Fungi have repeatedly delivered transformative advances across industries, from medicine to food to materials, yet these breakthroughs have emerged from a narrow base of organisms and well-studied systems. Although mycology has taken a big leap forward in the past decades because of advances in genomics, multi-omics, engineering, phenotyping and environmental monitoring, much fungal diversity remains taxonomically and functionally under-characterised, and many sustainability-relevant innovations remain limited by lack of investment, sparse infrastructure, and fragmented governance. We now have technologies that make previously inaccessible fungal questions tractable, which can help unlock the next generation of fungal breakthroughs. Informed by a workshop held in December 2025 that convened 20 leading experts across fungal disciplines, here we lay out key bottlenecks to fungal research and innovation through three lenses: functional mycology, human and institutional capacity, and governance. We identify selected sustainability-relevant fungal frontiers and use these to surface the recurrent gaps that cut across domains. We propose four elements of coordinated action across research and development, governance, and advocacy that could contribute to unlocking the full potential of fungi for sustainability transitions.
Abscisic acid (ABA) is a plant hormone that mediates abiotic stress tolerance and regulates growth and development. ABA binds to members of the PYL/RCAR ABA receptor family that initiate signal transduction inhibiting type 2C protein phosphatases. Although crosstalk between ABA and the hormone Jasmonic Acid (JA) has been shown, the molecular entities that mediate this interaction have yet to be fully elucidated. We report a link between ABA and JA signaling through a direct interaction of the ABA receptor PYL6 (RCAR9) with the basic helix-loop-helix transcription factor MYC2. PYL6 and MYC2 interact in yeast two hybrid assays and the interaction is enhanced in the presence of ABA. PYL6 and MYC2 interact in planta based on bimolecular fluorescence complementation and co-immunoprecipitation of the proteins. Furthermore, PYL6 was able to modify transcription driven by MYC2 using JAZ6 and JAZ8 DNA promoter elements in yeast one hybrid assays. Finally, pyl6 T-DNA mutant plants show an increased sensitivity to the addition of JA along with ABA in cotyledon expansion experiments. Overall, the present study identifies a direct mechanism for transcriptional modulation mediated by an ABA receptor different from the core ABA signaling pathway, and a putative mechanistic link connecting ABA and JA signaling pathways.
Neuromodulators are critical controllers of neural states, with dysfunctions linked to various neuropsychiatric disorders. Although many biological aspects of neuromodulation have been studied, the computational principles underlying how neuromodulation of distributed neural populations controls brain states remain unclear. In contrast to external contextual inputs, neuromodulation can act as a single scalar signal that is broadcast to a vast population of neurons. We model the modulation of synaptic weight in a recurrent neural network model and show that neuromodulators can dramatically alter the function of a network, even when highly simplified. We find that under structural constraints like those in brains, this provides a fundamental mechanism that can increase the computational capability and flexibility of a neural network. Diffuse synaptic weight modulation enables storage of multiple memories using a common set of synapses that are able to generate diverse, even diametrically opposed, behaviors. Our findings help explain how neuromodulators unlock specific behaviors by creating task-specific hyperchannels in neural activity space and motivate more flexible, compact and capable machine learning architectures.
Spatiotemporal flows of neural activity, such as traveling waves, have been observed throughout the brain since the earliest recordings; yet there is still little consensus on their functional role. Recent experiments and models have linked traveling waves to visual and physical motion, but these observations have been difficult to reconcile with standard accounts of topographically organized selectivity and feedforward receptive fields. Here, we introduce a theoretical framework that formalizes and generalizes the connection between 'motion' and flowing neural dynamics in the language of equivariant neural network theory. We consider 'motion' not only in physical or visual spaces, but also in more abstract representational spaces, and we argue that recurrent traveling-wave-like dynamics are not just useful but necessary for accurate and stable processing of any signal undergoing such motion. Formally, we show that for any non-trivial recurrent neural network to process a sequence undergoing a flow transformation (such as visual motion) in a structured equivariant manner, its hidden state dynamics must actively realize a homomorphic representation of the same flow through recurrent connectivity. In this "spatiotemporal perspective on dynamical computation", traveling waves and related flows are best understood as faithful dynamic representations of stimulus flows; and consequently the natural inclination of biological systems towards such dynamics may be viewed as an innate inductive bias towards efficiency and generalization in the spatiotemporally-structured dynamical world they inhabit.
Parasitic plants in the genus Orobanche display varying levels of host specificity, however, the molecular features determining host range are not fully understood. We sequenced the genomes of three Orobanche species with different host ranges: Orobanche minor (generalist), O. gracilis (Fabaceae-specific), and O. hederae (ivy-specific). Comparative analysis revealed considerable genome size variation but consistent holoparasitic gene loss patterns. While synteny analysis revealed strong collinearity between O. gracilis, O. hederae, and O. minor, we found distinct molecular repertoires among species. O. gracilis showed expanded protein-degrading and carbohydrate-active enzyme families, while putative strigolactone receptor (KAI2d) numbers varied from five in specialists to eleven in the generalist O. minor, suggesting diverse molecular strategies across different host ranges.
