Dual platform based sandwich assay surface-enhanced Raman scattering DNA biosensor for the sensitive detection of food adulteration

Label-Free Biochemical Sensing Using Processed Optical Fiber Interferometry: A Review

Over the last 20 years, optical fiber-based devices have been exploited extensively in the field of biochemical sensing, with applications in many specific areas such as the food processing industry, environmental monitoring, health diagnosis, bioengineering, disease diagnosis, and the drug industry due to their compact, label-free, and highly sensitive detection. The selective and accurate detection of biochemicals is an essential part of biosensing devices, which is to be done through effective functionalization of highly specific recognition agents, such as enzymes, DNA, receptors, etc., over the transducing surface. Among many optical fiber-based sensing technologies, optical fiber interferometry-based biosensors are one of the broadly used methods with the advantages of biocompatibility, compact size, high sensitivity, high-resolution sensing, lower detection limits, operating wavelength tunability, etc. This Review provides a comprehensive review of the fundamentals as well as the current advances in developing optical fiber interferometry-based biochemical sensors. In the beginning, a generic biosensor and its several components are introduced, followed by the fundamentals and state-of-art technology behind developing a variety of interferometry-based fiber optic sensors. These include the Mach-Zehnder interferometer, the Michelson interferometer, the Fabry-Perot interferometer, the Sagnac interferometer, and biolayer interferometry (BLI). Further, several technical reports are comprehensively reviewed and compared in a tabulated form for better comparison along with their advantages and disadvantages. Further, the limitations and possible solutions for these sensors are discussed to transform these in-lab devices into commercial industry applications. At the end, in conclusion, comments on the prospects of field development toward the commercialization of sensor technology are also provided. The Review targets a broad range of audiences including beginners and also motivates the experts helping to solve the real issues for developing an industry-oriented sensing device.

DNA-based detection of pork content in food

Determination of halal food is essential in ensuring the tranquillity of consumers, especially Muslims. Halal products mean they are free from prohibited ingredients according to Islamic law. One ingredient that is prohibited is food products containing pork and its derivatives. An accurate verification method with a fast result is necessary to meet this requirement for halal food. DNA quantification of pork is now believed to be able to make accurate and quick decisions, as DNA acts as a reservoir or biological characterization of all living things, including pigs, according to specific characteristics of molecular and connection settings. Various DNA-based methods developed include PCR, biosensor and CRISPR methods. This review discussed various DNA-based Keywords: biosensor, CRISPR, detection, DNA, pork, PCR methods, including PCR, biosensor and CRISPR, to detect pork content in food. Among these methods, CRISPR is considered the easiest, fastest and most accurate. Therefore, it is important to develop this method further in the future. In this article, we provide a short review on DNA-based methods for detection of pork content in food products.

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

SARS-CoV-2 detection by targeting four loci of viral genome using graphene oxide and gold nanoparticle DNA biosensor

The current COVID-19 pandemic outbreak poses a serious threat to public health, demonstrating the critical need for the development of effective and reproducible detection tests. Since the RT-qPCR primers are highly specific and can only be designed based on the known sequence, mutation sensitivity is its limitation. Moreover, the mutations in the severe acute respiratory syndrome β-coronavirus (SARS-CoV-2) genome led to new highly transmissible variants such as Delta and Omicron variants. In the case of mutation, RT-qPCR primers cannot recognize and attach to the target sequence. This research presents an accurate dual-platform DNA biosensor based on the colorimetric assay of gold nanoparticles and the surface-enhanced Raman scattering (SERS) technique. It simultaneously targets four different regions of the viral genome for detection of SARS-CoV-2 and its new variants prior to any sequencing. Hence, in the case of mutation in one of the target sequences, the other three probes could detect the SARS-CoV-2 genome. The method is based on visible biosensor color shift and a locally enhanced electromagnetic field and significantly amplified SERS signal due to the proximity of Sulfo-Cyanine 3 (Cy3) and AuNPs intensity peak at 1468 cm^-1. The dual-platform DNA/GO/AuNP biosensor exhibits high sensitivity toward the viral genome with a LOD of 0.16 ng/µL. This is a safe point-of-care, naked-eye, equipment-free, and rapid (10 min) detection biosensor for diagnosing COVID-19 cases at home using a nasopharyngeal sample.

Species-Specific Gene, spt5, in the Qualitative and Quantitative Detection of Boletus reticulatus

Boletus reticulatus is a wild edible fungus with high nutritional value in Yunnan Province. In this study, B. reticulatus was used as the research object to diagnose the species characteristics. A commercial kit was used to extract the DNA of various fungi, and the quality of DNA was determined by using universal fungus primers. Through sequence alignment, the spt5 gene was selected as the species-specific gene of B. reticulatus. This gene was then qualitatively and quantitatively analyzed by PCR. In the qualitative detection, the spt5 amplification products were only found in B. reticulatus which proved its good specificity. Meanwhile, SYBR Green I based quantitative PCR results were highly sensitive, and the limit of detection was 0.04 ng of genomic DNA. These experiments illustrated that spt5 is an ideal species-specific gene for the quantitative and qualitative detection of B. reticulatus. This method is also suitable for the analysis of the processed samples of B. reticulatus and the determination of the adulteration of edible wild mushrooms.

Experimentally designed chemometric models for the assay of toxic adulterants in turmeric powder

Turmeric is an indispensable culinary spice in different cultures and a principal component in traditional remedies. Toxic metanil yellow (MY), acid orange 7 (AO) and lead chromate (LCM) are deliberately added to adulterate turmeric powder. This work compares the ability of multivariate chemometric models with those of artificial intelligent networks to enhance the selectivity of spectral data for the rapid assay of these three adulterants in turmeric powder. Using a custom experimental design, we provide a data-driven optimization for the sensitive parameters of the partial least squares model (PLS), artificial neural network (ANN) and genetic algorithm (GA). The optimized models are validated using sets of genuine turmeric samples from five different geographical regions spiked with standard adulterant concentrations. The optimized GA-PLS and GA-ANN models reduce the root mean square error of prediction by 18.4%, 31.1% and 55.3% and 25.0%, 69.9% and 88.4% for MY, AO and LCM, respectively.

Magnetic-Responsive Surface-Enhanced Raman Scattering Platform with Tunable Hot Spot for Ultrasensitive Virus Nucleic Acid Detection

Surface-enhanced Raman scattering (SERS)-based biosensors are promising tools for virus nucleic acid detection. However, it remains challenging for SERS-based biosensors using a sandwiching strategy to detect long-chain nucleic acids such as nucleocapsid (N) gene of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because the extension of the coupling distance (CD) between the two tethered metallic nanostructures weakens electric field and SERS signals. Herein, we report a magnetic-responsive substrate consisting of heteoronanostructures that controls the CD for ultrasensitive and highly selective detection of the N gene of SARS-CoV-2. Significantly, our findings show that this platform reversibly shortens the CD and enhances SERS signals with a 10-fold increase in the detection limit from 1 fM to 100 aM, compared to those without magnetic modulation. The optical simulation that emulates the CD shortening process confirms the CD-dependent electric field strength and further supports the experimental results. Our study provides new insights into designing a stimuli-responsive SERS-based platform with tunable hot spots for long-chain nucleic acid detection.

CRISPR-/Cas12a-Mediated Liposome-Amplified Strategy for the Surface-Enhanced Raman Scattering and Naked-Eye Detection of Nucleic Acid and Application to Food Authenticity Screening

Surface-enhanced Raman scattering (SERS) has been recognized as a powerful tool for biosensors due to the ultrahigh sensitivity and unique fingerprint information. However, there are some limitations in trace target nucleic acid detection for the restricted signal-transducing and amplification strategies. Inspired by CRISPR/Cas12a with specific target DNA-activated collateral single-strand DNA (ssDNA) cleavage activity and liposome with signal molecule-loading properties, we first proposed a sensitive SERS-based on-site nucleic acid detection strategy mediated by CRISPR/Cas12a with trans-cleavage activity on ssDNA linkers utilized to capture liposomes. Liposomes loading two kinds of signal molecules, 4-nitrothiophenol (4-NTP) and cysteine, could achieve the dual-mode detection of target DNA with SERS and naked eye, respectively. The promptly amplified signals were initiated by the triggered breakdown of signal molecule-loaded liposomes. Emancipated 4-NTP, a biological-silent Raman reporter, would achieve highly selective and sensitive SERS measurement. Released cysteine induced the aggregation of plasmonic gold nanoparticles, leading to an obvious red to blue colorimetric shift to realize portable naked-eye detection. With this strategy, target nucleic acid concentration was dexterously converted into SERS and visualization signals and could be detected as low as 100 aM and 10 pM, respectively. The approach was also successfully applied to determine meat adulteration, achieving the detection of a low adulteration ratio in the complicated food matrix. We anticipate that this strategy will not only be regarded as a universal platform for the on-site detection of food authenticity but also broaden SERS application for the accurate determination of diverse biomarkers.

Attachment of Single-Stranded DNA to Certain SERS-Active Gold and Silver Substrates: Selected Practical Tips

Layers formed from single-stranded DNA on nanostructured plasmonic metals can be applied as “working elements” in surface–enhanced Raman scattering (SERS) sensors used to sensitively and accurately identify specific DNA fragments in various biological samples (for example, in samples of blood). Therefore, the proper formation of the desired DNA layers on SERS substrates is of great practical importance, and many research groups are working to improve the process in forming such structures. In this work, we propose two modifications of a standard method used for depositing DNA with an attached linking thiol moiety on certain SERS-active structures; the modifications yield DNA layers that generate a stronger SERS signal. We propose: (i) freezing the sample when forming DNA layers on the nanoparticles, and (ii) when forming DNA layers on SERS-active macroscopic silver substrates, using ω-substituted alkanethiols with very short alkane chains (such as cysteamine or mercaptopropionic acid) to backfill the empty spaces on the metal surface unoccupied by DNA. When 6-mercapto-1-hexanol is used to fill the unoccupied places on a silver surface (as in experiments on standard gold substrates), a quick detachment of chemisorbed DNA from the silver surface is observed. Whereas, using ω-substituted alkanethiols with a shorter alkane chain makes it possible to easily form mixed DNA/backfilling thiol monolayers. Probably, the significantly lower desorption rate of the thiolated DNA induced by alkanethiols with shorter chains is due to the lower stabilization energy in monolayers formed from such compounds.

Development and perspectives of rapid detection technology in food and environment

Food safety become a hot issue currently with globalization of food trade and food supply chains. Chemical pollution, microbial contamination and adulteration in food have attracted more attention worldwide. Contamination with antibiotics, estrogens and heavy metals in water environment and soil environment have also turn into an enormous threat to food safety. Traditional small-scale, long-term detection technologies have been unable to meet the current needs. In the monitoring process, rapid, convenient, accurate analysis and detection technologies have become the future development trend. We critically synthesizing the current knowledge of various rapid detection technology, and briefly touched upon the problem which still exist in research process. The review showed that the application of novel materials promotes the development of rapid detection technology, high-throughput and portability would be popular study directions in the future. Of course, the ultimate aim of the research is how to industrialization these technologies and apply to the market.