The ocean is a net source of NO, a potent greenhouse gas and ozone-depleting agent. However, the removal of NO via microbial NO consumption is poorly constrained and rate measurements have been restricted to anoxic waters. Here we expand NO consumption measurements from anoxic zones to the sharp oxygen gradient above them, and experimentally determine kinetic parameters in both oxic and anoxic seawater for the first time. We find that the substrate affinity, O tolerance, and community composition of NO-consuming microbes in oxic waters differ from those in the underlying anoxic layers. Kinetic parameters determined here are used to model in situ NO production and consumption rates. Estimated in situ rates differ from measured rates, confirming the necessity to consider kinetics when predicting NO cycling. Microbes from the oxic layer consume NO under anoxic conditions at a much faster rate than microbes from anoxic zones. These experimental results are in keeping with model results which indicate that NO consumption likely takes place above the oxygen deficient zone (ODZ). Thus, the dynamic layer with steep O and NO gradients right above the ODZ is a previously ignored potential gatekeeper of NO and should be accounted for in the marine NO budget.
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http://dx.doi.org/10.1038/s41396-020-00861-2 | DOI Listing |
PLoS One
December 2024
SILA Department, Institute of Health and Nature, Ilisimatusarfik-University of Greenland, Nuuk, Greenland.
The consumption of prey intestines and their content, known as gastrophagy, is well-documented among Arctic Indigenous peoples, particularly Inuit. In Greenland, Inuit consume intestines from various animals, including the ptarmigan, a small herbivorous grouse bird. While gastrophagy provides the potential to transfer a large number of intestinal microorganisms from prey to predator, including to the human gut, its microbial implications remain to be investigated.
View Article and Find Full Text PDFChemSusChem
December 2024
Universität Greifswald: Universitat Greifswald, Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, GERMANY.
As global plastic consumption and littering escalate, innovative approaches to sustainable waste management are crucial. Enzymatic depolymerization has emerged as a promising recycling method for polyesters via monomer recovery under mild conditions. However, current research mainly focuses on using a single plastic feedstock, which can only be derived from complex and costly plastic waste sorting.
View Article and Find Full Text PDFmSystems
December 2024
Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Unlabelled: Dietary fiber confers multiple health benefits originating from the expansion of beneficial gut microbial activity. However, very few studies have established the metabolic consequences of interactions among specific fibers, microbiome composition, and function in either human or representative animal models. In a study design reflective of realistic population dietary variation, fecal metagenomic and metabolomic profiles were analyzed from healthy dogs fed 12 test foods containing different fiber sources and quantities (5-13% as-fed basis).
View Article and Find Full Text PDFInfect Immun
December 2024
Laboratory of Applied Immunology, Institute of Biology Sciences, University of Brasília, Brasília, Brazil.
Dormancy is an adaptation in which cells reduce their metabolism, transcription, and translation to stay alive under stressful conditions, preserving the capacity to reactivate once the environment reverts to favorable conditions. Dormancy and reactivation of () are closely linked to intracellular residency within macrophages. Our previous work showed that murine macrophages rely on the viable but not cultivable (VBNC-a dormancy phenotype) fungus from active , with striking differences in immunometabolic gene expression.
View Article and Find Full Text PDFMetabolite production, consumption, and exchange are intimately involved with host health and disease, as well as being key drivers of host-microbiome interactions. Despite the increasing prevalence of datasets that jointly measure microbiome composition and metabolites, computational tools for linking these data to the status of the host remain limited. To address these limitations, we developed MMETHANE, an open-source software package that implements a purpose-built deep learning model for predicting host status from paired microbial sequencing and metabolomic data.
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