Biosensors for waterborne virus detection: Challenges and strategies

An AI-assisted microfluidic paper-based multiplexed surface-enhanced raman scattering (SERS) biosensor with electrophoretic removal and electrical modulation for accurate acute myocardial infarction (AMI) diagnosis and prognosis

SERS detects single molecules with exceptional sensitivity. To counter the issue of selectivity faced by point-of-care, herein, an externally applied electric field that allows electrical modulation and electromigrates unbound SERS tags without multiple washing steps is successfully developed and demonstrated to improve the biosensor's selectivity and sensitivity in multiplexed detection of cTnI, HDL, and LDL in human serum at a low LoD. Ultra-sensitive detectors can detect signals from non-specifically absorbed species, and these species can cover up overlapping analyte peaks, amplifying the effect of non-specific binding. Even though antifouling molecules can prevent non-specific adsorption at the sensor interface, this approach does not completely eliminate it. Our significant findings show that an electrically regulated device can electromigrate non-specifically bound species without cross-reacting with endogenous albumin proteins. Stability, repeatability, and reproducibility were good, with an RSD of 10%. Artificial intelligence was employed to interpret and analyze high-dimensional fingerprint SERS spectra using feature selection and dimensionality reduction for accurate acute myocardial infarction diagnosis and prognosis. These machine learning methods allow quantification of cTnI, HDL, and LDL biomarkers with low RMSE. Machine learning classifiers showed strong AUROC values of 0.950 ± 0.111 and 0.884 ± 0.139 for early and recurrent AMI detection, respectively. A high negative predictive value (NPV) of ≥99% indicates an effective early AMI rule-out. In short, this work demonstrated that a simple, low-cost, electrophoretic modulated biosensor with machine learning can diagnose, rule out, and predict recurring AMI.

Recent developments in waterborne pathogen detection technologies

Waterborne pathogens find their way into water bodies through contamination of fecal discharge, stormwater run-offs, agriculture and industrial activities, and poor water infrastructure. These organisms are responsible for causing diarrheal, gastroenteritis, cholera, and typhoid diseases which raise an alarming sense on public human health due to the high mortality rate, especially in children. Several studies have indicated that these waterborne diseases can be managed by monitoring pathogens in water using traditional culture-based and molecular techniques. However, these methods have shown several setbacks such as the longer duration for detection and the inability to detect pathogens at low concentrations. Effective management of these diseases requires rapid, sensitive, highly selective, fast, and efficient economic methods to monitor pathogens in water. Since the creation of biosensors, these tools have been applied and shown the ability to detect pathogens at low concentrations. The highlights of biosensor systems are that they are fast, portable, easy to use, highly sensitive, and specific. The capabilities of biosensors have given these tools exposure to be widely applied in detecting pharmaceutical pollutants, pesticides, toxins, residues of detergents, and cosmetics from household activities in soil and water. With such difficulties faced for detecting waterborne pathogens, this review evaluates the effectiveness of technologies for waterborne pathogens detection and their drawbacks. It further highlights biosensors as the current reliable method available for detecting pathogens in water and its future capabilities in sustaining safe potable water.

Navigating the complex landscape of waterborne disease research

Waterborne pathogens and associated diseases continue to pose a significant global health challenge, requiring effective monitoring, detection, and treatment strategies. This review examines the current state of waterborne pathogen management, highlighting persistent issues and recent advancements. Here, we review cutting-edge detection methods and treatment technology, emphasizing their roles in water safety and outbreak prevention. The impact of climate change on waterborne pathogen dynamics is explored, alongside a discussion of interdisciplinary research approaches. We also aimed to investigate the crucial relationship between waterborne disease control and Sustainable Development Goals (SDGs), focusing on community engagement, well-being, water sanitation, public health policies, and international cooperation. The PRISMA protocol systematic process was used to filter papers for this study and carry out the review process. Machine learning and remote sensing techniques are promising features in the pathogen detection field. SDGs 3, 6, 11, 13, and 17 are the most closely interrelated with waterborne diseases. This review provides an in-depth overview of waterborne pathogen management, contributing to improved global water quality and public health strategies. This integrated approach aims to enhance health outcomes and promote resilience against waterborne diseases, particularly for vulnerable communities.

High Quality-Factor All-Dielectric Metacavity for Label-Free Biosensing

High sensitivity and high quality-factor are crucial for achieving outstanding sensing performance in photonic biosensors. However, strong optical field confinement and high light-biomolecule interactions on photonic surfaces are usually contradictory and challenging to satisfy simultaneously. Here, a distinctive configuration for addressing this issue is reported: embedding a nanophotonic metasurface inside a micro vertical cavity as a meta-channel (metacavity) biosensor. The analyte solution serves as the cavity medium, thereby maximizing the light-analyte interaction. Simulation validation is conducted to optimize the metacavity with high structural robustness and remarkable optical and sensing properties. Large-scale low-cost metacavity biosensors are realized by combining anodic aluminum oxide template technique and wafer bonding. Experimentally, the metacavity biosensor demonstrates a notable quality-factor (maximum 4140) and high bulk refractometric sensitivity (450 nm RIU-1), resulting in an unprecedented figure-of-merit (1670 RIU-1). Moreover, the metacavity biosensor achieves high surface sensitivity, together with a detection-limit of 119 viral copies mL-1 for label-free severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudovirus sensing, revealing remarkable performance in both bulk and surface sensing.

Towards Point-of-Care Single Biomolecule Detection Using Next Generation Portable Nanoplasmonic Biosensors: A Review

Over the past few years, nanoplasmonic biosensors have gained widespread interest for early diagnosis of diseases thanks to their simple design, low detection limit down to the biomolecule level, high sensitivity to even small molecules, cost-effectiveness, and potential for miniaturization, to name but a few benefits. These intrinsic natures of the technology make it the perfect solution for compact and portable designs that combine sampling, analysis, and measurement into a miniaturized chip. This review summarizes applications, theoretical modeling, and research on portable nanoplasmonic biosensor designs. In order to develop portable designs, three basic components have been miniaturized: light sources, plasmonic chips, and photodetectors. There are five types of portable designs: portable SPR, miniaturized components, flexible, wearable SERS-based, and microfluidic. The latter design also reduces diffusion times and allows small amounts of samples to be delivered near plasmonic chips. The properties of nanomaterials and nanostructures are also discussed, which have improved biosensor performance metrics. Researchers have also made progress in improving the reproducibility of these biosensors, which is a major obstacle to their commercialization. Furthermore, future trends will focus on enhancing performance metrics, optimizing biorecognition, addressing practical constraints, considering surface chemistry, and employing emerging technologies. In the foreseeable future, these trends will be merged to result in portable nanoplasmonic biosensors offering detection of even a single biomolecule.

Optical biosensing of monkeypox virus using novel recombinant silica-binding proteins for site-directed antibody immobilization

The efficient immobilization of capture antibodies is crucial for timely pathogen detection during global pandemic outbreaks. Therefore, we proposed a silica-binding protein featuring core functional domains (cSP). It comprises a peptide with a silica-binding tag designed to adhere to silica surfaces and tandem protein G fragments (2C2) for effective antibody capture. This innovation facilitates precise site-directed immobilization of antibodies onto silica surfaces. We applied cSP to silica-coated optical fibers, creating a fiber-optic biolayer interferometer (FO-BLI) biosensor capable of monitoring the monkeypox virus (MPXV) protein A29L in spiked clinical samples to rapidly detect the MPXV. The cSP-based FO-BLI biosensor for MPXV demonstrated a limit of detection (LOD) of 0.62 ng/mL in buffer, comparable to the 0.52 ng/mL LOD achieved using a conventional streptavidin (SA)-based FO-BLI biosensor. Furthermore, it achieved LODs of 0.77 ng/mL in spiked serum and 0.80 ng/mL in spiked saliva, exhibiting no cross-reactivity with other viral antigens. The MPXV detection process was completed within 14 min. We further proposed a cSP-based multi-virus biosensor strategy capable of detecting various pandemic strains, such as MPXV, the latest coronavirus disease (COVID) variants, and influenza A protein, to extend its versatility. The proposed cSP-modified FO-BLI biosensor has a high potential for rapidly and accurately detecting MPXV antigens, making valuable contributions to epidemiological studies.

Dual-Mode Virus Detection: Combining Electrochemical and Fluorescence Modalities for Enhanced Sensitivity and Reliability

This study introduces a dual-mode biosensor specifically designed for the quantitative detection of viruses in rapid analysis. The biosensor is unique in its use of both optical (fluorescence) and electrochemical (impedance) detection methods using the same nanocomposites, providing a dual confirmation system for virus (norovirus-like particles) quantification. The system is based on using two antibody-conjugated nanocomposites: CdSeS quantum dots and Au-N,S-GQD nanocomposites. For optical detection, the principle relies on the fluorescence quenching of CdSeS by Au-N,S-GQD in a sandwich structure with the target. Conversely, electrochemical detection is based on the change in impedance caused by the formation of the same sandwich structure. The biosensor demonstrated exceptional sensitivity, capable of detecting norovirus at concentrations of as low as femtomolar in the electrochemical method and picomolar in the optical method. In the dual-responsive concentration range from 10-13 to 10-10 M, the sensor is highly sensitive in both methods, creating significant changes in fluorescence intensity and impedance in the presence of virus. Furthermore, the biosensor exhibits a high degree of specificity, with a negligible response to nontarget proteins, even within complex test solutions. This work represents a significant advancement in the field of biosensor technology, offering a fast, accurate, and reliable method for diagnosing viral infections and diseases.

Precision epidemiology at the nexus of mathematics and nanotechnology: Unraveling the dance of viral dynamics

The intersection of mathematical modeling, nanotechnology, and epidemiology marks a paradigm shift in our battle against infectious diseases, aligning with the focus of the journal on the regulation, expression, function, and evolution of genes in diverse biological contexts. This exploration navigates the intricate dance of viral transmission dynamics, highlighting mathematical models as dual tools of insight and precision instruments, a theme relevant to the diverse sections of Gene. In the context of virology, ethical considerations loom large, necessitating robust frameworks to protect individual rights, an aspect essential in infectious disease research. Global collaboration emerges as a critical pillar in our response to emerging infectious diseases, fortified by the predictive prowess of mathematical models enriched by nanotechnology. The synergy of interdisciplinary collaboration, training the next generation to bridge mathematical rigor, biology, and epidemiology, promises accelerated discoveries and robust models that account for real-world complexities, fostering innovation and exploration in the field. In this intricate review, mathematical modeling in viral transmission dynamics and epidemiology serves as a guiding beacon, illuminating the path toward precision interventions, global preparedness, and the collective endeavor to safeguard human health, resonating with the aim of advancing knowledge in gene regulation and expression.