Precise in-field molecular diagnostics of crop diseases by smartphone-based mutation-resolved pathogenic RNA analysis

DNAzyme-driven Z-scheme g-C3N4/V2C heterojunction reactivation for photoelectrochemical assessment of bacterial viability

Assessment of bacterial viability is vital for food and clinical biosafety, as it reveals pathogen survival and metabolic state, helping predict their potential to persist and cause illness. Herein, we presented a visible light-driven photoelectrochemical assay (termed DzPEC) designed for signal-on detection of live pathogenic bacteria. The DzPEC assay was fabricated using a DNAzyme-functionalized Z-scheme g-C3N4/V2C bio-heterojunction as a photoresposive material and SiO2 as a photoquencher. The DzPEC assay, which utilizes DNAzyme to target the metabolic endoprotein RNase H2 that is secreted into the extracellular matrix, allows for bacterial viability assessment. Leveraging the Z-scheme heterojunction with high photoactive performance, the DzPEC assay for Salmonella enterica (S. enterica), used as a bacteria model, exhibited a detection limit of 141 CFU/mL and the ability to detect live bacterial abundnace as low as 0.1 %. The DzPEC assay demonstrated a strong correlation with RT-qPCR in the detection of S. enterica contamination in complex food and clinical matrices. These findings highlighted the potential of the DzPEC assay in bacterial viability phenotyping and live bacteria-associated biosafety monitoring.

An electrochemical biosensing platform initiated simultaneously from multi-directions with programmable enzyme-free strategy for DNA variant detection

Single-nucleotide variations (SNVs) represent vital clinical and biological information in the onset and progression of many cancers, but lacking of cost-effective, high-sensitive and reliable SNVs detection method. In this study, we propose a programmable electrochemical biosensing strategy initiated simultaneously from multi-directions by enzyme-free amplifying circuit for high-sensitivity SNVs detection. Through elaborate design, we utilized the power of conventional enzyme-free catalytic reaction to activate a multidirectional initiation self-assembly process, enabling multiple amplification. This innovative cascade strategy significantly improved the amplification performance and detection sensitivity. Subsequently, KRAS gene of cancer cells was used as proof-of concept model for SNVs recognition to demonstrate the capability. With the help of cascade design, the single-base differences between SNV sequence and wild-type sequence (WT) could be differentiated and amplified effectively. Consequently, abundant Y-shaped DNA structure efficiently was induced by DNA variant to generate on the electrode surface, facilitating the incorporation of methylene blue (MB) redox indicator. Therefore, a "signal-on" electrochemical biosensing platform was constructed. Our enzyme-free biosensor achieved a low detection limit of 36 aM and a broader linear range spanning from 100 aM to 1 nM under optimal experimental conditions. The capability of proposed cascaded DNA network to detect DNA variants in complex cancer cells and serum samples indicated the potential applicability in real sample analysis.

Cobalt MOF-hybridized nanozyme catalysts breaking pH limitations for boosted chlorpyrifos sensing performance

Given the potential dangers of organophosphorus pesticides to food safety and human health, the development of a reliable and precise detection platform for pesticides is essential. In this study, we present a novel 'armor-plating' laccase-mimetic catalyst (DNA-Cu@MOFs)-based colorimetric platform, which enables stable and selective pesticide detection. The DNA-Cu@MOFs enhance catalytic stability and overcome pH limitations, enabling effective catalysis under neutral and alkaline physiological conditions, making them well-suited for practical applications in biosensor development. By combining the catalytic properties of DNA-Cu@MOFs with a high-affinity biorecognition element (acetylcholinesterase), the platform achieves a linear detection range of 3.0-90 ng mL-1 for chlorpyrifos, with a detection limit of 0.75 ng mL-1. Notably, this platform demonstrates significant stability in chlorpyrifos detection even in the presence of environmental interferents. This robust colorimetric platform offers new possibilities for pesticide detection and provides a solid foundation for the development of comprehensive and accurate pesticide monitoring systems.

Portable solutions for plant pathogen diagnostics: development, usage, and future potential

The increasing prevalence of plant pathogens presents a critical challenge to global food security and agricultural sustainability. While accurate, traditional diagnostic methods are often time-consuming, resource-intensive, and unsuitable for real-time field applications. The emergence of portable diagnostic tools represents a paradigm shift in plant disease management, offering rapid, on-site detection of pathogens with high accuracy and minimal technical expertise. This review explores portable diagnostic technologies' development, deployment, and future potential, including handheld analyzers, smartphone-integrated systems, microfluidics, and lab-on-a-chip platforms. We examine the core technologies underlying these devices, such as biosensors, nucleic acid amplification techniques, and immunoassays, highlighting their applicability to detect bacterial, viral, and fungal pathogens in diverse agricultural settings. Furthermore, the integration of these devices with digital technologies, including the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), is transforming disease surveillance and management. While portable diagnostics have clear advantages in speed, cost-effectiveness, and user accessibility, challenges related to sensitivity, durability, and regulatory standards remain. Innovations in nanotechnology, multiplex detection platforms, and personalized agriculture promise to further enhance the efficacy of portable diagnostics. By providing a comprehensive overview of current technologies and exploring future directions, this review underscores the critical role of portable diagnostics in advancing precision agriculture and mitigating the impact of plant pathogens on global food production.

Machine learning-assisted melamine-Cu nanozyme and cholinesterase integrated array for multi-category pesticide intelligent recognition

Expanding target pesticide species and intelligent pesticide recognition were formidable challenges for existing cholinesterase inhibition methods. To improve this status, multi-active Mel-Cu nanozyme with mimetic Cu-N sites was prepared for the first time. It exhibited excellent laccase-like and peroxidase-like activities, and can respond to some pesticides beyond the detected range of enzyme inhibition methods, such as glyphosate, carbendazim, fumonisulfuron, etc., through coordination and hydrogen bonding. Inspired by the signal complementarity of Mel-Cu and cholinesterase, an integrated sensor array based on the Mel-Cu laccase-like activity, Mel-Cu peroxidase-like activity, acetylcholinesterase, and butyrylcholinesterase was creatively constructed. And it could successfully discriminate 12 pesticides at 0.5-50 μg/mL, which was significantly superior to traditional enzyme inhibition methods. Moreover, on the basis of above array, a unified stepwise prediction model was built using classification and regression algorithms in machine learning, which enabled concentration-independent qualitative identification as well as precise quantitative determination of multiple pesticide targets, simultaneously. The sensing accuracy was verified by blind sample analysis, in which the species was correctly identified and the concentration was predicted within 10% error, suggesting great intelligent recognition ability. Further, the proposed method also demonstrated significant immunity to interference and practical application feasibility, providing powerful means for pesticide residue analysis.

Space-Confined Amplification for In Situ Imaging of Single Nucleic Acid and Single Pathogen on Biological Samples

Direct in situ imaging of nucleic acids on biological samples is advantageous for rapid analysis without DNA extraction. However, traditional nucleic acid amplification in aqueous solutions tends to lose spatial information because of the high mobility of molecules. Similar to a cellular matrix, hydrogels with biomimetic 3D nanoconfined spaces can limit the free diffusion of nucleic acids, thereby allowing for ultrafast in situ enzymatic reactions. In this study, hydrogel-based in situ space-confined interfacial amplification (iSCIA) is developed for direct imaging of single nucleic acid and single pathogen on biological samples without formaldehyde fixation. With a polyethylene glycol hydrogel coating, nucleic acids on the sample are nanoconfined with restricted movement, while in situ amplification can be successfully performed. As a result, the nucleic acids are lighted-up on the large-scale surface in 20 min, with a detection limit as low as 1 copy/10 cm2. Multiplex imaging with a deep learning model is also established to automatically analyze multiple targets. Furthermore, the iSCIA imaging of pathogens on plant leaves and food is successfully used to monitor plant health and food safety. The proposed technique, a rapid and flexible system for in situ imaging, has great potential for food, environmental, and clinical applications.

Preamplification-free viral RNA diagnostics with single-nucleotide resolution using MARVE, an origami paper-based colorimetric nucleic acid test

The evolution and mutation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are urgent concerns as they pose the risk of vaccine failure and increased viral transmission. However, affordable and scalable tools allowing rapid identification of SARS-CoV-2 variants are not readily available, which impedes diagnosis and epidemiological surveillance. Here we present a colorimetric nucleic acid assay named MARVE (multiplexed, preamplification-free, single-nucleotide-resolved viral evolution) that is convenient to perform and yields single-nucleotide resolution. The assay integrates nucleic acid strand displacement reactions with enzymatic amplification to colorimetrically sense viral RNA using a metal ion-incorporated DNA probe (TEprobe). We provide detailed guidelines to design TEprobes for discriminating single-nucleotide variations in viral RNAs, and to fabricate a test paper for the detection of SARS-CoV-2 variants of concern. Compared with other nucleic acid assays, our assay is preamplification-free, single-nucleotide-resolvable and results are visible via a color change. Besides, it is smartphone readable, multiplexed, quick and cheap ($0.30 per test). The protocol takes ~2 h to complete, from the design and preparation of the DNA probes and test papers (~1 h) to the detection of SARS-CoV-2 or its variants (30-45 min). The design of the TEprobes requires basic knowledge of molecular biology and familiarity with NUPACK or the Python programming language. The fabrication of the origami papers requires access to a wax printer using the CAD and PDF files provided or requires users to be familiar with AutoCAD to design new origami papers. The protocol is also applicable for designing assays to detect other pathogens and their variants.

Fructose@histone synergistically improve the performance of DNA-templated Cu NPs: rapid analysis of LAM in tuberculosis urine samples using a handheld fluorometer and a smartphone RGB camera

This study presented a nanoparticle-enhanced aptamer-recognizing homogeneous detection system combined with a portable instrument (NASPI) to quantify lipoarabinomannan (LAM). This system leveraged the high binding affinity of aptamers, the high sensitivity of nanoparticle cascade amplification, and the stabilization effect of dual stabilizers (fructose and histone), and used probe-Cu2+ to achieve LAM detection at concentrations ranging from 10 ag mL-1 to 100 fg mL-1, with a limit of detection of 3 ag mL-1 using a fluorometer. It can also be detected using an independently developed handheld fluorometer or the red-green-blue (RGB) camera of a smartphone, with a minimum detection concentration of 10 ag mL-1. We validated the clinical utility of the biosensor by testing the LAM in the urine of patients. Forty urine samples were tested, with positive LAM results in the urine of 18/20 tuberculosis (TB) cases and negative results in the urine of 6/10 latent tuberculosis infection cases and 10/10 non-TB cases. The assay results revealed a 100% specificity and a 90% sensitivity, with an area under the curve of 0.9. We believe that the NASPI biosensor can be a promising clinical tool with great potential to convert LAM into clinical indicators for TB patients.

A simple graphene oxide-based DNA purification strategy for plant pathogen detection

BACKGROUND

The on-site molecular detection of plant pathogens is particularly important for the development of sustainable agriculture. Extracting DNA from plant tissues, microbes or coexisting environments is complex, labor-intensive and time-consuming. To facilitate this process, we propose a DNA purification strategy based on graphene oxide (GO).

RESULTS

The excellent adsorption ability of GO was verified by visualizing changes in its microscopic surface and macroscopic mixture. To further optimize the DNA purification, we determined the optimal GO concentration and treatment time at 95 °C (2 mg mL-1 and 2 min, respectively). We confirmed that our strategy is effective on plant tissues and various microorganisms, and that the obtained DNA can be directly used for polymerase chain reaction amplification. Combining the proposed GO-based DNA purification method with the loop-mediated isothermal amplification method is superior, in terms of the required steps, time, cost and detection effect, to the cetyltrimethylammonium bromide method and a commercial kit for detecting plant pathogens.

CONCLUSION

We present a feasible, rapid, simple and low-cost DNA purification method with high practical value for scientific applications in plant pathogen detection. This strategy can also provide important technical support for future research on plant-microbial microenvironments. © 2024 Society of Chemical Industry.

Quantitative, high-sensitivity measurement of liquid analytes using a smartphone compass

Smartphone ubiquity has led to rapid developments in portable diagnostics. While successful, such platforms are predominantly optics-based, using the smartphone camera as the sensing interface. By contrast, magnetics-based modalities exploiting the smartphone compass (magnetometer) remain unexplored, despite inherent advantages in optically opaque, scattering or auto-fluorescing samples. Here we report smartphone analyte sensing utilizing the built-in magnetometer for signal transduction via analyte-responsive magnetic-hydrogel composites. As these hydrogels dilate in response to targeted stimuli, they displace attached magnetic material relative to the phone's magnetometer. Using a bilayer hydrogel geometry to amplify this motion allows for sensitive, optics-free, quantitative liquid-based analyte measurements that require neither any electronics nor power beyond that contained within the smartphone itself. We demonstrate this concept with glucose-specific and pH-responsive hydrogels, including glucose detection down to single-digit micromolar concentrations with potential for extension to nanomolar sensitivities. The platform is adaptable to numerous measurands, opening a path towards portable, inexpensive sensing of multiple analytes or biomarkers of interest.