRs. As the breadth of GPCR pharmacogenomic data becomes clearer, the opportunity for routine assessment of GPCR variants to predict disease risk, drug response, and potential adverse drug effects will become possible