Denitrifying bacteria respond to and shape microscale gradients within particulate matrices

Heterotrophic denitrification enables facultative anaerobes to continue growing even when limited by oxygen (O2) availability. Particles in particular provide physical matrices characterized by reduced O2 permeability even in well-oxygenated bulk conditions, creating microenvironments where microbial denitrifiers may proliferate. Whereas numerical particle models generally describe denitrification as a function of radius, here we provide evidence for heterogeneity of intraparticle denitrification activity due to local interactions within and among microcolonies. Pseudomonas aeruginosa cells and microcolonies act to metabolically shade each other, fostering anaerobic processes just microns from O2-saturated bulk water. Even within well-oxygenated fluid, suboxia and denitrification reproducibly developed and migrated along sharp 10 to 100 µm gradients, driven by the balance of oxidant diffusion and local respiration. Moreover, metabolic differentiation among densely packed cells is dictated by the diffusional supply of O2, leading to distinct bimodality in the distribution of nitrate and nitrite reductase expression. The initial seeding density controls the speed at which anoxia develops, and even particles seeded with few bacteria remain capable of becoming anoxic. Our empirical results capture the dynamics of denitrifier gene expression in direct association with O2 concentrations over microscale physical matrices, providing observations of the co-occurrence and spatial arrangement of aerobic and anaerobic processes.

Environmental parameters and microbial community profiles as indication towards microbial activities and diversity in aquaponic system compartments

Background An aquaponic system couples cultivation of plants and fish in the same aqueous medium. The system consists of interconnected compartments for fish rearing and plant production, as well as for water filtration, with all compartments hosting diverse microbial communities, which interact within the system. Due to the design, function and operation mode of the individual compartments, each of them exhibits unique biotic and abiotic conditions. Elucidating how these conditions shape microbial communities is useful in understanding how these compartments may affect the quality of the water, in which plants and fish are cultured. Results We investigated the possible relationships between microbial communities from biofilms and water quality parameters in different compartments of the aquaponic system. Biofilm samples were analyzed by total community profiling for bacterial and archaeal communities. The results implied that the oxygen levels could largely explain the main differences in abiotic parameters and microbial communities in each compartment of the system. Aerobic system compartments are highly biodiverse and work mostly as a nitrifying biofilter, whereas biofilms in the anaerobic compartments contain a less diverse community. Finally, the part of the system connecting the aerobic and anaerobic processes showed common conditions where both aerobic and anaerobic processes were observed. Conclusion Different predicted microbial activities for each compartment were found to be supported by the abiotic parameters, of which the oxygen saturation, total organic carbon and total nitrogen differentiated clearly between samples from the main aerobic loop and the anaerobic compartments. The latter was also confirmed using microbial community profile analysis.

Anaerobic threshold

This chapter describes the changes that occur when anaerobic processes start to supplement aerobic metabolism during a cardiopulmonary exercise test (CPET). Lactic acid is produced, which is buffered by bicarbonate to produce carbon dioxide and water. The anaerobic threshold (AT) should be seen when VO2 is at least 40% of predicted maximum oxygen uptake (VO2max). A low AT indicates poor oxygen delivery to muscles. This can be seen in heart disease, peripheral vascular disease or anaemia. AT is useful for predicting operative risk.