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RNA-Seq analysis and targeted mutagenesis for improved free fatty acid production in an engineered cyanobacterium.

Ruffing AM - Biotechnol Biofuels (2013)

Bottom Line: Recent studies investigating cyanobacterial FFA production have demonstrated the potential of this process, yet FFA production was also shown to have negative physiological effects on the cyanobacterial host, ultimately limiting high yields of FFAs.Gene knockout of two porins and the overexpression of ROS-degrading proteins and hypothetical proteins reduced the toxic effects of FFA production, allowing for improved growth, physiology, and FFA yields.Comparative transcriptomics, analyzing gene expression changes associated with FFA production and other stress conditions, identified additional key genes involved in cyanobacterial stress response.

View Article: PubMed Central - HTML - PubMed

Affiliation: Sandia National Laboratories, Department of Bioenergy and Defense Technologies, MS 1413, P,O, Box 5800, 87185-1413, Albuquerque, NM, USA. aruffin@sandia.gov.

ABSTRACT

Background: High-energy-density biofuels are typically derived from the fatty acid pathway, thus establishing free fatty acids (FFAs) as important fuel precursors. FFA production using photosynthetic microorganisms like cyanobacteria allows for direct conversion of carbon dioxide into fuel precursors. Recent studies investigating cyanobacterial FFA production have demonstrated the potential of this process, yet FFA production was also shown to have negative physiological effects on the cyanobacterial host, ultimately limiting high yields of FFAs.

Results: Cyanobacterial FFA production was shown to generate reactive oxygen species (ROS) and lead to increased cell membrane permeability. To identify genetic targets that may mitigate these toxic effects, RNA-seq analysis was used to investigate the host response of Synechococcus elongatus PCC 7942. Stress response, nitrogen metabolism, photosynthesis, and protein folding genes were up-regulated during FFA production while genes involved in carbon and hydrogen metabolisms were down-regulated. Select genes were targeted for mutagenesis to confirm their role in mitigating FFA toxicity. Gene knockout of two porins and the overexpression of ROS-degrading proteins and hypothetical proteins reduced the toxic effects of FFA production, allowing for improved growth, physiology, and FFA yields. Comparative transcriptomics, analyzing gene expression changes associated with FFA production and other stress conditions, identified additional key genes involved in cyanobacterial stress response.

Conclusions: A total of 15 gene targets were identified to reduce the toxic effects of FFA production. While single-gene targeted mutagenesis led to minor increases in FFA production, the combination of these targeted mutations may yield additional improvement, advancing the development of high-energy-density fuels derived from cyanobacteria.

No MeSH data available.


Related in: MedlinePlus

Photosynthetic yield measurements for the targeted mutants: (A) hypothetical protein overexpression mutants; (B) ROS-degrading protein overexpression mutants; (C) knockout mutants, including include one hypothetical protein mutant (Δ0444) and 4 putative transport proteins (Δ2175, Δ1224, Δ1464, and Δ1607). Data are averages of 3 biological replicates with error bars indicating the standard deviation of these measurements. An asterisk (*) above the data for day 7 indicates that difference between the control (SE02a) and mutant strain was determined to be statistically significant by ANOVA analysis (see Table S7 in Additional data file 3 for calculated p-values).
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Figure 3: Photosynthetic yield measurements for the targeted mutants: (A) hypothetical protein overexpression mutants; (B) ROS-degrading protein overexpression mutants; (C) knockout mutants, including include one hypothetical protein mutant (Δ0444) and 4 putative transport proteins (Δ2175, Δ1224, Δ1464, and Δ1607). Data are averages of 3 biological replicates with error bars indicating the standard deviation of these measurements. An asterisk (*) above the data for day 7 indicates that difference between the control (SE02a) and mutant strain was determined to be statistically significant by ANOVA analysis (see Table S7 in Additional data file 3 for calculated p-values).

Mentions: Photosynthetic yield measurements were analyzed to serve as an estimate of overall cell physiology. For the control strain SE02a, photosynthetic yield declined severely after induction at day 4, with photosynthetic yield measurements approaching zero at day 7 (Figure 3). Hypothetical protein overexpression mutants (S1655#2 and #5, S0122#4, and S0900#2), ROS-degrading protein overexpression mutants (S1214#1, S0801#1, and S1656#1) and a porin knockout mutant (Δ1464#2) all showed significantly elevated photosynthetic yields at day 7, ranging from 0.3 to 0.4 (Figure 3). Not surprisingly, these mutants also had increased relative cell concentrations and relative extracellular FFA concentrations, with the exception of Δ1464#2, which had increased relative extracellular FFA concentrations but no change in relative cell concentration (Figure 2). The general positive correlation between the three measured parameters of cell concentration, extracellular FFA concentration, and photosynthetic yield suggests that the corresponding genetic targets are involved in cellular defense mechanisms for FFA toxicity. While the ROS-degrading proteins are involved in well-known stress response mechanisms [10], the identification of 3 hypothetical proteins (Synpcc7942_1655, Synpcc7942_0122, and Synpcc7942_0900) and 2 porin proteins (Synpcc7942_1464 and Synpcc7942_1607) that counteract the toxic effects of FFA production provides new targets for improving cyanobacterial FFA production.


RNA-Seq analysis and targeted mutagenesis for improved free fatty acid production in an engineered cyanobacterium.

Ruffing AM - Biotechnol Biofuels (2013)

Photosynthetic yield measurements for the targeted mutants: (A) hypothetical protein overexpression mutants; (B) ROS-degrading protein overexpression mutants; (C) knockout mutants, including include one hypothetical protein mutant (Δ0444) and 4 putative transport proteins (Δ2175, Δ1224, Δ1464, and Δ1607). Data are averages of 3 biological replicates with error bars indicating the standard deviation of these measurements. An asterisk (*) above the data for day 7 indicates that difference between the control (SE02a) and mutant strain was determined to be statistically significant by ANOVA analysis (see Table S7 in Additional data file 3 for calculated p-values).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3750487&req=5

Figure 3: Photosynthetic yield measurements for the targeted mutants: (A) hypothetical protein overexpression mutants; (B) ROS-degrading protein overexpression mutants; (C) knockout mutants, including include one hypothetical protein mutant (Δ0444) and 4 putative transport proteins (Δ2175, Δ1224, Δ1464, and Δ1607). Data are averages of 3 biological replicates with error bars indicating the standard deviation of these measurements. An asterisk (*) above the data for day 7 indicates that difference between the control (SE02a) and mutant strain was determined to be statistically significant by ANOVA analysis (see Table S7 in Additional data file 3 for calculated p-values).
Mentions: Photosynthetic yield measurements were analyzed to serve as an estimate of overall cell physiology. For the control strain SE02a, photosynthetic yield declined severely after induction at day 4, with photosynthetic yield measurements approaching zero at day 7 (Figure 3). Hypothetical protein overexpression mutants (S1655#2 and #5, S0122#4, and S0900#2), ROS-degrading protein overexpression mutants (S1214#1, S0801#1, and S1656#1) and a porin knockout mutant (Δ1464#2) all showed significantly elevated photosynthetic yields at day 7, ranging from 0.3 to 0.4 (Figure 3). Not surprisingly, these mutants also had increased relative cell concentrations and relative extracellular FFA concentrations, with the exception of Δ1464#2, which had increased relative extracellular FFA concentrations but no change in relative cell concentration (Figure 2). The general positive correlation between the three measured parameters of cell concentration, extracellular FFA concentration, and photosynthetic yield suggests that the corresponding genetic targets are involved in cellular defense mechanisms for FFA toxicity. While the ROS-degrading proteins are involved in well-known stress response mechanisms [10], the identification of 3 hypothetical proteins (Synpcc7942_1655, Synpcc7942_0122, and Synpcc7942_0900) and 2 porin proteins (Synpcc7942_1464 and Synpcc7942_1607) that counteract the toxic effects of FFA production provides new targets for improving cyanobacterial FFA production.

Bottom Line: Recent studies investigating cyanobacterial FFA production have demonstrated the potential of this process, yet FFA production was also shown to have negative physiological effects on the cyanobacterial host, ultimately limiting high yields of FFAs.Gene knockout of two porins and the overexpression of ROS-degrading proteins and hypothetical proteins reduced the toxic effects of FFA production, allowing for improved growth, physiology, and FFA yields.Comparative transcriptomics, analyzing gene expression changes associated with FFA production and other stress conditions, identified additional key genes involved in cyanobacterial stress response.

View Article: PubMed Central - HTML - PubMed

Affiliation: Sandia National Laboratories, Department of Bioenergy and Defense Technologies, MS 1413, P,O, Box 5800, 87185-1413, Albuquerque, NM, USA. aruffin@sandia.gov.

ABSTRACT

Background: High-energy-density biofuels are typically derived from the fatty acid pathway, thus establishing free fatty acids (FFAs) as important fuel precursors. FFA production using photosynthetic microorganisms like cyanobacteria allows for direct conversion of carbon dioxide into fuel precursors. Recent studies investigating cyanobacterial FFA production have demonstrated the potential of this process, yet FFA production was also shown to have negative physiological effects on the cyanobacterial host, ultimately limiting high yields of FFAs.

Results: Cyanobacterial FFA production was shown to generate reactive oxygen species (ROS) and lead to increased cell membrane permeability. To identify genetic targets that may mitigate these toxic effects, RNA-seq analysis was used to investigate the host response of Synechococcus elongatus PCC 7942. Stress response, nitrogen metabolism, photosynthesis, and protein folding genes were up-regulated during FFA production while genes involved in carbon and hydrogen metabolisms were down-regulated. Select genes were targeted for mutagenesis to confirm their role in mitigating FFA toxicity. Gene knockout of two porins and the overexpression of ROS-degrading proteins and hypothetical proteins reduced the toxic effects of FFA production, allowing for improved growth, physiology, and FFA yields. Comparative transcriptomics, analyzing gene expression changes associated with FFA production and other stress conditions, identified additional key genes involved in cyanobacterial stress response.

Conclusions: A total of 15 gene targets were identified to reduce the toxic effects of FFA production. While single-gene targeted mutagenesis led to minor increases in FFA production, the combination of these targeted mutations may yield additional improvement, advancing the development of high-energy-density fuels derived from cyanobacteria.

No MeSH data available.


Related in: MedlinePlus