ACS Sensors

Measuring the precise dynamics of specific neuromodulators in neurons is key to understanding how information is transmitted and processed in the brain. Despite the growing use of intensity-based neural activity sensors such as dLight in recent years, it remains challenging to monitor the dynamics of multiple neurochemicals simultaneously in live neurons. Unlike intensiometric sensors that are susceptible to artifacts caused by fluctuations in excitation power and rapid photobleaching, fluorescence lifetime-based sensors are less affected by these factors and can provide more stable measurements. Here we introduce dHaloLife635, a novel genetically encoded fluorescence-lifetime-based dopamine (DA) sensor that exhibits a fluorescence lifetime change up to -0.20 ns upon dopamine binding. dHaloLife635 consists of a G protein-coupled dopamine receptor (DRD1), a circularly permuted HaloTag (cpHaloTag), and a cell-permeable dye JF635 functionalized with a HaloTag ligand, a reactive chloroalkane linker (JF635-HTL). When dopamine binds to the dHaloLife635 sensor, it induces a conformational change in the cpHaloTag that alters the local environment of the conjugated dye, thereby changing its fluorescence lifetime. In live HEK293T cells and primary neurons, dHaloLife635 responds selectively to dopamine but not to serotonin, L-DOPA, or GABA, demonstrating excellent specificity. This dHaloLife635 sensor represents an initial step toward the establishment of a broader family of chemigenetic lifetime sensors that exhibit distinct fluorescence lifetime signatures upon binding their respective targets, thereby enabling highly specific and sensitive, real-time monitoring of multiple neurochemical dynamics in vivo.

Extracellular L-lactate reports cellular metabolism, but resolving its dynamics alongside intracellular metabolism and neuronal activity remains challenging. Here we develop eLACCO3 and R-eLACCO3, green and red cell-surface lactate biosensors with Ca2+-independent responses and faster response and recovery kinetics in cultured cells. Selected variants provide larger fluorescence responses than their predecessors in brain cells, slices, and living mice and improve detection of glucose-evoked extracellular lactate oscillations. Combining R-eLACCO3 with GCaMP6f enabled imaging of extracellular L-lactate simultaneously with odor-evoked activity in anesthetized mice and cortical activity in awake mice. These biosensors enable multiplexed measurements of extracellular lactate dynamics in relation to intracellular metabolism and neuronal activity.

Extracellular signal-regulated kinase (ERK) governs many cellular processes, and its spatiotemporal activity dynamics are important for downstream signaling specificity. Existing fluorescent ERK activity biosensors, however, fall short in enabling spectrally multiplexed, spatially resolved, or deep tissue measurements. Here, we introduce a chemigenetic, single-fluorophore biosensor, WHaloEKAR, that reports ERK activities through changes in fluorescence lifetime. WHaloEKAR combines large lifetime changes (-0.81 ns) with the spectral versatility of the self-labeling protein HaloTag giving access to orange, red, and far-red ERK biosensors. The latter enabled the investigation of heterogeneous ERK activity at distinct subcellular locations in cultured cell lines and primary cortical rat neurons via fluorescence lifetime imaging microscopy (FLIM). Moreover, multiplexed FLIM measurements allowed to study ERK activity in parallel to the second messengers calcium and cyclic adenosine monophosphate. Finally, WHaloEKAR enabled the investigation of ERK activity in 3D samples as well as in live animals.

Methotrexate (MTX) is a narrow-therapeutic-index drug widely used in cancer and autoimmune disease treatment, for which delayed clearance can cause severe toxicity and requires close therapeutic drug monitoring. Here, we integrate high-stringency Capture-SELEX, biophysical characterization, molecular modeling, mutational validation, and electrochemical transduction to develop two structurally distinct MTX-binding DNA aptamer families. Full-length 3315 and 930 bound MTX with apparent KD values of 89 and 408 nM, respectively. Systematic truncation generated compact functional variants: 3315-55 retained 63 nM affinity and broad buffer tolerance, whereas 930-65 reached an apparent KD of 44 nM in 10 mM Mg2, revealing markedly different ion dependencies. Biolayer interferometry confirmed rapid and reversible MTX recognition, while 3315 variants retained binding in serum-containing buffer. Computational analysis and site-directed mutagenesis identified distinct recognition architectures: a compact G-rich scaffold coupled to a central binding interface in 3315 and a localized Mg2+-stabilized binding pocket in 930. Methylene blue-labeled 3315-55 and 930-65 were integrated into electrochemical aptamer-based sensors, producing concentration-dependent responses to 100-1000 uM MTX in PBS, discriminating MTX from folic acid, and responding to MTX directly in undiluted human blood. Together, these results establish a structure-guided workflow linking aptamer discovery, mechanistic validation, and electrochemical translation, providing new molecular recognition elements and a foundation for future reagent-less MTX therapeutic drug monitoring.

Hormone dynamics are central to a multitude of conditions in women's health; however, limitations in the cost, convenience, and multiplexing capacity of current hormone assays preclude routine longitudinal hormone testing. This limitation severely restricts our understanding in this historically neglected field, presenting a need for improved bioanalytical tools to support hormone-informed care. Silicon photonic resonator sensors have excellent multiplexing capacity and scalable fabrication, and offer strong potential to meet this important need. Here we demonstrate, for the first time, multiplexed silicon photonic detection of two urinary hormone biomarkers, follicle-stimulating hormone (FSH) and pregnanediol-3-glucuronide (PdG), using sub-wavelength grating ring resonators and a polydopamine-based, regenerable surface chemistry. We combine a sandwich immunoassay for FSH and an antigen-down competitive immunoassay for PdG on the same chip, both amplified using a commercially available quantum-dot-streptavidin conjugate and with on-chip regeneration over multiple measurement cycles. In artificial urine, this proof-of-principle multiplexed assay achieves limits of detection of 0.594 ng/mL for FSH and 19.1 ng/mL for PdG. This architecture is inherently scalable to tens of hormone targets on a millimetre-scale chip (a >10x multiplexing improvement over typical lateral-flow immunoassays) enabling future low-cost, quantitative at-home hormone panels that could transform research, diagnostics, and treatment in women's health.

Continuous biomarker monitoring with affinity biosensors remains limited by probe saturation, slow dissociation, signal carryover, and regeneration methods that require chemical washing, harsh buffers, or external reset modules. Here, we report a flow-programmed, self-regenerative electrochemical aptamer-based biosensor for continuous 17{beta}-estradiol monitoring. The platform restores the sensing interface by tuning buffer flow through the device, enabling repeated sensing-regeneration cycles without chemical stripping or active-reset hardware. The biosensor achieves a 1.46 pM limit of detection, and a log-linear dynamic range from 100 pM to 1 M in real human sweat, covering physiologically relevant estradiol concentrations. It exhibits high selectivity, with responses to potential molecularly similar interferents remaining below 10% of the 17{beta}-estradiol signal. Under dynamic flow operation, the device shows reversible signal recovery and stable electrochemical performance, with higher buffer-wash flow reducing baseline carryover between measurements. A coupled binding-transport simulation captures the flow-dependent regeneration trends and maps how wash-flow rate, wash duration, and apparent aptamer affinity affect regeneration efficiency. Ex vivo testing in real human sweat, including samples from pregnant women, supports translational relevance. This work establishes buffer-flow programming as a reagent-free route to regenerable electrochemical aptamer sensing for automated, wearable-compatible estradiol monitoring.

Unlike nucleic acids, proteins cannot be directly amplified. Ultrasensitive detection must therefore couple efficient analyte-to-signal conversion with strong suppression of target-independent background. Consistently detecting ~100 molecules (below which Poisson sampling noise alone causes CV to exceed 10%) across protein targets in a format as scalable and accessible as PCR remains unsolved. Separation-based ultrasensitive immunoassays require target binding stable enough to survive stringent washing and are therefore constrained by wash-induced signal loss and, more fundamentally, the relative scarcity of exceptionally tight binders. Performance consequently varies across targets; detection limits below 1,000 molecules remain rare. Conventional separation-free proximity assays avoid washing but incur background from random probe collisions, with reported detection limits frequently exceeding 100,000 molecules. Here we introduce Successive Proximity Extension Amplification Reaction (SPEAR), a separation-free architecture in which autonomous engineered DNA nanodevices emulate biological kinetic proofreading. Two successive irreversible proximity-extension steps compound discrimination between analyte-dependent and background reactions, suppressing spurious signals while preserving efficient analyte-to-signal conversion. This design reduces reliance on high-affinity binders and enables sub-fM detection from 1 uL samples through simple 3-step mixing followed by standard qPCR readout. Across 11 biomarkers tested, SPEAR consistently achieved sub-100-molecule detection limits. Where compared, it outperformed ultrasensitive separation-based platforms, analytically and clinically, including for low-abundance Alzheimer's disease biomarkers. SPEAR also precisely quantified SARS-CoV-2 neutralizing antibody titers from finger-prick dried blood spots, concordant with the cell-based reference assay on venous blood. It detected a distinct mixed phosphorylation state of Tau, and targeting this state resolved previously observed capillary-venous discordance and improved amyloid-status discrimination. These results establish engineered autonomous successive molecular discrimination as a practical strategy for near-single-molecule protein detection, extending the sensitivity, scalability and accessibility of PCR-based testing to non-amplifiable analytes.

Forster resonance energy transfer (FRET) is commonly used to monitor protein-protein interactions in situ. The high spatiotemporal resolution and facile implementation inside complex molecular environments have spearheaded FRET's widespread adoption in biosensing. Despite these advantages, current FRET biosensors are largely restricted to the detection of the presence/absence of individual inputs and are thus unable to sense several multiplexable inputs simultaneously within complex milieu of biological environments. In this work, we introduce a generalizable strategy to construct genetically encoded protein-based FRET biosensors capable of recognizing multiple inputs following Boolean logic-type (YES/OR/AND) operations. These topologically specified FRET sensors powerfully expand the input capacity in sensing protein-protein interactions while providing a user-programmable platform for monitoring heterogeneous biological activities both in vitro and in living cells.

Perovskite quantum dots (PQDs) are exceptionally promising next-generation optical materials for bioimaging applications. This paper presents an optical PQDs nanocomposite method to identify bacterial species associated with breast cancer, employing a LSTM deep learning model. The results indicate that the developed PQD-based nano-sensor offers impressive sensitivity, selectivity, and practical application. The four bacterial species identified in the study, Pseudomonas aeruginosa, Vibrio parvula, Acinetobacter baumannii, and Streptococcus vestibularis, were considered the most relevant indicators of breast cancer. With rapid detection, an intuitive design, and improved reliability, the PQD sensor could be an excellent breast cancer diagnostic tool for a point-of-care application. Furthermore, it has the potential to be integrated into healthcare systems, specifically in resource-limited settings, thereby improving the accessibility and efficiency of early breast cancer detection.

Electrochemical aptamer-based (EAB) sensors have emerged as a promising framework for reagentless, real-time molecular monitoring in complex biological matrices. Signal transduction in a prominent benchmark system--targeting aminoglycoside antibiotics--has been nearly universally attributed to target-specific, binding-induced conformational changes that modulate the distance between a redox reporter and the electrode surface. Here, using a suite of interfacial electrochemical and optical characterization methods, we systematically show that charge-screening, not structure switching, dominates the signaling mechanism in the case of the aminoglycoside EAB sensor. First, we demonstrate that the legacy aminoglycoside sensor sequence exhibits apparent affinities and relative electron kinetic modulations similar to unrelated control sequences, including generic stem-loop hairpins, unstructured poly-T sequences, and short duplexes. Multi-modal validation via bio-layer interferometry (BLI), circular dichroism (CD), and fluorescence spectroscopy confirms that this promiscuous target association occurs across disparate DNA sequences and without detectable conformational reconfiguration. Further investigation via charge-scaling polyamine assays and on-electrode fluorescence imaging demonstrate that the dominant signal transduction mechanism in these sensors is instead driven by macro-scale electrostatic backbone charge-screening.

Non-small-cell lung cancer (NSCLC) diagnosis is challenged owing to the need for reliable, non-invasive biomarkers. Circulating cell-free microRNAs (ccf-miRNAs) are promising candidates, but their low levels and short sequences in blood complicate detection. In this study, a novel nano-hybrid fluorescent array was developed to enable rapid and sensitive identification of NSCLC-related ccf-miRNAs. The array consists of poly(T)-modified fluorescent nano-polystyrene beads for capturing target miRNAs, and fluorophore-labeled, sequence-specific locked nucleic acid (LNA) probes for their detection. This design forms a sandwich structure with the target miRNA. Nano cytometry and fluorescence microscopy assessed both the capture and specificity of detection. The assay was tested on plasma samples for miR-16-5p and U6, evaluating selectivity, sensitivity, and reproducibility. The results showed that the poly(T)-modified beads efficiently captured the target miRNAs, and the LNA probes accurately distinguished the sequences. The assay enabled direct detection of miR-16-5p and U6 from plasma without amplification, demonstrating high selectivity, sensitivity, and reproducibility. Combining enrichment with nano-polystyrene beads and sequence-specific LNA probes addressed the main challenges of ccf-miRNA detection, namely their low abundance and short sequence length. As ccf-miRNAs are linked to NSCLC progression, this method could assist in early diagnosis, disease monitoring, and assessment of treatment response. The target-independent nature of the poly(T) capture layer allows for easy calibration to new miRNAs by changing the LNA probes, rendering it suitable for multiplex detection in clinical settings. However, further preclinical and clinical studies are needed before adoption in routine practice. This nano-hybrid fluorescent array presents a rapid and reliable approach for detecting low-abundance ccf-miRNAs in plasma. Its encouraging performance and flexible design show potential for future application in NSCLC diagnosis and monitoring, subject to additional confirmation.

Fluorescent base analogues have proven to be valuable probes of RNA structure. Pyrrolocytosine (pC), an analogue of cytosine, exhibits highly environment-sensitive fluorescence within RNA and is strongly quenched in hydrogen-bonded contexts. In this work, we incorporated pC into the aptamer domain of the B. subtilis guanine riboswitch to determine if this quenching mechanism could allow for sensing of RNA-small molecule interactions. We utilized complementary fluorescence spectroscopy methods to under-stand the functional impacts and ligand-sensitivity of pC substitutions distal to and within the binding pocket. We found that pC substitution within a static structural region exhibits the expected ligand-independent fluorescence properties. When placed in the ligand binding pocket, pC exhibits a moderately decreased affinity for the ligands guanine (G) and hypoxanthine (Hx) while maintaining high specificity for G. We found that pC behaves as a turn-off sensor, with distinct changes in fluorescence upon G or Hx binding. These differences are dependent on the number of hydrogen bonds formed with pC and are resolvable in both time-dependent and steady-state fluorescence measurements. Our results show that pC can be used to study RNA-small molecule interactions and can discriminate between similar ligands even when they have identical binding modes.

Neuropeptides regulate a wide range of physiological processes throughout the nervous and endocrine systems, yet their spatiotemporal dynamics in vivo remain poorly understood. While recently developed intensiometric sensors can detect neuropeptides, their use in vivo is often confounded by artifacts induced by hemodynamic changes, pH fluctuations, and motion. Here, we present a general strategy for engineering dual-excitation ratiometric (Ex-ratiometric) neuropeptide sensors by tuning the excited-state proton transfer properties of the fluorescent reporter. Dual excitation at 405 nm and 488 nm produces a ratiometric signal that intrinsically corrects fluorescence fluctuations unrelated to ligand binding. Using an AlphaFold3-guided in silico design approach combined with experimental validation, we developed a suite of Ex-ratiometric sensors. As a representative example, Ex-NTS2.0 enables robust detection of neurotensin (NTS) in vivo while remaining largely resistant to hemodynamics, pH, and motion-induced artifacts. Overall, these findings establish a scalable and mechanistically grounded platform for developing new Ex-ratiometric tools and provide a broadly applicable strategy for sensitive detection of neuropeptide dynamics in living systems.

Glycine transporter 1 (GlyT1) is a clinically investigated target whose conformational plasticity enables ligands to engage distinct extracellular and intracellular binding sites. However, methods to directly quantify intracellular binding remain limited and largely rely on radioligand-based approaches. Here, we report a NanoBRET-based binding assay to quantify intracellular GlyT1 target engagement in living cells using a fluorescent tracer derived from the GlyT1 inhibitor Cmpd1. With a structure-based approach followed by pharmacological characterization we identified a suitable meta-substituted exit vector for linker and fluorophore attachment while maintaining GlyT1 binding. A series of fluorescent probes was synthesized and evaluated, leading to the development of GlyT1-probe which displayed high-affinity binding and enabled robust NanoBRET measurements. Unlike the functional uptake assay, the NanoBRET assay distinguished intracellular from extracellular GlyT1 inhibitors and resolved structure-activity relationships at the intracellular binding site. This assay provides a quantitative approach to interrogate conformation-selective GlyT1 target engagement in living cells, facilitating the characterization of GlyT1 ligands targeting the intracellular site.

Finite-bandgap charge-based FET biosensors are known to be insensitive to electronic tunneling noise in the semiconductor and interference from weakly-charged proteins in physiological samples. However, their signal is still corrupted by pH fluctuations and condensing counterions in the bulk electrolyte. Here, we demonstrate that electrolyte noise is screened by the Stern layer beyond the linear Debye-Huckel limit, when the interfacial potential drop is larger than the thermal voltage. Using a fully nonlinear Gouy-Chapman-Stern (GCS) theory, a universal calibration curve is derived and shown to collapse the low-noise FET signals for miRNA, extracellular vesicles (EV), and protein, captured either directly or through silica and magnetic nanoparticle charge reporters, over eleven decades of analyte concentration. The theory involves the dissociation constant KD and a gain parameter {chi}, which represents the competing effects of the reporter charge and buffer Debye screening that must be large to produce the low-noise GCS condition. The limit of detection (LOD) is shown to be KD/{chi}, which can be optimized by varying the probe density, charge reporter, and buffer solution. An optimized hybridization buffer then yields {chi} ~ 22 (LOD ~1 pM) for miRNA detection, and multivalent capture reduces KD by four orders of magnitude for EV detection (relative to protein detection) with {chi} ~ 34 (LOD ~10 fM).

Circulating microRNAs (miRNAs) have emerged as promising liquid biopsy markers; however, their clinical translation is restricted by low abundance, biological heterogeneity, and the complexity of multiplex profiling. Herein, we develop a targeted cycling-mediated duplex-specific nuclease (DSN)-nanozyme signal amplification platform (TC-DSN-Nano) that establishes a compartmentalized catalytic transduction strategy for multiplexed miRNA analysis. By encapsulating gold nanozymes within liposomal nanoreactors, this platform spatially separates molecular recognition from catalytic signal generation, preserving nanozyme activity during sensor construction. Upon target miRNA recognition, DSN-mediated recycling induces regenerative release of nanozyme-loaded liposomes from magnetic substrates, converting individual miRNA molecules into amplified catalytic outputs without conventional nucleic acid amplification. The platform enables programmable profiling of six prostate cancer (PCa) associated miRNAs in serum samples. Furthermore, machine learning-assisted integration of multiplexed miRNA signatures enables accurate discrimination among healthy donors, nonmetastatic PCa patients, and metastatic PCa patients, achieving an overall classification accuracy of 90.5%. This work establishes a general compartmentalized nanozyme transduction framework that integrates molecular recycling, catalytic amplification, and computational analysis for liquid biopsy-based cancer stratification.

Fermentation is a process through which microorganisms are used to transform basic molecules into high value substances in various applications such as biopharma, food production, and biofuel generation. In such processes, monitoring the health of microbial cells is essential, as it is a key factor in the final product yield. Traditional methods of assessing the health of fermenter populations have involved manually extracting samples from the fermenter for benchtop testing, which lacked the accuracy and efficacy of real-time continuous measurements. This has opened the door for inline sensors to be integrated into fermenters for continuous measurement; including microfluidic based Electrochemical Impedance Spectroscopy (EIS). EIS utilizes a range of frequencies to gain insight into the characteristics of microbial populations, such as cell size and membrane capacitance. EIS cytometry, in particular, has emerged as a relevant tool, as it enables single-cell level detection in real-time. However, current EIS cytometry devices cannot be deployed directly within fermenters due to the high cell density conditions. This has limited EIS analysis in fermenters to bulk measurements averaged across a population. Here, we present a microfluidic chip that uses passive cell-flux-partitioning geometry to direct cells from high-density culture through a single-cell-constrained flow path containing integrated impedance-sensing electrodes. The proposed chip combines geometric channel design and embedded electrodes to enable continuous impedance measurements from cell-containing flow while operating at input cell densities on the scale of 10^9 CFU/mL. This work demonstrates a first step toward integrating single-cell-constrained microfluidic handling with impedance sensing for inline monitoring in industrial biomanufacturing.

Transition-metal ion Forster resonance energy transfer (tmFRET) measures short-range distances and conformational changes in proteins, but its distance sensitivity depends on the donor-acceptor pair. Here, we establish the metal-chelating noncanonical amino acid bipyridylalanine (bpyA) as a flexible, genetically encoded acceptor platform whose Forster distance (R0) can be tuned without changing protein labeling. Cu2+, Cu2+ complexed with nitrilotriacetic acid (NTA), and Fe2+ form distinct acceptors at the same bpyA site, allowing distance sensitivity to be adjusted by changing the solution conditions. We incorporated bpyA at two sites in maltose binding protein (MBP) and labeled nearby engineered cysteines with the donor fluorophore BODIPY. The resulting [Cu(bpyA)]2+, [CuNTA(bpyA)]2+, and [Fe(bpyA)]2+ acceptors provided R0 values ranging from 13.9 to 21.2 [A]. Analysis of time-resolved tmFRET data recovered donor-acceptor distance distributions and maltose-dependent changes consistent with structural predictions. At the 237/295 site pair, both copper and iron acceptors resolved the maltose-dependent decrease in distance. At the 309/322 site pair, [Cu(bpyA)]2+ did not appreciably resolve the distance increase, whereas adding NTA shifted R0 toward shorter distances and enabled detection of an increase from 12.1 to 14.4 [A]. These results demonstrate that a single bpyA-labeled protein preparation supports multiple tmFRET acceptors, providing a cysteine-independent acceptor-labeling strategy with adjustable distance sensitivity.

In vitro-transcribed (IVT) messenger RNA (mRNA) therapeutics require rigorous quality control of 5' capping efficiency and 3' poly(A) tail length, both of which constitute critical quality attributes (CQAs). Current analytical workflows for these CQAs rely on hybridization with nucleic acid probes and biotin-based affinity purification, which constrain throughput and increase per-assay cost. Here, we report a rationally designed 5' untranslated region (5' UTR) that sustains high translational efficiency while enabling probe-free, one-step purification for rapid quantification of capping efficiency and poly(A) tail length distribution. This approach exploits a strategically engineered 5' UTR incorporating a purine-only RNase A-resistant fragment terminating at a single pyrimidine cleavage site, together with a translation-enhancing element comprising an N6-methyladenosine (m6A) deposition motif and an 18S rRNA complementarity sequence. This dual-function design accommodates GA-rich sequence segments without compromising mRNA translational output. Compared with conventional probe- and biotin-dependent workflows, the present method substantially reduces cost and processing time and is compatible with simultaneous detection of segmented AmGn poly(A) tail variants. This integrated platform provides a simplified, probe-free and construct-universal for high-throughput in-process control (IPC) of mRNA therapeutics.

Gram-positive bacteria use secreted peptides and peptide-responsive transcription factors for quorum sensing. Here, we demonstrate that intracellular expression of these peptide effectors with their cognate transcription factors leads to regulation of gene expression in both in vitro and in vivo systems. Because both effector and regulatory parts can be readily expressed, complex circuits, including auto-activation schemes, can be developed, with switch-like behaviors. Moreover, the peptide effectors can be fused to proteins, enabling a direct intracellular readout of translation and potentially allowing any protein to encode regulatory interactions in cells. Our results support a foundation for regulatory circuits that extend beyond canonical components such as LacI and TetR.