It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Saturday, January 24, 2026
Sourdough starters reveal a recipe for predicting microbial species survival
Scientists use microbes in bread dough to test a simple way to understand how species live together in nature
“Evolution may well give one microbial species the upper hand, changing the flavor of the bread baked with a starter—or reshaping a person’s gut microbiota,” says Lawrence Uricchio, right, with Kasturi Lele in the lab.
People have long said that “bread is life.” Now, researchers at Tufts University are using the bubbling mixtures of flour and water known as sourdough starters to explore what shapes life at the microscopic level. Their findings, published in Ecology, demonstrate a simple way to predict how microbial species will live together, providing insights that could inform baking, food safety, and human health.
A major question in ecology is if it’s possible to predict which microbial species will thrive together based on how pairs of species interact, or if more complex group effects are needed to explain the patterns of coexistence of species seen in nature.
Some ecologists are skeptical of using “pairwise interactions” to predict real microbial communities because of previous studies, which often featured artificial combinations of species or lab conditions unlike their natural habitats.
By studying microbes isolated from real sourdough cultures, the Tufts team showed that a simple pair-based model could reliably forecast how up to nine species of microbes will interact.
The same model may help explain how microbial communities behave in food facilities, farms, hospitals, and even our own bodies. Realistic models could help scientists anticipate which species will persist and which will disappear—and foretell dangerous events such as foodborne illness outbreaks or the emergence of antibiotic-resistant bacteria.
Sourdough starters work by cultivating wild yeasts and lactic acid bacteria that are already present in flour and in the surrounding environment, including on our hands and kitchen items. By mixing flour and water, bakers create the conditions that let these microbes awaken and begin to multiply until these microbial populations grow large and active enough to make dough rise and to give sourdough its distinctive tang.
“Sourdough starters include a wide diversity of microbes overall,” says the study’s senior author, Lawrence Uricchio, Youniss Family Professor of Innovation and an assistant professor of biology at Tufts. “Yet within these starters, certain species consistently appear together in non-random patterns.” Most starters contain just a handful of bacterial species and one or two types of yeast.
Uricchio says this provided a perfect microcosm for testing if a simple model based on pairwise interactions could answer big-picture questions about how species will thrive in their natural environment. He compares pairwise interactions to predicting the outcome of a chess game when you know the strengths of each player.
But given that real ecosystems are much messier than a chess match, many scientists argue that natural ecosystems instead involve more complex interactions. Uricchio says these interactions are more like a game of rock, paper, scissors among three or more players. “With so many possible outcomes, it becomes much harder to predict who will win,” he says.
To test a pairwise interaction model and its applicability to circumstances with more than two microbial “players,” the Tufts researchers isolated microbes from sourdough starters and measured the growth of microbes either by themselves or in pairs.
They used these measurements to build the model and then compared its predictions to what actually happened when they let larger communities of up to nine species of yeast and bacteria grow together in lab dishes.
Their findings suggest that pairwise interactions alone indeed can reliably predict which microbes will coexist and how abundant they will be in some complex multi-species communities. Only two of the nine species behaved differently from the model’s predictions. And, critically, the researchers improved those predictions by adjusting their model to reflect sourdough’s real-world life cycle.
Learning from the Life Cycle of a Loaf
This cycle begins when a baker mixes flour and water and lets naturally occurring microbes in the environment begin to grow. Over the next week or two, the baker “feeds” the mixture—refreshing it daily with new flour and water—until the starter becomes active enough to make dough rise properly. For each new loaf, the baker uses a portion of the starter and then replenishes the remainder with more flour and water, maintaining the culture through regular feedings.
“There’s constant fluctuation, where the microbes awaken and grow, then their population size goes way down, and then it goes back up again,” says Uricchio. “When our parameters for pairwise interactions did not include this repeated reduction of the population followed by growth, they didn’t do quite as good a job.”
“We found that certain species naturally found in sourdough starters can outcompete others, but grow very slowly,” says Kasturi Lele, a doctoral student in biology at Tufts who co-led the study in the Uricchio Lab alongside Benjamin Wolfe, associate professor of biology. “When we accounted for the repeated reduction of the microbial population followed by growth that happens in actual starters, our model revealed that these particular species do not reproduce to the point where they actually drive out some of the other species.”
The researchers say this insight could help inform pairwise interaction models that better predict—and potentially prevent—microbial changes that threaten human, animal, or environmental health.
Many real-world microbial communities experience the same kind of boom-and-bust cycles seen in sourdough starters. For example, a course of antibiotics can sharply reduce microbes in a patient’s gut, creating a temporary opening for harmful bacteria normally kept in check by other beneficial microorganisms to surge. Similar population crashes can occur when food-processing equipment is sanitized, when hospital rooms are disinfected between patients, or when soil microbes are disrupted by pesticides.
Home bakers may be reassured to learn that the microbial communities in sourdough starters appear remarkably stable. “They seem to live quite a long time and to resist invasions by other microbes,” Uricchio says. “So perhaps it’s not surprising that some people keep these starters going for many years without them spoiling.”
The researchers are already taking the next step in understanding natural communities, with Lele working on models that can follow these microbes as they evolve. As genetic changes accumulate over time, a once stable microbial community could shift, says Uricchio. “Evolution may well give one microbial species the upper hand, changing the flavor of the bread baked with a starter or reshaping a person’s gut microbiota.”
“Sourdough starters include a wide diversity of microbes overall. Yet within these starters, certain species consistently appear together in non-random patterns,” says Lawrence Uricchio.
Polyploid genomes, formed through repeated whole-genome duplication and hybridization, underpin the evolution of many important crops, yet their internal structure often remains unresolved when ancestral species are unknown. This study presents a new genome-wide strategy to disentangle complex polyploid genomes by exploiting the evolutionary signatures of long terminal repeat retrotransposons. By systematically comparing similarity patterns of these elements across chromosomes, the research reconstructs subgenome architecture and infers the timing of major genome-merging events. Applied to the cultivated octoploid strawberry, the approach reveals a multi-step evolutionary history shaped by successive allopolyploidization events, offering a clearer picture of how complex plant genomes assemble and diversify over millions of years.
Whole-genome duplication has repeatedly reshaped plant genomes and driven evolutionary innovation, ecological adaptation, and crop diversification. In allopolyploid species, chromosomes originate from different ancestral genomes, forming multiple subgenomes that diverge and interact over time. Identifying these subgenomes is essential for understanding genome evolution, yet traditional methods rely heavily on known diploid progenitors, which are often extinct or unknown. Transposable elements, especially long terminal repeat retrotransposons, accumulate in lineage-specific patterns and retain molecular traces of past evolutionary events. However, robust frameworks for translating these patterns into reliable subgenome assignments have broad gaps. Based on these challenges, there is a need to develop new strategies to reconstruct polyploid genome evolution in the absence of known progenitor genomes.
Researchers from the U.S. Department of Agriculture and collaborating institutions reported a new bioinformatic framework in Horticulture Research, published (DOI: 10.1093/hr/uhaf132) on May 21, 2025, that reconstructs the evolutionary history of complex polyploid genomes. Using a serial similarity matrix approach based on long terminal repeat retrotransposons, the team reassessed the genome of cultivated octoploid strawberry (Fragaria × ananassa). Their analysis clarifies subgenome structure and identifies multiple ancient genome-merging events that shaped the modern strawberry, resolving long-standing debates about its evolutionary origin.
The researchers developed a method that tracks genome evolution through three conceptual phases: before progenitor species diverged, during their independent evolution, and after genome merger. Long terminal repeat retrotransposons proliferating during the divergence phase retain subgenome-specific signatures. By calculating similarity matrices of these elements across chromosomes and examining clustering patterns at different similarity thresholds, the team created a “serial similarity matrix” that captures evolutionary signals across time.
The method was first validated in well-characterized allopolyploid crops, including teff and cotton, where it correctly separated known subgenomes and distinguished pre- and post-polyploidization events. It was also tested on artificially constructed polyploid genomes, confirming its sensitivity to divergence time and transposon abundance.
Applied to octoploid strawberry, the approach identified four distinct subgenomes and revealed three sequential allopolyploidization events occurring between approximately 3.1–4.2, 1.9–3.1, and 0.8–1.9 million years ago. The analysis supports close relationships between two strawberry subgenomes and Fragaria vesca and Fragaria iinumae, while challenging earlier models that proposed additional diploid progenitors. The results indicate that extinct or unsampled relatives likely contributed to strawberry genome formation, highlighting the complexity of polyploid evolution.
“This work demonstrates how transposable elements can function as evolutionary time stamps embedded in plant genomes,” said one of the study's senior authors. “By focusing on when and where these elements expanded, we can reconstruct genome history even when direct ancestral references are missing. This method provides a powerful new lens for studying polyploid crops and moves beyond reliance on incomplete progenitor data, offering a more objective and reproducible framework for evolutionary genomics.”
Beyond strawberry, this approach has broad implications for crop genomics and plant breeding. Many agriculturally important species—including wheat, cotton, and sugarcane—are polyploids with complex evolutionary histories. Accurate subgenome resolution can improve gene annotation, trait mapping, and comparative genomics, ultimately supporting precision breeding and crop improvement. By enabling reconstruction of genome evolution without known ancestors, the serial similarity matrix method expands the toolkit for studying biodiversity, speciation, and adaptation. It also provides a transferable framework for investigating other complex polyploid organisms, helping bridge evolutionary biology and applied agricultural science.
This work was supported by the National Institute of Food and Agriculture (NIFA)—Specialty Crop Research Initiative (SCRI) Grant 2022-51181-38241 to Q.Y..
Horticulture Research is an open access journal of Nanjing Agricultural University and ranked number one in the Horticulture category of the Journal Citation Reports ™ from Clarivate, 2023. The journal is committed to publishing original research articles, reviews, perspectives, comments, correspondence articles and letters to the editor related to all major horticultural plants and disciplines, including biotechnology, breeding, cellular and molecular biology, evolution, genetics, inter-species interactions, physiology, and the origination and domestication of crops.
Corn is a colossal grain in the global food and feed chain, with the U.S. producing roughly 30% of the world's supply, or nearly 278 million metric tons in the 2024-25 growing season alone. But its journey from wild grass to staple crop began in central Mexico with teosinte (from the Nahuatl word "teocintli," meaning "sacred corn"). Over thousands of years, domestication and selective breeding transformed teosinte into the corn we enjoy at backyard barbecues today.
Now, researchers are returning to this wild crop relative to investigate traits that may have inadvertently been left behind, traits that influence how roots interact with soil microbes and cycle nitrogen.
In a study published in Science Advances, researchers compared modern corn with maize lines integrated with specific, inherited traits from teosinte. They found that these traits create distinct microbial environments in the rhizosphere – the narrow zone of soil around their roots – subtly affecting nitrogen cycling under field conditions.
"The key here is we can use wild genetic variation in our crops to make our modern agricultural system more sustainable," said Alonso Favela, lead author on the study and a plant microbial ecologist in the University of Arizona School of Plant Sciences.
It's an increasingly popular way of thinking about sustainability in agricultural, focused on reconnecting modern crops with traits tied to their evolutionary history. Researchers are already looking at wild crop relatives for characteristics such as heat tolerance and pest resistance. Favela's research team focuses underground, to ancestral traits that may conduct nitrogen efficiency.
"If we can reintroduce these traits, modern maize becomes more sustainable, potentially making corn production cheaper via lower nitrogen inputs and keeping more of that nitrogen in the field as opposed to the surrounding environment," he said.
What's happening below the surface
Nitrogen is essential for crop growth, yet plants take up only about half of nitrogen fertilizer applied to fields. The remainder is often transformed by soil microbes into forms that escape into the environment, whether through gases released into the atmosphere, such as nitrous oxide, or in soluble forms that can leach into nearby streams or groundwater systems.
These microbial processes occur in the rhizosphere, where plants' roots and microbes closely interact. Understanding how plants influence, or in some ways conduct, this microbial orchestra has become an important focus in both soil science and agricultural research.
"The microbes I study are called nitrifiers. They're really, really weird microbes, and they metabolize nitrogen, much like we metabolize sugars," Favela said. "They love agricultural fields because that's a huge area where nitrogen is being actively enriched."
While in nature, plants have evolved to compete with these "nitrogen-metabolizing" microbes for available nitrogen, commodified corn has been bred within nitrogen abundance and has largely lost this competitive edge.
"Modern maize doesn't really manage its nitrogen because there's so much nitrogen around, but teosinte is really good at competing with these microbes," Favela said. "By reintroducing some of its characteristics, we alter the relationship with these nitrifying microbes, so instead of a large fraction of the applied nitrogen going to these microbes that don't contribute to yield – it's going to the plant and staying in the fields."
To understand how teosinte's inherited root traits influence soil microbial communities, the research team conducted field experiments at the University of Illinois Crop Sciences Research and Education Center in Urbana. There, model maize (known by growers as B73), teosinte, maize-teosinte near isogenic lines, and their hybrid were grown in conventional agricultural plots, under uniform tillage and fertility conditions. Throughout the growing season, the researchers sampled rhizosphere soil and analyzed the activity and composition of nitrogen cycling microbes. Combing this data with the genetic panel allowed them to map the region in the teosinte genome that contributed to altered interactions in the soil.
The team identified key introgression regions were enriched in genes linked to secondary metabolism, suggesting that changes in plant chemistry played a role in reshaping how the rhizosphere microbiome functions. Follow-up work at the U of A confirmed the mechanism: chemical signals the roots released, known as exudates, were driving these microbiome changes.
What they found is that when maize carry these teosinte-derived traits, its roots release a different mix of metabolites, or chemical compounds, into the soil.
Looking to the past for future sustainability
Moving forward, Favela and the research team are exploring how these findings can be scaled up to commercial agriculture. One approach may be breeding specific teosinte-derived genes into elite corn varieties. In other words, giving modern maize a "memory boost" of its wild ancestry.
"Part of the study's results suggest that microbiome-shaping plant traits can be reintroduced into modern maize hybrids without reducing yield," Favela said. "It may even improve plant growth and nitrogen use under lower fertilizer conditions."
Another avenue may be developing soil amendments directly related to the natural compounds identified in root exudates, which could provide a targeted, organic method of limiting nitrogen losses.
Rewilding corn may sound like a step backward, but for Favela it's really a matter of biodiversity.
"There's a lot that may have been lost without even knowing. At the end of the day, this work is about having more diversity to work with," he said. "These wild varieties, or just wild plants, have characteristics that can still be used to improve our modern agricultural system."
With already thin profit margins and increasingly uncertain farm labor and other input costs, precision agriculture technology could improve New England’s small and medium-sized farms’ efficiency, productivity, and resilience. Unfortunately, factors such as up-front costs and validation of the technology’s accuracy in the region remain a barrier to adoption. A research team at UNH led by Benjamin Fraser, visiting assistant professor and director of the Basic and Applied Spatial Analysis Lab, has shown that unmanned aerial vehicles (UAVs), commonly used in precision agriculture, are able to provide effective surveillance of fields planted with corn, including brown-midrib (BMR) corn, an important variety for silage production.
BMR corn provides key silage advantages to dairy farmers, but it is more expensive to grow than many other varieties and is susceptible to disease late in the growing season. Monitoring BMR corn is therefore critical for the New Hampshire dairy industry, but it is also time- and labor-intensive, and field-level inspections often miss early signs of disease. A recent paper presents findings from eight weeks of UAV surveillance of New Hampshire corn fields that assessed its ability to analyze corn characteristics at field- and plot-scale levels. The paper shows that the UAV imagery can differentiate between varieties of corn and estimate crop yields with high accuracy.
“The findings demonstrate that low-cost, consumer available (or ‘off-the-shelf’) UAV sensors with limited spectral range are highly likely to produce accurate results and that the imagery can be used in several ways to inform future corn farming practices,” says Fraser.
Precision monitoring of corn
The applications for precision agriculture tools such as UAVs are varied, from monitoring for weeds and diseases to calculating yields to optimizing harvest timing and site selection, and they are used extensively on large farms in Midwest and Western states. Yet, at this time, usage of precision agriculture methods remains low, about 25%, on small Northeastern farms, largely because of the up-front investment required.
The paper adds to a growing body of research indicating that precision agriculture does provide important advantages in the long term. Overall, it promises to lower costs, particularly for labor, and deliver better outcomes for farmers, bolstering the sustainability of commercial agriculture on small farms in New Hampshire and throughout New England.
The paper, published in Agricultural Research, provides a case study for the use of precision monitoring of corn to collect field- and plot-specific data. The experiment was conducted on UNH agricultural fields planted with brown-midrib (BMR) and non-brown-midrib (non-BMR) varieties. BMR corn has been in use and studied for a century, is easily digested by dairy cows, and can improve milk production. However, BMR corn is susceptible to disease risks and grows and develops quickly, requiring frequent monitoring.
The UAV imagery data was multispectral, meaning that it was acquired across multiple color bands. Using red edge and near infrared wavelengths and a machine learning classification of corn varieties, the researchers were able to distinguish the subtle differences between BMR and non-BMR corn by field with accuracies of up to 98.7%. Narrow-band red edge image data showed high potential for estimating corn yields.
“The team explored ways that UAV imagery could inform field-specific management practices to reduce crop damage and costs,” says Fraser. “It brought many areas of expertise, including Tom Beaudry, a certified crop advisor for dairy producers in New Hampshire, Vermont, and Massachusetts, Carl Majewski, a UNH extension specialist, and Peter Davis and Aaron Palmer, UNH farm managers.”
The team’s research mitigates risks for farmers looking to work with new remote crop monitoring technologies by demonstrating the accuracy and utility of UAV observations. UAVs provide farmers with an affordable, flexible tool for proactively monitoring plant pests and diseases and assessing leaf area and yield. Using the data for consistent, reliable modeling of crop health and yield also provides vital insight for food management and for improving production methods.
“Our team is planning to work with additional private farms in the upcoming field seasons,” concludes Fraser. “We’ll look to quantify direct causes and amounts of loss within corn fields using the lessons learned from this research.”
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The University of New Hampshire inspires innovation and transforms lives in our state, nation and world. More than 15,000 students from 50 states and 87 countries engage with an award-winning faculty in top-ranked programs in business, engineering, law, health and human services, liberal arts and the sciences across more than 200 programs of study. A Carnegie Classification R1 institution, UNH partners with NASA, NOAA, NSF, and NIH, and received over $250 million in competitive external funding in FY24 to further explore and define the frontiers of land, sea and space.
Journal
Agricultural Research
Method of Research
Experimental study
Subject of Research
Not applicable
Article Title
Use of Unmanned Aerial Vehicles in Precision Agriculture: An Exploration of Remotely Sensed Data and Methods for Monitoring Corn Varieties
Article Publication Date
16-Jan-2026
Breakthroughs for preventing pistachio hull split
UC Davis scientists offer insights into breakage, with potential benefits for fruit crops
When pistachio hulls split before the nuts are harvested, insects and fungi can get inside, damaging the nut, costing farmers money and contaminating the nuts. About 4% of the overall crop experiences hull split, but some cultivars can split as much as 40% under certain conditions.
Now, for the first time, scientists at the University of California, Davis, are seeking solutions for California’s $2-billion-a-year pistachio industry. New research reveals how the hull is built and how cell walls in certain layers break down, along with the genes and corresponding mechanisms that spark and control those changes.
Pectin, a component of cell walls, makes fruit skin strong in part by keeping cells hitched to each other. In pistachio hulls, the composition of pectin changes as the hull ripens, causing the cells to come unhitched. This leads to cracks and tears in the hull.
In the Journal of Experimental Botany, recent Ph.D. graduate Shuxiao “Susan” Zhang, a student in the lab of Department of Plant Sciences Professor Georgia Drakakaki, identified genes that control how cell walls change as the fruit ripens, leading to the hull breaking down. The research will help breeders select for traits that will make the hulls less vulnerable to tearing and cracking.
“This is the first time anyone has studied the pistachio hull at the anatomical and cellular level while also looking at gene expression and physiological data,” Drakakaki said. “Susan really got into the details of how the hull is built with different layers and how the cells in those layers are of different sizes. The layers respond differently to changes in pectin, and that causes the hull to split in different ways.”
Zhang built on the work of two more scientists in the department and their teams. Grey Monroe, an assistant professor, and Barbara Blanco-Ulate, an associate professor, assembled a reference genome of Pistacia vera ‘Kerman,’ the leading female pistachio cultivar in California. They also defined the stages of the nut’s growth and the characteristics at each stage. Their work was published last year.
A model for fruit split in a variety of crops
Over three years, the team took samples of pistachio hulls from trees in a commercial orchard near Fresno and at the Wolfskill Experimental Orchard, operated by UC Davis near Winters, Calif. They worked with the most common varieties grown in the state, including Kerman, Golden Hills and Lost Hills. They took samples from trees at different points late in the hulls’ development, stretching over several months.
Using special imaging tools and techniques, Zhang and her team measured hull thickness and cell size, and they counted hulls that were intact, tattered, cracked or both. They also measured how well cells in the hull were sticking to each other, and in each sample counted the cells that had come unhitched.
Then the team pulled out RNA from the samples to learn which genes were being expressed at different stages as the hull develops and breaks down. They found that key genes express differently as that process unfolds.
Since all hulls were intact at 91 days after flowering, Zhang and team reasoned that fruit ripening may be linked with hull split. So, the team also examined the genes – including those involved in pectin modification -- that change the cell wall as the fruit ripens. Researchers discovered that cells in the interior layer of the hull expand, while cells in the exterior layer tend to stay the same size. This, in combination with changes in the cell wall, led to different types of hull breakdown.
“This is one of the major novelty factors for our paper,” Zhang said. “Loads of people have looked at pectin in all kinds of fruits, but not many people have observed that, depending on which cell layer you’re in, the pectin, cell size and so on will change differently during ripening.”
The physics of forces operating within the cell layers and humidity also influence degradation of the hull, Zhang found.
Because pistachio hulls are the fruit of the tree, even though we eat the seed, the research has applications for many non-berry fruit crops, Zhang concluded.
The California Pistachio Board funded most of this research, with additional support from the United States Department of Agriculture’s National Institute of Food and Agriculture, the James Monroe McDonald Endowment and the University of California Agricultural and Natural Resources.
Pistachios were harvested at various points during the later stages of fruit ripening, then placed in a solution to preserve them for later examination.
Pistachios, with the greenish hull still on them, are placed on a dissecting microscope to observe the different layers of the hull.
Credit
Trina Kleist/UC Davis
Cells come unhitched from each other in this image of a pistachio hull where it has split. Look at about three o’clock in this photo where it’s violet; the cells look like they're all squished together. To get this image, scientist Shuxiao Zhang took advantage of the cells’ autoflourescence and used a Zeiss LSM980 microscope with 20x objectives.
The green signal shows that CKL2 interacts with a 14-3-3 protein at the membranes in root cells colonized by a fungus. The pink signal (in the cell nucleus) is a control to confirm that the cell is transformed.
The plant is Medicago truncatula, and the fungus is Rhizophagus irregularis.
For 450 million years, plants and soil fungi have been trading partners. The fungi weave through plant roots, delivering phosphorus and other soil minerals in exchange for sugars and fats produced by the plant through photosynthesis. This ancient collaboration supports roughly 80% of Earth's plant species—including corn, wheat, and other crops that feed billions of people.
Scientists have long understood that these partnerships matter for agriculture. What they haven't understood is exactly how plants and fungi coordinate at the molecular level to build and maintain their relationship.
Now, a team from the Boyce Thompson Institute (BTI), led by Professor Maria Harrison, has coupled two powerful tools that allow scientists to identify which proteins work together to make these partnerships function—and to verify those interactions in living plant roots, where the collaboration actually occurs.
The challenge
Proteins are molecular machines that carry out nearly every function in living cells. For plant-fungus partnerships to work, specific proteins must physically connect and cooperate. Identifying which proteins partner with which has been technically difficult because the specialized cells where plant-fungus exchanges occur are rare, making up only a tiny fraction of root tissue.
"We've known for years that certain proteins are essential for establishing these symbioses, but we couldn't see who they were working with," said Harrison. "These tools let us ask—and answer—those questions in the cells where the partnership actually happens."
Two new tools
Working as postdoctoral researchers in Harrison's lab, Sergey Ivanov, Lena Müller, and François Lefèvre combined and modified a complementary pair of approaches. First, they generated a library of plant and fungal proteins. These are used in a screening system in yeast cells, which tests the protein of interest for its connections with thousands of potential partners, with results read through DNA sequencing. Think of it as a high-throughput matchmaking service for proteins.
The second tool, which is an adaptation of a method used widely in biology, makes proteins glow only when they physically touch inside plant root cells. This fluorescence-based method confirms that partnerships identified in yeast actually occur in the right place in living plants—at the cellular membranous "trading floor" where nutrients change hands.
"The beauty of combining these two methods is that we can cast a wide net to find candidate partners, then test whether those interactions are happening in the right location," said Ivanov, lead author of the study. "That second step—verification in living roots in the correct cells and the correct space inside the cell—has been a bottleneck in the field."
Proof of concept
To demonstrate that their tools work, the team studied a protein called CKL2, which previous research had shown to be essential for plant-fungus partnerships. Without CKL2, the relationship fails to develop properly.
The screening revealed that CKL2's top partners belong to a family called 14-3-3 proteins—molecules known to connect other proteins and regulate important cellular processes. The fluorescence test confirmed these proteins interact at the periarbuscular membrane, the specialized boundary where plants and fungi exchange nutrients.
When researchers reduced 14-3-3 protein levels in plant cells, fungal colonization dropped by about 31%, suggesting that these proteins play a meaningful role in sustaining the partnership.
Agricultural implications
Understanding precisely how plants and fungi coordinate their partnership at the molecular level provides researchers and plant breeders with targets for developing crop varieties that form more effective symbioses. Crops that extract phosphorus and other nutrients more efficiently through fungal partnerships would require less synthetic fertilizer—cutting input costs for farmers while reducing fertilizer runoff.
The research team is making these resources available to the broader scientific community, providing other laboratories with tools to study additional proteins essential to this widespread and agriculturally important biological collaboration.
"We can now systematically identify which proteins control nutrient exchange and verify their interactions in living roots," said Harrison. In addition to improving nutrient uptake, these plant-fungi partnerships also help bolster plant resilience against disease and environmental stress.
The study was published in New Phytologist, and funding was provided by the US National Science Foundation and the TRIAD Foundation.
About the Boyce Thompson Institute (BTI) As an independent nonprofit research institute affiliated with Cornell University, our scientists are committed to advancing solutions for global food security, agricultural sustainability, and human health. Through groundbreaking research, transformative education, and rapid translation of discoveries into real-world applications, BTI bridges fundamental plant and molecular science with practical impact. Discovery inspired by plants. Learn more at BTIscience.org.
Yeast two-hybrid-sequencing and bifluorescence complementation resources for assessing protein–protein interactions in arbuscular mycorrhizal roots: CKL2 as a case study
A Genetic tug-of-war shapes the biosynthesis of bioactive saponins
Nanjing Agricultural University The Academy of Science
Triterpenoid saponins are key bioactive compounds responsible for the medicinal value of many plants, yet how plants regulate the balance between saponin production and sterol biosynthesis has remained unclear. This study identifies two closely related enzymes that compete for the same metabolic precursor but drive it toward distinct biochemical outcomes. By uncovering how these enzymes function, interact, and are differentially regulated, the research reveals a molecular mechanism that determines whether metabolic flux is directed toward pharmacologically valuable saponins or essential sterols. The findings provide a mechanistic framework for understanding saponin biosynthesis and offer new molecular targets for improving the quality and yield of medicinal plant products.
Triterpenoid saponins are widely valued for their diverse pharmacological activities and also play important defensive roles in plants. These compounds are synthesized through the cyclization of a common precursor, 2,3-oxidosqualene, a reaction catalyzed by the 2,3-oxidosqualene cyclase (OSC) enzyme family. Different OSCs can channel this precursor into either saponin or sterol biosynthetic pathways, but the regulatory logic governing this metabolic branching has remained poorly understood. Previous studies mainly focused on enzyme structure or downstream modifications, while gene-level regulation received less attention. Based on these challenges, it is necessary to conduct in-depth research on how specific OSC genes and their regulators coordinate saponin biosynthesis.
Researchers from North China University of Science and Technology reported (DOI: 10.1093/hr/uhaf133) on May 21, 2025, in Horticulture Research a comprehensive molecular analysis of saponin biosynthesis in Eleutherococcus senticosus. The study identified two key OSC genes that determine whether metabolic flux is directed toward triterpenoid saponins or sterols. By combining genome-wide screening, biochemical assays, promoter analysis, and transcription factor studies, the research clarifies how enzyme competition and gene regulation together shape the accumulation of medicinally important saponins.
The researchers first identified ten OSC genes in the E. senticosus genome and narrowed them down to two functionally dominant candidates through expression profiling and metabolite correlation analysis. Functional assays confirmed that one enzyme acts exclusively as a β-amyrin synthase, directing metabolism toward oleanane-type saponins, while the other functions as a cycloartenol synthase that feeds sterol biosynthesis. Both enzymes localize primarily to the cytoplasm and compete for the same substrate, creating a metabolic trade-off.
Detailed structural analyses revealed distinct conserved amino acid triplets that define the catalytic specificity of each enzyme. Site-directed mutagenesis demonstrated that even single amino acid changes could dramatically alter product profiles or abolish enzyme activity. Beyond enzyme function, the study showed that gene expression is finely regulated by light quality, DNA methylation, and multiple transcription factors. Importantly, several transcription factors were found to exert opposite regulatory effects on the two competing genes, simultaneously promoting saponin synthesis while repressing sterol formation, or vice versa. This coordinated regulation provides a molecular explanation for how plants optimize secondary metabolite production.
According to the researchers, the most significant insight of this work is the discovery of a coordinated regulatory system that controls metabolic direction at both enzymatic and transcriptional levels. They note that identifying transcription factors capable of oppositely regulating two competing biosynthetic genes is particularly striking, as such dual control has rarely been documented in plants. This mechanism allows the plant to fine-tune resource allocation between growth-related sterols and defense- or health-related saponins, offering a powerful strategy for metabolic optimization.
The findings have important implications for medicinal plant improvement and metabolic engineering. By targeting specific OSC genes or their regulatory transcription factors, it may be possible to enhance the accumulation of valuable saponins without compromising plant viability. This strategy could support the development of higher-quality herbal medicines and functional plant products. More broadly, the study provides a conceptual model for controlling metabolic branch points in plant secondary metabolism. Such insights may be applied to other medicinal or industrial crops, enabling more precise manipulation of bioactive compound synthesis through genetic and environmental regulation.
This work was financially supported by the National Natural Science Foundation of China (32470398), the Central Guidance for Local Science and Technology Development Fund Projects (236Z2501G), and Natural Science Foundation of Hebei Province (H2020209033).
Horticulture Research is an open access journal of Nanjing Agricultural University and ranked number one in the Horticulture category of the Journal Citation Reports ™ from Clarivate, 2023. The journal is committed to publishing original research articles, reviews, perspectives, comments, correspondence articles and letters to the editor related to all major horticultural plants and disciplines, including biotechnology, breeding, cellular and molecular biology, evolution, genetics, inter-species interactions, physiology, and the origination and domestication of crops.
Soybean farmers around the world face a persistent and costly enemy hidden beneath the soil: soybean cyst nematode (SCN), a microscopic roundworm that attacks plant roots and drains yields. SCN is one of the most damaging pests affecting soybean production globally, resulting in significant losses every year.
Most soybean varieties grown today rely on a very narrow set of resistance genes that originated from just a few soybean lines. Over time, SCN has adapted to these defenses, making the resistant varieties less effective and leaving farmers with fewer tools to protect their yields.
To identify new sources of resistance, a research team co-led by Gunvant Patil and Vikas Devkar from Texas Tech University, along with Sushil Chhapekar and Henry Nguyen from the University of Missouri, analyzed the genomes of over 1,100 soybean accessions, including both cultivated and wild varieties. They carefully compared key regions associated with resistance, revealing several soybean accessions with unique genetic profiles that are not found in commonly used resistant varieties. Some of these plants showed strong or broad resistance to multiple SCN populations, meaning they can defend against a wider range of soybean cyst nematodes.
The study also revealed a surprising finding: Soybean lines with similar profiles of known resistance genes sometimes showed very different levels of protection against the nematode. This suggests that additional, previously unknown resistance genes are helping the plant defend against infection, thus opening doors to discovering entirely novel resistance genes and mechanisms.
One soybean line in particular, known as PI 602492, and a wild soybean line PI 522226 stood out for their consistent resistance to several SCN populations. Importantly, their resistance appears to function independently of the genes that dominate modern soybean breeding.
Speaking about these new findings, Gunvant Patil said, “What excites us most is the discovery of entirely new and underutilized genetic sources of soybean cyst nematode (SCN) resistance that work independently of the resistance used in most commercial soybean varieties today.” He added, “Identifying accessions that remain effective against multiple nematode populations offers a real opportunity to overcome resistance breakdown and build more durable protection for soybean crops worldwide.”
Beyond immediate applications, this research highlights the value of wild and exotic soybean relatives, which are often overlooked in breeding programs. These plants harbor genetic diversity that could help future-proof crops against evolving pests under conditions of increasing agricultural pressure and climate change.
Molecular Plant-Microbe Interactions® (MPMI) is a gold open access journal that publishes fundamental and advanced applied research on the genetics, genomics, molecular biology, biochemistry, and biophysics of pathological, symbiotic, and associative interactions of microbes, insects, nematodes, or parasitic plants with plants.
