Nanopore Sensor Watches the Brain’s Adrenaline Assembly Line Molecule by Molecule

Every thought, movement and surge of alertness depends on a handful of small molecules that neurons and endocrine cells manufacture with extraordinary precision. Dopamine, noradrenaline and adrenaline — the catecholamines — are assembled inside our cells along a branched metabolic pathway that begins with the dietary amino acid phenylalanine. For decades, biochemists could describe this assembly line on paper, but watching it actually run, in real time and at the level of individual molecules, remained out of reach. Now a team reporting in Nature Nanotechnology has built a single-molecule sensor capable of doing exactly that, capturing the entire route from phenylalanine to adrenaline as it unfolds.

The study, led by Mingqian Zhang, Ziyi Li, Lei Liu and Hai-Chen Wu of the Institute of Chemistry at the Chinese Academy of Sciences together with colleagues, reconstitutes the complete catecholamine biosynthetic pathway in a test tube using purified enzymes and their required cofactors. The researchers then coupled this miniature chemical factory to an engineered protein nanopore — a nanoscale pore embedded in a membrane through which an ionic current flows. Whenever a metabolite from the pathway interacts with the pore, it briefly perturbs that current, producing an electrical fingerprint specific to that molecule. By reading these fingerprints as they accumulate, the team could follow the transformation of each intermediate into the next, second by second.

The technical heart of the work lies in how the researchers achieved specificity. Small molecules are notoriously difficult for nanopores to distinguish because they zip through the pore too quickly and too subtly to leave clean, separable signals. The team solved this by integrating two orthogonal molecular recognition modalities within a single nanopore platform. In essence, different chemical strategies were used to make different members of the pathway register at the pore: some metabolites, such as the catecholamines themselves, generate characteristic blockade patterns as they translocate, while the amino acids phenylalanine and tyrosine were detected through a tailored probe chemistry involving a copper-coordinated molecular adaptor and a cucurbituril host that captures the amino acid and presents it to the pore as a distinct complex.

With this dual recognition scheme in place, the researchers demonstrated highly specific detection of all six key players in the pathway: phenylalanine, tyrosine, levodopa, dopamine, noradrenaline and adrenaline. Extended data traces show characteristic current blockades and dwell-time distributions for each analyte at 100 micromolar concentration, recorded in a high-salt buffer at a transmembrane potential of +100 millivolts. Gaussian fits to the blockade histograms and single-exponential fits to the dwell times confirm that each metabolite produces a statistically distinct signature, which is the prerequisite for unambiguous identification in a mixed sample.

Having validated each molecule individually, the team turned to the full cascade. They initiated the enzymatic sequence and sampled the reaction mixture every five minutes, feeding each sample to the nanopore. The resulting single-channel recordings amount to a time-lapse film of neurotransmitter synthesis: phenylalanine signals fade as tyrosine rises, tyrosine gives way to levodopa, and levodopa is converted onward to dopamine, noradrenaline and finally adrenaline. Because the readout is label-free and single-molecule, nothing was added to the reaction to make it visible, and no amplification step could distort the quantitative picture of pathway dynamics.

This time-resolved view matters because the catecholamine pathway is not a simple conveyor belt. It is a branched network whose flux is governed by enzyme kinetics, cofactor availability and regulatory feedback, and disruption at any node is implicated in conditions ranging from Parkinson’s disease and attention-deficit hyperactivity disorder to orthostatic hypotension and stress-related endocrine disorders. Conventional analytical methods — liquid chromatography, mass spectrometry, electrochemistry, ELISAs — can measure metabolite concentrations at chosen endpoints, but they are generally snapshot techniques that require aliquots, labels or lengthy separation steps, making continuous, coupled monitoring of a multi-enzyme cascade cumbersome.

The platform also opened a window on pathology. A striking application involves iodotyrosine dehalogenase 1, or DEHAL1, an enzyme best known for recycling iodide in the thyroid, where it removes iodine from iodinated tyrosine residues. Defects in the DEHAL1 gene cause hypothyroidism, and 3-iodo-L-tyrosine, the substrate of this enzyme, has long been known to inhibit tyrosine hydroxylase, the rate-limiting enzyme that converts tyrosine to levodopa. The researchers used their nanopore assay to examine what happens to the catecholamine cascade when dehalogenase activity is compromised. They found that 6-methylisothiocyanate, a compound that disrupts the dehalogenase, perturbs catecholamine biosynthesis in a way that offers a mechanistic explanation for how DEHAL1 deficiency may compromise neurotransmitter production — potentially linking an inherited thyroid disorder to impaired catecholamine output.

Figure 5 of the study, titled ‘Effect of thyroiditis-like disorders on catecholamine metabolism,’ presents this perturbation experiment, with extended recordings showing how the cascade changes when monoiodotyrosine is present. The single-molecule records reveal shifts in the relative abundance of the pathway intermediates, illustrating the value of the method: rather than inferring a block from diminished end-product levels, researchers can see exactly where flux stalls and which intermediates accumulate. That level of mechanistic detail is precisely what drug developers and enzymologists need when trying to dissect regulatory nodes in metabolic networks.

Broader implications extend well beyond catecholamines. The authors describe their integrated enzymology-and-nanopore-sensing platform as a general framework for studying complex biochemical pathways with single-molecule resolution. Because protein nanopores can be engineered with different recognition elements, the same design philosophy could in principle be applied to other branched metabolic cascades, to drug-metabolism studies, or to screening enzyme inhibitors in real time. The approach builds on two decades of stochastic sensing, in which engineered pores have been taught to identify analytes as diverse as metal ions, nucleotides, amino acids, peptides, proteins and microRNAs, and it extends that lineage from static identification to dynamic pathway monitoring.

The team has deposited its source data publicly on Zenodo, and the paper — received in December 2025, accepted in August 2026 and published on 1 September 2026 — carries no reported competing interests. What the work ultimately delivers is a new kind of laboratory instrument: a single pore through which the chemistry of a neurotransmitter can be watched being born. If the framework generalizes as its authors hope, metabolic biochemists may soon spend far less time taking snapshots of pathways and far more time watching them move.

Subject of Research: Time-resolved single-molecule monitoring of catecholamine biosynthesis from phenylalanine using an engineered nanopore sensor

Article Title: Nanopore-enabled time-resolved monitoring of catecholamine-related phenylalanine metabolism

Article References: Zhang, M., Li, Z., Hao, W., Yi, Y., Zhou, K., Liu, L., & Wu, H.-C. (2026). Nanopore-enabled time-resolved monitoring of catecholamine-related phenylalanine metabolism. Nature Nanotechnology. https://doi.org/10.1038/s41565-026-02273-3

Image Credits: AI Generated

DOI: 10.1038/s41565-026-02273-3

Keywords: nanopore sensing, catecholamines, dopamine, adrenaline, phenylalanine metabolism, single-molecule detection, neurotransmitter biosynthesis, DEHAL1, iodotyrosine dehalogenase, label-free biosensing, Nature Nanotechnology, enzymology