Dynamic Addressing Molecular Robot (DAMR): An Effective and Efficient Trial-and-Error Approach for the Analysis of Single Nucleotide Polymorphisms.

Accurate and efficient molecular recognition plays a crucial role in the fields of molecular detection and diagnostics. Conventional trial-and-error-based molecular recognition approaches have always been challenged in distinguishing minimal differences between targets and non-targets, such as single nucleotide polymorphisms (SNPs) of oligonucleotides. To address these challenges, here, a novel concept of dynamic addressing analysis is proposed. In this concept, by dissecting the regions of the target and creating a corresponding recognizer, it is possible to eliminate the inaccuracy and inefficiency of recognition. To achieve this concept, a Dynamic Addressing Molecular Robot (DAMR), a DNA-based dynamic addressing device is developed which is capable of dynamically locating targets. DAMR is designed to first bind to the conserved region of the target while addressing the specific region dynamically until accurate recognition is achieved. DAMR has provided an approach for analyzing low-resolution targets and has been used for analyzing SNP of miR-196a2 in both cell and serum samples, which has opened new avenues for effective and efficient molecular recognition.

DNA-Programmed Four-Bit Quaternary Fluorescence Encoding (FLUCO) Enables 51-Colored Bioimaging Analysis.

Color encoding plays a crucial role in painting, digital photography, and spectral analysis. Achieving accurate, target-responsive color encoding at the molecular level has the potential to revolutionize scientific research and technological innovation, but significant challenges persist. Here, we propose a multibit DNA self-assembly system based on computer-aided design (CAD) technology, enabling accurate, target-responsive, amplified color encoding at the molecular level, termed fluorescence encoding (FLUCO). As a model, we establish a quaternary FLUCO system using four-bit DNA self-assembly, which can accurately encode 51 colors, presenting immense potential in applications such as spatial proteomic imaging and multitarget analysis. Notably, FLUCO enables the simultaneous imaging of multiple targets exceeding the limitations of channels using conventional imaging equipment, and marks the integration of computer science for molecular encoding and decoding. Overall, our work paves the way for target-responsive, controllable molecular encoding, facilitating spatial omics analysis, exfoliated cell analysis, and high-throughput liquid biopsy.

Tumor-associated antigen-specific cell imaging based on upconversion luminescence and nucleic acid rolling circle amplification.

Tumor-associated antigen (TAA)-based diagnosis has gained prominence for early tumor screening, treatment monitoring, prognostic assessment, and minimal residual disease detection. However, limitations such as low sensitivity and difficulty in extracting non-specific binding membrane proteins still exist in traditional detection methods. Upconversion luminescence (UCL) exhibits unique physical and chemical properties under wavelength near-infrared light excitation. Rolling circle amplification (RCA) is an efficient DNA amplification technique with amplification factors as high as 105. Therefore, the above two excellent techniques can be employed for highly accurate imaging analysis of tumor cells. Herein, we developed a novel nanoplatform for TAA-specific cell imaging based on UCL and RCA technology. An aptamer-primer complex selectively binds to Mucin 1 (MUC1), one of TAA on cell surface, to trigger RCA reaction, generating a large number of repetitive sequences. These sequences provide lots of binding sites for complementary signal probes, producing UCL from lanthanide-doped upconversion nanoparticles (UCNPs) after releasing quencher group. The experimental results demonstrate the specific attachment of upconversion nanomaterials to cancer cells which express a high level of MUC1, indicating the potential of UCNPs and RCA in tumor imaging.

Metabolic Glycoengineering-Programmed Nondestructive Capture of Circulating Tumor Cells.

Circulating tumor cells (CTCs) are the "seeds" for malignant tumor metastasis, and they serve as an ideal target for minimally invasive tumor diagnosis. Abnormal glycolysis in tumor cells, characterized by glycometabolism disorder, has been reported as a universal phenomenon observed in various types of tumors. This provides a potential powerful tool for universal CTC capture. However, to the best of our knowledge, no metabolic glycoengineering-based CTC capture strategies have been reported. Here, we proposed a nondestructive CTC capture method based on metabolic glycoengineering and a nanotechnology-based proximity effect, allowing for highly specific, sensitive, and universal CTC capture. To achieve this goal, cells are first labeled with DNA tags through metabolic glycoengineering and then captured through a DNA tetrahedra-functionalized dual-tentacle magnetic nanodevice. Due to the difference in metabolic performance, only tumor cells are labeled with more densely packed DNA tags and captured through enhanced intermolecular interaction mediated by the proximity effect. In summary, we have constructed a versatile platform for nondestructive CTC capture, offering a novel perspective for the application of CTC liquid biopsy in tumor diagnosis and treatment.

Synthetic biology-based bioreactor and its application in biochemical analysis.

In the past few years, synthetic biologists have established some biological elements and bioreactors composed of nucleotides under the guidance of engineering methods. Following the concept of engineering, the common bioreactor components in recent years are introduced and compared. At present, biosensors based on synthetic biology have been applied to water pollution monitoring, disease diagnosis, epidemiological monitoring, biochemical analysis and other detection fields. In this paper, the biosensor components based on synthetic bioreactors and reporters are reviewed. In addition, the applications of biosensors based on cell system and cell-free system in the detection of heavy metal ions, nucleic acid, antibiotics and other substances are presented. Finally, the bottlenecks faced by biosensors and the direction of optimization are also discussed.