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Interacting with proteins is a crucial way for long noncoding RNAs (lncRNAs) to exert their biological responses. Here we report a high throughput strategy to characterize lncRNA interacting proteins in vivo by combining tobramycin affinity purification and mass spectrometric analysis (TOBAP-MS). Using this method, we identify 140 candidate binding proteins for lncRNA highly upregulated in liver cancer (HULC). Intriguingly, HULC directly binds to two glycolytic enzymes, lactate dehydrogenase A (LDHA) and pyruvate kinase M2 (PKM2). Mechanistic study suggests that HULC functions as an adaptor molecule that enhances the binding of LDHA and PKM2 to fibroblast growth factor receptor type 1 (FGFR1), leading to elevated phosphorylation of these two enzymes and consequently promoting glycolysis. This study provides a convenient method to study lncRNA interactome in vivo and reveals a unique mechanism by which HULC promotes Warburg effect by orchestrating the enzymatic activities of glycolytic enzymes. Here the authors present a quantitative proteomics strategy to identify long noncoding RNA (lncRNA)-binding proteins and demonstrate its application by characterizing the lncRNA HULC (highly upregulated in liver cancer), which is shown to interact with glycolytic enzymes and modulate their activity.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis . This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell–cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M .  fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs. A large-scale single-cell transcriptomic atlas of the non-human primate Macaca fascicularis encompasses over 1 million cells from 45 adult tissues.

Osteoarthritis (OA) and osteoporosis (OP) are prevalent conditions with overlapping molecular mechanisms. Recent studies have brought attention to ferroptosis, a type of cell death that relies on iron, as a possible connection between these diseases. We performed a comprehensive analysis with datasets obtained from the Gene Expression Omnibus (GEO), focusing on differentially expressed genes (DEGs) in OA and OP. Functional enrichment and integrated analyses identified ferroptosis-related pathways. The role of ferroptosis in OP was further explored through in vivo studies using an ovariectomy-induced OP mouse model. The analysis revealed significant overlaps in DEGs related to ferroptosis pathways in both OA and OP. Key genes like TXNIP and SLC2A3 were implicated in the regulation of ferroptosis and associated with disease mechanisms. In vivo results confirmed increased ferroptosis markers in bone marrow stromal cells (BMSCs) from OP mice, supporting the hypothesis that ferroptosis contributes to bone density reduction and structural deterioration. Our findings highlight ferroptosis as a critical pathway in the pathogenesis of both OA and OP. Targeting ferroptosis-related genes and pathways could provide new therapeutic opportunities for managing these musculoskeletal diseases.

Single-cell RNA-seq technologies require library preparation prior to sequencing. Here, we present the first report to compare the cheaper BGISEQ-500 platform to the Illumina HiSeq platform for scRNA-seq. We generate a resource of 468 single cells and 1297 matched single cDNA samples, performing SMARTer and Smart-seq2 protocols on two cell lines with RNA spike-ins. We sequence these libraries on both platforms using single- and paired-end reads. The platforms have comparable sensitivity and accuracy in terms of quantification of gene expression, and low technical variability. Our study provides a standardized scRNA-seq resource to benchmark new scRNA-seq library preparation protocols and sequencing platforms.

Background In HBV-associated HCC, T cells often exhibit a state of functional exhaustion, which prevents the immune response from rejecting the tumor and allows HCC to progress. Moreover, polymerase-specific T cells exhibit more severe T-cell exhaustion compared to core-specific T cells. However, whether HBV DNA polymerase drives HBV-specific CD8 + T cell exhaustion in HBV-related HCC remains unclear. Methods We constructed a Huh7 cell line stably expressing HA-HBV-DNA-Pol and applied co-culture systems to clarify its effect on immune cell function. We also examined how HBV-DNA-Pol modulated PD-L1 expression in HCC cells. In addition, HBV-DNA-Pol transgenic mice were used to elucidate the underlying mechanism of HBV-DNA-Pol/PD-L1 axis-induced T cell exhaustion. Results Biochemical analysis showed that Huh7 cells overexpressing HBV-DNA-Pol inhibited the proliferation, activation, and cytokine secretion of Jurkat cells and that this effect was dependent on their direct contact. A similar inhibitory effect was observed in an HCC mouse model. PD-L1 was brought to our attention during screening. Our results showed that the overexpression of HBV-DNA-Pol upregulated PD-L1 mRNA and protein expression. PD-L1 antibody blockade reversed the inhibitory effect of Huh7 cells overexpressing HBV-DNA-Pol on Jurkat cells. Mechanistically, HBV-DNA-Pol interacts with PARP1, thereby inhibiting the nuclear translocation of PARP1 and further upregulating PD-L1 expression. Conclusions Our findings suggest that HBV-DNA-Pol can act as a regulator of PD-L1 in HCC, thereby directing anti-cancer immune evasion, which further provides a new idea for the clinical treatment of liver cancer.

Human cancer cell lines have long served as tools for cancer research and drug discovery, but the presence and the source of intra-cell-line heterogeneity remain elusive. Here, we perform single-cell RNA-sequencing and ATAC-sequencing on 42 and 39 human cell lines, respectively, to illustrate both transcriptomic and epigenetic heterogeneity within individual cell lines. Our data reveal that transcriptomic heterogeneity is frequently observed in cancer cell lines of different tissue origins, often driven by multiple common transcriptional programs. Copy number variation, as well as epigenetic variation and extrachromosomal DNA distribution all contribute to the detected intra-cell-line heterogeneity. Using hypoxia treatment as an example, we demonstrate that transcriptomic heterogeneity could be reshaped by environmental stress. Overall, our study performs single-cell multi-omics of commonly used human cancer cell lines and offers mechanistic insights into the intra-cell-line heterogeneity and its dynamics, which would serve as an important resource for future cancer cell line-based studies. Intra-cell line heterogeneity remains to be characterized. Here, the use of single multi-omics on a large panel of human cell lines identifies copy number variation, epigenetic variation and extrachromosomal DNA distribution as the main contributors to intra-cell line heterogeneity.

Citrus yellow vein clearing virus (CYVCV) is the causative agent of citrus yellow vein clearing disease, and poses a serious threat to the lemon industry in Asia. The common symptoms of CYVCV-infected lemon plants are leaf crinkling, leaf chlorotic mottling, and yellow vein clearing. However, the molecular mechanisms underlying CYVCV-citrus interaction that responsible for symptom occurrence is still unclarified. In this study, RNA-seq was performed to analyze the gene expression patterns of 'Eureka' lemon (Citrus limon Burm. f.) plants in response to CYVCV infection. There were 3691 differentially expressed genes (DEGs) identified by comparison between mock and CYVCV-infected lemon plants through RNA-seq. Bioinformatics analyses revealed that these DEGs were components of different pathways involved in phenylpropanoid biosynthesis, brassinosteroid biosynthesis, flavonoid biosynthesis and photosynthesis. Among these, the DEGs related to phytohormone metabolism and photosynthesis pathways were further enriched and analyzed. This study showed that different phytohormone-related genes had different responses toward CYVCV infection, however almost all of the photosynthesis-related DEGs were down-regulated in the CYVCV-infected lemon plants. The obtained RNA-seq data were validated by RT-qPCR using 12 randomly chosen genes, and the results of mRNA expression analysis were consistent with those of RNA-seq. The phytohormone biosynthesis, signaling and photosynthesis-related genes of lemon plants were probably involved in systemic infection and symptom occurrence of CYVCV. Notably, CYVCV infection had regulatory effects on the biosynthesis and signaling of phytohormone, which likely improve systemic infection of CYVCV. Additionally, CYVCV infection could cause structural changes in chloroplast and inhibition of photosynthesis pathway, which probably contribute to the appearance of leaf chlorotic mottling and yellow vein clearing in CYVCV-infected lemon plants. This study illustrates the dynamic nature of the citrus-CYVCV interaction at the transcriptome level and provides new insights into the molecular mechanism underlying the pathogenesis of CYVCV in lemon plants.

Nonalcoholic fatty liver disease (NAFLD) is one of major causes of end-stage liver disease in the coming decades, but it shows few symptoms until it develops into cirrhosis. We aim to develop classification models with machine learning to screen NAFLD patients among general adults. This study included 14,439 adults who took health examination. We developed classification models to classify subjects with or without NAFLD using decision tree, random forest (RF), extreme gradient boosting (XGBoost) and support vector machine (SVM). The classifier with SVM was showed the best performance with the highest accuracy (0.801), positive predictive value (PPV) (0.795), F1 score (0.795), Kappa score (0.508) and area under the precision-recall curve (AUPRC) (0.712), and the second top of area under receiver operating characteristic curve (AUROC) (0.850). The second-best classifier was RF model, which was showed the highest AUROC (0.852) and the second top of accuracy (0.789), PPV (0.782), F1 score (0.782), Kappa score (0.478) and AUPRC (0.708). In conclusion, the classifier with SVM is the best one to screen NAFLD in general population based on the results from physical examination and blood testing, followed by the classifier with RF. Those classifiers have a potential to screen NAFLD in general population for physician and primary care doctors, which could benefit to NAFLD patients from early diagnosis.

The change in natural runoff is highly relevant to total river flow dispatch and water resource utilization in the Yellow River Basin (YRB). Based on the annual mean temperature and total precipitation records from 70 meteorological stations from 1961–2020, the impact of climate change on the natural runoff of the YRB is investigated using the Mann-Kendall (M-K) test and Bivariate Wavelet analysis methods. Results show that the annual mean temperature over the YRB increased by 0.33 °C decade−1 during 1961–2020, with a warming rate of more than 0.40 °C decade−1 observed in its northern part. The annual total precipitation increases by 10–20 mm decade−1 in the northwest YRB, while it decreases by 20–30 mm decade−1 in the southeast YRB. The result of the M-K test shows abrupt variations in temperature and natural runoff, especially in the 1980s and 1990s. The decrease in natural runoff is closely tied to the increase (decrease) in temperature (precipitation), especially for the period 1993–2020. The bivariate wavelet coherence analysis further suggests that the decrease in the natural runoff, which has persisted over the past 60 years, is primarily driven by precipitation reduction rather than regional warming. In the stage of rapid warming, the inter-decadal influence of precipitation on natural runoff gradually changes to the influence of inter-annual fluctuation. The finding contributes to providing an important scientific basis for evaluating the optimal allocation of water resources in arid and semi-arid areas against the background of climate change.

Background Increasing evidence has demonstrated that non-coding RNAs, including the lncRNA MIR155HG, are involved in the pathogenesis of postmenopausal osteoporosis (PMOP). In the current study, we studied MIR155HG function in regulation of osteogenic differentiation and tried to reveal the underlying mechanisms. Methods Forty blood samples taken from 20 PMOP patients (PMOP group) and 20 postmenopausal individuals without osteoporosis (control group) were used to compare the contents of MIR155HG and miR-155-5p via RT-PCR. Alizarin red S staining and ALP staining were used to evaluate the osteogenic differentiation potential of bone marrow mesenchymal stem cells (BMSCs). Results Elevated levels of MIR155HG and miR-155-5p were observed in the blood samples of the PMOP group. Upregulation of MIR155HG resulted in decreased expression of OPN, OSX, ALP, RUNX2 and β-catenin but increased DKK1 expression, together with decreased Alizarin red S + and ALP + staining areas. However, downregulation of DKK1 did not obviously change the above indices induced by MIR155HG upregulation. Further experiments revealed that MIR155HG caused an increase in the expression of miR-155-5p, which also serves as an inhibitor of the osteogenic differentiation of BMSCs through binding to β-catenin. Consistent with DKK1 knockdown, downregulation of miR-155-5p only also did not obviously reverse the repressive effect of MIR155HG on osteoblastic differentiation, but downregulation of DKK1 and miR-155-5p synchronously restored the osteogenic differentiation ability of BMSCs suppressed by MIR155HG overexpression. Conclusion MIR155HG suppressed the osteoblastic differentiation of BMSCs by regulating miR-155-5p and DKK1 expression. Either inhibition of miR-155-5p and DKK1 or direct suppression of MIR155HG may be effective approaches for treating PMOP.