In the biogeochemical nitrogen cycle, microbial respiration processes compete for nitrate as an electron acceptor. Denitrification converts nitrate into nitrogenous gas and thus removes fixed nitrogen from the biosphere, whereas ammonification converts nitrate into ammonium, which is directly reusable by primary producers. We combined multiple parallel long-term incubations of marine microbial nitrate-respiring communities with isotope labeling and metagenomics to unravel how specific environmental conditions select for either process. Microbial generation time, supply of nitrite relative to nitrate, and the carbon/nitrogen ratio were identified as key environmental controls that determine whether nitrite will be reduced to nitrogenous gas or ammonium. Our results define the microbial ecophysiology of a biogeochemical feedback loop that is key to global change, eutrophication, and wastewater treatment.

TitleCritical biogeochemical functions in the subsurface are associated with bacteria from new phyla and little studied lineages

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four detergent cleanup methods (trichloroacetic acid (TCA) precipitation, chloroform/methanol/water (CMW) extraction, a commercial detergent removal spin column method (DRS) and filter-aided sample preparation (FASP)) to provide efficiency benchmarks with respect to protein, peptide, and spectral identifications in each case. Our results show that for protein-limited samples, FASP outperforms the other three cleanup methods, while at high protein amounts, all the methods are comparable. This information was used to investigate and contrast molecular weight-based fractionated with unfractionated lysates from three increasingly complex samples ( Escherichia coli K-12, a five microbial isolate mixture, and a natural microbial community groundwater sample), all of which were prepared with an SDS-FASP approach. The additional fractionation step enhanced the number of protein identifications by 8% to 25% over the unfractionated approach across the three samples.