ACS Sensors最新文献

Prompt and reliable bacterial identification and antibiotic susceptibility testing are vital for combating bacterial infections and drug resistance. Herein, we designed a bispecific metabolic monitoring platform that targets enzyme-catalyzed biochemical reactions for bacterial identification and antibiotic susceptibility testing. Specifically, we designed two kinds of coreshell-structured persistent luminescence nanoparticles with surface-confined red and green persistent luminescence, respectively. The persistent luminescence nanoparticles were functionalized with energy acceptors that can be specifically cleaved by bacterial enzymes. The surface-confined persistent luminescence amplified the Förster resonance energy transfer (FRET) efficacy from the nanoparticles to the surface energy acceptors, even though the diameter of the nanoparticles exceeded the critical size of FRET, which improved the sensitivity of bacterial enzyme monitoring. Due to the differentiated expression and secretion of enzymes, different species of bacteria produced discrepant red and green persistent luminescence after incubation with the persistent luminescence nanoprobes. Machine learning models were trained by the characteristic persistent luminescence patterns of bacteria for unknown bacterial identification. Prompt bacteria identification was realized, and the overall accuracy reached 100%. Moreover, the machine learning model could identify the active and inactive states of bacteria treated with antibiotics, which provided a prompt and convenient method to determine whether the bacteria were susceptible to the antibiotics. This study provides a robust method to monitor bacterial metabolism and offers a promising strategy for infection treatment, bacterial communication monitoring, and pathogenicity investigation.

Innate immunity represents the primary defense against invasive pathogens with phagocytosis playing a central role in host defense and mediating immune and inflammatory responses. However, pathogens such as Clostridium perfringens have developed strategies to overcome phagocytic clearance. Developing molecular tools to identify and target key factors in pathogenic immune evasion can deepen our understanding of host-pathogen interactions and aid in exploring novel therapeutic strategies. As a key enzyme in the sialylation process of C. perfringens, the virulence factor sialidase is a potential target for investigating pathogenic immune evasion. Herein, a "turn-on" thermally activated delayed fluorescent probe SA-HBT-PXZ is developed as a highly selective and sensitive sialidase sensor, enabling time-resolved fluorescence imaging of C. perfringens in live bacterial cells, tissue sections, and even infected mice. Furthermore, SA-HBT-PXZ is successfully employed to screen sialidase inhibitors based on prompt and delayed fluorescence emissions. The identified lead compounds effectively inhibit the activity of sialidases from C. perfringens, leading to an increased level of differentiation of macrophages into the M1 subtype. This, in turn, enhances the phagocytosis of C. perfringens and ultimately suppresses the immune escape of the bacteria. Our study provides a potential target and lead compounds for novel therapeutic strategies against C. perfringens infections.

Strand displacement amplification (SDA) is an isothermal DNA amplification technique. Herein, we developed a novel SDA system, designated All-U-Want SDA (AUW-SDA), which was used as a signal amplification strategy for the construction of nucleic acid detection biosensors. AUW-SDA is capable of target turnover and can be utilized for detection of nucleic acid sequences without available 3'-ends. Of particular significance is the ability of AUW-SDA to generate a substantial number of programmable sequences in accordance with the specifications of the sensor signal output methods, irrespective of the sequence of the target nucleic acid. We used the N gene of SARS-CoV-2 as a model target to develop a sensing platform with dual signal outputs. The colorimetric signals were generated by the G-quadruplex/hemin DNAzyme, in which the G-rich sequences were produced by AUW-SDA with a C-rich primer. On the other hand, by altering the sequence within the replaceable region of the primer, an activator sequence was obtained from AUW-SDA, which could trigger the activity of CRISPR/Cas12a, cleaving the probes modified with a fluorophore and quencher at each end and subsequently yielding the fluorescent signals. After the DNA sequences and reaction conditions were optimized, the limit of detection (LOD) values of the fluorescent and colorimetric assays were estimated to be 0.672 fM and 13.3 fM, respectively. The biosensors were utilized for biological sample detection. The reliability of the proposed method was validated against RT-qPCR results. In addition, a portable scanner-assisted high-throughput RGB analysis (PSHRA) method was developed. This method was applied to our biosensor for multilocus detection of SARS-CoV-2. The results obtained were satisfactory, indicating the potential of this approach for field testing or point-of-care (POC) diagnostics.

Solid-phase immunosorbent reactions, such as ELISA, are widely used for detecting, identifying, and quantifying protein markers. However, traditional centimeter scale well-based immunoreactors suffer from low surface-to-volume (S/V) ratios, leading to large sample consumption and a long assay time. Microfluidic technologies, particularly tubular microfluidic immunoreactors, have emerged as promising alternatives due to their high S/V ratios. Despite experimental advancements, multifactor theoretical studies on tubular microfluidic systems are limited. In this study, we present a theoretical model based on the first passage time method to analyze diffusion-controlled reaction kinetics in tubular microfluidic immunoreactors. We focus on key parameters including binding kinetics, reactor size, and solution viscosity. To validate the model, controlled laboratory experiments were conducted using our in-house developed tip optofluidic immunoassay (TOI). These experimental results confirmed the reliability of theoretical models in the behavior prediction of tubular microfluidic systems under real-world conditions. Our model revealed that accurate and rapid protein biomarker quantification requires not only the development of microscale bioreactors but also the design of next-generation probes with extraordinary binding affinity and specificity. This work offers insights into optimizing critical design parameters in future microfluidic immunoassay development, paving ways for next generation microliter-sized biomolecular analysis.

Detection of parts-per-trillion (ppt)-level acetone gas molecules at room temperature using suspended graphene on SiO₂ micropillars has rarely been achieved using solid-state devices or surface acoustic wave (SAW) sensors. This paper presents the effect of SiO₂ micropillars and suspended graphene as a guiding and sensing layer to detect acetone gas. The integration of suspended graphene with SiO₂ micropillars introduces a coupled resonance effect arising from the interaction between the mechanical vibrations of the graphene and the acoustic vibrations of the micropillars. This effect leads to the formation of hybrid resonance modes when the natural frequencies of the vibrations align. This coupling mechanism amplifies the displacement and energy of the Love wave propagating along the surface of the sensor, enhancing its overall performance. Additionally, the interaction of the Love waves with the SiO₂ micropillars and the suspended graphene generates characteristic dips in the transmission spectra. These dips correspond to the excitation of specific flexural and torsional resonance modes within the structure. A custom-fabricated SAW device, featuring micropillars with a diameter of 4 μm and heights of 1.0 and 1.2 μm, demonstrated exceptionally high sensitivity toward acetone gas at a concentration of 500 ppt. Moreover, the suspended graphene exhibited rapid response and recovery times across a wide range of acetone concentrations.

Bacterial spores are highly resilient and capable of surviving extreme conditions, making them a persistent threat in contexts such as disease transmission, food safety, and bioterrorism. Their ability to withstand conventional sterilization methods necessitates rapid and accurate detection techniques to effectively mitigate the risks they present. In this study, we introduce a surface-enhanced Raman spectroscopy (SERS) approach for detecting Bacillus thuringiensis spores by targeting calcium dipicolinate acid (CaDPA), a biomarker uniquely associated with bacterial spores. Our method uses probe sonication to disrupt spores, releasing their CaDPA, which is then detected by SERS on drop-dried supernatant mixed with gold nanorods. This simple approach enables the selective detection of CaDPA, distinguishing it from other spore components and background noise. We demonstrate detection of biogenic CaDPA from concentrations as low as 10³ spores/mL, with sensitivity reaching beyond CaDPA levels of a single spore. Finally, we show the method's robustness by detecting CaDPA from a realistic sample of fresh milk mixed with spores. These findings highlight the potential of SERS as a sensitive and specific technique for bacterial spore detection, with implications for fields requiring rapid and reliable spore identification.