Metabolic Engineering of Cyanobacteria Using Genome-Scale Modeling and Crispri

Photosynthetic cyanobacteria are attractive hosts for low-value fuels and chemicals as CO₂and sunlight are cheap and abundant feedstocks. However, the photoautotrophic metabolism has been difficult to manipulate for high specific productivities, due to a lack of synthetic-biology tools and systems-level analyses. Low specific productivities are particularly problematic if high-density culture is not possible due to light shading.

I will discuss my group’s approach and recent results on metabolic engineering of cyanobacteria for biofuel production[1, 2]. We use genome-scale modeling to find gene knockout strategies to enhance biofuel productivity from photoautotrophic metabolism. Two strategies can be applied for a range of biofuel pathways. One strategy exploits cofactor usage and another creates an imbalance in ATP and NADPH supply and demand. By considering expression data, we can reduce the number of require knockouts to achieve product-growth coupling[3]. To execute engineering strategies, we have implemented inducible, multiplex CRISPRi gene knockdown, which has not been used previously in cyanobacteria[4]. This tool will make it much easier to test metabolic engineering strategies as well as perform genetic logic in cyanobacteria. The cycle of prediction, execution, and analysis that we are following is expected to provide new cyanobacteria strains with specific productivities much higher than those reported so far. Finally, we are creating mutation libraries for cyanobacteria directed evolution and I will present our work on a microfluidics-based platform that can screen and sort cyanobacteria based on productivity and cell growth[5].

References

1. Anfelt J, Kaczmarzyk D, Shabestary K, Rockberg J, Renberg B, Uhlen M, Nielsen J, Hudson EP: Genetic and nutrient modulation of acetyl-CoA levels in Synechocystis for n-butanol production. Microb Cell Fact 2015, 14:1–12.

2. Anfelt J, Hallström B, Nielsen J, Uhlén M, Hudson EP: Using transcriptomics to improve butanol tolerance of Synechocystis sp. strain PCC 6803. Appl Environ Microbiol 2013, 79:7419–27.

3. Shabestary K and Hudson EP:Computational metabolic engineering strategies for growth-coupled biofuel production by Synechocystis. Manuscript

4. Yao L, Cengic I, Anfelt J, Hudson EP: Multiple gene repression in cyanobacteria using CRISPRi. ACS Synth Biol2015, 10.1021/acssynbio.5b00264

5. Hammar P, Angermayr S, Sjöström S, van der Meer J, Hellingwerf K, Hudson EP, Jönsson H: Single cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnol Biofuels 2015, 8:1–8.