Biosensors and Bioelectronics

Neurotransmitters in the gut play a vital role in human health and neuroscience, and their real-time monitoring is essential for understanding underlying physiological mechanisms. However, bioelectronic systems capable of measuring neurotransmitters in vivo at the anatomical site of interest remain underdeveloped and largely depend on bulky, off-the-shelf electronic components, thereby constraining the development of systems that are both practical and minimally invasive. Here, we report a miniature ingestible pill that is capable of real-time in vivo sensing of two key neurotransmitters: serotonin (5-HT) and dopamine (DA). The system incorporates a fully printed three-electrode-based electrochemical sensor for neurotransmitter sensing and a custom application-specific integrated circuit (ASIC) that integrates all major functional blocks on a single chip, enabling a platform for fully wireless monitoring of gut neurotransmitters. The pill, measuring 5.8 mm in diameter and 19 mm in length, supports multiple electrochemical sensing techniques, including amperometry and voltammetry, with only 42 A of average current consumption. We demonstrate the ingestible platform through in vivo studies in rat animal models, enabling real-time monitoring of gut neurotransmitters.

MicroRNAs (miRNAs) are ultra-short RNA molecules characterized by high sequence homology, frequent post-transcriptional modifications, and typically low abundance, particularly in circulating biofluids. These inherent biological features present substantial technical challenges for RT-qPCR- based quantification. Consequently, the development of miRNA RT-qPCR assays has required architectural adaptations at the reverse transcription (RT) stage to generate extended cDNA templates, thereby enabling effective downstream quantitative PCR amplification. One widely adopted approach involves the enzymatic addition of a poly(A) tail to the 3' end of miRNAs, followed by poly(T)-primed universal reverse transcription, which has gained broad acceptance due to its perceived sensitivity and simplified workflow. However, independent experimental evidence indicates that this architecture does not consistently provide the level of specificity required for reliable single-nucleotide (SN) discrimination, particularly when quantifying low-abundance circulating miRNA targets, as demonstrated in our previous study. An alternative strategy relies on miRNA-specific reverse transcription using stem-loop priming has been equally well accepted. When generically generated, this approach offers certain improved specificity, but its performance in resolving single-nucleotide differences remains limited. In this article, we employed precision engineering to maximize specificity for both reverse transcription and qPCR steps. By tailoring both primer design and reaction architecture to the specific sequence features of each miRNA, we enable robust single nucleotide discrimination among these ultra-short targets. Prototype of ten different miRNova assays quantifying miRNAs whose sequences are differed in various configurations were tested on synthetic miRNA targets. For miRNova assay validation, saliva samples were elite rugby players submitted to small RNA extraction, then RT-qPCR. Spike-in of synthetic targets was applied for each quantification point to characterized the sensitivity, specificity and accuracy of the assays. Comparative analysis was performed between miRNova and two commercially available kits on the same sample set. The obtained results show a superior performance of miRNova assays allowing for sensitive and accurate quantification of miRNAs in saliva samples. Altogether, this results in modular, reproducible assays optimized for low-abundance miRNA detection in challenging biofluids, including saliva, positioning the platform beyond existing sensitivity-focused solutions toward true diagnostic-grade specificity.

Rapid and highly selective sensing of ultra-low concentration protein biomarkers remains a critical challenge important for early disease diagnosis and monitoring. Here, we use conical SiO2 nanopore-based biosensing for the rapid detection of heart-type fatty acid binding protein (H-FABP). Antibodies were covalently immobilized on the nanopore surface through siloxane chemistry. The functionalized asymmetric nanopores generate a characteristic rectifying current-voltage response, which shows a distinct shift upon binding to the target protein due to partial neutralization of the negatively charged pore surface. The sensor exhibits excellent sensitivity in the attomolar to nanomolar concentration range with a detection limit (LOD) of [~]0.4 aM. Furthermore, the platform exhibits high selectivity, distinguishing H-FABP from non-target proteins (HSA and Hb) at concentrations six orders of magnitude higher. We also demonstrate that nanopores can be regenerated using sodium hypochloride and O2 plasma treatment, enabling repeated functionalization and reuse.

Fluorogenic aptamers (FAPs) are emerging molecular probes for viral RNA and DNA sensing. However, their use in multiplexed nucleic acid sensing has been hindered by cross-reactivity and overlapping emission spectra. Here we address these limitations by introducing a fluorescence-lifetime-based multiplexed detection strategy using variants of the DNA fluorogenic aptamer Lettuce that exhibits distinct fluorescence lifetimes when complexed with the fluorogen TO1-biotin. To effectively evolve Lettuce for diverse lifetimes, we developed a large-scale screening platform, termed FAP-FLIM-NGS (fluorogenic aptamer-based fluorescence lifetime imaging microscopy on next-generation sequencing chips), which measures the fluorescence lifetimes of [~]104 Lettuce/TO1-biotin complexes directly on an Illumina MiSeq flow cell. Using this approach, three variants with markedly different lifetimes were identified: a single mutant (smC14T, 6.0 ns) and two double mutants (dmA5T/C14T, 5.2 ns, and dmA5T/T22A, 4.4 ns). To demonstrate the utility of these Lettuce variants in multiplexed detection, a set of split Lettuce probes targeting viral RNA fragments derived from SARS-CoV-2, MERS-CoV, and influenza A were designed and tested. Phasor plot analysis confirmed that these probes can robustly distinguish individual targets as well as mixtures containing any two or all three targets purely based on distinct fluorescence lifetimes of probes, thereby overcoming the challenges of cross-reactivity and spectral overlap. Beyond this proof of concept, our findings establish a generalizable strategy for engineering FAPs with customized photophysical properties, opening new avenues for next-generation diagnostics and molecular sensing technologies.

Anthracycline chemotherapeutics are commonly used as frontline treatments for a wide array of cancers. However, their administration to patients results in substantial side effects, primarily cardiotoxicity, as well as myelosuppression and gastrointestinal toxicity. Current clinical management of such side effects is solely based on a lifetime dosage limit, which inhibits their anti-tumor efficacy. Many individualized factors, including age, family history of cardiovascular disease, treatment regimen, and other co-morbidities influence drug pharmacology. Despite this heterogeneity, there is no method for determining actual organ or tumor exposure to the treatment in an individual. Here, we developed an optical nanosensor array for four anthracyclines--doxorubicin, daunorubicin, epirubicin, and idarubicin. We used single-walled carbon nanotubes as the signal transducer due to their tunable near-infrared fluorescence. We screened twelve distinct ssDNA sequences paired with seven SWCNT (n,m) species at increasing concentrations of each of the four anthracyclines. The spectral responses were then used to develop machine learning-based classification models to identify different anthracycline types and concentrations. The optimized extreme gradient boosting model was able to classify high levels of each anthracycline with 100% accuracy. Concentration-based classification by PCA was performed for each anthracycline, distinguishing low ([≤] 5 {micro}M) and high (> 5 {micro}M) concentrations. Finally, we validated the sensor performance using synthetic urine and sweat. Our findings demonstrate the potential of carbon nanotube-based sensor array to measure the pharmacokinetics of anthracyclines in patients with the goal of enhancing anti-tumor efficacy and monitoring off-target toxicities.

Continuous monitoring of protein biomarkers could transform the management of acute and chronic diseases. Despite tremendous potential, wearable health monitors have remained largely limited to metabolites and small molecules. A key challenge is the limited availability of biointerfaces that reversibly track low-abundance proteins in vivo without user intervention. Here, we present the Differential Aptalyzer, a minimally invasive hydrogel microneedle platform for continuous monitoring of proteins in skin interstitial fluid. The platform combines high-affinity antibodies for selective target capture with aptamers for reversible electrochemical signal transduction. When integrated into a differential electrochemical chip and pulse-assisted sensor regeneration, this approach enables continuous monitoring of proteins in a wearable format. Using cardiac troponin I (cTnI) as a clinically-relevant model analyte, Differential Aptalyzer offers a broad dynamic range (0.003-0.640 ng/mL) and strong specificity against interfering proteins. Importantly, this platform reliably tracks both rising and falling exogenous cTnI levels injected into healthy mice, as well as endogenously elevated cTnI in a double-knockout mouse model of coronary artery disease, demonstrating its capability in continuous protein monitoring and identifying coronary artery disease cohorts.

While high-dimensional flow cytometry plays critical roles in resolving complex cellular networks, there remains a scarcity of comprehensive panels for the simultaneous profiling of diverse mouse cell types, primarily due to the inherent difficulty of multiplexing. To address this technical gap and resolve diverse cell populations in murine models, we designed a 27-color flow cytometry panel optimized for 3-laser spectral flow cytometers. This optimized panel enables broad and simultaneous detection of 16 distinct cell subsets from both lymphoid and myeloid lineages--including T cells, B cells, plasma cells, NK cells, innate lymphoid cells, dendritic cells, monocytes, macrophages, neutrophils, eosinophils, basophils, mast cells--along with non-immune cells, such as epithelial, endothelial, fibroblast, and neuronal cells. The panel has been successfully applied to various tissues, including spleen, thymus, bone marrow, peripheral blood, mesenteric lymph nodes, peritoneal lavage fluid, gut epithelium, and lamina propria. Applying this panel to a poly(I:C) model, we successfully tracked dynamic shifts in monocyte and neutrophil populations and identified a previously unrecognized, glucocorticoid-producing cell subset via reporter expression. This panel will facilitate high-dimensional immune profiling on standard 3-laser cytometers, providing a robust tool for dissecting cellular dynamics across diverse contexts.

Continuous biochemical sensing provides valuable insights into an individuals physiological state and the mechanisms underlying pathophysiological changes. However, most existing bioanalytical methods are not compatible with continuous biochemical sensing. A major technical challenge lies in achieving rapid measurement readouts while maintaining high specificity and sensitivity in complex biological fluids. Sensitive molecular detection typically requires slow analyte-binder dissociation and long incubation to reach equilibrium, whereas rapid and frequent measurements demand fast association-dissociation kinetics that are difficult to reconcile for low-abundance analytes. To address this challenge, we introduce a sensing mechanism termed photothermal recycling (PTR), which mimics the thermal cycling process in polymerase chain reaction. Using plasmonic photothermal effects, PTR rapidly recycles binders to enable frequent measurements. We demonstrate a digital PTR assay capable of multi-hour biochemical monitoring with subpicomolar(pM) sensitivity in buffer, diluted serum, and saliva. This approach leverages localized thermal energy to dynamically modulate biomolecular recognition, offering a new bioanalytical paradigm for continuous biochemical sensing across diverse application settings.

Extracellular vesicles (EVs) are cell-secreted biological nanoparticles that play a crucial role in intercellular communication and are gaining increasing attention as diagnostic biomarkers, therapeutic agents, and drug delivery vehicles. Consequently, the development of robust and sensitive methods for their characterization is essential. Herein we present the use of a microscope-mounted nanofluidic device for direct size determination and multi-parametric (3-color) fluorescence-based phenotyping of single biological nanoparticles that are in the size range of 20-200 nm in a method we denote Nano-SMF (SMF; size and multiplexed fluorescence). We demonstrate that it is possible to accurately determine the size of nanoparticles by analyzing their one-dimensional Brownian motion during directional flow through nanochannels, achieving size distributions for monodisperse nanoparticle solutions that are on par with TEM analysis, and size discrimination of nanoparticle mixtures that is significantly improved compared to conventional nanoparticle tracking analysis (NTA). Furter, we demonstrate that the method can be applied to analyze EVs directly in minute volumes of cell supernatant, avoiding pre-isolation or concentration steps. The method was applied to phenotype CD63- and CD81-positive EVs from a human embryonic kidney cell model, demonstrating that vesicle sub-populations defined by these two tetraspanin biomarkers differ significantly in size.

Extracellular vesicles (EVs) are lipid spheres released from cells. Research utilizing EVs has met several hurdles owing to the small size of the majority of EVs and other nanoparticles (<150 nm) and the lack of detection technologies capable of providing high-throughput single particle measurements at this scale. The use of high-throughput single particle measurements is critical for the assessment of EV heterogeneity and abundance which are features often used to assess the development of isolation protocols or particle characterization. The Coulter principle, known in the field as resistive pulse sensing (RPS), has been used for several decades to size and count cells. More recently, this technology has evolved to accommodate nanoparticle analysis. In the last decade a platform utilizing microfluidic resistive pulse sensing (MRPS) has been demonstrated for nanoparticles, offering ergonomic characterization of nanoparticles along with utilizing open format data. To date, assessment of MRPS accuracy and reporting standards have not been assessed. With the aim of increasing data accuracy, ergonomics, and reporting transparency, we developed a microfluidic resistive pulse sensing post-acquisition analysis software (RPSPASS) application for automated cohort calibration, population gating, statistical output, QC plot generation, alternative data file outputs, and standardized reporting templates.

In this paper, we aim to present a new intravital cells visualization method, which is based on use of a dye called ABDS ("A Beautiful dye for staining"), which can be prepared using a marker pen and is useful for eukaryotic cell research. Using a wide range of instruments, including optical measurements, microscopy studies and wet biology techniques, we have shown that ABDS is close by properties to Rhodamine 6G dye (R6G), which is well known as endoplasmic reticulum stainer. However, by the careful examination of the ABDS and R6G images (ABDS/R6G), we have proved for the first time that these dyes also stain the cytoplasmic membranes. The significant contrast between ABDS/R6G signal from cell membrane and endoplasmic reticulum allows them to be distinguished in the fluorescence photographs. Other important properties of ABDS are its availability, simplicity in manufacturing, safety for living cells in vitro, and bright stable fluorescence, which in contrast to commercial dye like DiBAC allows us to study cells in space and time with high detalization. The paper includes a method for preparing ABDS, a data set with its characteristics, comparison with other commercial dyes, as well as examples of ABDS usage in cells research. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/717455v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@f1ceacorg.highwire.dtl.DTLVardef@137abd2org.highwire.dtl.DTLVardef@1f19efcorg.highwire.dtl.DTLVardef@1fcbc9e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA protocol for high-resolution vital staining of the cells using an inexpensive dye based on permanent marker ink is proposed. C_LIO_LIThe absorption, emission and Raman spectra of the proposed dye are presented, and a direct comparison with commercial dyes Rhodamine 6G, DiBAC and Deep Red Cell Mask dye is made. C_LIO_LIThe main characteristics of the proposed dye are low toxicity, long-term fluorescence, and the ability to separately stain the endoplasmic reticulum and cytoplasmic membrane. C_LIO_LIThe ability of the Rhodamine 6G dye to stain cell membranes also has been proved. C_LI

Tumour biomarkers such as CA125, CA15-3, CA19-9, AFP and CEA are routinely used in the oncology clinic to diagnose cancer, monitor response to therapy, and detect relapse. However, their quantification depends on immunoassay-based methods that are time-consuming, reagent-dependent, and poorly suited to resource-limited settings. Here, we present a machine learning-assisted ATR-FTIR spectroscopy approach for label-free tumour biomarker analysis to enable simple and rapid quantification at the bedside. Using principal component analysis (PCA), we first demonstrate that these five clinically relevant biomarkers are spectrally separable, with the protein-associated region (1200-1700 cm-1) providing the greatest discriminative information. We then develop partial least squares regression (PLSR) models to quantify CA125 in phosphate-buffered saline (R2 = 0.95) and in human serum across a clinically relevant concentration range, achieving reliable predictions at and above the clinical decision threshold of 35 U/mL. A semi-quantitative classification model further demonstrated robust identification of elevated CA125, with a macro-average sensitivity of 0.86 and specificity of 0.92. These results support ATR-FTIR spectroscopy as a rapid, reagent-free platform for cancer biomarker monitoring, with potential utility in resource-limited settings. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/714840v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1be9c03org.highwire.dtl.DTLVardef@f49e5eorg.highwire.dtl.DTLVardef@1c93e39org.highwire.dtl.DTLVardef@1141e6f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Precise monitoring of intracellular glucose dynamics is essential for understanding carbon flux, optimizing microbial bioprocesses, and enabling responsive control of engineered metabolic pathways. Here, we develop a modular whole-cell biosensor in Escherichia coli that converts the native glucose repression phenotype of a CAP-sensitive promoter into a tunable, glucose-inducible output using CRISPR interference (CRISPRi). By placing a guide RNA (gRNA) under the control of the CAP promoter and positioning dCas9 to target the -10 region of a constitutive promoter driving sfGFP, we created an inversion circuit in which glucose suppresses gRNA expression, thereby relieving dCas9-mediated repression and activating fluorescence. Systematic evaluation of gRNA strand orientation and target site selection revealed that template-strand targeting yielded strong repression ([~]90 %) but reduced sensing range, whereas moderately repressive non-template gRNAs ([~]27-35 % repression) enabled optimal signal inversion. The resulting biosensor demonstrated a robust, linear fluorescence response across 200 M -50 mM glucose (R{superscript 2} > 0.97), with high specificity against other sugars and a strong correlation between glucose consumption and fluorescence accumulation (R{superscript 2} {approx} 0.996). To extend the functionality of the platform, we integrated the sensor with a secreted {beta}-glucosidase module that hydrolyzes cellobiose to glucose. The biosensor accurately quantified glucose released during cellobiose degradation, with engineered strains producing up to [~]33 mM glucose from 50 mM cellobiose in a two-plasmid system. This coupling of enzymatic conversion with intracellular sensing enabled real-time, non-destructive monitoring of metabolic transitions. Together, this work establishes a programmable CRISPRi-based strategy for inverting native promoter logic and provides a sensitive, specific, and modular platform for metabolite sensing in bacteria. The approach is broadly applicable for dynamic pathway regulation, monitoring carbon fluxes, and building responsive genetic circuits in metabolic engineering and synthetic microbial ecosystems. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/717388v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@5ad035org.highwire.dtl.DTLVardef@1b77f8org.highwire.dtl.DTLVardef@1614932org.highwire.dtl.DTLVardef@c9a54_HPS_FORMAT_FIGEXP M_FIG C_FIG

Circulating tumor cells (CTCs), and especially CTC-clusters, are linked to poor prognosis and may reveal mechanisms of metastasis and treatment resistance. Therefore, developing unbiased methods for the functional characterization of CTCs in liquid biopsies is an urgent need. Here, we present an evaluation of multiplex imaging mass cytometry (IMC) to analyze CTCs in mice with human xenograft tumors. In a single-step process, IMC uses metal-labeled antibodies to simultaneously detect a large number of proteins/modifications within minimally manipulated small volumes of blood from the tail vein or heart. We used breast cancer cell lines and a patient-derived xenograft (PDX) to assess antibodies for cross-species interpretation. Along with manual verification, HALO-AI-based cell segmentation was used to identify CTCs and quantify markers. Despite some limitations regarding human-specificity, this technology can be used to investigate the effect of genetic and pharmacological interventions on the properties of single and cluster CTCs in tumor-bearing mice.

Isoprenoid quinones are ubiquitous redox lipids that mediate electron transfer in various cellular processes across all domains of life. These molecules also serve as taxonomic and metabolic markers, facilitating the characterisation of microbial communities. However, their structural diversity and extreme hydrophobicity pose challenges for comprehensive detection and quantification in complex biological matrices. In this study, we present a semi-quantitative HPLC-MS/MS method that enables the sensitive analysis of the widest range of quinones reported to date. Using a 16-quinone standard mixture, we optimized separation within a 14-minute HPLC gradient and achieved femtomole-level sensitivity in targeted analyses. When applied to sewage sludges sampled weekly over three weeks, our method detected 57 distinct quinones, revealing stage-specific quinone profiles that reflect shifts in bacterial communities during wastewater treatment. This rapid and sensitive workflow provides a robust tool for accurate quinone profiling in complex samples, opening avenues for the discovery of novel quinones through untargeted approaches. By pushing the boundaries of quinone profiling, our method holds significant promise for advancing microbial ecology, environmental monitoring, and biotechnological applications. HighlightsO_LIuHPLC-Orbitrap method for the semi-quantitative profiling of isoprenoid quinones C_LIO_LIAnalysis of the widest range of isoprenoid quinones to date C_LIO_LIFemtomole-level sensitivity in just 14 minutes of chromatographic separation C_LIO_LIDetection of 57 quinones in complex wastewater sludge matrices C_LIO_LIMost comprehensive set of quinone standards including microbially-purified quinones C_LI

Many biochemical processes are dependent on the presence or absence of molecular oxygen (O2). Palladium-tetrapyrrol derivatives can be used to measure O2-concentrations and O2-turnover during biochemical reactions and microbial growth in standard microtiter plates (MTPs). Palladium(II)-5,10,15,20-(tetrapentafluorophenyl)-porphyrin (1; CAS 72076-09-6) and Palladium(II)-5,10,15,20-(tetraphenyl)tetrabenzoporphyrin (2; CAS 119654-64-7) are introduced with this study. Spectral analyses of both compounds revealed that fluorescence quenching by O2 is not evenly distributed throughout all wavelengths and can therefore be used ratiometrically. Experimentally determined fluorescence lifetimes are around 500 {micro}s and 300 {micro}s for 1 and 2, respectively. A simple protocol is disclosed, how to immobilize the indicators on the bottom of MTP wells to give clear transparent dye doped polymer layers. We propose a straightforward procedure of how fluorescence data can be processed and calibrated in terms of O2 concentrations. Diverse applications are demonstrated and discussed, which include oxygen consumption and production by microorganisms as well as by enzymatically catalysed biochemical reactions. Various aspects are critically considered, as there are e.g. the dependence of O2 solubility on temperature and salinity, the diffusion of O2 across diverse phase boundaries, the unwanted O2 ingress into the reaction volume, the oxygen binding capacity of the MTP plastic material and the pH-dependence of the sensor layer. The findings and methods presented here open up a broad variety of high throughput assays involving changes of dissolved O2 as measurands for biochemical and biological activity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/718663v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1d3e4a9org.highwire.dtl.DTLVardef@49228borg.highwire.dtl.DTLVardef@17af5acorg.highwire.dtl.DTLVardef@19717f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

Multivalent interactions are fundamental to many biological systems, including how antibodies bind to their respective antigens. Still, their accumulated binding strength, i.e. avidity, resulting from binding and rebinding events of multiple interacting points, remains difficult to measure. Classical assay platforms like ELISA and SPR lack control over antigen positioning, limiting the resolution of the binding characteristics that shape biological outcomes at nanoscale. Here, we present PANMAP, a planar and plate-based assay inspired by ELISA that uses DNA origami to present antigens at defined nanoscale patterns, enabling direct measurements of spatially resolved binding events, termed avidity profiles. Using IgG antibodies as a model system, PANMAP distinguishes between monovalent and bivalent binding states by combining equilibrium absorbance measurements with a simple biophysical model. The avidity profiles reveal how the balance shifts between monovalent and bivalent interactions as a function of antibody concentration and antigen spacing, with intermediate separation distances favoring bivalent binding events and excluded at both near and far distances. This spatial profiling allows decoupling of affinity dependency from avidity profiles to reveal how spatial constraints influence binding equilibria. Our approach fills a longstanding gap in multivalent interaction measurement and offers a new tool for antibody engineering, development of multivalent reagents, therapeutic screening, and mechanistic immunology.

Rapid pathogen evolution, exemplified by SARS-CoV-2 during the COVID-19 pandemic, threatens public health by eroding the effectiveness of vaccines, therapeutics, and diagnostic tools through continuous viral mutation. Although spike protein targeting monoclonal antibodies (mAbs) were developed within 10-12 months of the initial outbreak to serve as key theranostic agents, their redesign has struggled to keep pace with viral evolution, rendering many neutralizing antibodies ineffective. Here we demonstrate a novel platform that integrates a random-rational hybrid library diversification with high-throughput MiSeq screening to evolve aptamers as highly versatile recognition elements that can be easily reprogrammed to bind the spike proteins of emerging SARS-CoV-2 strains. Using a repurposed next-generation sequencing (NGS) platform, interactions between 3 different spike proteins and 11,806 unique aptamer variant designs can be effectively screened within a few days. Our starting point is a 40-nt aptamer that binds strongly to the wild-type (WT) spike protein but shows reduced and no affinity toward its Delta and Omicron strains, respectively. With this starting aptamer diversified, our rapid screening method yielded one double mutant that exhibits 4-fold improvement in binding to the Delta spike protein and another double mutant that converts its binding to the Omicron spike protein from no detectable affinity to the kd of nanomolar range. A selective WT binder was also identified with no binding the two variants of interest. Using this pipeline, we identified bases not previously recognized as part of the motif that contribute critically to spike protein binding. Moreover, our pipeline integrates screening data analysis with molecular dynamics simulations, providing insights into aptamer-protein binding interactions. A sensor was developed based on the identified WT-selective binder, enabling highly specific detection of the WT spike protein with minimal cross-reactivity and robust performance in 40% serum. Together, these results demonstrate that aptamers can be rapidly optimized to bind new variants or selectively recognize a specific strain using the repurposed NGS platform. This work highlights the platform as a highly adaptive technology capable of obtaining aptamers within days to keep pace with rapidly evolving pathogens in future pandemics. TeaserA novel high-throughput MiSeq screening platform to rapidly evolve spike-protein-binding aptamers to keep pace with viral evolution.

Accurate real-time monitoring of milk quality during milking is essential for sustainable dairy farming, yet factors such as cow parity may affect the performance of near-infrared (NIR) spectroscopic sensing systems. This study investigated how cow parity (the number of calvings) impacts the reliability and accuracy of NIR spectroscopy in assessing key milk quality indicators: fat content, lactose, and somatic cell count (SCC). Experiments were conducted at Hokkaido University with two cows in their second parity. Milk spectra were recorded across 700-1050 nm using the NIR system, while fat and lactose were measured with a MilkoScan device and SCC with a Fossomatic device. Calibration models were developed using first parity, second parity, and combined datasets through partial least squares regression. Model performance was evaluated via coefficients of determination and standard errors of prediction. Results showed comparable accuracy for milk fat and SCC across parities, whereas lactose measurements were more affected. Cross-validation between first and second parity datasets further confirmed parity-dependent variations, particularly for lactose. These findings suggest that cow parity should be considered when implementing NIR-based milk quality monitoring, supporting more precise, resource-efficient, and sustainable dairy management practices.

Accelerating the development of enzymatic degradation of polyesters such as poly(ethylene terephthalate) (PET) and poly(butylene terephthalate) (PBT) requires a rapid and parallelizable detection method. We developed a protein-based biosensor for the fast and accurate quantification of the PET and PBT degradation product, terephthalate (TPA), which we named TPAsense. Engineering TPAsense required overcoming low thermal stability and aggregation of the initial construct by introducing stabilizing mutations without disrupting the binding affinity to TPA. The sensor performance was validated by screening for the PBT degrading activity of a Leaf-branch Compost Cutinase (LCC) mutant library and comparing with liquid chromatography data. TPAsense detects nanomolar concentrations of TPA enabling shorter incubation times for screening workflows. In addition, a comparative analysis of PETase and PBTase kinetics was performed with TPAsense. Finally, we demonstrated the detection of PET microplastic in samples from a wastewater treatment plant by combining the biosensor and a PETase. TPAsense offers a platform to accelerate PETase and PBTase development for plastic waste recycling and detection of microplastic in the environment.