Initiative

Predictive Phenomics

Predictive Phenomics will address the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems.

Predictive Phenomics

Illustration by Stephanie King

The Predictive Phenomics Initiative (PPI) is an internal investment at the Pacific Northwest National Laboratory (PNNL) that’s focused on unraveling the mysteries of molecular function in complex biological systems. 

How do microbes store carbon underground? What happens to proteins when they’re exposed to disease? How can we harness microbes to create new products in a bioeconomy?

These are big questions with intricate answers, and we begin answering them by identifying a phenotype.

Phenomenal Phenomes

Researchers are studying microbial communities.

A phenome is a collection of phenotypes—characteristics or traits of a system or organism. Within PPI, researchers are identifying desirable phenotypes, or functions, in a biological system (e.g., improving carbon storage in soil communities, fostering growth of good bacteria in a human gut) and developing sophisticated models to help us understand how those functions change when the environment is subjected to change. 

This approach requires a fine-tuned understanding across many scales of the cellular systems, including an organism’s proteins, metabolites, genes, and more. It also marks a move toward a "post-genomic world" where we can overcome the trial-and-error limitations of current genetic engineering efforts by precisely predicting the effects of genetic and environmental changes on an organism.

Taking the Initiative 

Now in its fourth year, PPI is an umbrella for 17 interwoven research projects aimed at scaling up production of high-value materials, chemicals, and fuels; developing resilient ecosystems; and innovating biosensing systems that can enhance national security and improve human health. 

The project teams include researchers with varied scientific disciplines, and they rely on PNNL's expertise in molecular measurements, bioscience, chemistry, engineering, data analytics, and modeling to realize the power of predictive phenomics.

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