Editorul AI deblochează potențialul microbian pentru substanțe chimice și combustibili regenerabili

In a groundbreaking move toward sustainable bioengineering, researchers at Oak Ridge National Laboratory (ORNL) have harnessed the power of artificial intelligence to develop an AI editor to revolutionize genome editing. The team utilized CRISPR Cas9, a powerful bioengineering tool, and combined it with an innovative AI editor to genetically alter microbes, paving the way for renewable chemicals and fuels.

This scientific breakthrough not only promises a greener future but also addresses the challenges of precision editing, preventing costly “typos” in an organism’s genetic code, as reported by Interesting Engineering.

How does the AI editor transform microbe genomes?

CRISPR, known as Clustered Regularly Interspaced Short Palindromic Repeats, has been a game-changer in modifying genetic codes. Yet, its effectiveness has been limited to mammalian cells and fruit flies, leaving microbes largely untouched. To bridge this gap, ORNL scientists developed an artificial intelligence model named iterative random forest. Trained on a dataset featuring 50,000 guide RNAs targeting the E. coli bacteria’s genome, the AI editor decodes molecular mechanisms underlying guide RNA efficiency.

Erica Prates, a computational systems biologist at ORNL, highlighted the significance of this approach, stating that the model played a crucial role in identifying clues about the molecular mechanisms behind the efficiency of guide RNAs. This process resulted in the generation of a comprehensive library of molecular information, providing valuable insights to enhance the effectiveness of CRISPR technology.

Unlike other AI editors, this program boasts an explainable design, mitigating the notorious black box problem associated with complex AI systems. The improved CRISPR Cas9 models enable precise linking of genes to physical traits, facilitating the modification of microbe genomes for enhanced bioenergy feedstock plants and bacterial fermentation of biomass. Carrie Eckert, the Synthetic Biology group leader at Oak Ridge National Laboratory, highlighted the advancements made through their research, expressing that the team has significantly enhanced their predictions of guide RNA. She further suggested that the implications of this research extend to the human scale, particularly in the realm of drug development.

Similar AI applications in medical research

The transformative potential of AI extends beyond bioenergy as companies explore innovative applications in medical research. Insilico Medicine, for instance, achieved a milestone by creating the world’s first fully AI-generated drug, INS018_055, to treat idiopathic pulmonary fibrosis. Leveraging its Pharma.AI system, the company identified virus targets, designed new drug compounds, and predicted clinical trial success rates, achieving unprecedented success in preclinical drug candidates.

LabGenius, another trailblazing company, utilized artificial intelligence to streamline antibody production. Their AI program significantly accelerates the process by exploring millions of antibody combinations quickly. The system learns from experimental results, surpassing human efficiency in designing and producing antibodies. This approach not only speeds up development but also enhances the likelihood of generating superior results.

The AI editor developed by Oak Ridge National Laboratory represents a significant leap forward in sustainable bioengineering. By enhancing the CRISPR Cas9 genome editing tools with an AI model, scientists have unlocked the potential to harness renewable energy from microorganisms. This breakthrough not only improves the efficiency of genome editing for bioenergy feedstock plants but also holds promise for advancing drug development. As ORNL researchers continue refining their tool with data from other lab experiments and microbial species, one cannot help but wonder: What other revolutionary applications will AI editors unveil in the realm of bioengineering and beyond?

Source: https://www.cryptopolitan.com/ai-editor-microbial-potential-renewable/