Tuesday, July 01, 2025

 


Invention improves ‘gene gun,’ targets efficiency gains in plant research





Iowa State University
A better gene gun 

image: 

Iowa State engineers, left to right, Connor Thorpe and Shan Jiang helped invent the "Flow Guiding Barrel," which improves gene gun performance for the genetic modification of plants. Jiang is holding a Flow Guiding Barrel. A gene gun is on the left.

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Credit: Photo by Ryan Riley/Iowa State University College of Engineering





AMES, Iowa – Plant scientists have used a standard “gene gun” since 1988 to genetically modify crops for better yield, nutrition, pest resistance and other valuable traits.

 

That technology, which loads genetic materials on tiny particles and uses high pressure to shoot them into plant cells, has presented challenges to plant scientists, including inefficiency, inconsistency and even tissue damage caused by high-velocity particles.

 

But that was just the way these experiments worked, and plant scientists worked around the challenges.

 

“We didn’t even know we had a problem,” said Kan Wang, an Iowa State University agronomist and Charles F. Curtiss Distinguished Professor in Agriculture and Life Sciences.

 

Shan Jiang, an Iowa State associate professor of materials science and engineering, wondered if his research group could do something to improve that basic tool of plant research. Ultimately, he and the group determined plant scientists had been “shooting a bullet without a barrel” for 40 years.

 

A paper just published by the journal Nature Communications details the research team’s search for a solution, its subsequent findings and the invention that launched a startup company.

 

The project was more than solving a single engineering problem, though. Jiang, because of his research resume, really wanted to use his engineering approach to improve plant science and, potentially, human lives.

 

Post-doc lessons

After earning his doctorate from the University of Illinois Urbana-Champaign, Jiang went to work as a post-doctoral researcher in the Langer Lab at the Massachusetts Institute of Technology.

 

That’s the lab of Robert Langer, once called the “smartest man in Boston” by the Boston Globe and co-founder and, until last August, a board member for Moderna, Inc., a leader in the creation of mRNA medicine, including vaccines for COVID-19.

 

Jiang was one of 15 post-docs working on new ideas to deliver genetic materials for medical therapies.

 

“It was such difficult research,” he said.

 

But one outcome, even after research funding dried up, was the use of messenger RNA to produce proteins that could help the body fight off disease.

 

“That research had a profound impact in my life,” Jiang said. “When I arrived at Iowa State, I thought about what I wanted to do.”

 

But there was no research hospital and limited opportunities for medical research.

 

He looked around in the scientific literature and read about delivering DNA into plant cells to introduce or boost particular traits, including high crop yields, resistance to insects or tolerance of heat.

 

He picked up the phone and made a cold call.

 

Wang answered and was surprised to be talking to a materials engineer but was interested enough to schedule a lunch and talk about the challenges of plant science research, particularly the challenge of delivering genetic materials through a plant’s tough cell walls.

 

“It was such an overlooked area,” Jiang said. “Very few materials scientists were working on plant cell delivery. Agriculture is always overlooked – people want to cure cancer.”

 

From losing patience to a shock discovery

The decades-old “gene gun” used by plant scientists for what’s known as “biolistic” delivery of genetic information works by coating gold or tungsten microparticles, just a few millionths of a meter in size, with genetic material and then shooting particle and cargo into plant cells.

 

Some of those cells survive the particle bombardment, take up the introduced DNA and express the corresponding traits. Whole plants can then be grown from the transformed cells.

 

“However, biolistic delivery faces notable challenges with efficiency, consistency, and tissue damage caused by high-velocity microprojectiles, which hinder regeneration and transformation,” Jiang and co-authors wrote in their paper about the project (see team and paper details below). “Additionally, it often leads to fragmented and multiple transgene insertions in the genome, resulting in unpredictable gene expression.”

 

Jiang and his research collaborators began looking for solutions – “We tried to minimize the error bar,” he said.

 

The researchers tried everything they could think of, but Jiang said they made little progress. After four years, it was time to reconsider the time and effort spent on the project.

 

“We were losing hope and patience,” Jiang said.

 

In one last push for a solution, the research team ran computational fluid dynamics models of gene gun particle flows and discovered a bottleneck within an internal barrel. It seemed too narrow and restrictive, leading to particle loss, disrupted flow, decreased pressures, slower speeds, and uneven distribution at the target cells.

 

“These findings pinpoint critical limitations in the gene gun design and led us to hypothesize that engineering the flow dynamics within the gene gun could significantly improve its efficiency and consistency,” Jiang and his collaborators wrote.

 

To do that, the researchers designed a new internal barrel for the gene gun – they call it a “Flow Guiding Barrel” – and Connor Thorpe, a doctoral student and 3D-printing hobbyist, printed one for testing.

 

“It improved performance by 50%, then two, three, five, ten, twenty times,” Jiang said. “I was very shocked, to be honest with you.”

 

Easier plant transformations

The computer modeling shows a conventional gene gun directs about 21% of loaded particles toward its plant cell targets while a gene gun modified with the Flow Guiding Barrel delivers nearly 100%.

 

Subsequent tests by plant scientists found, for example, a 22-fold increase in transient transfection efficiency in tests with onions, a 17-fold improvement in viral infection efficiency in maize seedlings and double the efficiency of experiments using CRISPR genome editing tools in wheat.

 

“No previous device has achieved such improvements, offering substantial potential for advancing genotype independent transformation and genome editing for plants,” paper co-authors wrote.

 

Wang, the Iowa State plant scientist originally approached by Jiang, noted laboratory “improvements of 10-fold and sometimes 20-fold. We’re able to work far more efficiently.”

 

Yiping Qi, a professor of plant science and landscape architecture at the University of Maryland and a project collaborator, said the Flow Guiding Barrel “will make plant transformation and genome editing easier with improved efficiency.”

 

In one test, for example, he said the Flow Guiding Barrel allowed CRISPR reagents to penetrate deeper into the shoot apical meristem of bread wheat, the part of the plant where cell and leaf production occur.

 

“This translated to the higher efficiency of heritable genome editing in the next generation of wheat,” Qi said. “While this demonstration was done in wheat, one can envision such improvement can also benefit other crops, like barley, sorghum, etc.”

 

Support for research and development of the Flow Guiding Barrel came from Iowa State sources, including the Digital and Precision Agriculture Research and Innovation Platform; The Agriculture and Food Research Initiative of the U.S. Department of Agriculture’s National Institute of Food and Agriculture; the National Science Foundation; and the Department of Energy.

 

A startup for plant science

The Flow Guiding Barrel worked so well, Jiang; Thorpe; Wang; Kyle Miller, a former doctoral student in Jiang’s lab; and Alan Eggenberger, an Iowa State research scientist in materials science and engineering; took steps to investigate the commercial potential of the invention. Jiang and Thorpe also enrolled in Iowa State’s startup programs and later co-founded a company with Jibing Lin, an Iowa State graduate and startup leader. The U.S. Department of Energy’s Small Business Technology Transfer program has supported the company’s development.

 

“This project would not be possible without close collaboration with plant biologists,” Jiang said. “We believe the best way to give back is to make our tools commercially available so they can be broadly used in the plant science community.”

 

The Iowa State University Research Foundation filed for patent protection on the innovation and has licensed the commercial rights to the co-founders’ company, Hermes Biomaterials Inc. The company is based at the Iowa State University Research Park and is manufacturing its products in Iowa. The company continues its customer discovery work based on the National Science Foundation’s Innovation Corps program and has started selling products.

 

With efficiency gains of 10- and 20-fold, Jiang said the Flow Guiding Barrel could save plant scientists and agriculture companies millions of dollars in time and plant or product turnaround.

 

“This is a small device, and it seems overly simple,” Jiang said. “But the benefits it can bring are invaluable. It enables the development of safer and more effective strategies to improve crops that can better withstand environmental changes, enhance nutritional content, and contribute to sustainable energy production.”

 

– 30 –

 

The research team

Iowa State University Materials Science and Engineering: Shan Jiang, Connor Thorpe, Alan Eggenberger, Ritinder Sandhu

Iowa State Agronomy and Crop Bioengineering Center: Kan Wang, Qing Ji, Keunsub Lee, Steven Whitham

Iowa State Plant Pathology, Entomology and Microbiology: Aline Chicowski, Weihui Xu

University of Maryland Plant Science and Landscape Architecture: Yiping Qi, Weifeng Luo

 

Read the paper

“Enhancing biolistic plant transformation and genome editing with a flow guiding barrel,” Nature Communications, July 1, 2025, https://doi.org/10.1038/s41467-025-60761-x

ACCELERATIONISM

Signs of rising planetary strain highlight need for accelerated climate targets




International Institute for Applied Systems Analysis



Earth’s carbon-climate system may be more fragile than widely thought, according to a new IIASA-led study that looks at the planet’s response to human pressures from a planetary perspective.

In their paper published in Science of the Total Environment, researchers from IIASA and Lviv Polytechnic National University in Ukraine, presented a novel approach to measure and understand human pressure on planet Earth. The researchers explored how carbon emissions can be translated into measures of “stress” and “strain” to derive new insights into how the planet is changing.

“Until now, the scientific community has mainly measured Earth’s condition in gigatons of carbon per year. That’s important, but it doesn’t show how Earth as a physical system responds to the growing pressure we’re putting on it,” explains lead author Matthias Jonas, a researcher in the IIASA Advancing Systems Analysis Program. “We wanted to see how the entire Earth system stretches and strains under that burden.”

One of their key findings is the quantification of “stress power”, which is the rate at which humans are adding energy per volume to Earth’s system. In 2021, this stress power reached between 12.8 and 15.5 pascals per year. While this pressure may sound small (it is similar to the gentle push of a light breeze), spread over the entire atmosphere, land, and oceans, it is enough to signal that Earth’s system might be pushed outside its natural balance. For comparison, both strain and stress power center around zero for a balanced Earth not exposed to human-induced global warming.

The researchers also analyzed changes over time in Earth’s “delay time”, which describes how quickly the planet’s carbon system reacts to stress and identified a turning point between 1925 and 1945, suggesting that Earth’s system began shifting its response to stress much earlier than previously believed.

“This early turning point was unexpected,” says Jonas. “It suggests that Earth’s land and oceans may have started changing from their usual patterns as early as the first half of the 20th century. After that, instead of working as they used to, these systems were increasingly overwhelmed by human activities and eventually stopped absorbing CO₂ as effectively.”

This could mean countries need to act sooner than planned to cut greenhouse gas emissions.

“Meeting future emissions targets is important, but we also need to pay attention to how quickly Earth is becoming more fragile,” Jonas says. “Even if we hit our targets, the weakening of Earth’s natural systems could still leave us facing major disruptions sooner than expected. Earth’s shift to earlier fragility isn’t captured in climate models yet, but it needs to be.”

The team emphasizes the need for further research to quantify this shift and include their stress-strain approach in global climate modeling. They hope that by expanding how scientists track Earth’s condition from counting carbon alone to understanding how the planet physically reacts under pressure, the world can better prepare for the challenges ahead.

Reference:
Jonas, M., Bun, R., Ryzha, I., & Å»ebrowski, P. (2025). Human-induced carbon stress power upon Earth: Integrated data set, rheological findings and consequences. Science of the Total Environment DOI: 10.1016/j.scitotenv.2025.179922

 

About IIASA:
The International Institute for Applied Systems Analysis (IIASA) is an international scientific institute that conducts research into the critical issues of global environmental, economic, technological, and social change that we face in the twenty-first century. Our findings provide valuable options to policymakers to shape the future of our changing world. IIASA is independent and funded by prestigious research funding agencies in Africa, the Americas, Asia, and Europe. www.iiasa.ac.at

 

Self-driving lab: AI and automated biology combine to improve enzymes



University of Illinois at Urbana-Champaign, News Bureau






CHAMPAIGN, Ill. — By combining artificial intelligence with automated robotics and synthetic biology, researchers at the University of Illinois Urbana-Champaign have dramatically improved performance of two important industrial enzymes — and created a user-friendly, fast process to improve many more.

Led by Huimin Zhao, a professor of chemical and biomolecular engineering at the U. of I., the team reported its findings in the journal Nature Communications.

 “Enzymes have been increasingly used in energy production, in therapeutics, even in consumer products like laundry detergent. But they are not as widely used as they could be, because they still have limitations. Our technology can help address those limitations efficiently,” said Zhao, who also is affiliated with the Carl R. Woese Institute for Genomic Biology at the U. of I.

Enzymes are proteins that carry out specific catalytic functions that drive many biological processes. Those seeking to harness enzymes to advance medicine, technology, energy or sustainability often run into roadblocks involving an enzyme’s efficiency or its ability to single out a desired target amidst a complex chemical environment, Zhao said.

“Improving protein function, particularly enzyme function, is challenging because we don’t know exactly what kinds of mutations we should introduce — and it’s usually not just a single mutation; it’s a lot of synergistic mutations,” Zhao said. “With our model of integrating AI and automated synthetic biology, we offer an efficient way to solve that problem.”

Zhao’s group previously reported an AI model to predict an enzyme’s function based on its sequence. In the new paper, the researchers take their AI a step farther: predicting what changes to a known protein would improve its function.

“In a typically sized enzyme, the possible number of variations is larger than the number of atoms in the universe,” said Nilmani Singh, the co-first author of the paper. “So we use the AI method to help us create a relatively small library of potentially useful variant combinations, instead of randomly searching the whole protein sequence.”

However, training and improving an AI model is more than just code; it requires a lot of input, data and feedback. So the Illinois team coupled their AI models with the automated capabilities offered by the iBioFoundry, a center at the U. of I. dedicated to quick, user-friendly engineering and testing of biological systems ranging from enzymes to whole cells. Zhao directs the iBioFoundry, which is supported by the National Science Foundation.  

In the new paper, the researchers lay out their process: First, they ask the AI tool how to improve a desired enzyme’s performance. The AI tool searches datasets of known enzyme structures and suggests sequence changes. The automated protein-building machines at the iBioFoundry produce the suggested enzymes, which are then rapidly tested to characterize their functions. The data from those tests are fed into another AI model, which uses the information to improve the next round of suggested protein designs.

“It’s a step toward a self-driving lab: a lab that designs its own proteins, makes the proteins, tests them and makes the next one,” said Stephan Lane, the manager of the iBioFoundry and co-first author. “The designing and learning is done by an AI algorithm, and the building and testing is done by robotics.”

Using this method, the team produced variants of two key industrial enzymes with substantially improved performance. One enzyme, added to animal feed to improve its nutritional content, increased its activity by 26 times. The other, a catalyst used in industrial chemical synthesis, had 16 times greater activity and 90 times greater substrate preference, meaning it was far less likely to grab molecules that were not its target.    

“We described two enzymes in the paper, but it’s truly a generalized approach. We only need a protein sequence and an assay,” Zhao said. “We want to try to apply it to as many enzymes as possible.”

Next, the researchers plan to continue improving their AI models and upgrade equipment for even faster, higher-throughput synthesis and testing. They also have developed a user interface, enabling the system to run with a simple typed query. Their aim is to offer their method as a service for other researchers seeking to improve enzymes and speed drug development and innovations in energy and technology.

“For the user interface, the motivation is to allow people with different backgrounds to use the tool,” said graduate student Tianhao Yu, a coauthor of the paper. “If an experimental scientist doesn’t know how to run Python programs, then they can use our interface to help them run the program. They just need to use English to describe their needs, and it will automatically run.”

The National Science Foundation and the U.S. Department of Energy supported this work.

Editor's note: To reach Huimin Zhao, email zhao5@illinois.edu.  
The paper “A generalized platform for artificial intelligence-powered autonomous enzyme engineering” is available online. DOI: 10.1038/s41467-025-61209-y

 

Supportive housing offers high-impact, cost-effective response to homelessness and opioid use





Stanford University





Homelessness and opioid use disorder are two widespread public health problems in the United States. Providing housing and supportive services, without requiring drug treatment, is a surprisingly cost-effective approach to helping unhoused people with opioid use disorder, Stanford researchers found in a new study in JAMA Network Open

Worsened by the increasing prevalence of dangerous substances like fentanyl, overdoses are the leading cause of death among unhoused people. “If you’re living on the streets, you’re not going to be successfully treated for your opioid use disorder or for your other health conditions,” said senior author Margaret Brandeau, the Coleman F. Fung professor of engineering in the School of Engineering and a professor of health policy, by courtesy, in the Freeman Spogli Institute for International Studiesand the Stanford School of Medicine. Building on that fact, she wanted to study the impact of providing housing for this population.

Brandeau and her then-graduate student Isabelle Rao, now an assistant professor in industrial engineering at the University of Toronto, focused on the “housing first” approach in their study. This is one of the two general schools of thought in providing housing for people with substance use problems. The other, called “treatment first,” requires that individuals seek treatment before receiving housing. But that policy has faced challenges, said Brandeau. “It’s really, really hard for people on the street to get into treatment and to stay in treatment,” she said. “The treatment-first approach has not been particularly helpful in many populations.” 

Simulating supportive housing 

To study the impacts of a “housing first” intervention, Rao and Brandeau built a mathematical model simulating the treatment and health outcomes for 1,000 unhoused people with opioid use disorder. In the “status quo” model output, these individuals remained unhoused. In the “housing first” output, the same people were given housing, health care, and supportive services, with no requirement for sobriety or treatment. 

From previous research, the researchers already had a model of opioid treatment that reflected the dynamic process of recovery, complete with ups and downs as people go in and out of treatment. They built on that treatment model, adding in additional equations that estimated the health outcomes and treatment trajectory for unhoused people. 

Rao and Brandeau derived these equations from the research literature. Studies have found that people with stable housing are more likely to enter treatment for opioid use and have a higher likelihood of successful treatment. So, in the “housing first” model output, people were assigned a higher probability of recovery. 

The researchers also wanted to quantify the costs and benefits of the housing intervention compared to the status quo. Their analysis considered the costs of housing, supportive services such as a case worker, health care, and drug treatment. 

A cost-effective solution 

With all the variables inputted, Rao and Brandeau ran the model 25,000 times to capture a wide range of outcomes. The simulation found that, over five years, an average of 191 out of the 1,000 unhoused people with opioid use disorder died in the status quo scenario. In the supportive housing intervention, 140 people died over the same time period. 

The researchers also used the model to analyze lifetime outcomes for the 1,000 simulated individuals. First, they found out how many years people lived. Then they multiplied those years by a quality-of-life value between 0 and 1, where 1 means a person is in perfect health and 0 means they are dead. By multiplying the years they lived by the quality-of-life value, they calculated quality-adjusted life years. 

Compared to the status quo, the housing first intervention added 3.59 quality-adjusted life years. Essentially, that’s like giving each person an extra three and a half healthy years, on average. 

How much would these extra years cost? Adding up housing, treatment, and health care costs, the researchers found that the housing intervention would cost $96,000 per person over their lifetime. They divided this number by the quality-adjusted life years gained (3.59) to determine the increased cost for each of those years gained over the status quo: $26,200. 

In other words, each healthy year gained would cost those paying the bill an average of $26,200. By health economics standards, that extra cost is a great value for the health benefits it provides, said Brandeau. “These programs are highly cost-effective,” she said. “You’re investing money wisely to help improve outcomes for these marginalized individuals.” 

“Housed people have a higher likelihood of getting into treatment, which means that they have a higher likelihood of becoming abstinent, and that is going to save costs on the health care system,” said Rao. “You also save a bunch of lives, first from having fewer people who are addicted, and then also because people who are homeless have a much higher mortality rate.” Rao added that the model didn’t include the criminal justice costs associated with homelessness, which would have made the housing intervention even more cost-effective.

The researchers are planning to work with Santa Clara County officials to inform policies around homelessness. Rao is also planning to conduct outreach in Toronto, where homelessness and opioid use are also challenges. 

Brandeau adds that this research demonstrates how engineering know-how can be applied to solving societal problems. Sophisticated modelling is not just for designing efficient engines and sturdy structures. “Engineers are always trying to make things better,” she said. “We really want our work to make a difference. And homelessness is a significant humanitarian crisis in our country.”


For more information

Funding for the research came from the National Institute on Drug Abuse.

 

Environmental science is worth £3.3 billion to UK offshore wind



UK Public investment in environmental science has helped power the rise of the UK’s offshore wind energy sector, while protecting marine species and habitats.




UK Research and Innovation





Public investment in environmental science has helped power the rise of the UK’s offshore wind energy sector, while protecting marine species and habitats.

Offshore wind is an engine of growth for coastal regions and a key growth sector in the government’s industrial strategy.

As of the end of 2024 the UK had 45 operational offshore wind farms. These farms provide 17% of total UK electricity and support 32,000 jobs across the UK, predicted to grow to 100,000 by 2030.

23-fold return

A new study has found that long-term Natural Environment Research Council (NERC) funding delivered through our research centres has been an important factor in the development of the UK’s offshore wind industry.

It has delivered £3.3 billion in economic value (range: £1 billion to £5.5 billion) via research, data and modelling that is used by all of the sector’s main players. This represents a 23-fold return on NERC’s investment since 2000.

The study estimates that a further £3.6 billion in economic value could be attributed to the NERC funding in future (range: £1 billion to £6.1 billion). This is based on projected offshore wind farm development over the next 25 years.

Beyond economic gains, the investment also helps safeguard the UK’s £211 billion marine natural capital and supports national goals around growth, energy security and biodiversity.

Who benefits?

NERC’s investment delivers economic and environmental benefits to:

government departments: enhanced evidence base that informs policy, regulation and allocation of lease areas developers: reduced costs, delays and risks in securing consent, design, construction and operation investors: de-risking investment decisions statutory nature conservation bodies: enhanced evidence base for environmental impact assessment and identifying mitigation actions local communities: job creation, infrastructure investment UK public: enhanced energy security, lower carbon emissions, improved biodiversity protection Who was involved?

The study found that five NERC-funded research centres have become central to the offshore wind farm development process:

British Geological Survey: detailed mapping and understanding of seabed geology National Oceanography Centre: ocean and tidal models Plymouth Marine Laboratory: ocean front mapping from satellite data Sea Mammal Research Unit: long term seal data and models UK Centre for Ecology and Hydrology: long term seabird data and models The study was commissioned by NERC and undertaken by Human Economics and Howell Marine Consulting.

Supporting future growth

NERC continues to work with partners to provide insights to support the sustainable expansion of the UK’s offshore wind industry.

Recent investments include:

ecological consequences of offshore wind (ECOWind), a £9 million research programme joint with The Crown Estate, Crown Estate Scotland and the Department for Environment Food and Rural Affairs ecological effects of floating offshore wind (ECOFLOW), a £7 million research programme joint with The Crown Estate

The full report can be found here: https://www.ukri.org/wp-content/uploads/2025/06/NERC-230625-AssessingImpactNERCResearchFundingDevelopmentUKOffshoreWind-FinalSummaryReport.pdf