Model for acid-tolerant yeast helps guide industrial organic acid productionPosted on November 4, 2020
UNIVERSITY PARK, Pa. — Microbes and other microscopic organisms could serve as sustainable “factories” to create many types of industrial materials because they naturally convert nutrients such as sugars into byproducts. However, creating industrial amounts of organic acids from renewable resources poses a challenge, because not many organisms can grow in highly acidic environments. With the help of gene editing and computational modeling tools, a team of researchers explored one type of yeast that could survive in the harsh environment created by acidic products.
The team, which includes Penn State, the University of Illinois at Urbana-Champaign and Princeton University researchers, studied the yeast strain Issatchenkia orientalis, considered to be a “non-model” yeast because it has not been researched extensively. After reconstructing the yeast’s metabolism into a network model, the team examined its growth on different feedstock and subsequent byproducts. This strain was able to produce succinic acid, which is a precursor for industrial polymer production. The team reported its results in Metabolic Engineering Communications.
The researchers used a combination of genetic sequencing, gene editing, and sophisticated computational modeling to pinpoint which metabolic activities could be changed to maximize production of succinic acid without detriment to the yeast.
“The emergence of efficient CRISPR-Cas tools for making multiple genetic interventions in a single pass has emphasized the need for the development of predictive models and algorithms for suggesting which multiple genetic modifications to implement,” said Costas Maranas, the Donald B. Broughton Professor of chemical engineering and Institute for Computational and Data Sciences associate, Penn State, who co-led this study.
The computation-heavy approach, which ran on Penn State’s Roar supercomputer, was important in helping to refine the research direction, according to the researchers. The I. orientalis model covers 850 genes and contains 1,826 metabolic reactions, so identifying the right combination of genes and reactions to modify in order to produce succinic acid becomes a needle-in-a-haystack type of problem. Running thousands of computer simulations sifts through the hay and provides a much narrower set of experiments to test in a lab.
“With this approach, we can rank redesign hypotheses much faster than relying on a purely experimentalist approach,” said Patrick Suthers, postdoctoral scholar in chemical engineering, Penn State. “Our collaborators worked on developing genetic tools specifically for this organism, but even with their tools, it takes much longer to make modifications.”
The team’s analysis uses OptKnock, an optimization framework previously developed by the Maranas group, as part of the computational modeling.
Combining the computational techniques with traditional experiments not only informed the models with phenotypic measurements, but it also allowed the researchers to ensure their model was accurate in its predictions.
“One critical part of creating models is being able to say, yes, our predictions do make sense,” said Suthers. “In this case, our group focused on taking information from the genome in the organism, which our collaborators had sequenced. Then we take the genome and convert it into the functions that can take place in the cell.”
The result is a yeast model that can be used in any number of ways.
“Now that we have this comprehensive genome-scale model, we can look at things like the rates of organism growth and fluxes, and we can nail down key reactions in the metabolic system,” said Suthers. “We can also add in new genes to make new types of products.”
Collaborators on this research include Hoang Dinh and Siu Hung Joshua Chan, Penn State; Zia Fatma and Huimin Zhao, University of Illinois at Urbana-Champaign; and Yihui Shen and Joshua Rabinowitz, Princeton University.
The U.S. Department of Energy supported this work.
- Multi-institutional team to use AI to evaluate social, behavioral science claims
- Featured Researcher: Nick Tusay
- NSF invests in cyberinfrastructure institute to harness cosmic data
- Center for Immersive Experiences set to debut, serving researchers and students
- Distant Suns, Distant Worlds
- CyberScience Seminar: Researcher to discuss how AI can help people avoid adverse drug interactions
- AI could offer warnings about serious side effects of drug-drug interactions
- Taking RTKI drugs during radiotherapy may not aid survival, worsens side effects
- Cost-effective cloud research computing options now available for researchers
- Costs of natural disasters are increasing at the high end
- Model helps choose wind farm locations, predicts output
- Virus may jump species through ‘rock-and-roll’ motion with receptors
- Researchers seek to revolutionize catalyst design with machine learning
- Resilient Resumes team places third in Nittany AI Challenge
- ‘AI in Action’: Machine learning may help scientists explore deep sleep
- Clickbait Secrets Exposed! Humans and AI team up to improve clickbait detection
- Focusing computational power for more accurate, efficient weather forecasts
- How many Earth-like planets are around sun-like stars?
- Professor receives NSF grant to model cell disorder in heart
- SMH! Brains trained on e-devices may struggle to understand scientific info
- Whole genome sequencing may help officials get a handle on disease outbreaks
- New tool could reduce security analysts’ workloads by automating data triage
- Careful analysis of volcano’s plumbing system may give tips on pending eruptions
- Reducing farm greenhouse gas emissions may plant the seed for a cooler planet
- Using artificial intelligence to detect discrimination
- Four ways scholars say we can cut the chances of nasty satellite data surprises
- Game theory shows why stigmatization may not make sense in modern society
- Older adults can serve communities as engines of everyday innovation
- Pig-Pen effect: Mixing skin oil and ozone can produce a personal pollution cloud
- Researchers find genes that could help create more resilient chickens
- Despite dire predictions, levels of social support remain steady in the U.S.
- For many, friends and family, not doctors, serve as a gateway to opioid misuse
- New algorithm may help people store more pictures, share videos faster
- Head named for Ken and Mary Alice Lindquist Department of Nuclear Engineering
- Scientific evidence boosts action for activists, decreases action for scientists
- People explore options, then selectively represent good options to make difficult decisions
- Map reveals that lynching extended far beyond the deep South
- Gravitational forces in protoplanetary disks push super-Earths close to stars
- Supercomputer cluster donation helps turn high school class into climate science research lab
- Believing machines can out-do people may fuel acceptance of self-driving cars
- People more likely to trust machines than humans with their private info
- IBM donates system to Penn State to advance AI research
- ICS Seed Grants to power projects that use AI, machine learning for common good
- Penn State Berks team advances to MVP Phase of Nittany AI Challenge
- Creepy computers or people partners? Working to make AI that enhances humanity
- Sky is clearing for using AI to probe weather variability
- ‘AI will see you now’: Panel to discuss the AI revolution in health and medicine
- Privacy law scholars must address potential for nasty satellite data surprises
- Researchers take aim at hackers trying to attack high-value AI models
- Girls, economically disadvantaged less likely to get parental urging to study computers
- Seed grants awarded to projects using Twitter data
- Researchers find features that shape mechanical force during protein synthesis
- A peek at living room decor suggests how decorations vary around the world
- Interactive websites may cause antismoking messages to backfire
- Changing how government assesses risk may ease fallout from extreme financial events
- Predictability limit: Scientists find bounds of weather forecasting
- Faculty wins NSF CAREER Award to model structure of extreme weather events
- Mechanical force controls the speed of protein synthesis