Research progress on application of single-cell TCR/BCR sequencing technology to the tumor immune microenvironment, autoimmune diseases, and infectious diseases.

Single-cell omics is the profiling of individual cells through sequencing and other technologies including high-throughput analysis for single-cell resolution, cell classification, and identification as well as time series analyses. Unlike multicellular studies, single-cell omics overcomes the problem of cellular heterogeneity. It provides new methods and perspectives for in-depth analyses of the behavior and mechanism of individual cells in the cell population and their relationship with the body, and plays an important role in basic research and precision medicine. Single-cell sequencing technologies mainly include single-cell transcriptome sequencing, single-cell assay for transposase accessible chromatin with high-throughput sequencing, single-cell immune profiling (single-cell T-cell receptor [TCR]/B-cell receptor [BCR] sequencing), and single-cell transcriptomics. Single-cell TCR/BCR sequencing can be used to obtain a large amount of single-cell gene expression and immunomics data at one time, and combined with transcriptome sequencing and TCR/BCR diversity data, can resolve immune cell heterogeneity. This paper summarizes the progress in applying single-cell TCR/BCR sequencing technology to the tumor immune microenvironment, autoimmune diseases, infectious diseases, immunotherapy, and chronic inflammatory diseases, and discusses its shortcomings and prospects for future application.

The Role of Liquid Biopsy Analytes in Diagnosis, Treatment and Prognosis of Colorectal Cancer.

Colorectal cancer (CRC) is one of the most common malignant tumors of the digestive tract worldwide and is a serious threat to human life and health. CRC occurs and develops in a multi-step, multi-stage, and multi-gene process, in which abnormal gene expression plays an important role. CRC is currently diagnosed via endoscopy combined with tissue biopsy. Compared with tissue biopsy, liquid biopsy technology has received increasingly more attention and applications in the field of molecular detection due to its non-invasive, safe, comprehensive, and real-time dynamic nature. This review article discusses the application and limitations of current liquid biopsy analytes in the diagnosis, treatment, and prognosis of CRC, as well as directions for their future development.

Circular RNAs and Their Role in Exosomes.

As a novel class of endogenous non-coding RNAs discovered in recent years, circular RNAs (circRNAs) are highly conserved and stable covalently closed ring structures with no 5'-end cap or 3'-end poly(A) tail. CircRNAs are formed by reverse splicing, mainly by means of a noose structure or intron complementary pairing. Exosomes are tiny discoid vesicles with a diameter of 40-100 nm that are secreted by cells under physiological and pathological conditions. Exosomes play an important role in cell-cell communication by carrying DNA, microRNAs, mRNAs, proteins and circRNAs. In this review, we summarize the biological functions of circRNAs and exosomes, and further reveal the potential roles of exosomal circRNAs in different diseases, providing a scientific basis for the diagnosis, treatment, and prognosis of a wide variety of diseases.

Serum organic acid metabolites can be used as potential biomarkers to identify prostatitis, benign prostatic hyperplasia, and prostate cancer.

Background: Noninvasive methods for the early identify diagnosis of prostatitis, benign prostatic hyperplasia (BPH), and prostate cancer (PCa) are current clinical challenges. Methods: The serum metabolites of 20 healthy individuals and patients with prostatitis, BPH, or PCa were identified using untargeted liquid chromatography-mass spectrometry (LC-MS). In addition, targeted LC-MS was used to verify the organic acid metabolites in the serum of a validation cohort. Results: Organic acid metabolites had good sensitivity and specificity in differentiating prostatitis, BPH, and PCa. Three diagnostic models identified patients with PROSTATITIS: phenyllactic acid (area under the curve [AUC]=0.773), pyroglutamic acid (AUC=0.725), and pantothenic acid (AUC=0.721). Three diagnostic models identified BPH: citric acid (AUC=0.859), malic acid (AUC=0.820), and D-glucuronic acid (AUC=0.810). Four diagnostic models identified PCa: 3-hydroxy-3-methylglutaric acid (AUC=0.804), citric acid (AUC=0.918), malic acid (AUC=0.862), and phenyllactic acid (AUC=0.713). Two diagnostic models distinguished BPH from PCa: phenyllactic acid (AUC=0.769) and pyroglutamic acid (AUC=0.761). Three diagnostic models distinguished benign BPH from PROSTATITIS: citric acid (AUC=0.842), ethylmalonic acid (AUC=0.814), and hippuric acid (AUC=0.733). Six diagnostic models distinguished BPH from prostatitis: citric acid (AUC=0.926), pyroglutamic acid (AUC=0.864), phenyllactic acid (AUC=0.850), ethylmalonic acid (AUC=0.843), 3-hydroxy-3-methylglutaric acid (AUC=0.817), and hippuric acid (AUC=0.791). Three diagnostic models distinguished PCa patients with PROSTATITISA < 4.0 ng/mL from those with PSA > 4.0 ng/mL: 5-hydromethyl-2-furoic acid (AUC=0.749), ethylmalonic acid (AUC=0.750), and pyroglutamic acid (AUC=0.929). Conclusions: These results suggest that serum organic acid metabolites can be used as biomarkers to differentiate prostatitis, BPH, and PCa.

Bioinformatics Analysis: The Regulatory Network of hsa_circ_0007843 and hsa_circ_0007331 in Colon Cancer.

OBJECTIVE: To analyze the molecular regulation network of circular RNA (circRNA) in colon cancer (CC) by bioinformatics method. METHODS: hsa_circ_0007843 and hsa_circ_0007331 proved to be associated with CC in previous studies were chosen as the research object. ConSite database was used to predict the transcription factors associated with circRNA, and the CC-associated transcription factors were screened out after intersection. The CircInteractome database was used to predict the RNA-binding proteins (RBPs) interacting with circRNAs and screen out the CC-associated RBPs after an intersection. Furthermore, the CircInteractome database was used to predict the miRNAs interrelated with circRNAs, and the HMDD v3.2 database was used to search for miRNAs associated with CC. The target mRNAs of miRNA were predicted by the miRWalk v3.0 database. CC-associated target genes were screened out from the GeneCards database, and the upregulated genes were enriched and analyzed by the FunRich 3.1.3 software. Finally, the molecular regulatory network diagram of circRNA in CC was plotted. RESULTS: The ConSite database predicted a total of 14 common transcription factors of hsa_circ_0007843 and hsa_circ_0007331, among which Snail, SOX17, HNF3, C-FOS, and RORα-1 were related to CC. The CircInteractome database predicted that the RBPs interacting with these two circRNAs were AGO2 and EIF4A3, and both of them were related to CC. A total of 17 miRNAs interacting with hsa_circ_0007843 and hsa_circ_0007331 were predicted by CircInteractome database. miR-145-5p, miR-21, miR-330-5p, miR-326, and miR-766 were associated with CC according to the HMDDv3.2 database. miR-145-5p and miR-330-5p, lowly expressed in CC, were analyzed in the follow-up study. A total of 676 common target genes of these two miRNAs were predicted by the miRWalk3.0 database. And 57 target genes were involved in the occurrence and development of CC from the GeneCards database, with 23 genes downregulated and 34 genes upregulated. Additionally, GO analysis showed that the 34 upregulated genes were mainly enriched in biological processes such as signal transduction and cell communication. KEGG pathway analysis showed that the upregulated genes were closely related to integrin, ErbB receptor, and ALK1 signal pathways. Finally, a complete regulatory network of hsa_circ_0007843 and hsa_circ_0007331 in CC was proposed, whereby each one of the participants was either directly or indirectly associated and whose deregulation may result in CC progression. CONCLUSION: Predicting the molecular regulatory network of circRNAs by bioinformatics provides a new theoretical basis for further occurrence and development pathogenesis of CC and good guidance for future experimental research.

An Ultralocalized Cas13a Assay Enables Universal and Nucleic Acid Amplification-Free Single-Molecule RNA Diagnostics.

Existing methods for RNA diagnostics, such as reverse transcription PCR (RT-PCR), mainly rely on nucleic acid amplification (NAA) and RT processes, which are known to introduce substantial issues, including amplification bias, cross-contamination, and sample loss. To address these problems, we introduce a confinement effect-inspired Cas13a assay for single-molecule RNA diagnostics, eliminating the need for NAA and RT. This assay involves confining the RNA-triggered Cas13a catalysis system in cell-like-sized reactors to enhance local concentrations of target and reporter simultaneously, via droplet microfluidics. It achieves >10 000-fold enhancement in sensitivity when compared to the bulk Cas13a assay and enables absolute digital single-molecule RNA quantitation. We experimentally demonstrate its broad applicability for precisely counting microRNAs, 16S rRNAs, and SARS-CoV-2 RNA from synthetic sequences to clinical samples with excellent accuracy. Notably, this direct RNA diagnostic technology enables detecting a wide range of RNA molecules at the single-molecule level. Moreover, its simplicity, universality, and excellent quantification capability might render it to be a dominant rival to RT-qPCR.

Facile synthesis of ratiometric fluorescent carbon dots for pH visual sensing and cellular imaging.

A novel ratiometric emission N, S dual-doped carbon dots (N, S-CDs) were facilely developed for pH visual sensing via one-step hydrothermal method. The proposed N, S-CDs displayed intrinsic pH-sensitive behavior and exhibited ratiometric fluorescence emission (F563 nm/F645 nm) characteristic with the variation of pH values. Interestingly, a significant red shift of emission wavelength can be observed at 645 nm along with the emission at 563 nm decreased accordingly when the pH changed from 3.0 to 1.0. Simultaneously, the fluorescence of N, S-CDs aqueous solution was visually varied from yellow to red. The ratiometric pH linear response was in the region of 3.6 to 2.4 and the pKa was 2.90. Moreover, the N, S-CDs hold unique optical properties, good reversibility, superior biocompatibility and low cytotoxicity, which was further employed to monitor the intracellular pH fluctuations through the visible fluorescence changes between yellow and red. All these findings demonstrated that N, S-CDs can be utilized as the visual biosensor platform for tracking pH variations in extremely acidic environments such as gastric juice, which provided novel insights for clinical medical disease diagnosis (e.g., stomach disease detection) and other biomedical fields.

Dual-ligand functionalized carbon nanodots as green fluorescent nanosensors for cellular dual receptor-mediated targeted imaging.

The conjugation of ligands to nanoparticles as drug delivery systems that target specific cells is a promising approach for the delivery of therapeutic agents to tumor cells. Herein, we prepared green-emission fluorescent carbon nanodots (CNDs) by a facile hydrothermal method with d-(+)-glucosamine hydrochloride and l-aspartic acid as the precursors, then covalently conjugated with folate (FA), polyethyleneimine (PEI) and hyaluronic acid (HA) to develop dual ligand-decorated nanocarriers (FA-PEI-HA-CNDs) for the targeted imaging of cancer cells. FA-PEI-HA-CNDs integrated the excellent fluorescence property of CNDs, and can be used for the real-time and noninvasive location tracking of cancer cells. The cellular uptake study demonstrated that FA-PEI-HA-CNDs markedly improved the internalization efficiency in A-549 cells via folate/CD44 receptor-mediated endocytosis in comparison with that of the A549 cells pretreated with excess FA, HA, and FA and HA. Therefore, these dual folate/CD44 receptor-targeted CNDs (FA-PEI-HA-CNDs) show promising potential for cancer detection, drug delivery, and individualized treatment as performance platforms.