Bio-photovoltaic devices (BPVs) harness photosynthetic organisms to produce bioelectricity in an eco-friendly way. However, their low energy efficiency is still a challenge. A comprehension of metabolic constraints can result in finding strategies for efficiency enhancement. This study presents a systemic approach based on metabolic modeling to design a regulatory defined medium, reducing the intracellular constraints in bioelectricity generation of Synechocystis sp. PCC6803 through the cellular metabolism alteration. The approach identified key reactions that played a critical role in improving electricity generation in Synechocystis sp. PCC6803 by comparing multiple optimal solutions of minimal and maximal NADH generation using two criteria. Regulatory compounds, which controlled the enzyme activity of the key reactions, were obtained from the BRENDA database. The selected compounds were subsequently added to the culture media, and their effect on bioelectricity generation was experimentally assessed. The power density curves for different culture media showed the BPV fed by Synechocystis sp. PCC6803 suspension in BG-11 supplemented with NH4Cl achieved the maximum power density of 148.27 mW m-2. This produced power density was more than 40.5-fold of what was obtained for the BPV fed with cyanobacterial suspension in BG-11. The effect of the activators on BPV performance was also evaluated by comparing their overpotential, maximum produced power density, and biofilm morphology under different conditions. These findings demonstrated the crucial role of cellular metabolism in improving bioelectricity generation in BPVs.
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No competing interests reported.
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Posted 19 Mar, 2021
On 05 Apr, 2021
Received 29 Mar, 2021
Received 29 Mar, 2021
Received 29 Mar, 2021
Received 29 Mar, 2021
On 28 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
Invitations sent on 25 Mar, 2021
On 25 Mar, 2021
On 16 Mar, 2021
On 16 Mar, 2021
On 13 Mar, 2021
Posted 19 Mar, 2021
On 05 Apr, 2021
Received 29 Mar, 2021
Received 29 Mar, 2021
Received 29 Mar, 2021
Received 29 Mar, 2021
On 28 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
On 25 Mar, 2021
Invitations sent on 25 Mar, 2021
On 25 Mar, 2021
On 16 Mar, 2021
On 16 Mar, 2021
On 13 Mar, 2021
Bio-photovoltaic devices (BPVs) harness photosynthetic organisms to produce bioelectricity in an eco-friendly way. However, their low energy efficiency is still a challenge. A comprehension of metabolic constraints can result in finding strategies for efficiency enhancement. This study presents a systemic approach based on metabolic modeling to design a regulatory defined medium, reducing the intracellular constraints in bioelectricity generation of Synechocystis sp. PCC6803 through the cellular metabolism alteration. The approach identified key reactions that played a critical role in improving electricity generation in Synechocystis sp. PCC6803 by comparing multiple optimal solutions of minimal and maximal NADH generation using two criteria. Regulatory compounds, which controlled the enzyme activity of the key reactions, were obtained from the BRENDA database. The selected compounds were subsequently added to the culture media, and their effect on bioelectricity generation was experimentally assessed. The power density curves for different culture media showed the BPV fed by Synechocystis sp. PCC6803 suspension in BG-11 supplemented with NH4Cl achieved the maximum power density of 148.27 mW m-2. This produced power density was more than 40.5-fold of what was obtained for the BPV fed with cyanobacterial suspension in BG-11. The effect of the activators on BPV performance was also evaluated by comparing their overpotential, maximum produced power density, and biofilm morphology under different conditions. These findings demonstrated the crucial role of cellular metabolism in improving bioelectricity generation in BPVs.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
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