Why is metabolic labour divided in nitrification?

Costa, Engràcia; Pérez, Julio; Kreft, Jan‐Ulrich

doi:10.1016/j.tim.2006.03.006

Cited by 384 publications

(289 citation statements)

References 46 publications

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“…However, given its metabolic potential, the dominance of Nitrospira CG24 and the high abundance of Nitrospira-AMOX genes compared with other AMO genes, Nitrospira CG24 might mediate complete ammonium oxidation in this system. This would be in agreement with the suggestion that a microorganism that completely oxidizes ammonia to nitrate exists (Costa et al, 2006). The Nitrospira abundance observed in this study is consistent with earlier pyrosequencing and quantitative PCR-based analysis of the same system, where abundances of up to 65% and 18%, respectively, were measured, and Nitrospira 16S rRNA gene sequences were often up to two orders of magnitude more abundant than Nitrosospira and Nitrosomonas 16S rRNA sequences combined (Gülay et al, 2016).…”

Section: Predicted Metabolic and Geochemical Modelsupporting

confidence: 93%

Metagenomic analysis of rapid gravity sand filter microbial communities suggests novel physiology ofNitrospiraspp.

et al. 2016

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Rapid gravity sand filtration is a drinking water production technology widely used around the world. Microbially catalyzed processes dominate the oxidative transformation of ammonia, reduced manganese and iron, methane and hydrogen sulfide, which may all be present at millimolar concentrations when groundwater is the source water. In this study, six metagenomes from various locations within a groundwater-fed rapid sand filter (RSF) were analyzed. The community gene catalog contained most genes of the nitrogen cycle, with particular abundance in genes of the nitrification pathway. Genes involved in different carbon fixation pathways were also abundant, with the reverse tricarboxylic acid cycle pathway most abundant, consistent with an observed Nitrospira dominance. From the metagenomic data set, 14 near-complete genomes were reconstructed and functionally characterized. On the basis of their genetic content, a metabolic and geochemical model was proposed. The organisms represented by draft genomes had the capability to oxidize ammonium, nitrite, hydrogen sulfide, methane, potentially iron and manganese as well as to assimilate organic compounds. A composite Nitrospira genome was recovered, and amo-containing Nitrospira genome contigs were identified. This finding, together with the high Nitrospira abundance, and the abundance of atypical amo and hao genes, suggests the potential for complete ammonium oxidation by Nitrospira, and a major role of Nitrospira in the investigated RSFs and potentially other nitrifying environments.

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Section: Predicted Metabolic and Geochemical Modelsupporting

confidence: 93%

Metagenomic analysis of rapid gravity sand filter microbial communities suggests novel physiology ofNitrospiraspp.

et al. 2016

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“…This division of labour is reminiscent of cross-feeding in microorganisms, and although it may have evolutionary reasons different from those put forward for the case of microorganisms [44,45], it shows that the analysis of intracellular networks should be extended to intercellular networks. This is indeed a current trend [21,44,45]. Game theory is then helpful as well.…”

Section: Transition To Cooperationmentioning

confidence: 96%

“…Prior to those studies, Eigen and Winkler [13] considered many biological processes, including prebiotic evolution, to have properties of games. Recently, it has become more and more evident that game theory is relevant for biophysics [14][15][16] and biochemistry [17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Use of Game-Theoretical Methods in Biochemistry and Biophysics

et al. 2008

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Evolutionary game theory can be considered as an extension of the theory of evolutionary optimisation in that two or more organisms (or more generally, units of replication) tend to optimise their properties in an interdependent way. Thus, the outcome of the strategy adopted by one species (e.g., as a result of mutation and selection) depends on the strategy adopted by the other species. In this review, the use of evolutionary game theory for analysing biochemical and biophysical systems is discussed. The presentation is illustrated by a number of instructive examples such as the competition between microorganisms using different metabolic pathways for adenosine triphosphate production, the secretion of extracellular enzymes, the growth of trees and photosynthesis. These examples show that, due to conflicts of interest, the global optimum (in the sense of being the best solution for the whole system) is not always obtained. For example, some yeast species use metabolic pathways that waste nutrients, and in a dense tree canopy, trees grow taller than would be optimal for biomass productivity. From the viewpoint of game theory, the examples considered can be described by the Prisoner's Dilemma, snowdrift game, Tragedy of the Commons and rock-scissors-paper game.

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“…Different metabolic processes are often segregated into different microbial cell types (Costa et al, 2006;Johnson et al, 2012;Zelezniak et al, 2015). A canonical example is substrate cross-feeding.…”

Section: Introductionmentioning

confidence: 99%

“…Substrate cross-feeding occurs when one cell type partially consumes a primary substrate into a metabolic intermediate and another cell type then further consumes the intermediate. Substrate cross-feeding controls numerous environmentally and economically important microbial processes, including the mineralization of organic carbon (Schink, 1997;McInerney et al, 2009), the degradation of environmental contaminants (de Souza et al, 1998;Møller et al, 1998;Pelz et al, 1999;Drzyzga and Gottschal 2002;Holmes et al, 2006) and the recycling of fixed nitrogen into dinitrogen gas (N 2 ) (Martienssen and Schops, 1999;Van de Pas-Schoonen et al, 2005;Costa et al, 2006). While substrate cross-feeding is frequently observed within natural and engineered microbial communities, its effects on microbial processes are often unclear.…”

Section: Introductionmentioning

confidence: 99%

Segregating metabolic processes into different microbial cells accelerates the consumption of inhibitory substrates

2016

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Different microbial cell types typically specialize at performing different metabolic processes. A canonical example is substrate cross-feeding, where one cell type consumes a primary substrate into an intermediate and another cell type consumes the intermediate. While substrate cross-feeding is widely observed, its consequences on ecosystem processes is often unclear. How does substrate cross-feeding affect the rate or extent of substrate consumption? We hypothesized that substrate cross-feeding eliminates competition between different enzymes and reduces the accumulation of growth-inhibiting intermediates, thus accelerating substrate consumption. We tested this hypothesis using isogenic mutants of the bacterium Pseudomonas stutzeri that either completely consume nitrate to dinitrogen gas or cross-feed the intermediate nitrite. We demonstrate that nitrite crossfeeding eliminates inter-enzyme competition and, in turn, reduces nitrite accumulation. We further demonstrate that nitrite cross-feeding accelerates substrate consumption, but only when nitrite has growth-inhibiting effects. Knowledge about inter-enzyme competition and the inhibitory effects of intermediates could therefore be important for deciding how to best segregate different metabolic processes into different microbial cell types to optimize a desired biotransformation.

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Why is metabolic labour divided in nitrification?

Cited by 384 publications

References 46 publications

Metagenomic analysis of rapid gravity sand filter microbial communities suggests novel physiology ofNitrospiraspp.

Metagenomic analysis of rapid gravity sand filter microbial communities suggests novel physiology ofNitrospiraspp.

Use of Game-Theoretical Methods in Biochemistry and Biophysics

Segregating metabolic processes into different microbial cells accelerates the consumption of inhibitory substrates

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