RNA Sequencing Reveals the Involvement of Serum Exosomal miRNAs in Early Pregnancy in Cattle.

Low fertility is the main cause of the low productivity in beef cattle and is mainly associated with a lack of conception after fertilization. The establishment of early pregnancy in cattle is a complex physiological process, and embryo implantation is crucial for the successful establishment of pregnancy. Exosomal miRNAs play an important role in regulating mammalian embryo implantation and development. This study used synchronous estrus technology to extract exosomes from bovine serum at 0, 14, and 21 days of early pregnancy and analyzed the expression profile of exosomal miRNAs through RNA-seq technology. We identified 472 miRNA precursor sequences and 367 mature miRNA sequences in the three sample groups, with the majority of the miRNAs having high abundance. Differentially expressed miRNAs (DEmiRNAs) were screened, and 20 DEmiRNAs were obtained. The differential expression analysis results show that compared to day 0, there were 15 DEmiRNAs in the serum on day 14 and 5 on day 21 of pregnancy. Compared to the 14th day of pregnancy, there were eight DEmiRNAs in the serum on the 21st day of pregnancy. Bioinformatics analysis shows that the target genes of DEmiRNAs regulated the signaling pathways closely related to early pregnancy, including the VEGF, NF-κB, and MAPK signaling pathways. In addition, the newly discovered miRNAs were bta-miR-3604, bta-miR-2889, bta-miR-3432a, and bta-miR-409b. These results provide a theoretical reference for screening the molecular markers for early pregnancy establishment and maternal recognition of pregnancy (MRP) in cattle and new ideas for shortening the calving interval in cows.

Structural definition of pseudorabies virus dUTPase reveals a novel folding dimer in the herpesvirus family.

The pseudorabies virus (PRV) causes severe and fatal acute respiratory disease in pigs. During PRV proliferation, the enzyme deoxyuridine 5'-triphosphate nucleotide hydrolase (dUTPase) plays a pivotal role in maintaining a low dUTP/dTTP ratio, thereby ensuring the accuracy of viral DNA replication. However, its structure and catalytic mechanisms have not been fully elucidated. Here, we report the crystal structure of PRV dUTPase at a 2.24 Å resolution and demonstrate an unprecedented dimeric architecture, with a conserved enzyme activity center of the herpesvirus family. The enzyme activity center is located in a cavity between the two domains, forming a pocket for binding substrate dUMP and magnesium ions. Remarkably, the exquisite interface of the dimer is primarily composed of four antiparallel ß-sheets, which form 11 hydrogen bonds between the residues P33-V36 and R242-A248 to maintain protein stability. To the best of our knowledge, this is the first report demonstrating that dUTPase exists as a dimer in the herpesvirus family. These findings not only present a novel fold dimeric structure but also deepen the scope of our comprehension of structural diversity in dUTPase family.

The potential of bacterial anti-phagocytic proteins in suppressing the clearance of extracellular vesicles mediated by host phagocytosis.

Extracellular vesicles (EVs), characterized by low immunogenicity, high biocompatibility and targeting specificity along with excellent blood-brain barrier permeability, are increasingly recognized as promising drug delivery vehicles for treating a variety of diseases, such as cancer, inflammation and viral infection. However, recent findings demonstrate that the intracellular delivery efficiency of EVs fall short of expectations due to phagocytic clearance mediated by the host mononuclear phagocyte system through Fcγ receptors, complement receptors as well as non-opsonic phagocytic receptors. In this text, we investigate a range of bacterial virulence proteins that antagonize host phagocytic machinery, aiming to explore their potential in engineering EVs to counteract phagocytosis. Special emphasis is placed on IdeS secreted by Group A Streptococcus and ImpA secreted by Pseudomonas aeruginosa, as they not only counteract phagocytosis but also bind to highly upregulated surface biomarkers αVß3 on cancer cells or cleave the tumor growth and metastasis-promoting factor CD44, respectively. This suggests that bacterial anti-phagocytic proteins, after decorated onto EVs using pre-loading or post-loading strategies, can not only improve EV-based drug delivery efficiency by evading host phagocytosis and thus achieve better therapeutic outcomes but also further enable an innovative synergistic EV-based cancer therapy approach by integrating both phagocytosis antagonism and cancer targeting or deactivation.

RNA m6A detection using raw current signals and basecalling errors from Nanopore direct RNA sequencing reads.

MOTIVATION: Nanopore direct RNA sequencing (DRS) enables the detection of RNA N6-methyladenosine (m6A) without extra laboratory techniques. A number of supervised or comparative approaches have been developed to identify m6A from Nanopore DRS reads. However, existing methods typically utilize either statistical features of the current signals or basecalling-error features, ignoring the richer information of the raw signals of DRS reads. RESULTS: Here, we propose RedNano, a deep-learning method designed to detect m6A from Nanopore DRS reads by utilizing both raw signals and basecalling errors. RedNano processes the raw-signal feature and basecalling-error feature through residual networks. We validated the effectiveness of RedNano using synthesized, Arabidopsis, and human DRS data. The results demonstrate that RedNano surpasses existing methods by achieving higher area under the ROC curve (AUC) and area under the precision-recall curve (AUPRs) in all three datasets. Furthermore, RedNano performs better in cross-species validation, demonstrating its robustness. Additionally, when detecting m6A from an independent dataset of Populus trichocarpa, RedNano achieves the highest AUC and AUPR, which are 3.8%-9.9% and 5.5%-13.8% higher than other methods, respectively. AVAILABILITY AND IMPLEMENTATION: The source code of RedNano is freely available at https://github.com/Derryxu/RedNano.

Less-is-more: selecting transcription factor binding regions informative for motif inference.

Numerous statistical methods have emerged for inferring DNA motifs for transcription factors (TFs) from genomic regions. However, the process of selecting informative regions for motif inference remains understudied. Current approaches select regions with strong ChIP-seq signal for a given TF, assuming that such strong signal primarily results from specific interactions between the TF and its motif. Additionally, these selection approaches do not account for non-target motifs, i.e. motifs of other TFs; they presume the occurrence of these non-target motifs infrequent compared to that of the target motif, and thus assume these have minimal interference with the identification of the target. Leveraging extensive ChIP-seq datasets, we introduced the concept of TF signal 'crowdedness', referred to as C-score, for each genomic region. The C-score helps in highlighting TF signals arising from non-specific interactions. Moreover, by considering the C-score (and adjusting for the length of genomic regions), we can effectively mitigate interference of non-target motifs. Using these tools, we find that in many instances, strong ChIP-seq signal stems mainly from non-specific interactions, and the occurrence of non-target motifs significantly impacts the accurate inference of the target motif. Prioritizing genomic regions with reduced crowdedness and short length markedly improves motif inference. This 'less-is-more' effect suggests that ChIP-seq region selection warrants more attention.

Binding profiles for 954 Drosophila and C. elegans transcription factors reveal tissue specific regulatory relationships.

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the modERN (model organism Encyclopedia of Regulatory Networks) consortium that systematically assayed TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). We describe key features of these datasets, comprising 604 TFs identifying 3.6M sites in the fly and 350 TFs identifying 0.9 M sites in the worm. Applying a machine learning model to these data identifies sets of TFs with a prominent role in promoting target gene expression in specific cell types. TF binding data are available through the ENCODE Data Coordinating Center and at https://epic.gs.washington.edu/modERNresource, which provides access to processed and summary data, as well as widgets to probe cell type-specific TF-target relationships. These data are a rich resource that should fuel investigations into TF function during development.

Correction: Nie et al. Endoplasmic Reticulum Stress Mediated NLRP3 Inflammasome Activation and Pyroptosis in THP-1 Macrophages Infected with Bacillus Calmette-Guérin. Int. J. Mol. Sci. 2023, 24, 11692.

Lei Liu was not included as an author in the original publication [...].

GSK2656157, a PERK Inhibitor, Alleviates Pyroptosis of Macrophages Induced by Mycobacterium Bacillus Calmette-Guerin Infection.

Tuberculosis (TB) is the leading cause of human death worldwide due to Mycobacterium tuberculosis (Mtb) infection. Mtb infection can cause macrophage pyroptosis. PERK, as a signaling pathway protein on the endoplasmic reticulum, plays an important role in infectious diseases. It is not clear whether PERK is involved in the regulation of pyroptosis of macrophages during Mtb infection. In this study, Bacillus Calmette-Guerin (BCG) infection resulted in high expression of pro-caspase-1, caspase-1 p20, GSDMD-N, and p-PERK in the THP-1 macrophage, being downregulated with the pre-treatment of GSK2656157, a PERK inhibitor. In addition, GSK2656157 inhibited the secretion of IL-1ß and IL-18, cell content release, and cell membrane rupture, as well as the decline in cell viability induced by BCG infection. Similarly, GSK2656157 treatment downregulated the expressions of pro-caspase-1, caspase-1 p20, caspase-11, IL-1ß p17, IL-18 p22, GSDMD, GSDMD-N, and p-PERK, as well as reducing fibrous tissue hyperplasia, inflammatory infiltration, and the bacterial load in the lung tissue of C57BL/6J mice infected with BCG. In conclusion, the inhibition of PERK alleviated pyroptosis induced by BCG infection, which has an effect of resisting infection.

S100A4 Promotes BCG-Induced Pyroptosis of Macrophages by Activating the NF-κB/NLRP3 Inflammasome Signaling Pathway.

Pyroptosis is a host immune strategy to defend against Mycobacterium tuberculosis (Mtb) infection. S100A4, a calcium-binding protein that plays an important role in promoting cancer progression as well as the pathophysiological development of various non-tumor diseases, has not been explored in Mtb-infected hosts. In this study, transcriptome analysis of the peripheral blood of patients with pulmonary tuberculosis (PTB) revealed that S100A4 and GSDMD were significantly up-regulated in PTB patients' peripheral blood. Furthermore, there was a positive correlation between the expression of GSDMD and S100A4. KEGG pathway enrichment analysis showed that differentially expressed genes between PTB patients and healthy controls were significantly related to inflammation, such as the NOD-like receptor signaling pathway and NF-κB signaling pathway. To investigate the regulatory effects of S100A4 on macrophage pyroptosis, THP-1 macrophages infected with Bacillus Calmette-Guérin (BCG) were pre-treated with exogenous S100A4, S100A4 inhibitor or si-S100A4. This research study has shown that S100A4 promotes the pyroptosis of THP-1 macrophages caused by BCG infection and activates NLRP3 inflammasome and NF-κB signaling pathways, which can be inhibited by knockdown or inhibition of S100A4. In addition, inhibition of NF-κB or NLRP3 blocks the promotion effect of S100A4 on BCG-induced pyroptosis of THP-1 macrophages. In conclusion, S100A4 activates the NF-κB/NLRP3 inflammasome signaling pathway to promote macrophage pyroptosis induced by Mtb infection. These data provide new insights into how S100A4 affects Mtb-induced macrophage pyroptosis.

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing.

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.