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Highly sensitive and specific molecular detection is essential for advancing early cancer diagnosis. In this paper, we present an imaging system that combines swept source Raman spectroscopy with surface-enhanced Raman scattering (SERS) nanoparticles to enhance cancer detection capability. By incorporating a high-efficiency superconducting nanowire single-photon detector (SNSPD), the system achieves remarkable detection sensitivity to the femtomolar concentrations. This performance was demonstrated under practical conditions using only 30 mW excitation power and 40 ms wavelength point exposure time, enabling ultra-sensitive acquisition. Imaging experiments on both cell and tissue samples confirm the system’s compatibility with various biological applications. Combining high sensitivity, speed, and specificity, this platform offers a promising approach for molecular imaging and early stage cancer detection using SERS-based probes. 

Enabled by long-read sequencing technologies, particularly Single Molecule, Real-Time sequencing, N6-methyladenine (6mA) footprinting is a transformative methodology for revealing the heterogenous and dynamic distribution of nucleosomes and other DNA-binding proteins. Here, we present ipdTrimming, a novel 6mA-calling pipeline that outperforms existing tools in both computational efficiency and accuracy. Utilizing this optimized experimental and computational framework, we are able to map nucleosome positioning and transcription factor occupancy in nuclear DNA and establish high-resolution, long-range binding events in mitochondrial DNA. Our study highlights the potential of 6mA footprinting to capture coordinated nucleoprotein binding and to unravel epigenetic heterogeneity. 

Abstract DNA modifications, such as N6-methyladenine (6mA), play important roles in various processes in eukaryotes. Single-molecule, real-time (SMRT) sequencing enables the direct detection of DNA modifications without requiring special sample preparation. However, most SMRT-based studies of 6mA rely on ensemble-level consensus by combining multiple reads covering the same genomic position, which misses the single-molecule heterogeneity. While recent methods have aimed at single-molecule level detection of 6mA, limitations in sequencing platforms, resolution, accuracy, and usability restrict their application in comprehensive epigenetic studies. Here, we present SMAC (single-molecule 6mA analysis of CCS reads), a novel framework for accurately detecting 6mA at the single-molecule level using SMRT circular consensus sequencing (CCS) data from the Sequel II system. It is an automated method that streamlines the entire workflow by packaging both existing softwares and built-in scripts, with user-defined parameters to allow easy adaptation for various studies. By utilizing the statistical distribution characteristics of enzyme kinetic indicators on single DNA molecules rather than a fixed cutoff, SMAC significantly improves 6mA detection accuracy at the single-nucleotide and single-molecule levels. It simplifies analysis by providing comprehensive information, including quality control, statistical analysis, and site visualization, directly from raw sequencing data. SMAC is a powerful new tool that enables de novo detection of 6mA and empowers investigation of its functions in modulating physiological processes. 

Abstract N⁶-adenine methylation occurs in both DNA and RNA (referred to as 6mA and m6A, respectively). As an extensively characterized epi-transcriptomic mark found in virtually all eukaryotes, m6A in mRNA is deposited by METTL3-METTL14 complex. As a transcription-associated epigenetic mark abundantly present in many unicellular eukaryotes, 6mA is coordinately maintained by two AMT1 complexes, distinguished by their mutually exclusive subunits, AMT6 and AMT7. These are all members of MT-A70 family methyltransferases (MTases). Despite their functional importance, no structure for holo-complexes with cognate DNA/RNA substrate has been resolved. Here, we employ AlphaFold3 (AF3) and molecular dynamics (MD) simulations for structural modeling ofTetrahymenaAMT1 complexes, with emphasis on ternary holo-complexes with double-stranded DNA (dsDNA) substrate and cofactor. Key structural features observed in these models are validated by mutagenesis and various other biophysical and biochemical approaches. Our analysis reveals the structural basis for DNA substrate recognition, base flipping, and catalysis in the prototypical eukaryotic DNA 6mA-MTase. It also allows us to delineate the reaction pathway for processive DNA methylation involving translocation of the closed form AMT1 complex along dsDNA. As the active site is highly conserved across MT-A70 family of eukaryotic 6mA/m6A-MTases, the structural insight will facilitate rational design of small molecule inhibitors, especially for METTL3-METTL14, a promising target in cancer therapeutics. 

Abstract N6‐adenine (6mA) DNA methylation plays an important role in gene regulation and genome stability. The 6mA methylation inTetrahymena thermophilais mainly mediated by the AMT complex, comprised of the AMT1, AMT7, AMTP1, and AMTP2 subunits. To date, how this complex assembles on the DNA substrate remains elusive. Here we report the structure of the AMT complex bound to the OCR protein from bacteriophage T7, mimicking the AMT–DNA encounter complex. The AMT1–AMT7 heterodimer approaches OCR from one side, while the AMTP1 N‐terminal domain, assuming a homeodomain fold, binds to OCR from the other side, resulting in a saddle‐shaped architecture reminiscent of what was observed for prokaryotic 6mA writers. Mutation of the AMT1, AMT7, and AMTP1 residues on the OCR‐contact points led to impaired DNA methylation activity to various extents, supporting a role for these residues in DNA binding. Furthermore, structural comparison of the AMT1–AMT7 subunits with the evolutionarily related METTL3–METTL14 and AMT1–AMT6 complexes reveals sequence conservation and divergence in the region corresponding to the OCR‐binding site, shedding light on the substrate binding of the latter two complexes. Together, this study supports a model in which the AMT complex undergoes a substrate binding‐induced open‐to‐closed conformational transition, with implications in its substrate binding and processive 6mA methylation. 

Imaging of surface-enhanced Raman scattering (SERS) nanoparticles (NPs) has been intensively studied for cancer detection due to its high sensitivity, unconstrained low signal-to-noise ratios, and multiplexing detection capability. Furthermore, conjugating SERS NPs with various biomarkers is straightforward, resulting in numerous successful studies on cancer detection and diagnosis. However, Raman spectroscopy only provides spectral data from an imaging area without co-registered anatomic context. This is not practical and suitable for clinical applications. Here, we propose a custom-made Raman spectrometer with computer-vision-based positional tracking and monocular depth estimation using deep learning (DL) for the visualization of 2D and 3D SERS NPs imaging, respectively. In addition, the SERS NPs used in this study (hyaluronic acid-conjugated SERS NPs) showed clear tumor targeting capabilities (target CD44 typically overexpressed in tumors) by anex vivoexperiment and immunohistochemistry. The combination of Raman spectroscopy, image processing, and SERS molecular imaging, therefore, offers a robust and feasible potential for clinical applications.