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Metatranscriptomics and metagenomics data sets benchmarked with internal standards were used to characterize the expression patterns for biogeochemically relevant bacterial and archaeal genes mediating carbon, nitrogen, phosphorus and sulfur uptake and metabolism through the salinity gradient of the Amazon River Plume. The genes were identified in 48 metatranscriptomic and metagenomic data sets summing to >500 million quality-controlled reads from six locations in the plume ecosystem. The ratio of transcripts per gene copy (a direct measure of expression made possible by internal standard additions) showed that the free-living bacteria and archaea exhibited only small changes in the expression levels of biogeochemically relevant genes through the salinity and nutrient zones of the plume. In contrast, the expression levels of genes in particle-associated cells varied over orders of magnitude among the stations, with the largest differences measured for genes mediating aspects of nitrogen cycling (nifH, amtB and amoA) and phosphorus acquisition (pstC, phoX and phoU). Taxa varied in their baseline gene expression levels and extent of regulation, and most of the spatial variation in the expression level could be attributed to changes in gene regulation after removing the effect of shifting taxonomic composition. We hypothesize that changes in microbial element cycling along the Amazon River Plume are largely driven by shifting activities of particle-associated cells, with most activities peaking in the mesohaline regions where N2 fixation rates are elevated.

A typical marine bacterial cell in coastal seawater contains only ∼200 molecules of mRNA, each of which lasts only a few minutes before being degraded. Such a surprisingly small and dynamic cellular mRNA reservoir has important implications for understanding the bacterium’s responses to environmental signals, as well as for our ability to measure those responses. In this perspective, we review the available data on transcript dynamics in environmental bacteria, and then consider the consequences of a small and transient mRNA inventory for functional metagenomic studies of microbial communities.