A novel DNA biosensor for the ultrasensitive detection of DNA methyltransferase activity based on a high-density "hot spot" SERS substrate and rolling circle amplification strategy

Highly sensitive and reproducible SERS substrate based on ordered multi-tipped Au nanostar arrays for the detection of myocardial infarction biomarker cardiac troponin I

Acute myocardial infarction (AMI) is a severe cardiovascular disease, for which early diagnosis is critical for reducing mortality and improving patient outcomes. Cardiac troponin I (cTnI) is widely recognized as the "gold standard" biomarker for AMI due to its high specificity and sensitivity. The concentration of cTnI correlates directly with different stages of AMI. Therefore, the accurate detection of cTnI concentration is of paramount importance. However, the low concentration of cTnI in biological fluids requires ultrasensitive detection methods. In this study, we developed a sandwiched surface enhanced Raman scattering (SERS)-based biosensor composed of SERS-immune substrate, target antigen, and SERS nanotags and realized sensitive and accurate detection of cTnI. The SERS-immune substrate features an ordered, multi-tipped monolayer of Au nanostars fabricated using a three-phase interfacial self-assembly method and 4-(2-hydroxyerhyl)piperazine-1-erhanesulfonic acid (HEPES) buffer modification. Compared to Au nanosphere SERS substrates, the Au nanostar SERS substrates exhibited about a 3-fold increase in Raman enhancement and demonstrated good uniformity and batch stability. This novel SERS detection platform, leveraging dual plasmonic enhancement from both the SERS-immune substrate and SERS nanotags, achieves detection of cTnI with a limit of detection (LOD) as low as 9.09 pg mL-1 and a relative standard deviation (RSD) as low as 11.24%. Thus, the Au nanostar SERS substrates developed in this study demonstrate significant potential for rapid and accurate detection of cTnI.

Surface-Enhanced Raman Scattering (SERS) combined with machine learning enables accurate diagnosis of cervical cancer: from molecule to cell to tissue level

The rising number of cervical cancer cases is placing a heavy economic strain on the country and its people. Improving survival rates hinges on early detection, precise diagnosis, and thorough treatment. Common screening and diagnostic methods like Pap smears, HPV testing, colposcopy, and histopathological exams are used in clinical practice, but they are often costly, time-consuming, invasive, subjective, and may lack the necessary sensitivity and specificity for accurate diagnosis. Developing a quick, non-invasive, and precise method for cervical cancer screening is crucial. Raman spectroscopy offers structural insights without damaging samples, but its weak signals and interference from biological fluorescence limit its clinical use. Surface-Enhanced Raman Scattering (SERS) overcomes these challenges, and recent advances, especially when combined with machine learning, enhance cervical cancer diagnosis by enabling precise detection of tumor. This paper comprehensively reviews and summarizes the application of SERS in cervical cancer diagnosis, ranging from molecular biomarker detection to live cell level and then to tissue level diagnosis. By integrating with machine learning, it facilitates the development of accurate, non-invasive diagnosis of cervical cancer.

Bottom-Up Metasurfaces for Biotechnological Applications

Metasurfaces are the 2D counterparts of metamaterials, and their development is accelerating rapidly in the past years. This progress enables the creation of devices capable of uniquely manipulating light, with applications ranging from optical communications to remote biosensing. Metasurfaces are engineered by rational assembly of subwavelength elements, defined as meta-atoms, giving rise to unique physical properties arising from the collective behavior of meta-atoms. These meta-atoms are typically organized using effective, reproducible, and precise nanofabrication methods that require a lot of effort to achieve scalable and cost-effective metasurfaces. In contrast, bottom-up methods based on colloidal nanoparticles (NPs) have developed in the last decade as a fascinating alternative for accelerating the technological spread of metasurfaces. The present review takes stock of recent advances in the fabrication and applications of hybrid metasurfaces prepared by bottom-up methods, resulting in disordered metasurfaces. In particular, metasurfaces prepared with plasmonic NPs are emphasized for their multifold applications, which are discussed from a biotechnology perspective. However, some examples of organized metasurfaces prepared by merging bottom-up and top-down approaches are also described. Finally, leveraging the historical disordered metasurface evolution, the review draws new perspectives for random metasurface design and applications.

Aptamer-Proximity Ligation Coupled with Rolling Circle Amplification Strategy for an Ultrasensitive Analysis of Tumor-Derived Extracellular Vesicles PD-L1

Tumor-derived extracellular vesicles (T-EVs) PD-L1 are an important biomarker for predicting immunotherapy response and can help us understand the mechanism of resistance to immunotherapy. However, this is due to the interference from a large proportion of nontumor-derived EVs. It is still challenging to accurately analyze T-EVs PD-L1 in complex human fluids. Herein, a simple and ultrasensitive method based on the dual-aptamer-proximity ligation assay (PLA)-guided rolling circle amplification (RCA) for the analysis of T-EVs PD-L1 was developed. First, dual aptamers with strong binding affinity were utilized for the recognition of EpCAM and PD-L1 on EVs, and then the aptamer-based PLA occurred. With the aid of the high signal amplification ability of RCA guided by the dual-aptamer-based PLA and efficient magnetic separation, the biosensor could realize highly sensitive quantification of EpCAM and PD-L1 dual-positive EVs with a low detection limit of 7.5 particles/μL. In addition, this method based on the aptamer-PLA-guided RCA was used to discriminate cancer patients from healthy donors with 100% accuracy without additional purification. Overall, this strategy might provide a practical tool for the analysis of multiple proteins on EVs, exhibiting great potential in early cancer diagnosis and treatment.

SERS analysis of single cells and subcellular components: A review

SERS is a rapidly advancing and non-destructive technique that has been proven to be more reliable and convenient than other traditional analytical methods. Due to its sensitivity and specificity, this technique is earning its place as a routine and powerful tool in biological and medical studies, especially for the analysis of living cells and subcellular components. This paper reviewed the research progress of single-cell SERS that has been made in the last few years and discussed challenges and future perspectives of this technique. The reviewed SERS platforms have been categorized according to their nature into the following types: (1) colloid-based, substrate-based, or hybrid; (2) ligand-based or ligand-free, and (3) label-based or label-free. The advantages and disadvantages of each type and their potential applications in various fields are thoroughly discussed.

Fluorogenic RNA Aptamer-Based Amplification and Transcription Strategy for Label-free Sensing of Methyltransferase Activity in Complex Matrixes

DNA methyltransferase is significant in cellular activities and gene expression, and its aberrant expression is closely linked to various cancers during initiation and progression. Currently, there is a great demand for reliable and label-free techniques for DNA methyltransferase evaluation in tumor diagnosis and cancer therapy. Herein, a low-background fluorescent RNA aptamer-based sensing approach for label-free quantification of cytosine-guanine (CpG) dinucleotides methyltransferase (M.SssI) is reported. The fluorogenic light-up RNA aptamers-based strategy exhibits high selectivity via restriction endonuclease, padlock-based recognition, and RNA transcription. By combining rolling circle amplification (RCA), and RNA transcription with fluorescence response of RNA aptamers of Spinach-dye compound, the proposed platform exhibited efficiently ultrahigh sensitivity toward M.SssI. Eventually, the detection can be achieved in a linear range of 0.02-100 U mL-1 with a detection limit of 1.6 × 10-3 U mL-1. Owing to these superior features, the method is further applied in serum samples spiked M.SssI, which delivers a recovery ranging from 92.0 to 107.0% and a relative standard deviation <7.0%, providing a promising and practical tool for determining M.SssI in complex biological matrices.

A robust tag-free aptasensor for fluorescent detection of kanamycin assisted by signal intensification potency of rolling circle amplification

Rolling circle amplification (RCA) process as an excellent DNA amplifier strategy possesses the merits of high performance and easy operation. In this research, a sensitive RCA-based fluorescent aptasensor was fabricated for the detection of kanamycin residues in food. The aptasensing approach consisted of two main steps; immobilization of biotinylated kanamycin aptamer on streptavidin magnetic beads (SMB) and separation of free complementary strands (CS) from the SMB-aptamer/kanamycin at the first step. For the second step, RCA procedure was applied as signal magnifier and SYBR Green was added as fluorescent indicator dye. The linear relation between the aptasensor response and kanamycin concentration was obtained from 5 nM to 100 nM with the detection limit of 1.93 nM (S/N = 3). The aptasensor displayed satisfactory selectivity among other antibiotics. The developed aptasensor is reliable for monitoring kanamycin in milk as a common foodstuff.

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

A CRISPR-Cas12a integrated SERS nanoplatform with chimeric DNA/RNA hairpin guide for ultrasensitive nucleic acid detection

Background: CRISPR-Cas12a has been integrated with nanomaterial-based optical techniques, such as surface-enhanced Raman scattering (SERS), to formulate a powerful amplification-free nucleic acid detection system. However, nanomaterials impose steric hindrance to limit the accessibility of CRISPR-Cas12a to the narrow gaps (SERS hot spots) among nanoparticles (NPs) for producing a significant change in signals after nucleic acid detection. Methods: To overcome this restriction, we specifically design chimeric DNA/RNA hairpins (displacers) that can be destabilized by activated CRISPR-Cas12a in the presence of target DNA, liberating excessive RNA that can disintegrate a core-satellite nanocluster via toehold-mediated strand displacement for orchestrating a promising "on-off" nucleic acid biosensor. The core-satellite nanocluster comprises a large gold nanoparticle (AuNP) core surrounded by small AuNPs with Raman tags via DNA hybridization as an ultrabright Raman reporter, and its disassembly leads to a drastic decrease of SERS intensity as signal readouts. We further introduce a magnetic core to the large AuNPs that can facilitate their separation from the disassembled nanostructures to suppress the background for improving detection sensitivity. Results: As a proof-of-concept study, our findings showed that the application of displacers was more effective in decreasing the SERS intensity of the system and attained a better limit of detection (LOD, 10 aM) than that by directly using activated CRISPR-Cas12a, with high selectivity and stability for nucleic acid detection. Introducing magnetic-responsive functionality to our system further improves the LOD to 1 aM. Conclusion: Our work not only offers a platform to sensitively and selectively probe nucleic acids without pre-amplification but also provides new insights into the design of the CRISPR-Cas12a/SERS integrated system to resolve the steric hindrance of nanomaterials for constructing biosensors.

Self-Assembly of DNA Tiles with G-Quadruplex DNAzyme Catalytic Activity for Sensing Applications

DNA tiles form through self-assembly of a small number of DNA strands that interact through basic repeated interactions, allowing the growth of nanoscale structures seeded by molecular inputs. If an approach for catalytic signal amplification can be integrated into the resultant nanostructure, then one can anticipate biosensing or diagnostic applications mediated by DNA tile self-assembly. Here, two-dimensional DNA tiles with split quadruplexes were designed as diagnostic tools for nucleic acid sensing without the use of protein enzymes. The presence of a target sequence leads to formation of extended microscale structures with arrayed multiple G-quadruplexes across the tile plane, with catalytic activity coupled to a colorimetric reporter. Such a mechanism has potential for low-cost signal amplification using unmodified DNA without the use of protein enzymes for biosensing.

Nanoarchitectured prototypes of mesoporous silica nanoparticles for innovative biomedical applications

Despite exceptional morphological and physicochemical attributes, mesoporous silica nanoparticles (MSNs) are often employed as carriers or vectors. Moreover, these conventional MSNs often suffer from various limitations in biomedicine, such as reduced drug encapsulation efficacy, deprived compatibility, and poor degradability, resulting in poor therapeutic outcomes. To address these limitations, several modifications have been corroborated to fabricating hierarchically-engineered MSNs in terms of tuning the pore sizes, modifying the surfaces, and engineering of siliceous networks. Interestingly, the further advancements of engineered MSNs lead to the generation of highly complex and nature-mimicking structures, such as Janus-type, multi-podal, and flower-like architectures, as well as streamlined tadpole-like nanomotors. In this review, we present explicit discussions relevant to these advanced hierarchical architectures in different fields of biomedicine, including drug delivery, bioimaging, tissue engineering, and miscellaneous applications, such as photoluminescence, artificial enzymes, peptide enrichment, DNA detection, and biosensing, among others. Initially, we give a brief overview of diverse, innovative stimuli-responsive (pH, light, ultrasound, and thermos)- and targeted drug delivery strategies, along with discussions on recent advancements in cancer immune therapy and applicability of advanced MSNs in other ailments related to cardiac, vascular, and nervous systems, as well as diabetes. Then, we provide initiatives taken so far in clinical translation of various silica-based materials and their scope towards clinical translation. Finally, we summarize the review with interesting perspectives on lessons learned in exploring the biomedical applications of advanced MSNs and further requirements to be explored.