The concept of “legacy effects” refers to the capacity of soil microorganisms such as bacteria and fungi to “remember” past environmental stresses, influencing not only their own physiology but also the plants they inhabit. These ecological memories impact critical ecosystem functions, including carbon sequestration and nutrient cycling, but their precise mechanisms have remained elusive. Dr. Maggie Wagner, associate professor of ecology and evolutionary biology at the University of Kansas and co-author of the study, emphasized the transformative potential of understanding these effects. She noted that legacy effects might profoundly affect not only natural ecosystems but also agricultural productivity by modulating plant responses to drought and other stresses.

Wagner and her colleagues embarked on a comprehensive soil sampling campaign encompassing six distinct sites across Kansas. These locations spanned from the moist, lower-altitude eastern regions to the arid and elevated western High Plains, shaped by the rain shadow of the Rocky Mountains. This geographic gradient provided a natural laboratory to examine how differing climate histories could imprint on soil microbial communities and how these imprints influenced plant growth. The results underscored striking differences in microbial legacy effects shaped by the variable precipitation patterns and altitudes of these regions.

Central to this investigation was the novel experimental approach combining classical culturing methods with cutting-edge genetic and physiological analyses. The team grew plants in soils harboring distinct microbial communities with documented “memories” of either well-watered or drought conditions over five months. Remarkably, despite thousands of microbial generations occurring in this period, the drought memory persisted, influencing plant growth and stress tolerance. This finding highlights the robustness and ecological significance of microbial legacy effects in real-world soil environments.

The study focused primarily on two plant species: corn (Zea mays), a globally important crop, and big bluestem grass (Andropogon gerardii), a native prairie species. The researchers observed that native grasses exhibited much stronger positive responses to microbial communities from their home soils compared to corn grown in those same environments. This pattern likely reflects the co-evolutionary history between native plants and their resident microbial assemblages, a relationship that agricultural crops have not shared due to their domestication and spread from geographically distinct regions.

Digging deeper into the molecular dialogue between plants and their soil microbes, the team employed genetic analyses to identify key genes influenced by legacy effects. Of particular interest was the activation of the gene encoding nicotianamine synthase in plants grown with drought-conditioned microbial communities. Nicotianamine synthase catalyzes the production of nicotianamine, a molecule critical for iron acquisition and has been implicated in enhancing drought tolerance. This gene’s elevated expression under drought, but only in the presence of drought-conditioned microbes, reveals a fascinating tripartite interaction linking climate history, microbial memory, and plant stress physiology.

The implications of these findings extend far beyond ecology and basic science. For farmers and agricultural biotechnologists, this research offers a roadmap for harnessing beneficial soil microbes to bolster crop resilience under increasingly unpredictable climatic conditions. By identifying microbes with specific drought memories and understanding how they interact with plant genetics, it may be possible to develop microbial inoculants that enhance crop performance sustainably. This is particularly timely as microbial commercialization in agriculture is a multibillion-dollar industry with rapid growth and innovation.

Collaboration across disciplines and continents was integral to this study. Researchers from the University of Nottingham in the UK contributed expertise in microbial ecology, while geneticists and plant physiologists from multiple institutions, including the Universidad Nacional Autónoma de México and the Ministério da Agricultura e Ambiente in Cabo Verde, enriched the study’s scope. This interdisciplinary approach enabled the team to bridge gaps between microbiology, evolutionary biology, and plant sciences, driving a holistic understanding of legacy effects in complex soil ecosystems.

The study’s findings also provide a framework for future research avenues, such as discerning how widespread legacy effects are across other crops and ecosystems, and exploring the molecular underpinnings of microbial-plant interactions under various environmental conditions. More detailed investigations into how legacy effects influence microbial gene expression and community dynamics could yield new strategies for managing soil health and promoting sustainable agriculture globally.

Dr. Wagner stresses the importance of viewing soil microbes not merely as passive passengers in agriculture but as active agents shaped by evolutionary histories that influence plant ecology fundamental to food security. This nuanced perspective could inform policy and farming practices aiming to optimize microbial communities in soil through crop rotation, soil amendments, or targeted microbial treatments tailored to local climate legacies.

In essence, this research represents a paradigm shift in how we perceive soil ecosystems — as dynamic, historically informed entities rather than static environments. It highlights the potential to unlock nature’s hidden adaptations to address urgent challenges such as drought resilience and sustainable food production. By integrating molecular genetics, ecology, and practical agronomy, the University of Kansas-led team sets the stage for a new chapter in ecological and agricultural science optimized for the realities of climate change.

Subject of Research: Legacy effects of soil microbial communities on plant performance under drought conditions.

Article Title: Legacy Effects of Soil Microbes Influence Plant Gene Expression and Drought Tolerance in Kansas Soils.

News Publication Date: 30-Oct-2025

Web References:

• Original Article DOI: 10.1038/s41564-025-02148-8
• National Science Foundation Division of Integrative Organismal Systems: https://www.nsf.gov/bio/ios

Image Credits: Maggie Wagner

The study, carried out by KU’s School of Social Welfare, evaluated an intervention known as Resilience Alliance, tailored specifically for child welfare professionals. Spanning 12 weeks, this program equips participants with tools to recognize and mitigate secondary traumatic stress, develop resilience skills, and implement strategies to manage the emotional toll inherent in their work. Distinguishing itself from prior efforts, the intervention was delivered remotely and condensed into a shorter timeframe without sacrificing efficacy, offering a scalable professional support model for agencies.

Secondary traumatic stress emerges as a profound occupational hazard for those in child welfare roles. Workers are frequently exposed to narratives and scenarios involving child abuse, neglect, and family disruption, which can evoke trauma symptoms akin to post-traumatic stress disorder (PTSD). The University of Kansas team, led by researchers including Brennan Miller and Becci Akin, undertook this study against a backdrop of limited evidence identifying practical methods for reducing STS and its adverse consequences for staff retention and service quality.

The intervention’s delivery model grouped participants by analogous job roles, such as pairing caseworkers exclusively with fellow caseworkers. This stratification was strategically employed to foster peer support and nuanced discussions reflecting shared experiences within specific job functions. Moreover, the remote format addressed logistical challenges, mitigating barriers related to geographic dispersion and time constraints that often limit access to professional development and mental health initiatives.

Participants—175 child welfare professionals from across Kansas—were randomized into two groups: one receiving the standard Resilience Alliance curriculum and a second group who additionally engaged in loving-kindness meditation sessions. Assessment instruments administered pre- and post-intervention measured levels of secondary traumatic stress and resilience indicators. Results revealed a statistically significant decline in STS across all participants, underscoring the intervention’s efficacy. Interestingly, the addition of loving-kindness meditation did not produce measurable incremental benefits beyond the core program.

This research portrays resilience not as an inherent trait but as a trainable skill, an important conceptual departure. The Resilience Alliance intentionally cultivates participants’ abilities to reinterpret and regulate emotional responses to adverse work situations, shifting potentially debilitating emotions into productive coping mechanisms. This skill-based approach marks a paradigm shift in the mental health support landscape for child welfare workers, proposing that resilience can be consciously developed and strengthened.

Secondary traumatic stress adversely affects both mental and physical health, manifesting through disrupted sleep, anxiety, and heightened stress. The intervention’s comprehensive curriculum focused on building awareness around these symptoms and equipping participants with practical techniques for self-care and emotional regulation. By promoting psychological wellbeing, the program not only benefits the workforce but also enhances their capacity to deliver high-quality support to vulnerable clients.

The Kansas research team benefited from substantial funding—a six-year, $8 million grant from the U.S. Department of Health and Human Services, Administration for Children and Families—which facilitated rigorous evaluation of strategies to improve child welfare agency practices. This investment reflects the federal commitment to addressing workforce challenges that contribute to high turnover rates, which jeopardize continuity and effectiveness in child welfare services.

Beyond empirical validation, the Resilience Alliance’s remote and condensed delivery format offers operational efficiencies, reducing financial and time investments for agencies. Traditional interventions of this nature often extend over longer durations, imposing logistical burdens. The streamlined 12-week course demonstrated that scalability and accessibility could coexist with robust outcomes, suggesting a sustainable model for wide adoption across diverse jurisdictions.

Hosting the program as a remote intervention class also reflects an evolution in mental health and professional training modalities. The COVID-19 pandemic accelerated the adoption of telehealth and online platforms, and this study capitalizes on that momentum. Such flexibility is crucial, particularly in rural and under-resourced areas where physical attendance at training sessions is impractical.

An important aspect of the study’s significance is its implications for reducing workforce burnout and turnover. By mitigating secondary traumatic stress, child welfare agencies may retain experienced staff longer, preserve institutional knowledge, and enhance service quality to families and children. The ripple effect of workforce stability extends to improved client outcomes, as consistent case management fosters trust and more effective intervention.

Looking forward, the research team advocates for further investigation into Resilience Alliance’s applicability for supervisory and administrative personnel within child welfare systems. Leadership staff face distinctive stressors and influence organizational culture; equipping them with resilience skills could propagate benefits throughout the entire agency infrastructure. Additionally, continuous evaluation could refine the program and explore supplementary modalities that maximize impact.

Embedded within the original grant was a sustainability strategy designed to support ongoing training dissemination through the Children’s Alliance of Kansas. Complementing this, the Kansas Legislature has allocated funding to ensure the program’s continuation statewide. These measures exemplify how robust research can inform policy, enabling durable infrastructure for worker support and systemic improvements in child welfare.

In conclusion, the KU researchers’ findings emphasize the viability of targeted resilience training as an antidote to secondary traumatic stress among child welfare professionals. By reimagining resilience as a skill that can be cultivated rather than a fixed characteristic, this intervention charts an innovative path forward. It holds promise not only for enhancing the wellbeing and retention of child welfare staff but also for ultimately improving outcomes for vulnerable families dependent on their services.

Subject of Research: People

Article Title: Investigating the effects of resilience and meditation interventions on secondary traumatic stress among child welfare professionals: A randomized clinical trial

News Publication Date: 28-Jul-2025

Web References: https://psycnet.apa.org/doiLanding?doi=10.1037%2Ftrm0000609

Keywords: Health and medicine, Human health, Social sciences, Social research, Caregivers, Health equity, Home care

The machine learning that powers such websites will scan millions of images on the internet, analyze them and assemble facets of them into fresh, but fake, images.

Now, University of Kansas researchers are working to use a similar machine-learning process to build new proteins designed to detect water pollutants. With a new three-year, $1.5 million grant from the National Science Foundation’s Molecular Foundations for Biotechnology program, a KU researcher will use machine learning to create “deep-fake” membrane beta-barrel proteins — a class of naturally successful biosensors — designed to detect polluting metal ions in water.

“These beta barrels are super useful because they can bring things across membranes,” said principal investigator Joanna Slusky, associate professor of molecular biosciences at KU. “Barrels make good enzymes — there are so many different things that barrels can do.”

Previous research on the tube-like beta barrels has altered their binding properties for a variety of tasks. However, much of this work was arduous and completed by hand, usually resulting with minor variations of a limited number of scaffolds, or barrel structures.

“In this case, we’re using machine learning to generate large numbers of barrels,” Slusky said. “But, how about if we can both generate barrels and have them be useful? We asked ourselves, ‘What’s a biotechnology application of barrels?’ Well, one would be metal sensors that could perhaps detect metal pollutants.”

Slusky and her co-principal investigators, professors Rachel Kolodny and Margarita Osadchy of Haifa University in Israel (along with KU postdoctoral fellow Daniel Montezano), will develop a new machine-learning process that generates beta-barrels with scaffolds similar to those found in nature, but with different sequences.

“There’s a website called ‘This X Does Not Exist,’” Slusky said. “If you go to that site, you see all these AI-generated things and people don’t really exist. But a computer made an image, for instance, of a cat. But that’s not really a cat — a computer took a bunch of pictures of cats and said, ‘OK, we can just sort of generate as many cat pictures as you want now, because we figured out what is a cat.’ We need to make something real so we see it more like generating a recipe.

“The question is, how to make computers generate a recipe for proteins.”

Beta barrels are well-suited to advancement through machine learning because “natural proteins are sort of a small blip in the number of possible sequences.”

If a computer algorithm can learn the essence of what makes a protein a protein, Slusky said, it will avoid generating useless sequences.

“Most sequences would never actually be proteins— they wouldn’t have a particular fold,” she said. “They would just kind of bond with themselves in weird, nonpredictable ways over and over again. To be a protein, you need a sequence that makes one shape. When people tried to make random sequences, or even somewhat directed sequences, they found that only a very, very small percentage of them might actually be a protein.”

With machine learning creating new and viable sequences resulting in this common fold, Slusky and her colleagues hope to generate a beta-barrel especially well-suited to finding metal ions in water. This result of the work will be biosensors based on beta barrels that can identify pollutants like lead in waterways.

“If we make them the right size, this molecule will be ideal to put some particular metal in, and you can have the right substituents so that it would bind that metal,” Slusky said. “Because it’s in a membrane, it can give you some sort of conductance difference — there’s a difference between when it’s bound and when it’s not bound. If you’re able to do that, you could sense for different metals, and different concentrations of those metals. There are a lot of big steps we want to accomplish, but I’m hopeful and excited.”

The work also will help train undergraduate researchers in Slusky’s lab, as well as inform Slusky’s teaching at KU as well as outreach to high-school science students.