The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research.

Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.

BNT12, a novel hybrid peptide of opioid and neurotensin pharmacophores, produces potent central antinociception with limited side effects.

The development of multitarget opioid drugs has emerged as an attractive approach for innovative pain management with reduced side effects. In the present study, a novel hybrid peptide BNT12 containing the opioid and neurotensin (NT)-like fragments was synthesized and pharmacologically characterized. In acute radiant heat paw withdrawal test, intracerebroventricular (i.c.v.) administration of BNT12 produced potent antinociception in mice. The central antinociceptive activity of BNT12 was mainly mediated by µ-, δ-opioid receptor, neurotensin receptor type 1 (NTSR1) and 2 (NTSR2), supporting a multifunctional agonism of BNT12 in the functional assays. BNT12 also exhibited significant antinociceptive effects in spared nerve injury (SNI)-neuropathic pain, complete Freund's adjuvant (CFA)-induced inflammatory pain, acetic acid-induced visceral and formalin-induced pain after i.c.v. administration. Furthermore, BNT12 exhibited substantial reduction of acute antinociceptive tolerance, shifted the dose-response curve to the right by only 1.3-fold. It is noteworthy that BNT12 showed insignificant chronic antinociceptive tolerance at the supraspinal level. In addition, BNT12 exhibited reduced or no opioid-like side effects on conditioned place preference (CPP) response, naloxone-precipitated withdrawal response, acute hyperlocomotion, motor coordination, gastrointestinal transit, and cardiovascular responses. The present investigation demonstrated that the novel hybrid peptide BNT12 might serve as a promising analgesic candidate with limited opioid-like side effects.

Predictive model for assessing malnutrition in elderly hospitalized cancer patients: A machine learning approach.

BACKGROUND: Malnutrition is prevalent among elderly cancer patients. This study aims to develop a predictive model for malnutrition in hospitalized elderly cancer patients. METHODS: Data from January 2022 to January 2023 on cancer patients aged 60+ were collected, involving 22 variables. Key variables were identified using the LASSO (Least Absolute Shrinkage and Selection Operator) method, and nine machine learning models were tested. SHAP was used to interpret the XGBoost model. Malnutrition prevalence was assessed. RESULTS: Among 450 participants, 46.4 % were malnourished. Key predictors identified were ADL (Activities of Daily Living), ALB (Albumin), BMI (Body Mass Index) and age. XGBoost had the highest AUC of 0.945, accuracy of 0.872, and sensitivity of 0.968. Higher ADL and age increased malnutrition risk, while lower ALB and BMI reduced it. CONCLUSIONS: The XGBoost model is highly effective in detecting malnutrition in elderly cancer patients, enabling early and rapid nutritional assessments.

Age-related compositional and functional changes in the adult and breastfed buffalo rumen microbiome.

Introduction: The buffalo is an important domestic animal globally, providing milk, meat, and labor to more than 2 billion people in 67 countries. The rumen microorganisms of buffaloes play an indispensable role in enabling the healthy functionality and digestive function of buffalo organisms. Currently, there is a lack of clarity regarding the differences in the composition and function of rumen microorganisms among buffaloes at different growth stages. Methods: In this study, metagenomics sequencing technology was applied to examine the compositional and functional differences of rumen microorganisms in adult and breastfed buffaloes. Results: The results revealed that the rumen of adult buffaloes had significantly higher levels of the following dominant genera: Prevotella, UBA1711, RF16, Saccharofermentans, F23-D06, UBA1777, RUG472, and Methanobrevibacter_A. Interestingly, the dominant genera specific to the rumen of adult buffaloes showed a significant positive correlation (correlation>0.5, p-value<0.05) with both lignocellulose degradation-related carbohydrate-active enzymes (CAZymes) and immune signaling pathways activated by antigenic stimulation. The rumen of breastfed buffaloes had significantly higher levels of the following dominant genera: UBA629, CAG- 791, Selenomonas_C, Treponema_D, Succinivibrio, and RC9. Simultaneously, the rumen-dominant genera specific to breastfed buffaloes were significantly positively correlated (correlation>0.5, p-value<0.05) with CAZymes associated with lactose degradation, amino acid synthesis pathways, and antibiotic-producing pathways. Discussion: This indicates that rumen microorganisms in adult buffaloes are more engaged in lignocellulose degradation, whereas rumen microorganisms in breastfed buffaloes are more involved in lactose and amino acid degradation, as well as antibiotic production. In conclusion, these findings suggest a close relationship between differences in rumen microbes and the survival needs of buffaloes at different growth stages.

Molecular evolution of Phytocyanin gene and analysis of expression at different coloring periods in apple (Malus domestica).

BACKGROUND: PC (phytocyanin) is a class of copper-containing electron transfer proteins closely related to plant photosynthesis, abiotic stress responses growth and development in plants, and regulation of the expression of some flavonoids and phenylpropanoids, etc., however, compared with other plants, the PC gene family has not been systematically characterized in apple. RESULTS: A total of 59 MdPC gene members unevenly distributed across 12 chromosomes were identified at the genome-wide level. The proteins of the MdPC family were classified into four subfamilies based on differences in copper binding sites and glycosylation sites: Apple Early nodulin-like proteins (MdENODLs), Apple Uclacyanin-like proteins (MdUCLs), Apple Stellacyanin-like proteins (MdSCLs), and Apple Plantacyanin-like proteins (MdPLCLs). Some MdPC members with similar gene structures and conserved motifs belong to the same group or subfamily. The internal collinearity analysis revealed 14 collinearity gene pairs among members of the apple MdPC gene. Interspecific collinearity analysis showed that apple had 31 and 35 homologous gene pairs with strawberry and grape, respectively. Selection pressure analysis indicated that the MdPC gene was under purifying selection. Prediction of protein interactions showed that MdPC family members interacted strongly with the Nad3 protein. GO annotation results indicated that the MdPC gene also regulated the biosynthesis of phenylpropanoids. Chip data analysis showed that (MdSCL3, MdSCL7 and MdENODL27) were highly expressed in mature fruits and peels. Many cis-regulatory elements related to light response, phytohormones, abiotic stresses and flavonoid biosynthetic genes regulation were identified 2000 bp upstream of the promoter of the MdPC gene, and qRT-PCR results showed that gene members in Group IV (MdSCL1/3, MdENODL27) were up-regulated at all five stages of apple coloring, but the highest expression was observed at the DAF13 (day after fruit bag removal) stage. The gene members in Group II (MdUCL9, MdPLCL3) showed down-regulated or lower expression in the first four stages of apple coloring but up-regulated and highest expression in the DAF 21 stage. CONCLUSION: Herein, one objective of these findings is to provide valuable information for understanding the structure, molecular evolution, and expression pattern of the MdPC gene, another major objective in this study was designed to lay the groundwork for further research on the molecular mechanism of PC gene regulation of apple fruit coloration.

Analysis of the components of Mycobacterium tuberculosis heat-resistant antigen (Mtb-HAg) and its regulation of γδ T-cell function.

BACKGROUND: Mycobacterium tuberculosis heat-resistant antigen (Mtb-HAg) is a peptide antigen released from the mycobacterial cytoplasm into the supernatant of Mycobacterium tuberculosis (Mtb) attenuated H37Ra strain after autoclaving at 121 °C for 20 min. Mtb-HAg can specifically induce γδ T-cell proliferation in vitro. However, the exact composition of Mtb-HAg and the protein antigens that are responsible for its function are currently unknown. METHODS: Mtb-HAg extracted from the Mtb H37Ra strain was subjected to LC‒MS mass spectrometry. Twelve of the identified protein fractions were recombinantly expressed in Escherichia coli by genetic engineering technology using pET-28a as a plasmid and purified by Ni-NTA agarose resin to stimulate peripheral blood mononuclear cells (PBMCs) from different healthy individuals. The proliferation of γδ T cells and major γδ T-cell subset types as well as the production of TNF-α and IFN-γ were determined by flow cytometry. Their proliferating γδ T cells were isolated and purified using MACS separation columns, and Mtb H37Ra-infected THP-1 was co-cultured with isolated and purified γδ T cells to quantify Mycobacterium viability by counting CFUs. RESULTS: In this study, Mtb-HAg from the attenuated Mtb H37Ra strain was analysed by LC‒MS mass spectrometry, and a total of 564 proteins were identified. Analysis of the identified protein fractions revealed that the major protein components included heat shock proteins and Mtb-specific antigenic proteins. Recombinant expression of 10 of these proteins in by Escherichia coli genetic engineering technology was used to successfully stimulate PBMCs from different healthy individuals, but 2 of the proteins, EsxJ and EsxA, were not expressed. Flow cytometry results showed that, compared with the IL-2 control, HspX, GroEL1, and GroES specifically induced γδ T-cell expansion, with Vγ2δ2 T cells as the main subset, and the secretion of the antimicrobial cytokines TNF-α and IFN-γ. In contrast, HtpG, DnaK, GroEL2, HbhA, Mpt63, EsxB, and EsxN were unable to promote γδ T-cell proliferation and the secretion of TNF-α and IFN-γ. None of the above recombinant proteins were able to induce the secretion of TNF-α and IFN-γ by αß T cells. In addition, TNF-α, IFN-γ-producing γδ T cells inhibit the growth of intracellular Mtb. CONCLUSION: Activated γδ T cells induced by Mtb-HAg components HspX, GroES, GroEL1 to produce TNF-α, IFN-γ modulate macrophages to inhibit intracellular Mtb growth. These data lay the foundation for subsequent studies on the mechanism by which Mtb-HAg induces γδ T-cell proliferation in vitro, as well as the development of preventive and therapeutic vaccines and rapid diagnostic reagents.

Inhibition of miR-199b-5p reduces pathological alterations in osteoarthritis by potentially targeting Fzd6 and Gcnt2.

Osteoarthritis (OA) is a degenerative disease with a high prevalence in the elderly population, but our understanding of its mechanisms remains incomplete. Analysis of serum exosomal small RNA sequencing data from clinical patients and gene expression data from OA patient serum and cartilage obtained from the GEO database revealed a common dysregulated miRNA, miR-199b-5p. In vitro cell experiments demonstrated that miR-199b-5p inhibits chondrocyte vitality and promotes extracellular matrix degradation. Conversely, inhibition of miR-199b-5p under inflammatory conditions exhibited protective effects against damage. Local viral injection of miR-199b-5p into mice induced a decrease in pain threshold and OA-like changes. In an OA model, inhibition of miR-199b-5p alleviated the pathological progression of OA. Furthermore, bioinformatics analysis and experimental validation identified Gcnt2 and Fzd6 as potential target genes of MiR-199b-5p. Thus, these results indicated that MiR-199b-5p/Gcnt2 and Fzd6 axis might be a novel therapeutic target for the treatment of OA.

Modified Unit-Mediated Strand Displacement Reactions for Direct Detection of Single Nucleotide Variants in Active Double-Stranded DNA.

Accurate identification of single nucleotide variants (SNVs) in key driver genes holds a significant value for disease diagnosis and treatment. Fluorescent probes exhibit tremendous potential in specific, high-resolution, and rapid detection of SNVs. However, additional steps are required in most post-PCR assays to convert double-stranded DNA (dsDNA) products into single-stranded DNA (ssDNA), enabling them to possess hybridization activity to trigger subsequent reactions. This process not only prolongs the complexity of the experiment but also introduces the risk of losing target information. In this study, we proposed two strategies for enriching active double-stranded DNA, involving PCR based on obstructive groups and cleavable units. Building upon this, we explored the impact of modified units on the strand displacement reaction (SDR) and assessed their discriminatory efficacy for mutations. The results showed that detection of low variant allele frequencies (VAF) as low as 0.1% can be achieved. The proposed strategy allowed orthogonal identification of 45 clinical colorectal cancer tissue samples with 100% specificity, and the results were generally consistent with sequencing results. Compared to existing methods for enriching active targets, our approach offers a more diverse set of enrichment strategies, characterized by the advantage of being simple and fast and preserving original information to the maximum extent. The objective of this study is to offer an effective solution for the swift and facile acquisition of active double-stranded DNA. We anticipate that our work will facilitate the practical applications of SDR based on dsDNA.

A compendium of ruminant gastrointestinal phage genomes revealed a higher proportion of lytic phages than in any other environments.

BACKGROUND: Ruminants are important livestock animals that have a unique digestive system comprising multiple stomach compartments. Despite significant progress in the study of microbiome in the gastrointestinal tract (GIT) sites of ruminants, we still lack an understanding of the viral community of ruminants. Here, we surveyed its viral ecology using 2333 samples from 10 sites along the GIT of 8 ruminant species. RESULTS: We present the Unified Ruminant Phage Catalogue (URPC), a comprehensive survey of phages in the GITs of ruminants including 64,922 non-redundant phage genomes. We characterized the distributions of the phage genomes in different ruminants and GIT sites and found that most phages were organism-specific. We revealed that ~ 60% of the ruminant phages were lytic, which was the highest as compared with those in all other environments and certainly will facilitate their applications in microbial interventions. To further facilitate the future applications of the phages, we also constructed a comprehensive virus-bacteria/archaea interaction network and identified dozens of phages that may have lytic effects on methanogenic archaea. CONCLUSIONS: The URPC dataset represents a useful resource for future microbial interventions to improve ruminant production and ecological environmental qualities. Phages have great potential for controlling pathogenic bacterial/archaeal species and reducing methane emissions. Our findings provide insights into the virome ecology research of the ruminant GIT and offer a starting point for future research on phage therapy in ruminants. Video Abstract.

Synthesis of tunable thickness-to-diameter ratio microcapsules via a diffusion-controlled process for temperature-responsive release.

Designing microcapsules with a complicated functionalized shell to respond to an external stimulus has attracted much attention for triggered release; however, simplifying the synthesis process remains a significant challenge. Herein, we initially propose a novel, simple synthesis strategy that utilizes a mixed solvent as the organic phase to control the diffusion of common monomers during interfacial polymerization, resulting in the successful preparation of microcapsules with tunable thickness-to-diameter ratios (T/D). The morphology of microcapsules is confirmed by scanning electron microscopy. We also observe that the T/D of the designed microcapsules progressively increases as the diffusion of monomers occurs, and the glass transition temperature of microcapsules is controlled. Furthermore, microcapsule-based crosslinking agents are applied to investigate the crosslinking reaction of poly(vinyl chloride). Rotational rheometer results indicate that the microcapsules exhibit an excellent external stimulus response, precisely triggering release at the predetermined temperature. This simple approach for the preparation of microcapsules with tunable physical properties has great potential for triggered release in diverse applications.

The relationship between heavy metals and metabolic syndrome using machine learning.

Background: Exposure to high levels of heavy metals has been widely recognized as an important risk factor for metabolic syndrome (MetS). The main purpose of this study is to assess the associations between the level of heavy metal exposure and Mets using machine learning (ML) method. Methods: The data used in this study are from the national health and nutrition examination survey 2003-2018. According to the demographic information and heavy metal exposure level of participants, a total of 22 variables were included. Lasso was used to screen out the key variables, and 9 commonly used ML models were selected to establish the associations with the 5-fold cross validation method. Finally, we choose the SHapley Additive exPlanations (SHAP) method to explain the prediction results of Adaboost model. Results: 11,667 eligible individuals were randomly divided into two groups to train and verify the prediction model. Through lasso, characteristic variables were selected from 24 variables as predictors. The AUC (area under curve) of the models selected in this study were all greater than 0.7, and AdaBoost was the best model. The AUC value of AdaBoost was 0.807, the accuracy was 0.720, and the sensitivity was 0.792. It is noteworthy that higher levels of cadmium, body mass index, cesium, being female, and increasing age were associated with an increased probability of MetS. Conversely, lower levels of cobalt and molybdenum were linked to a decrease in the estimated probability of MetS. Conclusion: Our study highlights the AdaBoost model proved to be highly effective, precise, and resilient in detecting a correlation between exposure to heavy metals and MetS. Through the use of interpretable methods, we identified cadmium, molybdenum, cobalt, cesium, uranium, and barium as prominent contributors within the predictive model.

DNA-based molecular classifiers for the profiling of gene expression signatures.

Although gene expression signatures offer tremendous potential in diseases diagnostic and prognostic, but massive gene expression signatures caused challenges for experimental detection and computational analysis in clinical setting. Here, we introduce a universal DNA-based molecular classifier for profiling gene expression signatures and generating immediate diagnostic outcomes. The molecular classifier begins with feature transformation, a modular and programmable strategy was used to capture relative relationships of low-concentration RNAs and convert them to general coding inputs. Then, competitive inhibition of the DNA catalytic reaction enables strict weight assignment for different inputs according to their importance, followed by summation, annihilation and reporting to accurately implement the mathematical model of the classifier. We validated the entire workflow by utilizing miRNA expression levels for the diagnosis of hepatocellular carcinoma (HCC) in clinical samples with an accuracy 85.7%. The results demonstrate the molecular classifier provides a universal solution to explore the correlation between gene expression patterns and disease diagnostics, monitoring, and prognosis, and supports personalized healthcare in primary care.

Targeted plasma proteomic analysis uncovers a high-performance biomarker panel for early diagnosis of gastric cancer.

BACKGROUND: Gastric cancer (GC) is characterized by high morbidity, high mortality and low early diagnosis rate. Early diagnosis plays a crucial role in radically treating GC. The aim of this study was to identify plasma biomarkers for GC and early GC diagnosis. METHODS: We quantified 369 protein levels with plasma samples from discovery cohort (n = 88) and validation cohort (n = 50) via high-throughput proximity extension assay (PEA) utilizing the Olink-Explore-384-Cardiometabolic panel. The multi-protein signatures were derived from LASSO and Ridge regression models. RESULTS: In the discovery cohort, 13 proteins (GDF15, ITIH3, BOC, DPP7, EGFR, AMY2A, CCDC80, CD163, GPNMB, LTBP2, CTSZ, CCL18 and NECTIN2) were identified to distinguish GC (Stage I-IV) and early GC (HGIN-I) groups from control group with AUC of 0.994 and AUC of 0.998, severally. The validation cohort yielded AUC of 0.930 and AUC of 0.818 for GC and early GC, respectively. CONCLUSIONS: This study identified a multi-protein signature with the potential to benefit clinical GC diagnosis, especially for Asian and early GC patients, which may contribute to the development of a less-invasive, convenient, and efficient early screening tool, promoting early diagnosis and treatment of GC and ultimately improving patient survival.

Peripheral inflammation triggering central anxiety through the hippocampal glutamate metabolized receptor 1.

AIMS: This study aimed to investigate the relationship between ulcerative colitis (UC) and anxiety and explore its central mechanisms using colitis mice. METHODS: Anxiety-like behavior was assessed in mice induced by 3% dextran sodium sulfate (DSS) using the elevated plus maze and open-field test. The spatial transcriptome of the hippocampus was analyzed to assess the distribution of excitatory and inhibitory synapses, and Toll-like receptor 4 (TLR4) inhibitor TAK-242 (10 mg/kg) and AAV virus interference were used to examine the role of peripheral inflammation and central molecules such as Glutamate Receptor Metabotropic 1 (GRM1) in mediating anxiety behavior in colitis mice. RESULTS: DSS-induced colitis increased anxiety-like behaviors, which was reduced by TAK-242. Spatial transcriptome analysis of the hippocampus showed an excitatory-inhibitory imbalance mediated by glutamatergic synapses, and GRM1 in hippocampus was identified as a critical mediator of anxiety behavior in colitis mice via differential gene screening and AAV virus interference. CONCLUSION: Our work suggests that the hippocampus plays an important role in brain anxiety caused by peripheral inflammation, and over-excitation of hippocampal glutamate synapses by GRM1 activation induces anxiety-like behavior in colitis mice. These findings provide new insights into the central mechanisms underlying anxiety in UC and may contribute to the development of novel therapeutic strategies for UC-associated anxiety.

Investigation on Combustion Characteristics and Molecular Structures of Heiyanquan Mining Area, Xinjiang, China.

In order to comprehend the molecular composition of coal and better understand the process of coal combustion, this study involved the development of a molecular structure model for Heiyanquan coal in Xinjiang, as well as the optimization and annealing dynamics simulation of the model. Thermogravimetric analysis (TG), Fourier transform infrared spectroscopy (FTIR), and high-resolution transmission electron microscopy (HRTEM) were utilized to investigate the spontaneous combustion characteristics of coal at different temperatures (room temperature, 50-500 °C with 50 °C interval). The findings revealed that the coal primarily consists of aromatic carbon, with the aromatic structure mainly comprising naphthalene, anthracene, and phenanthrene, and the aliphatic carbon mainly consisting of CH2 and CH, along with a small quantity of minerals. The empirical molecular formula of Heiyanquan coal was determined to be C175H125O21N3. After the optimization, the total energy of the model was significantly reduced, and the aromatic layers tended to align in a regular parallel manner, with van der Waals energy playing a crucial role in maintaining structural stability. As the temperature increased, the activation energy of the three stages also increased, with the combustion stage exhibiting the highest activation energy. The presence of hydroxyl groups and oxygen-containing functional groups was found to mainly participate in the reaction, while the content of aromatic hydrocarbons remained relatively stable, C=C exhibited a decreasing trend, and C-O displayed an increasing trend. Moreover, it was observed that 1 × 1 and 2 × 2 were the predominant aromatic stripes in the coal samples, accounting for more than 90% of the total stripes.

Development of the Static and Dynamic Gene Expression Regulation Toolkit in Pseudomonas chlororaphis.

The advancement of metabolic engineering and synthetic biology has promoted in-depth research on the nonmodel microbial metabolism, and the potential of nonmodel organisms in industrial biotechnology is becoming increasingly evident. The nonmodel organism Pseudomonas chlororaphis is a safe plant growth promoting bacterium for the production of phenazine compounds; however, its application is seriously hindered due to the lack of an effective gene expression precise regulation toolkit. In this study, we constructed a library of 108 promoter-5'-UTR (PUTR) and characterized them through fluorescent protein detection. Then, 6 PUTRs with stable low, intermediate, and high intensities were further characterized by report genes lacZ encoding ß-galactosidase from Escherichia coli K12 and phzO encoding PCA monooxygenase from P. chlororaphis GP72 and thus developed as a static gene expression regulation system. Furthermore, the stable and high-intensity expressed PMOK_RS0128085UTR was fused with the LacO operator to construct an IPTG-induced plasmid, and a self-induced plasmid was constructed employing the high-intensity PMOK_RS0116635UTR regulated by cell density, resulting in a dynamic gene expression regulation system. In summary, this study established two sets of static and dynamic regulatory systems for P. chlororaphis, providing an effective toolkit for fine-tuning gene expression and reprograming the metabolism flux.

Rapamycin inhibits B16 melanoma cell viability invitro and invivo by inducing autophagy and inhibiting the mTOR/p70­S6k pathway.

Rapamycin is an immunosuppressant that has been shown to prevent tumor growth following organ transplantation. However, its exact mode of antitumor action remains unknown. The present study used the B16-F10 (B16) murine melanoma model to explore the antitumor mechanism of rapamycin, and it was revealed that rapamycin reduced B16 cell viability in vitro and in vivo. In addition, in vitro and in vivo, the results of western blotting showed that rapamycin reduced Bcl2 expression, and enhanced the protein expression levels of cleaved caspase 3 and Bax, indicating that it can induce the apoptosis of B16 melanoma cells. Furthermore, the results of cell cycle analysis and western blotting showed that rapamycin induced B16 cell cycle arrest in the G1 phase, based on the reduction in the protein expression levels of CDK1, cyclin D1 and CDK4, as well as the increase in the percentage of cells in G1 phase. Rapamycin also significantly increased the number of autophagosomes in B16 melanoma cells, as determined by transmission electron microscopy. Furthermore, the results of RT-qPCR and western blotting showed that rapamycin upregulated the protein expression levels of microtubule-associated protein light chain 3 (LC3) and Beclin-1, while downregulating the expression of p62 in vitro and in vivo, thus indicating that rapamycin could trigger cellular autophagy. The present study revealed that rapamycin in combination with chloroquine (CQ) further increased LC3 expression compared with that in the CQ group, suggesting that rapamycin induced an increase in autophagy in B16 cells. Furthermore, the results of western blotting showed that rapamycin blocked the phosphorylation of p70 ribosomal S6 kinase (p70-S6k) and mammalian target of rapamycin (mTOR) proteins in vitro and in vivo, thus suggesting that rapamycin may exert its antitumor effect by inhibiting the phosphorylation of the mTOR/p70-S6k pathway. In conclusion, rapamycin may inhibit tumor growth by inducing cellular G1 phase arrest and apoptosis. In addition, rapamycin may exert its antitumor effects by inducing the autophagy of B16 melanoma cells in vitro and in vivo, and the mTOR/p70-S6k signaling pathway may be involved in this process.

A Circular RNA Generated from Nebulin (NEB) Gene Splicing Promotes Skeletal Muscle Myogenesis in Cattle as Detected by a Multi-Omics Approach.

Cattle and the draught force provided by its skeletal muscle have been integral to agro-ecosystems of agricultural civilization for millennia. However, relatively little is known about the cattle muscle functional genomics (including protein coding genes, non-coding RNA, etc.). Circular RNAs (circRNAs), as a new class of non-coding RNAs, can be effectively translated into detectable peptides, which enlightened us on the importance of circRNAs in cattle muscle physiology function. Here, RNA-seq, Ribosome profiling (Ribo-seq), and peptidome data are integrated from cattle skeletal muscle, and detected five encoded peptides from circRNAs. It is further identified and functionally characterize a 907-amino acids muscle-specific peptide that is named circNEB-peptide because derived by the splicing of Nebulin (NEB) gene. This peptide localizes to the nucleus and cytoplasm and directly interacts with SKP1 and TPM1, key factors regulating physiological activities of myoblasts, via ubiquitination and myoblast fusion, respectively. The circNEB-peptide is found to promote myoblasts proliferation and differentiation in vitro, and induce muscle regeneration in vivo. These findings suggest circNEB-peptide is an important regulator of skeletal muscle regeneration and underscore the possibility that more encoding polypeptides derived by RNAs currently annotated as non-coding exist.