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Low probability of initiating nirS transcription explains observed gas kinetics and growth of bacteria switching from aerobic respiration to denitrification.

Hassan J, Bergaust LL, Wheat ID, Bakken LR - PLoS Comput. Biol. (2014)

Bottom Line: The model is based on the hypothesis that nirS has a low probability (rden, h(-1)) of initial transcription, but once initiated, the transcription is greatly enhanced through positive feedback by NO, resulting in the recruitment of the transcribing cell to denitrification.The resulting Fden (fraction of the cells recruited to denitrification) falls within 0.038-0.161.In contrast, if the recruitment of the entire population is assumed, the simulated denitrification kinetics deviate grossly from those observed.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Sciences, Norwegian University of Life Sciences, Ås, Norway.

ABSTRACT
In response to impending anoxic conditions, denitrifying bacteria sustain respiratory metabolism by producing enzymes for reducing nitrogen oxyanions/-oxides (NOx) to N2 (denitrification). Since denitrifying bacteria are non-fermentative, the initial production of denitrification proteome depends on energy from aerobic respiration. Thus, if a cell fails to synthesise a minimum of denitrification proteome before O2 is completely exhausted, it will be unable to produce it later due to energy-limitation. Such entrapment in anoxia is recently claimed to be a major phenomenon in batch cultures of the model organism Paracoccus denitrificans on the basis of measured e(-)-flow rates to O2 and NOx. Here we constructed a dynamic model and explicitly simulated actual kinetics of recruitment of the cells to denitrification to directly and more accurately estimate the recruited fraction (Fden). Transcription of nirS is pivotal for denitrification, for it triggers a cascade of events leading to the synthesis of a full-fledged denitrification proteome. The model is based on the hypothesis that nirS has a low probability (rden, h(-1)) of initial transcription, but once initiated, the transcription is greatly enhanced through positive feedback by NO, resulting in the recruitment of the transcribing cell to denitrification. We assume that the recruitment is initiated as [O2] falls below a critical threshold and terminates (assuming energy-limitation) as [O2] exhausts. With rden = 0.005 h(-1), the model robustly simulates observed denitrification kinetics for a range of culture conditions. The resulting Fden (fraction of the cells recruited to denitrification) falls within 0.038-0.161. In contrast, if the recruitment of the entire population is assumed, the simulated denitrification kinetics deviate grossly from those observed. The phenomenon can be understood as a 'bet-hedging strategy': switching to denitrification is a gain if anoxic spell lasts long but is a waste of energy if anoxia turns out to be a 'false alarm'.

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Simulations of the treatments with 1 vol.%  using  = 0.0052 h−1.The figure compares the measured and simulated O2 depletion (mol vial−1) and N2 accumulation (molN vial−1) for the treatments with 1 vol.% O2 in the headspace () at the time of inoculation; separate plots are shown for each initial concentration of  (0.2, 1, and 2 mM). At each sampling time, the simulated O2 is visibly reduced; that is because sampling implies 3.4% dilution of the headspace (with He). This contrasts with the simulations of the treatments with low O2 (Fig. 7), where the leakage of O2 into the system is more dominant.
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pcbi-1003933-g008: Simulations of the treatments with 1 vol.% using  = 0.0052 h−1.The figure compares the measured and simulated O2 depletion (mol vial−1) and N2 accumulation (molN vial−1) for the treatments with 1 vol.% O2 in the headspace () at the time of inoculation; separate plots are shown for each initial concentration of (0.2, 1, and 2 mM). At each sampling time, the simulated O2 is visibly reduced; that is because sampling implies 3.4% dilution of the headspace (with He). This contrasts with the simulations of the treatments with low O2 (Fig. 7), where the leakage of O2 into the system is more dominant.

Mentions: To find a more adequate value, was calibrated to produce the best possible match between the simulated and measured N2 through optimisation. (The optimisation was carried out in Vensim DSS 6.2 Double Precision, http://vensim.com/). Table 4 presents the optimal for each treatment; no consistent effect of initial [O2] and [] was found on the optimal results. The average for all the treatments = 0.0052, which appears to give reasonable fit between the simulated and measured N2 (See Figs. 7, 8, and 9). This indicates that the simulations with  = 0.0052 should provide a reasonable approximation of (the fraction recruited to denitrification) during the actual experiment.


Low probability of initiating nirS transcription explains observed gas kinetics and growth of bacteria switching from aerobic respiration to denitrification.

Hassan J, Bergaust LL, Wheat ID, Bakken LR - PLoS Comput. Biol. (2014)

Simulations of the treatments with 1 vol.%  using  = 0.0052 h−1.The figure compares the measured and simulated O2 depletion (mol vial−1) and N2 accumulation (molN vial−1) for the treatments with 1 vol.% O2 in the headspace () at the time of inoculation; separate plots are shown for each initial concentration of  (0.2, 1, and 2 mM). At each sampling time, the simulated O2 is visibly reduced; that is because sampling implies 3.4% dilution of the headspace (with He). This contrasts with the simulations of the treatments with low O2 (Fig. 7), where the leakage of O2 into the system is more dominant.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4222654&req=5

pcbi-1003933-g008: Simulations of the treatments with 1 vol.% using  = 0.0052 h−1.The figure compares the measured and simulated O2 depletion (mol vial−1) and N2 accumulation (molN vial−1) for the treatments with 1 vol.% O2 in the headspace () at the time of inoculation; separate plots are shown for each initial concentration of (0.2, 1, and 2 mM). At each sampling time, the simulated O2 is visibly reduced; that is because sampling implies 3.4% dilution of the headspace (with He). This contrasts with the simulations of the treatments with low O2 (Fig. 7), where the leakage of O2 into the system is more dominant.
Mentions: To find a more adequate value, was calibrated to produce the best possible match between the simulated and measured N2 through optimisation. (The optimisation was carried out in Vensim DSS 6.2 Double Precision, http://vensim.com/). Table 4 presents the optimal for each treatment; no consistent effect of initial [O2] and [] was found on the optimal results. The average for all the treatments = 0.0052, which appears to give reasonable fit between the simulated and measured N2 (See Figs. 7, 8, and 9). This indicates that the simulations with  = 0.0052 should provide a reasonable approximation of (the fraction recruited to denitrification) during the actual experiment.

Bottom Line: The model is based on the hypothesis that nirS has a low probability (rden, h(-1)) of initial transcription, but once initiated, the transcription is greatly enhanced through positive feedback by NO, resulting in the recruitment of the transcribing cell to denitrification.The resulting Fden (fraction of the cells recruited to denitrification) falls within 0.038-0.161.In contrast, if the recruitment of the entire population is assumed, the simulated denitrification kinetics deviate grossly from those observed.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Sciences, Norwegian University of Life Sciences, Ås, Norway.

ABSTRACT
In response to impending anoxic conditions, denitrifying bacteria sustain respiratory metabolism by producing enzymes for reducing nitrogen oxyanions/-oxides (NOx) to N2 (denitrification). Since denitrifying bacteria are non-fermentative, the initial production of denitrification proteome depends on energy from aerobic respiration. Thus, if a cell fails to synthesise a minimum of denitrification proteome before O2 is completely exhausted, it will be unable to produce it later due to energy-limitation. Such entrapment in anoxia is recently claimed to be a major phenomenon in batch cultures of the model organism Paracoccus denitrificans on the basis of measured e(-)-flow rates to O2 and NOx. Here we constructed a dynamic model and explicitly simulated actual kinetics of recruitment of the cells to denitrification to directly and more accurately estimate the recruited fraction (Fden). Transcription of nirS is pivotal for denitrification, for it triggers a cascade of events leading to the synthesis of a full-fledged denitrification proteome. The model is based on the hypothesis that nirS has a low probability (rden, h(-1)) of initial transcription, but once initiated, the transcription is greatly enhanced through positive feedback by NO, resulting in the recruitment of the transcribing cell to denitrification. We assume that the recruitment is initiated as [O2] falls below a critical threshold and terminates (assuming energy-limitation) as [O2] exhausts. With rden = 0.005 h(-1), the model robustly simulates observed denitrification kinetics for a range of culture conditions. The resulting Fden (fraction of the cells recruited to denitrification) falls within 0.038-0.161. In contrast, if the recruitment of the entire population is assumed, the simulated denitrification kinetics deviate grossly from those observed. The phenomenon can be understood as a 'bet-hedging strategy': switching to denitrification is a gain if anoxic spell lasts long but is a waste of energy if anoxia turns out to be a 'false alarm'.

Show MeSH
Related in: MedlinePlus