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Carbon Nanotube-Based Sensors Enable Real-Time In Vivo Metabolite Monitoring

A recent study published in Proceedings of the National Academy of Sciences presents a novel sensor architecture using carbon nanotubes to enable real-time, in vivo monitoring of metabolites with high accuracy and versatility.

Study: Tandem metabolic reaction–based sensors unlock in vivo metabolomics. Image Credit: Den Schrodinger/Shutterstock.com

In this work, researchers introduced a single-wall carbon nanotube (SWCNT) electrode design capable of supporting tandem metabolic pathway-like reactions linked to oxidoreductase-based electrochemical analysis. By integrating multifunctional enzymes and cofactors, the architecture broadens the range of detectable metabolites and overcomes key limitations of earlier sensor technologies.

Background

Measuring metabolites in biological systems is essential to understanding how metabolism interacts with complex physiological processes. This insight forms the foundation for developing more effective diagnostics and treatments.

While technologies like mass spectrometry are powerful and widely used in metabolomics, they’re typically restricted to ex vivo analysis. That means they capture only a snapshot of the metabolome at a single point in time, missing the dynamic shifts that occur within living organisms. These methods also come with steep resource requirements, complex sample prep, and significant costs—making them less practical for ongoing or personalized monitoring.

These limitations have created a clear need for real-time, in vivo metabolite monitoring tools that can deliver continuous data without the heavy overhead of traditional systems. Such advances could unlock new insights in fast-evolving fields like microbiome research and individualized healthcare.

The Current Study

To meet this need, the research team developed a SWCNT-based electrode system designed to mimic tandem metabolic pathway-like reactions (TMR). This system uses a carefully integrated combination of multifunctional enzymes and cofactors to trigger sequential transformations of metabolites into detectable signals.

The use of SWCNTs offers key advantages. Their high surface area and electrocatalytic efficiency enable greater enzyme loading and faster reaction rates, while the direct integration of cofactors supports self-mediation. This eliminates the need for extra mediators, reduces the risk of electrode fouling, and enhances the sensor's compatibility with in vivo environments.

The architecture is also designed with flexibility in mind. By assigning different enzymes or cofactors to separate electrodes within the same system, the sensor can simultaneously monitor multiple metabolites—a significant step toward comprehensive, real-time biochemical profiling.

Results and Discussion

Initial testing of the TMR-based sensor system showed impressive results. The researchers were able to track up to twelve distinct metabolites with a signal-to-noise ratio increase of up to 100-fold. Just as importantly, the sensors demonstrated strong operational stability, maintaining reliable function for several days.

The system proved effective for noninvasive monitoring, detecting low concentrations of endogenous metabolites in biofluids like sweat and saliva. It also showed potential in capturing signals from bacterial metabolites relevant to neurological function, highlighting its promise for gut-brain axis research.

With its ability to pair a wide array of metabolites to oxidoreductase reactions, the sensor design has the potential to cover more than two-thirds of all currently known metabolites. This level of reach could have a major impact on clinical and research applications alike, enabling richer, more personalized diagnostic and therapeutic strategies.

Beyond diagnostics, the architecture’s biocompatibility and adaptability make it suitable for a variety of biological contexts, from experimental models to eventual integration into wearable or implantable devices. Continuous, real-time tracking of metabolic changes could help clinicians respond to disease progression or treatment effects with much greater precision.

Conclusion

This work introduces a robust and adaptable sensor platform that leverages carbon nanotube electrodes to replicate natural metabolic pathways, enabling real-time monitoring of metabolites with unprecedented reliability and range. By addressing long-standing barriers in in vivo metabolomics, the research opens up new possibilities for understanding the dynamic nature of metabolism in health and disease.

As this technology evolves, its ability to generate large, multidimensional metabolic datasets could help shape the future of personalized medicine and offer deeper insights into complex biological systems.

Journal Reference

Cheng X., Li Z., et al. (2025). Tandem metabolic reaction–based sensors unlock in vivo metabolomics. Proceedings of the National Academy of Sciences, 122(9), e2425526122. DOI: 10.1073/pnas.2425526122, https://www.pnas.org/doi/10.1073/pnas.2425526122

Dr. Noopur Jain

Written by

Dr. Noopur Jain

Dr. Noopur Jain is an accomplished Scientific Writer based in the city of New Delhi, India. With a Ph.D. in Materials Science, she brings a depth of knowledge and experience in electron microscopy, catalysis, and soft materials. Her scientific publishing record is a testament to her dedication and expertise in the field. Additionally, she has hands-on experience in the field of chemical formulations, microscopy technique development and statistical analysis.    

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