ACS Central Science最新文献

Enzyme-based electrochemical biosensors hold great promise for applications in health/disease monitoring, drug discovery, and environmental monitoring. However, inherently non-conductive nature of proteinaceous enzymes often hampers effective electron transfer at enzyme-electrode interface, limiting biosensor performance of enzyme bioelectrodes. To address this problem, we present an approach to synthesize polyaniline (PAN)-based conductive single enzyme nanocomposites of glucose oxidase (GOx) (denoted as PAN-GOx). To prevent multimerization of enzymes during nanocomposite synthesis and enable single enzyme wrapping, we activate GOx surface with phenylamine groups based on the programmed diffusion of reactants in the reaction solution. Subsequent in-situ polymerization enables the synthesis of nanoscale conductive PAN layer (∼2.7 nm thickness) grafted from individual GOx molecule. PAN-GOx retains 83% and 74% of its specific activity and catalytic efficiency, respectively, compared to free GOx, while demonstrating a ∼500% improved conductivity. Furthermore, PAN-GOx-based glucose biosensors show an approximately 16- and 3-fold higher sensitivity compared to biosensors prepared by using free GOx and a mixture of PAN and GOx, respectively. This study provides a facile method to fabricate conductive single enzyme nanocomposites with enhanced electron transfer, which can potentially be further modified and/or compounded with conductive materials for demonstrating high performance enzymatic bioelectrodes.

The CRISPR-Cas12a system has emerged as a promising tool for molecular diagnostics due to its indiscriminate trans-ssDNase activity. However, the sensitivity of Cas12a-based diagnostics remains insufficient for clinical use without a pre-amplification step such as loop-mediated isothermal amplification, and therefore the trans-cleavage activity of Cas12a needs to be enhanced. Here, we present a novel strategy to enhance the trans-cleavage activity of Cas12a by reducing the steric hindrance from cis-cleavage products. We have designed Cas12a variants with alanine mutations in the target strand loading (TSL) domain, resulting in reduced affinity for target strand (TS) overhangs to the catalytic site and significantly increased trans-cleavage efficiency by up to 5.8-fold. In addition, we used a novel salt dilution method to exploit the enhanced trans-cleavage activity of Cas12a under low ionic strength conditions (7-fold), significantly improving the sensitivity of our Cas12a-based detection system. To demonstrate the clinical potential of our Cas12a-based detection system, we validated its ability to detect small amounts of hepatitis B virus (HBV) DNA model using the combination of the KE1096AA Cas12a mutant and the salt dilution method, which enables the detection of DNA at atto-molar concentrations. Our strategy to enhance the trans-cleavage activity of Cas12a paves the way for the development of more sensitive and efficient Cas12a-based diagnostics.

Cancer-derived small extracellular vesicles (sEVs) in body fluids hold promise as biomarkers for cancer diagnosis. For sEV-based liquid biopsy, isolation of sEVs with a high-purity and cancer-sEV detection with an extremely high sensitivity are essential because body fluids include much higher density of normal-cell-derived sEVs and other biomolecules and bioparticles. Here, we propose an isolation-analysis-integrated cancer-diagnosis platform based on dielectrophoresis(DEP)-ELISA technique which enables a three orders of magnitude higher sensitivity over conventional ELISA method and direct cancer diagnosis from blood plasma with high accuracy. The limit of detection (LOD) for sEVs in human plasma was as low as 10⁴ sEVs/mL without a time-consuming and low-yield sEV isolation and purification process. The capability of this platform was validated by monitoring mice with cancer cell inoculation and assessing the effect of cancer-sEV-inhibiting drug. Using the developed sEV-based liquid biopsy, we diagnosed clinical samples from healthy donors (N = 39) and cancer patients (N = 90). The diagnostic accuracy was 94.2%, 98.6%, and 91.3% for breast, colon, and lung cancers, respectively. This integrated sEV isolation and analysis platform could be applied for high-sensitivity biomarker profiling and sEV-based liquid biopsy.

Here, a photoelectrochemical (PEC) immunosensor based on the FJU-200@CdSe heterostructure was developed for epidermal growth factor receptor (EGFR) detection. This is the first application of FJU-200 in PEC. After modification using CdSe quantum dots (QDs), FJU-200 and CdSe QDs formed an S-scheme heterostructure due to the interleaved energy band structure and the difference in Fermi energy (Ef) levels, which generated an efficient and stable PEC signal. When EGFR bound specifically to the antibody, a large spatial site resistance was generated, which hindered the electron transfer at the interface and the PEC signal was quenched. The proposed PEC sensing platform exhibited excellent detection performance for EGFR, with a good linear relationship with the photocurrent change value (ΔI) in the detection range of 10 fg/mL-100 ng/mL, and the detection limit was as low as 1.08 fg/mL. This work illustrates the potential electron transfer pathway between FJU-200 and CdSe QDs and creatively applies to the construction of PEC immunosensors, providing a new option for the detection of EGFR as well as other substances to be tested.

The accurate assessment of kidney dysfunction is crucial in clinical practice, necessitating the exploration of reliable biomarkers. However, current methods for measuring SDMA often fall short in terms of sensitivity and specificity. In this study, we employed phage display technology to identify high affinity peptides that specifically bind to SDMA. The selected peptide was subsequently integrated into a novel Ni-Cr layered double hydroxide-graphene oxide (NCL-GO) nanoarchitecture. We characterized the electrochemical properties of the biosensor using cyclic voltammetry, electrochemical impedance spectroscopy and differential pulse voltammetry, systematically evaluating critical parameters such as limit of detection (LOD), reproducibility, and performance in complex biological matrices including urine. The NCL-GO architecture not only enhances the surface area available for electrochemical reactions but also facilitates rapid electron transfer kinetics which are essential for the accurate quantification of small molecule, SDMA. The electrochemical biosensor exhibited an outstanding limit of detection of 0.1 ng/mL in the 0-1 ng/mL range and 7.2 ng/mL in the 1-100 ng/mL range, demonstrating exceptional sensitivity and specificity for SDMA. Furthermore, the biosensor displayed excellent reproducibility with a relative standard deviation of 4.9%. Notably, it maintained robust chirality sensing capabilities, even in complex biological fluids. These findings suggest that this biosensor could play a pivotal role in early disease diagnosis and therapeutic monitoring, ultimately improving clinical outcomes and advancing biomedical research.

The contamination of mycotoxins is a serious problem around the world. It has detrimental effects on human beings and leads to tremendous economic loss. It is essential to develop a rapid and non-destructive method for contamination recognition particularly for early alarm. In this study, the whole-cell biosensor array was constructed and employed for rapid recognition of wheat contamination by combining with machine learning algorithms. Seven key VOCs were explored through univariate coupling to multivariate analysis of orthogonal partial least squares-discrimination analysis (OPLS-DA) models. The promoters of dnaK, katG, oxyR, soxS obtained from the stress-responsive of key VOCs were fused to the bacterial operon and fabricated on the whole-cell biosensor. The constructed whole-cell biosensor array was consisted with four kinds of sensors and 18 sensor unit. The bioluminescent intensity combined with linear machine learning algorithm of partial least squares discriminant analysis (PLS-DA) and non-linear algorithms of back propagating artificial neural network (BP-ANN) and least square support vector machine (LS-SVM) were employed to establish discrimination models for mold contamination especially for early warning. The Monte-Carlo strategy was performed to generate thirty subsets for modeling to give more reliable results. As a result, the whole-cell biosensor combined with non-linear algorithm of LS-SVM was practicable for detecting mold identification for wheat early-warning with the accuracy of 97.24%. Additionally, this study provides practical and effective methods not only for wheat quality guarantee and supervision but also for other foodstuffs.

Continuous monitoring of sweat nutrients offers valuable insights into metabolic cycling and health levels. However, existing methods often lack adaptability and real-time capabilities. Here, we propose a skin-mountable flexible biosensor integrated with metal-organic framework (MOF)-derived composites for real-time monitoring of sweat ascorbic acid (AA) levels. The biosensor features a miniaturized, highly integrated system capable of an imperceptible, stretchable skin patch with dimensions of 16.9 × 9.9 × 0.1 mm³, ensuring conformal integration with curvilinear skin contours. The introduction of a copper-based MOF anchored with poly(3,4-ethylenedioxythiophene) (Cu-MOF/PEDOT) significantly enhances sensing performance toward AA, achieving a detection limit of 0.76 μM and a sensitivity of 725.7 μA/(mM·cm²). Moreover, a miniaturized flexible circuit enables wireless communication, resulting in a lightweight, wearable platform weighing only 1.3 g. Structural and electrochemical analyses confirm the favorable sensitivity, reversibility, and stability of the biosensor, while in-vivo validation in human subjects further reveals the capability to track sweat AA variations during nutrient intake and sustained exercise, showcasing its potential in metabolic cycle assessment and health management. The biosensor presents a promising avenue for scalable health monitoring using adaptable and user-friendly technologies.

This work demonstrates a novel, non-fluorescence approach to the length identification of polymerase chain reaction (PCR) and recombinase polymerase amplification (RPA) products, utilizing capillary flow velocities on paper microfluidic chips. It required only a blank paper chip, aminated microspheres, and a smartphone, with a rapid assay time and under ambient lighting. A smartphone evaluated the initial capillary flow velocities on the paper chips for the PCR and RPA products from various bacterial samples, where the pre-loaded aminated microspheres differentiated their flow velocities. Flow velocities were analyzed at different time frames and compared with the instantaneous flow velocities and interfacial tension (γ_LV) data. Subsequent error analysis justified the use of the initial time frames. A robust linear relationship could be established between the initial flow velocities against the square root of the product lengths, with R² values of 0.981 for PCR and 0.993 for RPA. The assay seemed not to have a significant dependency on the cycle numbers and initial target concentrations. This novel method can be potentially used with various paper microfluidic methods of nucleic acid amplification tests towards rapid and handheld assays.

CoRPLA (CRISPR-regulated One-pot Recombinase Polymerase Loop-mediated Amplification) is an amplicon-depleted skin-temperature operated iNAAT designed for at-home testing. It uses specially designed loop primers to enhance isothermal amplification, triggering Cas12 for in-situ amplicon depletion and signal amplification. This method addresses issues like amplicon-derived aerosol contamination and complex assay formats, enabling quantitative detection with sub-attomolar sensitivity (0.5 cps/μL). CoRPLA employs a DNA hydrogel wearable tape for real-time, colorimetric readout, allowing visual differentiation of pathogen loads. It was validated with clinical samples for SARS-CoV-2, RSV, influenza A, and HPV, successfully identifying multi-level viral loads of the positive cases with results consistent with qPCR. Offering high sensitivity while eliminating false positives from aerosol contamination, CoRPLA bridges the molecular assay from benchtop to home for daily viral infections monitoring.

Sucrose, a common sugar primarily derived from sugarcane, is a crucial national strategic resource. However, its yield is significantly affected by various serious diseases, with pokkah boeng disease being one of the most damaging. Therefore, developing a sensitive method for the accurate detection of the pokkah boeng disease pathogen is crucial for ensuring the safety of sugar. This work presents a portable dual-modal detection device, assisted by a smartphone, which is based on MoS₂@GDY, Mn₃O₄@Au nanomenzyme, cross-N DNA framework and Exo III exonuclease-assisted CHA signal amplification technology. The cross-N DNA framework provides many binding sites and is not restricted by AuNPs scattering positions, enhancing the signal output strength of the sensor. Additionally, the detection system incorporates a high-power-density capacitor to further amplify the electrochemical detection signal, increasing sensitivity by 9.1 times. Moreover, the use of electrochemical and colorimetric dual-mode detection effectively avoids mutual interference, reducing the likelihood of false positives from a single signal. Under optimized conditions, the proposed method has a linear range of 0.0001-10,000 pM, and with a detection limit of 6.1 aM (S/N=3). This high-sensitivity, high-reliability portable sensing method shows significant potential for the early detection and real-time on-site monitoring of the pokkah boeng disease pathogen.