The use of fossil fuels will bring extremely serious harm to the atmospheric environment, such as acid rain, smog, greenhouse effect and so on. The harmfulness of fossil fuels is obvious, so why do people continue to use them in industry and agriculture?
Largely for economic reasons. From government-led energy networks to the production of some textiles and other products in life. Many of the commodities involved are derived from fossil fuels, and if they are stopped or replaced altogether, they will pay a large economic cost.
Scientists imagine that if people can find a low-cost and efficient alternative to fossil fuels, it may be possible to improve the environmental pollution caused by fuel combustion.
Recently, biologists at the Pacific Northwest National Laboratory proposed that the preparation of enzyme glyconic acid from a high-value chemical may be used as an alternative to fossil fuel-derived products.
Figure | Data Integration and Supercomputing (Source: Pacific Northwest National Laboratory)
Data scientist Professor Neeraj Kumar and his team members use data integration and supercomputing to influence engineering changes in microbes, which in turn affect microbial metabolism. Based on a large number of previous experimental simulations, the team is expected to use the experience gained from previous samples to mass-produce itaconic acid.
Scientists have prepared fossil fuel alternatives
It is not easy for nature to find microorganisms that produce well-being, on the one hand, there are very few natural microorganisms that can meet the needs of different chemicals in the fields of chemicals, energy and medicines; on the other hand, the economic use value of natural microorganisms is relatively low.
Therefore, traditional bio-manufacturing faces many bottlenecks, and it is crucial to find sustainable and green ways to prepare alternative fuels and increase environmental and economic value.
Regardless of whether fossil fuels can be used up or human beings stop using fossil fuels due to environmental problems. Under the condition that fossil fuels become too expensive, the world economy and population growth raise the demand for energy supply to the limits that technology cannot meet.
Kumar took new inspiration from synthetic biology to try to prepare itaconic acid using microbes as inexpensive production materials.
Figure | different media for yarrow lipolytic yeast (Source: Pacific Northwest National Laboratory)
"We need to determine which genes in the itaconic acid production pathway can and can't, and we can easily estimate how many chemicals these yeasts can produce," Kumar said. The biggest challenge in this work is whether a balance between cellular health and biological production can be found. ”
With the continuous advancement and breakthrough of synthetic biology technology, the ability of cell factories to build has been greatly improved, which has made it possible to rapidly prepare various chemicals. Scientists can achieve this through the design of optimal synthetic pathways, the creation of synthetic pathways, the optimization of synthetic pathways, and the improvement of cell preparation performance.
Relying on synthetic biotechnology, scientists can prepare more high-efficiency cell factories, and typical chemical fuels such as olefins and the production of long-chain alcohols have emerged. The potential of itaconic acid in the building blocks of renewable chemistry can be replaced by fossil fuel-related products. In 2004, it was evaluated by the U.S. Department of Energy as one of the "highest value-added chemicals in biomass."
The computational predictions of the RNA sequencing data coincided with the experimental results
Itaconic acid is naturally produced by several fungi, and Northwestern National Laboratory scientist Dai Ziyu borrowed genes from other fungal organisms to enable Lipolytic Yersella to produce the chemical Itaconic acid.
Biologist Erin Bredeweg has studied improved yeast with different gene combinations. Later, Kumar approached her to collaborate, hoping to build a more effective well-being. At the time, Bradwig and her team had prepared a metabolic and proteomic profile of improved yeast and then passed the data to Kumar without reservation.
Based on a "design-build-test-learn" strategy, Kumar and his research assistant Andrew McNaughton used machine learning to examine this trait to see which non-essential genes could be removed from yeast and which useful genes could be further added to increase itaconic acid production.
Once they choose to "design" the organism with genes, they can immediately begin preparing the inivariant. Based on Kumar and McNaughton's predictions, they found that the computational predictions of the RNA sequencing data coincided with the experimental results after adding or removing certain genes from different versions of yeast created by Bradwig.
Bredwig said: "At the moment, this research is still in its early stages, but in the future it can show a lot of potential. Machine learning and scientists' reasoning can explain that thinking about how complex cellular systems such as yeast respond to individual genetic changes with new ideas is beyond the possibility of modeling them through metabolism alone. ”
Yeast and other microbes, while easily producing high-yield chemicals like ethanol, also face some challenges, which Kumar hopes to overcome by applying a system that combines machine learning with metabolic modeling and multi-omics datasets in actual production.
-End -
reference:
https://phys.org/news/2021-11-microbe-factories-sustainable-chemicals.html