Label-free Detection for a DNA Methylation Assay Using Raman Spectroscopy

New advances in signal amplification strategies for DNA methylation detection in vitro

5-methylcytosine (5 mC) DNA methylation is a prominent epigenetic modification ubiquitous in the genome. It plays a critical role in the regulation of gene expression, maintenance of genome stability, and disease control. The potential of 5 mC DNA methylation for disease detection, prognostic information, and prediction of response to therapy is enormous. However, the quantification of DNA methylation from clinical samples remains a considerable challenge due to its low abundance (only 1% of total bases). To overcome this challenge, scientists have recently developed various signal amplification strategies to enhance the sensitivity of DNA methylation biosensors. These strategies include isothermal nucleic acid amplification and enzyme-assisted target cycling amplification, among others. This review summarizes the applications, advantages, and limitations of these signal amplification strategies over the past six years (2018-2023). Our goal is to provide new insights into the selection and establishment of DNA methylation analysis. We hope that this review will offer valuable insights to researchers in the field and facilitate further advancements in this area.

Molecular alterations in metaphase chromosomes induced by bleomycin

Chromosomes are intranuclear structures, their main function is to store and transmit genetic information during cell division. They are composed of tightly packed DNA in the form of chromatin, which is constantly exposed to various damaging factors. The resulting changes in DNA can have serious consequences (e.g. mutations) if they are not repaired or repaired incorrectly. In this article, we studied chromosomes isolated from human cervical cancer cells (HeLa) exposed to a genotoxic drug causing both single- and double-strand breaks. Specifically, we used bleomycin to induce DNA damage. We followed morphological and chemical changes in chromosomes upon damage induction. Atomic force microscopy was used to visualize the morphology of chromosomes, while Raman microspectroscopy enabled the detection of changes in the chemical structure of chromatin with the resolution close to the diffraction limit. Additionally, we extracted spectra corresponding to chromosome I or chromatin from hyperspectral Raman maps with convolutional neural networks (CNN), which were further analysed with the principal component analysis (PCA) algorithm to reveal molecular markers of DNA damage in chromosomes. The applied multimodal approach revealed simultaneous morphological and molecular changes, including chromosomal aberrations, alterations in DNA conformation, methylation pattern, and increased protein expression upon the bleomycin treatment at the level of the single chromosome.

Highly efficient, label free, ultrafast plasmonic SERS biosensor (silver nanoarrays/Si) to detect GJB2 gene expressed deafness mutations in real time validated with PCR studies

Rapid diagnostics of any gene mutations related to organ loss is highly demanded now-a days to consume time as well to reduce cost. Currently, Surface enhanced Raman spectroscopy (SERS) is evolved to be a rapid investigating tool to screen gene mutations down to single molecule sensing with regard to the design and development of substrates used for sensing. The current research focuses on particular towards direct detection of deafness mutations associated with single and dual sites related to GJB2 gene. SERS Sensor construction is achieved with plasmonic silver nanoarrays on Si (SNA/Si) substrate by effortless wet chemical methods (Reaction time: 35 s; Concentration: 20 mM). The fabricated SNA/Si facilitates direct sensing of the deafness mutations of GJB2 gene in single as well dual sites with the enhancement of plasmonic hotspots. Normal DNA DMF-33 (GGGGGG) as well as Mutant DNA at single site DMF-9 (GGGGG) were validated by their guanine fingerprint Raman bands intensity quenching for mutant DNA DMF-9 at 1366 cm-1 and 1595 cm-1 respectively. Likewise, double mutations in DMF-19 are substitutional from G to A, portrayed highly intense fingerprint of Adenine Raman bands at 739 cm-1, 1432 cm-1, 1572 cm-1 in comparison to normal DNA (DMF-33). The findings were well analyzed with Raman mapping data which carries almost 625 scans for each DNA sample. The fabricated sensor exhibited the highest sensitivity towards DNA detection down to 0.1 pg/μL with utmost reproducibility. The current study aims to bring in creation of library files for deafness mutations to facilitate clinical diagnostics in a simple and rapid approach.

SERS-based methods for the detection of genomic biomarkers of cancer

Genomic biomarkers of cancer are based on changes in nucleic acids, which include abnormal expression levels of some miRNAs, point mutations in DNA sequences, and altered levels of DNA methylation. The presence of tumor-related nucleic acids in body fluids (blood, saliva, or urine) makes it possible to achieve a non-invasive early-stage cancer diagnosis. Currently existing techniques for the discovery of nucleic acids require complex, time-consuming, costly assays and have limited multiplexing abilities. Surface-enhanced Raman spectroscopy (SERS) is a vibrational spectroscopy technique that is able to provide molecular specificity combined with trace sensitivity. SERS has gained research attention as a tool for the detection of nucleic acids because of its promising potential: label-free SERS can decrease the complexity of assays currently used with fluorescence-based detection due to the absence of the label, while labeled SERS may outperform the gold standard in terms of the multiplexing ability. The first papers about SERS-based methods for the measurement of genomic biomarkers were written in 2008, and since then, more than 150 papers have been published. The aim of this paper is to review and evaluate the proposed SERS-based methods in terms of their level of development and their potential for liquid biopsy application, as well as to contribute to their further evolution by attracting research attention to the field. This goal will be reached by grouping, on the basis of their experimental protocol, all the published manuscripts on the topic and evaluating each group in terms of its limit of detection and applicability to real body fluids. Thus, the methods are classified according to their working principles into five main groups, including capture-based, displacement-based, sandwich-based, enzyme-assisted, and specialized protocols.

Preparation and Characterization of a Nano-Inclusion Complex of Quercetin with β-Cyclodextrin and Its Potential Activity on Cancer Cells

Quercetin (QRC), a flavonoid found in foods and plants such as red wine, onions, green tea, apples, and berries, possesses remarkable anti-inflammatory and antioxidant properties. These properties make it effective in combating cancer cells, reducing inflammation, protecting against heart disease, and regulating blood sugar levels. To enhance the potential of inclusion complexes (ICs) containing β-cyclodextrin (β-CD) in cancer therapy, they were transformed into nano-inclusion complexes (NICs). In this research, NICs were synthesized using ethanol as a reducing agent in the nanoprecipitation process. By employing FT-IR analysis, it was observed that hydrogen bonds were formed between QRC and β-CD. Moreover, the IC molecules formed NICs through the aggregation facilitated by intermolecular hydrogen bonds. Proton NMR results further confirmed the occurrence of proton shielding and deshielding subsequent to the formation of NICs. The introduction of β-CDs led to the development of a distinctive feather-like structure within the NICs. The particle sizes were consistently measured around 200 nm, and both SAED and XRD patterns indicated the absence of crystalline NICs, providing supporting evidence. Through cytotoxicity and fluorescence-assisted cell-sorting analysis, the synthesized NICs showed no significant damage in the cell line of MCF-7. In comparison to QRC alone, the presence of high concentrations of NICs exhibited a lesser degree of toxicity in normal human lung fibroblast MRC-5 cells. Moreover, the individual and combined administration of both low and high concentrations of NICs effectively suppressed the growth of cancer cells (MDA-MB-231). The solubility improvement resulting from the formation of QRC-NICs with β-CD enhanced the percentage of cell survival for MCF-7 cell types.

Fused Raman spectroscopic analysis of blood and saliva delivers high accuracy for head and neck cancer diagnostics

As a rapid, label-free, non-destructive analytical measurement requiring little to no sample preparation, Raman spectroscopy shows great promise for liquid biopsy cancer detection and diagnosis. We carried out Raman analysis and mass spectrometry of plasma and saliva from more than 50 subjects in a cohort of head and neck cancer patients and benign controls (e.g., patients with benign oral masses). Unsupervised data models were built to assess diagnostic performance. Raman spectra collected from either biofluid provided moderate performance to discriminate cancer samples. However, by fusing together the Raman spectra of plasma and saliva for each patient, subsequent analytical models delivered an impressive sensitivity, specificity, and accuracy of 96.3%, 85.7%, and 91.7%, respectively. We further confirmed that the metabolites driving the differences in Raman spectra for our models are among the same ones that drive mass spectrometry models, unifying the two techniques and validating the underlying ability of Raman to assess metabolite composition. This study bolsters the relevance of Raman to provide additive value by probing the unique chemical compositions across biofluid sources. Ultimately, we show that a simple data augmentation routine of fusing plasma and saliva spectra provided significantly higher clinical value than either biofluid alone, pushing forward the potential of clinical translation of Raman spectroscopy for liquid biopsy cancer diagnostics.

Nanoplatform to Investigate Tumor-Initiating Cancer Stem Cells: Breaking the Diagnostic Barrier

Drug-resistant capacity in a small population of tumor-initiating cancer stem cells (tiCSCs) can be due to aberrant epigenetic changes. However, currently available conventional detection methods are inappropriate and cannot be applied to investigate the scarce population (tiCSCs). In addition, selective inhibitor drugs are shown to reverse epigenetic changes; however, each cancer type is discrete. Hence, it is essential to probe the resultant changes in tiCSCs even after therapy. Therefore, we have developed a multimode nanoplatform to investigate tiCSCs, detect epigenetic changes, and subsequently explore their transformation signals following drug therapy. We performed this by developing a surface-enhanced Raman scattering (SERS)-active nanoplatform integrated with n-dopant using an ultrafast laser ionization technique. The dopant functionalization enhances Raman scattering ability and permits label-free analysis of biomarkers in tiCSCs with the resolution down to the cellular level. Here, we investigated epigenetic biomarkers of tiCSCs in pancreatic and lung cancers. An extended study using inhibitor drugs demonstrates an unexpected increase of tiCSCs from lung cancer; this difference can be attributed to transformation changes in lung tiCSC. Thus, our work brings new insight into the differentiation abilities of CSCs upon epigenetic reversal, emphasizing unique perceptions in cancer treatment.

Discrimination between Carbapenem-Resistant and Carbapenem-Sensitive Klebsiella pneumoniae Strains through Computational Analysis of Surface-Enhanced Raman Spectra: a Pilot Study

In clinical settings, rapid and accurate diagnosis of antibiotic resistance is essential for the efficient treatment of bacterial infections. Conventional methods for antibiotic resistance testing are time consuming, while molecular methods such as PCR-based testing might not accurately reflect phenotypic resistance. Thus, fast and accurate methods for the analysis of bacterial antibiotic resistance are in high demand for clinical applications. In this pilot study, we isolated 7 carbapenem-sensitive Klebsiella pneumoniae (CSKP) strains and 8 carbapenem-resistant Klebsiella pneumoniae (CRKP) strains from clinical samples. Surface-enhanced Raman spectroscopy (SERS) as a label-free and noninvasive method was employed for discriminating CSKP strains from CRKP strains through computational analysis. Eight supervised machine learning algorithms were applied for sample analysis. According to the results, all supervised machine learning methods could successfully predict carbapenem sensitivity and resistance in K. pneumoniae, with a convolutional neural network (CNN) algorithm on top of all other methods. Taken together, this pilot study confirmed the application potentials of surface-enhanced Raman spectroscopy in fast and accurate discrimination of Klebsiella pneumoniae strains with different antibiotic resistance profiles. IMPORTANCE With the low-cost, label-free, and nondestructive features, Raman spectroscopy is becoming an attractive technique with great potential to discriminate bacterial infections. In this pilot study, we analyzed surfaced-enhanced Raman spectroscopy (SERS) spectra via supervised machine learning algorithms, through which we confirmed the application potentials of the SERS technique in rapid and accurate discrimination of Klebsiella pneumoniae strains with different antibiotic resistance profiles.

Optical bio-sensing of DNA methylation analysis: an overview of recent progress and future prospects

DNA methylation as one of the most important epigenetic modifications has a critical role in regulating gene expression and drug resistance in treating diseases such as cancer. Therefore, the detection of DNA methylation in the early stages of cancer plays an essential role in disease diagnosis. The majority of routine methods to detect DNA methylation are very tedious and costly. Therefore, designing easy and sensitive methods to detect DNA methylation directly and without the need for molecular methods is a hot topic issue in bioscience. Here we provide an overview on the optical biosensors (including fluorescence, FRET, SERs, colorimetric) that have been applied to detect the DNA methylation. In addition, various types of labeled and label-free reactions along with the application of molecular methods and optical biosensors have been surveyed. Also, the effect of nanomaterials on the sensitivity of detection methods is discussed. Furthermore, a comprehensive overview of the advantages and disadvantages of each method are provided. Finally, the use of microfluidic devices in the evaluation of DNA methylation and DNA damage analysis based on smartphone detection has been discussed.

Here, we provide an overview on the optical biosensors (including fluorescence, FRET, SERs, colorimetric) that have been applied to detect the DNA methylation.

Stearoyl-CoA Desaturase 1 Activity Determines the Maintenance of DNMT1-Mediated DNA Methylation Patterns in Pancreatic β-Cells

Metabolic stress, such as lipotoxicity, affects the DNA methylation profile in pancreatic β-cells and thus contributes to β-cell failure and the progression of type 2 diabetes (T2D). Stearoyl-CoA desaturase 1 (SCD1) is a rate-limiting enzyme that is involved in monounsaturated fatty acid synthesis, which protects pancreatic β-cells against lipotoxicity. The present study found that SCD1 is also required for the establishment and maintenance of DNA methylation patterns in β-cells. We showed that SCD1 inhibition/deficiency caused DNA hypomethylation and changed the methyl group distribution within chromosomes in β-cells. Lower levels of DNA methylation in SCD1-deficient β-cells were followed by lower levels of DNA methyltransferase 1 (DNMT1). We also found that the downregulation of SCD1 in pancreatic β-cells led to the activation of adenosine monophosphate-activated protein kinase (AMPK) and an increase in the activity of the NAD-dependent deacetylase sirtuin-1 (SIRT1). Furthermore, the physical association between DNMT1 and SIRT1 stimulated the deacetylation of DNMT1 under conditions of SCD1 inhibition/downregulation, suggesting a mechanism by which SCD1 exerts control over DNMT1. We also found that SCD1-deficient β-cells that were treated with compound c, an inhibitor of AMPK, were characterized by higher levels of both global DNA methylation and DNMT1 protein expression compared with untreated cells. Therefore, we found that activation of the AMPK/SIRT1 signaling pathway mediates the effect of SCD1 inhibition/deficiency on DNA methylation status in pancreatic β-cells. Altogether, these findings suggest that SCD1 is a gatekeeper that protects β-cells against the lipid-derived loss of DNA methylation and provide mechanistic insights into the mechanism by which SCD1 regulates DNA methylation patterns in β-cells and T2D-relevant tissues.

Protein Quantification and Imaging by Surface-Enhanced Raman Spectroscopy and Similarity Analysis

Protein quantification techniques such as immunoassays have been improved considerably, but they have several limitations, including time-consuming procedures, low sensitivity, and extrinsic detection. Because direct surface-enhanced Raman spectroscopy (SERS) can detect intrinsic signals of proteins, it can be used as an effective detection method. However, owing to the complexity and reliability of SERS signals, SERS is rarely adopted for quantification without a purified target protein. This study reports an efficient and effective direct SERS-based immunoassay (SERSIA) technique for protein quantification and imaging. SERSIA relies on the uniform coating of gold nanoparticles (GNPs) on a target-protein-immobilized substrate by simple centrifugation. As centrifugation induces close contact between the GNPs and target proteins, the intrinsic signals of the target protein can be detected. For quantification, the protein levels in a cell lysate are estimated using similarity analysis between antibody-only and protein-conjugated samples. This method reliably estimates the protein level at a sub-picomolar detection limit. Furthermore, this method enables quantitative imaging of immobilized protein at a micrometer range. Because this technique is fast, sensitive, and requires only one type of antibody, this approach can be a useful method to detect proteins in biological samples.

Plasmonic Gold Nanohole Array for Surface-Enhanced Raman Scattering Detection of DNA Methylation

Surface-enhanced Raman spectroscopy (SERS), which utilizes nanogaps between noble-metal nanostructures as hot spots to yield ultrasensitive SERS signals, is an outstanding label-free and straightforward tool for DNA methylation analysis. Herein, a plasmonic gold nanohole array (PGNA) with well-controlled hot spots and an open surface was designed as a SERS substrate for DNA methylation detection. A finite-difference time-domain (FDTD) simulation was first employed to investigate the electric field distributions of the PGNA as a function of the geometric parameters. The plasmonic response was tuned to 785 cm^-1 to match the ring breathing vibrational band of cytosine, the intensity change of which was revealed to be a marker of DNA methylation. Then, guided by the FDTD simulation results, the PGNA was fabricated via the electron beam lithography (EBL) technique. The fabricated PGNA had an open and easily accessible surface topology, a SERS enhancement factor of ∼10⁶, and a relative standard deviation (RSD) of 7.1% for 500 repetitions over an area of 20 × 20 μm² using 1 μM Rhodamine 6G as the Raman reporter. The fabricated PGNA was further used as a platform for determining DNA methylation. The proposed method exhibited a sensitivity for detecting 1% of methylation changes. Moreover, insight into the dynamic information on methylation events was obtained by combining principal component analysis (PCA) with 2D correlation spectroscopy analysis. Finally, clear discrimination of the different methylation sites, such as 5-methylcytosine and N6-methyladenine, was demonstrated.