Seeing is believing: metabolic sensors illuminate cell‑specific metabolic requirements

The cellular metabolic space represents a molecular layer closely linked to cellular phenotypes, highlighting the importance of metabolism as a key dimension to better understand biological systems. Cellular metabolism is far from merely supporting basic housekeeping functions; it dynamically regulates processes such as signalling, immunity, development and regeneration (Tippetts et al. 2023). These processes do not rely on static metabolic programmes. Instead, the diversity of metabolic strategies across tissues is fundamental to the organism's overall health and resilience. Metabolic activities must be tightly aligned with the specific biological tasks that each cell and tissue performs. When a metabolic imbalance happens, cells may fail to execute their functions, contributing to disorders ranging from immune dysfunction to neurological deficits (DeBerardinis & Thompson 2012). Despite this central role, our understanding of metabolic differences across tissues and how these differences support cell‑specific functions remains surprisingly limited. Mapping these metabolic distinctions and linking them to biological tasks will help reveal what goes wrong when systems fail. Such insights may help to clarify why certain tissues are more vulnerable to specific metabolic stresses while others remain comparatively resilient, improving our ability to predict how metabolic diseases develop and why they affect organs differently. But this knowledge will have implications that extend beyond disease biology. For instance, it will also help illuminate how cells, and ultimately whole animals, cope with environmental changes and how metabolically plastic they are in adapting to these challenges. Because cellular metabolism is strongly shaped by the surrounding microenvironment, removing cells from their native context can itself perturb metabolic activity. For this reason, it is essential to study metabolic processes in vivo. Developing improved techniques, tools and protocols that allow metabolism to be quantified and manipulated within living tissues, while taking advantage of powerful experimental model systems, will be crucial for accurately mapping true cellular metabolic states. In support of this perspective, in an article in this issue of The Journal of Physiology, Müller et al. combined the genetic strengths of Drosophila melanogaster with live imaging of metabolic sensors to investigate neuronal metabolism (Müller et al. 2026). Metabolic biosensors provide powerful tools for investigating how specific metabolites support cell-type-specific functions. By enabling real‑time, in vivo measurements, these sensors capture metabolic states within native microenvironments. This capability makes it possible to pinpoint when and where metabolic pathways are required, providing insights that traditional approaches, such as targeted metabolomics, often miss. Although metabolic biosensors have been available since the early 2000's (Deuschle et al. 2005), their use has remained relatively limited, in part due to technical constraints. Expanding both the diversity and the application of these genetic biosensors will be essential to tackling the question of how cells transform metabolites into functions. The Schirmeier laboratory previously demonstrated that glial glycolysis is essential for neuronal survival (Volkenhoff et al. 2015). Neurons are also known to take up circulating sugars; however, it remained unclear what these sugars were being used for. Although it had been proposed that these sugars fuel the pentose phosphate pathway (PPP), enhancing NADPH production to counteract the elevated levels of reactive oxygen species (ROS) generated during high neuronal activity, this hypothesis had never been formally tested. Müller et al. have now shown that disruption of the oxidative branch of the PPP leads to increased neurodegeneration accompanied by behavioural changes, supporting the hypothesis that the activity of this pathway provides the reducing power required to counteract ROS. This raised the question of whether this phenotype is specifically linked to the pathway's capacity to generate NADPH. To address this question, Müller et al. generated new transgenic fly lines, expressing the iNap1 sensor to monitor NADPH levels and HyPerRed sensor to monitor H2O2 levels (as a proxy of ROS). Using these two metabolic sensors, and imaging both eye imaginal discs and adult brains, the authors showed that neuronal-specific knockdown of the oxidative branch of the PPP leads to elevated oxidative stress, likely driven by reduced NADPH levels (Müller et al. 2026). This work therefore provides the first direct link between PPP activity, neuronal ROS regulation and its protective roles in neurodegeneration. These observations underscore the importance of cell-specific metabolic programmes in sustaining cellular and organ functions. They further highlight specific metabolites, and metabolic sensors as a tool to visualize them in complex tissues, as windows into physiological states that traditional metabolomics cannot fully capture, positioning live metabolic imaging as a powerful approach for dissecting tissue-specific metabolism. In this paper, Müller et al. showcase the power of combining metabolic sensors with Drosophila genetics, demonstrating how this combination can drive significant breakthroughs across diverse research areas. Their work demonstrates that metabolism is not merely a passive readout but an active determinant of cellular function. In particular, they highlight the essential role of the oxidative branch of the PPP in maintaining NADPH levels and redox balance, directly linking metabolic activity to neuronal survival. Despite these advances, challenges remain, including technical limitations and the need for broader adoption of metabolic biosensors. Addressing these issues will require active communication and collaboration within the scientific community along with continued methodological improvements and integration with complementary approaches such as spatial metabolomics or stable isotope tracing combined with genetic manipulations. Together, these efforts will be crucial to unravel how metabolism shapes cellular and tissue functions. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. None of the authors has any conflict of interests. Both authors have read and approved the final version of this manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed. Research in Z.C.S.’s lab is supported by funding from Gulbenkian Institute for Molecular Medicine (GIMM), from Portuguese Foundation for Science and Technology (FCT) CEECINST/00021/2021/CP1771/CT0002 and 2023.00860.BD, and from the Chan Zuckerberg Initiative (CZI) DAF, an advised fund of Silicon Valley Community Foundation (Grant agreement No. 2023-331 947).