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1.
Sci Adv ; 10(33): eado7729, 2024 Aug 16.
Article in English | MEDLINE | ID: mdl-39141735

ABSTRACT

Nitrogenases are the only known enzymes that reduce molecular nitrogen (N2) to ammonia. Recent findings have demonstrated that nitrogenases also reduce the greenhouse gas carbon dioxide (CO2), suggesting CO2 to be a competitor of N2. However, the impact of omnipresent CO2 on N2 fixation has not been investigated to date. Here, we study the competing reduction of CO2 and N2 by the two nitrogenases of Rhodobacter capsulatus, the molybdenum and the iron nitrogenase. The iron nitrogenase is almost threefold more efficient in CO2 reduction and profoundly less selective for N2 than the molybdenum isoform under mixtures of N2 and CO2. Correspondingly, the growth rate of diazotrophically grown R. capsulatus strains relying on the iron nitrogenase notably decreased after adding CO2. The in vivo CO2 activity of the iron nitrogenase facilitates the light-driven extracellular accumulation of formate and methane, one-carbon substrates for other microbes, and feedstock chemicals for a circular economy.


Subject(s)
Carbon Dioxide , Formates , Methane , Nitrogen , Nitrogenase , Carbon Dioxide/metabolism , Methane/metabolism , Nitrogenase/metabolism , Formates/metabolism , Nitrogen/metabolism , Rhodobacter capsulatus/metabolism , Nitrogen Fixation , Oxidation-Reduction
2.
mSystems ; 9(1): e0096623, 2024 Jan 23.
Article in English | MEDLINE | ID: mdl-38059636

ABSTRACT

Microbes can be found in abundance many kilometers underground. While microbial metabolic capabilities have been examined across different geochemical settings, it remains unclear how changes in subsurface niches affect microbial needs to sense and respond to their environment. To address this question, we examined how microbial extracellular sensor systems vary with environmental conditions across metagenomes at different Deep Mine Microbial Observatory (DeMMO) subsurface sites. Because two-component systems (TCSs) directly sense extracellular conditions and convert this information into intracellular biochemical responses, we expected that this sensor family would vary across isolated oligotrophic subterranean environments that differ in abiotic and biotic conditions. TCSs were found at all six subsurface sites, the service water control, and the surface site, with an average of 0.88 sensor histidine kinases (HKs) per 100 genes across all sites. Abundance was greater in subsurface fracture fluids compared with surface-derived fluids, and candidate phyla radiation (CPR) bacteria presented the lowest HK frequencies. Measures of microbial diversity, such as the Shannon diversity index, revealed that HK abundance is inversely correlated with microbial diversity (r2 = 0.81). Among the geochemical parameters measured, HK frequency correlated most strongly with variance in dissolved organic carbon (r2 = 0.82). Taken together, these results implicate the abiotic and biotic properties of an ecological niche as drivers of sensor needs, and they suggest that microbes in environments with large fluctuations in organic nutrients (e.g., lacustrine, terrestrial, and coastal ecosystems) may require greater TCS diversity than ecosystems with low nutrients (e.g., open ocean).IMPORTANCEThe ability to detect extracellular environmental conditions is a fundamental property of all life forms. Because microbial two-component sensor systems convert information about extracellular conditions into biochemical information that controls their behaviors, we evaluated how two-component sensor systems evolved within the deep Earth across multiple sites where abiotic and biotic properties vary. We show that these sensor systems remain abundant in microbial consortia at all subterranean sampling sites and observe correlations between sensor system abundances and abiotic (dissolved organic carbon variation) and biotic (consortia diversity) properties. These results suggest that multiple environmental properties may drive sensor protein evolution and highlight the need for further studies of metagenomic and geochemical data in parallel to understand the drivers of microbial sensor evolution.


Subject(s)
Dissolved Organic Matter , Ecosystem , Bacteria/genetics , Metagenome , Environment
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