Spatial structure of RNA expression: RNA-seq and similar methods can record gene expression within and among cells. Current methods typically lose positional information and many require arduous single-cell isolation and sequencing. Ståhl et al. have developed a way of measuring the spatial distribution of transcripts by annealing fixed brain or cancer tissue samples directly to bar-coded reverse transcriptase primers, performing reverse transcription followed by sequencing and computational reconstruction, and they can do so for multiple genes. Science , this issue p. 78

Microbes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing >35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.

Growing evidence from metagenome-wide association studies link multiple common disorders to microbial dysbiosis but effects of drug treatment are often not accounted for; here, the authors re-analyse two previous metagenomic studies of type 2 diabetes mellitus patients together with a novel cohort to determine the effects of the widely prescribed antidiabetic drug metformin and highlight the need to distinguish the effects of a disease from the effects of treatment on the gut microbiota. There is growing evidence from metagenome-wide association studies that several common human disorders, such as type 2 diabetes mellitus (T2D), are associated with intestinal dysbiosis, an unhealthy imbalance of the gut microbiota. However, the contribution of antidiabetic drug treatment to dysbiosis is often not accounted for. Oluf Pedersen and colleagues analysed two previous metagenomic studies of T2D patients that yielded divergent conclusions regarding the association of the disease with dysbiosis, together with a novel cohort, to determine the effects of the widely prescribed antidiabetic drug metformin. They find that metformin is indeed a confounding factor, but that a unified signature of gut microbiome shifts in T2D is still apparent. In recent years, several associations between common chronic human disorders and altered gut microbiome composition and function have been reported1,2. In most of these reports, treatment regimens were not controlled for and conclusions could thus be confounded by the effects of various drugs on the microbiota, which may obscure microbial causes, protective factors or diagnostically relevant signals. Our study addresses disease and drug signatures in the human gut microbiome of type 2 diabetes mellitus (T2D). Two previous quantitative gut metagenomics studies of T2D patients that were unstratified for treatment yielded divergent conclusions regarding its associated gut microbial dysbiosis3,4. Here we show, using 784 available human gut metagenomes, how antidiabetic medication confounds these results, and analyse in detail the effects of the most widely used antidiabetic drug metformin. We provide support for microbial mediation of the therapeutic effects of metformin through short-chain fatty acid production, as well as for potential microbiota-mediated mechanisms behind known intestinal adverse effects in the form of a relative increase in abundance of Escherichia species. Controlling for metformin treatment, we report a unified signature of gut microbiome shifts in T2D with a depletion of butyrate-producing taxa3,4. These in turn cause functional microbiome shifts, in part alleviated by metformin-induced changes. Overall, the present study emphasizes the need to disentangle gut microbiota signatures of specific human diseases from those of medication.

Several bacterial species have been implicated in the development of colorectal carcinoma (CRC), but CRC‐associated changes of fecal microbiota and their potential for cancer screening remain to be explored. Here, we used metagenomic sequencing of fecal samples to identify taxonomic markers that distinguished CRC patients from tumor‐free controls in a study population of 156 participants. Accuracy of metagenomic CRC detection was similar to the standard fecal occult blood test (FOBT) and when both approaches were combined, sensitivity improved > 45% relative to the FOBT, while maintaining its specificity. Accuracy of metagenomic CRC detection did not differ significantly between early‐ and late‐stage cancer and could be validated in independent patient and control populations ( N = 335) from different countries. CRC‐associated changes in the fecal microbiome at least partially reflected microbial community composition at the tumor itself, indicating that observed gene pool differences may reveal tumor‐related host–microbe interactions. Indeed, we deduced a metabolic shift from fiber degradation in controls to utilization of host carbohydrates and amino acids in CRC patients, accompanied by an increase of lipopolysaccharide metabolism.