Destruxins are cyclic hexadepsipeptides, ring-shaped molecules assembled from amino acids and hydroxy acids, that more than forty known analogs call home. They are the chemical weapons that Metarhizium fungi deploy against insect hosts, disrupting immune cells and muscle function, and they also mediate the fungus’s interactions with plants. Beyond agriculture, destruxins have attracted attention in medical research for antiviral, antimicrobial, anticancer, antiangiogenic, and immunosuppressive properties. Yet the environmental triggers that switch their biosynthesis on or off have remained murky, with reports in the literature sometimes contradicting one another.

The research team, led by Pamela Vrabl at the University of Innsbruck’s Institute of Microbiology, hypothesized that light might act not as a simple trigger but as a modulator whose effects depend on the nutritional state of the culture. This idea rests on a growing body of evidence from other fungi, including Aspergillus nidulans and Penicillium species, where the same wavelength can either boost or suppress secondary metabolite production depending on the medium. To test this in Metarhizium, the team grew the production strain M. brunneum BIPESCO 5 in 4.5-liter stirred-tank bioreactors under two radically different diets: a nutrient-rich Sabouraud medium with 4 percent glucose, and a defined minimal medium in which nitrogen was the limiting nutrient.

Each medium was subjected to five illumination regimes: complete darkness, red light centered at 660 nanometers, green light at 528 nanometers, and blue light at 455 nanometers, all delivered at an intensity of 1.4 milliwatts per square centimeter, plus ultraviolet-A irradiation at 340 and 375 nanometers at 1.1 milliwatts per square centimeter. LED panels were mounted in front of the glass bioreactor vessels and shrouded in light-tight fabric to prevent cross-contamination between treatments. Irradiance was verified with calibrated photodiode power sensors and spectrometers, ensuring that differences in output could not be attributed to sloppy light measurement.

Across 21 independent bioreactor batch cultivations, each run for 90 hours with triplicate sampling at ten time points, the fungus followed the classic growth pattern of filamentous fungi under carbon excess: a lag phase, exponential growth terminated by depletion of the first essential nutrient, a prolonged deceleration phase, and finally stationary phase. In the nutrient-rich medium, phosphate ran out first; in the minimal medium, ammonium did. Destruxin production began only after exponential growth had ended, consistent with the general principle that secondary metabolites accumulate once primary growth stalls.

The first major result concerned nutrition alone. Cultures grown under nitrogen limitation produced roughly twice as much destruxin A and B in absolute terms as those in the rich medium—up to 42.9 milligrams per liter of destruxin A and 22.7 milligrams per liter of destruxin B in darkness, compared with 19.1 and 8.6 milligrams per liter respectively in the rich medium. When normalized to fungal dry mass, the gap widened dramatically: nitrogen-limited cultures produced up to five times more destruxin A and nearly seven times more destruxin B per gram of biomass than their well-fed counterparts. This aligns with the long-standing observation that reduced nitrogen availability tends to elevate secondary metabolite levels in fungi, although the authors note that the regulatory role of nitrogen in destruxin biosynthesis remains incompletely understood and that published reports on the topic vary considerably.

The second and more striking result was that light did matter—but its direction flipped with the diet. In the nutrient-rich medium, shorter wavelengths enhanced production: cultures exposed to ultraviolet-A, blue, or green light produced significantly more destruxin A than those kept in darkness or under red light, and biomass-normalized destruxin B also rose significantly with shorter wavelengths. In the nitrogen-limited medium, the same short-wavelength treatments had the opposite effect, significantly reducing destruxin A and B levels relative to darkness and red light. Red light, by contrast, behaved much like darkness in both media. Destruxin E, the third analog measured, showed no significant light response in either medium, though its concentrations fluctuated wildly between replicate cultures—possibly because the molecule hydrolyzes into a related form called destruxin E-diol.

Perhaps the most telling detail lay in the ratios. Although light exposure swung the absolute concentrations of destruxins A and B up and down, the ratio between the two remained essentially constant within each medium—roughly 70:30 in the rich medium and 60:40 under nitrogen limitation—regardless of wavelength. Statistical analysis confirmed strong positive correlations between the two metabolites across all light treatments, with Pearson correlation coefficients reaching 0.94 in the minimal medium and 0.97 when data from both media were pooled. This pattern suggests that the biosynthetic pathway for destruxins A and B, whose genes are known to be clustered in the Metarhizium genome, is governed primarily by nutritional status, while light modulates the total flux running through it rather than rerouting it toward one product or the other.

The findings place destruxin regulation alongside a broader phenomenon in fungal physiology: nutrient-dependent light responses, in which the same photic signal produces different metabolic outcomes depending on carbon and nitrogen availability. Similar crosstalk has been documented for sterigmatocystin production in Aspergillus nidulans, where changing the carbon source could reverse whether light or darkness favored toxin synthesis, and for the antibiotic xanthoepocin in Penicillium ochrochloron. For Metarhizium, whose ecological repertoire spans insect pathogen, soil saprotroph, and plant-associated endophyte, such flexibility makes evolutionary sense: the fungus encounters everything from absolute darkness underground to green-light-dominated leaf surfaces and full sun, and its chemistry presumably adapts accordingly.

For biotechnologists, the practical implications are immediate. Destruxin yields in fermentation could potentially be increased by co-optimizing nutrient formulation and illumination regime rather than treating light as an afterthought, and shifting the product profile toward a preferred analog might become feasible by tuning the two variables in concert. The authors caution that mechanistic and scale-up studies will be needed before such strategies reach the production floor, and they emphasize that rigorous standardization of both cultivation and light conditions—wavelength and intensity alike—will be essential for untangling the molecular machinery underneath. What the study establishes beyond doubt is that destruxin biosynthesis is not a simple on/off switch but a finely tuned adaptive system, one that listens to both the menu and the light before deciding what to make.

Subject of Research: Nutrient-dependent effects of light wavelength on destruxin biosynthesis in the entomopathogenic fungus Metarhizium brunneum

Article Title: Nutrient-dependent influence of red, green, blue, and UV-A light on the production of destruxin A, B, and E in Metarhizium brunneum bioreactor batch cultures

Article References: Schobert, J., Erckert, S. A., Schinagl, C. W., Schöbel, H., Strasser, H., & Vrabl, P. (2026). Nutrient-dependent influence of red, green, blue, and UV-A light on the production of destruxin A, B, and E in Metarhizium brunneum bioreactor batch cultures. Frontiers in Photobiology, 4, Article 1753405. https://doi.org/10.3389/fphbi.2026.1753405

Image Credits: AI Generated

DOI: 10.3389/fphbi.2026.1753405

Keywords: Metarhizium brunneum, destruxins, fungal photobiology, secondary metabolism, bioreactor cultivation, nitrogen limitation, light wavelength, entomopathogenic fungi, biological pest control, UV-A irradiation, biotechnology, fungal physiology

To capture sporulation in the act, the team followed time courses of P. infestans growing both on artificial media and on tomato leaves, comparing gene expression across the transition from vegetative growth to spore formation. The scale of the program was striking: more than 4,000 genes are up-regulated during sporulation, a substantial fraction of the pathogen’s genome pressed into service for a single developmental event. These genes are associated with signal transduction, cell structure remodeling, vesicle trafficking, metabolism, and flagellar assembly, all processes required to build a sporangium and, later, to allow its contents to germinate and swim toward a new host. The breadth of the program reflects the sheer complexity of the sporangium itself, a multicellular-scale structure that must be constructed, provisioned, and released under precise conditions.

One of the most consequential discoveries concerns the fate of the messenger RNAs produced during this developmental surge. Most of the sporulation-induced transcripts remain abundant in mature sporangia, meaning the spores are not merely passive packages of structural material but carry a rich cargo of regulatory and metabolic messages. This persistence suggests that the mRNAs synthesized as the sporangium forms are stored for later use, potentially priming the spore for germination the moment it encounters a hospitable environment. For a pathogen whose spores must survive dispersal through air and water before landing on a susceptible leaf, such pre-loading of the translational machinery could provide a decisive head start in the race to infect.

The environmental trigger at the heart of the process turned out to be nutritional. Through media manipulation and metabolomic studies, the researchers found that sporulation is initiated by nitrogen limitation, with the amino acid asparagine—and possibly other amino acids—playing the principal role in signaling that conditions are right for reproduction. This makes ecological sense: a colony exhausts local nutrients before committing to spore production, ensuring that the resulting spores disperse rather than competing with the parent colony for dwindling resources. The identification of asparagine as a key signal provides a concrete molecular handle on a process that has long been observed but poorly understood, and it hints at potential intervention strategies that could disrupt the starvation-sensing pathway and prevent spore formation altogether.

Light, by contrast, does not simply switch sporulation on or off. In P. infestans, illumination delays sporulation, and the new data indicate that light acts on a later regulatory step rather than at the entry point into the developmental program. Many of the sporulation-induced transcripts oscillate with a day/night cycle, rising and falling in rhythm with light, while others remain light-neutral, unaffected by illumination. Both blue and red wavelengths produce the light response, a spectral profile characteristic of cryptochromes, a class of flavoprotein photoreceptors well known in plants and fungi for transducing light information into transcriptional changes. The oscillating transcripts suggest that the pathogen times its spore production to coincide with favorable parts of the daily cycle, potentially releasing spores when humidity and temperature maximize survival.

The cryptochrome hypothesis was put to a direct test through gene silencing experiments. When the researchers silenced one of the pathogen’s cryptochrome genes, sporulation was abolished, demonstrating that this single photoreceptor is required for the process. This is a rare demonstration in oomycetes that a specific light sensor is essential for a major developmental transition, and it establishes the cryptochrome as a linchpin connecting the environmental world to the pathogen’s reproductive decisions. Because cryptochromes are conserved across many microbial eukaryotes, the finding may illuminate how other filamentous pathogens integrate light cues into their life cycles, and it marks the protein as an attractive target for chemical inhibitors designed to blind the pathogen at the critical moment of spore formation.

Humidity plays yet another role, and a subtly different one. Spore development in P. infestans requires high humidity, but when the researchers examined transcription under low-humidity conditions, they found only limited effects on the sporulation-associated gene program. This dissociation between the transcriptional program and the physical completion of development points to humidity acting at a late checkpoint: the genes are switched on and the developmental machinery is engaged regardless of moisture, but the final stages of spore maturation stall without sufficient atmospheric water. In practical terms, this means dry conditions can suppress the pathogen’s spread without preventing it from preparing to reproduce, a nuance that matters for forecasting models and for timing fungicide applications to the windows when spores can actually complete their development.

Perhaps the most evolutionarily revealing part of the study came from comparisons with P. capsici, a related species that, unlike P. infestans, actually requires light to sporulate. The comparative analysis yielded evidence of substantial rewiring of the transcriptional program between the two species, showing that even closely related pathogens with seemingly similar life cycles have evolved different regulatory logic connecting environmental signals to spore formation. The contrasting light responses within the genus correlate with ecological niche: P. infestans is primarily a leaf colonizer, exposed to the full daily light cycle on the plant surface, while P. capsici is a root colonizer, living in soil where light is scarce and its presence may serve as a cue that the pathogen has emerged into a dispersal-friendly environment. Evolution, in other words, has tuned the same basic developmental program to opposite environmental logic depending on where each species makes its living.

The implications of this work extend well beyond basic biology. Sporulation is the bottleneck through which every epidemic of late blight must pass, and each of the three environmental inputs characterized here—nitrogen status, light, and humidity—represents a potential point of vulnerability. Understanding that asparagine availability triggers the program, that a cryptochrome is required for its completion, and that humidity gates a late checkpoint gives researchers a framework for predicting when fields are at greatest risk and for designing control measures that target the pathogen’s sensory and regulatory apparatus rather than simply poisoning it. As Phytophthora species continue to devastate potatoes, tomatoes, and a widening range of crops worldwide, the ability to eavesdrop on the pathogen’s decision to reproduce may prove one of the most powerful tools yet added to the fight against an ancient and adaptable enemy.

Subject of Research: Transcriptional and environmental regulation of sporulation in Phytophthora pathogens

Article Title: Transcriptional programs controlling sporulation in Phytophthora respond to nutrition, humidity, and cryptochrome-mediated light signals

Article References: Vu, A. L., Harris, T. A., & Judelson, H. S. (2026). Transcriptional programs controlling sporulation in Phytophthora respond to nutrition, humidity, and cryptochrome-mediated light signals. PLOS Pathogens, 22(10), e1014705. https://doi.org/10.1371/journal.ppat.1014705

Image Credits: AI Generated

DOI: 10.1371/journal.ppat.1014705

Keywords: Phytophthora infestans, sporulation, cryptochrome, transcriptional regulation, nitrogen limitation, asparagine, humidity, light signaling, oomycete, plant pathology, gene silencing, PLOS Pathogens

The research, published in Environmental Earth Sciences, was led by Yong Li and Zhongyao Liang of Xiamen University together with colleagues at the Tianjin Municipal Engineering Design and Research Institute and the Nanjing Institute of Geography and Limnology. The team built a multi-scale interpretable machine-learning framework and applied it to nearly four years of daily water-quality monitoring at Shahu Lake, a shallow, 45-square-kilometre water body lying at 1,093 to 1,102 metres above sea level where the foothills of the Helan Mountains meet the alluvial plain of the Yellow River. Like many lakes in arid and semi-arid China, Shahu Lake experiences pronounced swings in its eutrophication status, driven by artificial water replenishment and a warming, variable climate.

At the heart of the study is a model built on the XGBoost algorithm, a gradient-boosted tree method prized for its efficiency with noisy, multivariate environmental data. The researchers fed the model daily measurements of water temperature, chemical oxygen demand measured by the manganese method, ammonia nitrogen, total phosphorus, total nitrogen, turbidity, and the nitrogen-to-phosphorus ratio, all drawn from the China National Environmental Monitoring Centre between November 2021 and August 2025. After screening out eighteen anomalous readings, just over one percent of the record, the team retained a complete set of 1,370 daily observations, splitting them eighty-twenty into training and independent testing sets. Hyperparameters were tuned with Bayesian optimization combined with five-fold cross-validation.

The resulting model performed remarkably well. It achieved a coefficient of determination of 0.889 on the training data and 0.810 on the unseen testing data, with root-mean-square errors of 3.78 and 5.13 micrograms per litre respectively and Kling-Gupta efficiencies above 0.81 in both cases. Those figures indicate strong predictive accuracy and, crucially, good generalisation, meaning the model had not simply memorised the training record but had learned relationships that hold for data it had never seen. Yet prediction alone was never the goal. The real innovation lies in how the researchers interrogated the model, using the TreeSHAP recursive algorithm, an exact method for attributing each prediction to individual input variables, to peel apart the drivers of chlorophyll-a, the standard proxy for phytoplankton biomass.

What makes the study distinctive is that the interpretation is deliberately multi-scale. Most previous applications of SHAP in aquatic science have averaged feature importance across an entire dataset, a global view that can mask drivers that matter only during particular seasons or events. Li and colleagues computed global importance across all 1,370 days, regional importance within the summer bloom window of July to September, and local importance for the ten most extreme chlorophyll-a events on record. At the regional scale they normalised SHAP values within each feature to remove scale differences, a methodological refinement designed to make season-specific comparisons meaningful.

The global picture largely confirms classical eutrophication theory. Water temperature emerged as the single most influential driver, with the model showing chlorophyll-a responses turning sharply positive as waters warm from about 15 to 24 degrees Celsius before plateauing at higher temperatures. Chemical oxygen demand, a proxy for organic matter and its mineralisation, ranked second, pointing to the role of internal nutrient recycling in shallow lakes, where decaying organic matter on the lakebed releases nitrogen and phosphorus back into the water column. Among nutrients, phosphorus consistently outweighed nitrogen in long-term importance, echoing the foundational whole-lake experiments of David Schindler and supporting the long-standing paradigm that phosphorus control is the backbone of lasting eutrophication management.

But the regional analysis revealed something the global view had concealed. During the July-to-September bloom period, the hierarchy of drivers shifted markedly. Nitrogen-related variables, particularly ammonia nitrogen and the nitrogen-to-phosphorus ratio, rose in importance, while the system effectively transitioned from chronic phosphorus limitation to transient nitrogen limitation under elevated thermal conditions. The response to water temperature peaked narrowly between 23 and 24 degrees Celsius, matching the optimal thermal niche for rapid cyanobacterial proliferation. The authors interpret this seasonal nitrogen stress not as an independent cause of blooms but as a consequence of them: as phosphorus fuels rapid growth, phytoplankton draw down available nitrogen until it becomes the immediate bottleneck, constraining bloom persistence and even influencing how much Microcystis biomass sinks out of the water column.

The local-scale analysis added a further layer of nuance. When the researchers examined the ten highest chlorophyll-a events individually, they found that each followed a distinct decision pathway through the model, even though the samples shared broadly similar environmental backgrounds. Water temperature contributed a strong, consistent 15.6 to 17.5 micrograms per litre in every case, functioning as the essential prerequisite for extreme blooms, with chemical oxygen demand adding a stable 3.65 to 5.08 micrograms per litre. Nutrient contributions, however, diverged sharply from event to event. Under persistently high phosphorus, the influence of total nitrogen versus the nitrogen-to-phosphorus ratio shifted depending on immediate nitrogen availability, and in a few instances nitrogen variables actually registered negative contributions, which the authors attribute to Liebig-style co-limitation by light, temperature, or phosphorus rather than any evidence that nitrogen depletion suppresses blooms under natural conditions.

These findings carry direct management implications. The framework argues for a dual-tiered strategy: long-term recovery still demands sustained reduction of both external and internal phosphorus loads, but during the summer bloom window managers may need adaptive controls on short-term nitrogen fluxes as well. Ignoring the transient nitrogen limitation, the authors warn, could foster nitrogen-depleted conditions that favour cyanobacterial dominance, a concern consistent with recent dual-nutrient reduction studies on Lake Erie and other systems. More broadly, the study positions interpretable machine learning as a state-dependent decision-support tool, capable of telling lake managers not just what matters on average but what matters now, in this season, under these conditions.

The authors are careful to note the limits of their approach. Because the analysis rests on observational data from a single monitoring station, the identified relationships are statistical associations rather than strict causal mechanisms, and the specific feature attributions may not extrapolate to lakes with different data distributions. Nonetheless, the framework’s central lesson is likely to resonate far beyond Shahu Lake: eutrophication is not governed by a single rule but by rules that change with time and state, and only analytical tools that respect those shifts, combining high-frequency monitoring, gradient-boosted models, and exact multi-scale attribution, can hope to keep pace with blooms that are becoming more frequent and more intense in a warming world.

Subject of Research: Multi-scale interpretable machine learning analysis of chlorophyll-a dynamics and eutrophication drivers in Shahu Lake

Article Title: Unraveling multi-scale drivers of Chl-a dynamics via interpretable machine learning: a case study of Shahu Lake

Article References: Li, Y., Huang, Y., Lin, L., Kong, X., & Liang, Z. (2026). Unraveling multi-scale drivers of Chl-a dynamics via interpretable machine learning: a case study of Shahu Lake. Environmental Earth Sciences, 85(15), Article 398. https://doi.org/10.1007/s12665-026-13133-7

Image Credits: AI Generated

DOI: 10.1007/s12665-026-13133-7

Keywords: chlorophyll-a, algal blooms, eutrophication, Shahu Lake, interpretable machine learning, XGBoost, SHAP, phosphorus limitation, nitrogen limitation, water quality monitoring, cyanobacteria, lake management