Autophagy and cell wall integrity pathways coordinately regulate the development and pathogenicity through MoAtg4 phosphorylation in Magnaporthe oryzae.

Autophagy and Cell wall integrity (CWI) signaling are critical stress-responsive processes during fungal infection of host plants. In the rice blast fungus Magnaporthe oryzae, autophagy-related (ATG) proteins phosphorylate CWI kinases to regulate virulence; however, how autophagy interplays with CWI signaling to coordinate such regulation remains unknown. Here, we have identified the phosphorylation of ATG protein MoAtg4 as an important process in the coordination between autophagy and CWI in M. oryzae. The ATG kinase MoAtg1 phosphorylates MoAtg4 to inhibit the deconjugation and recycling of the key ATG protein MoAtg8. At the same time, MoMkk1, a core kinase of CWI, also phosphorylates MoAtg4 to attenuate the C-terminal cleavage of MoAtg8. Significantly, these two phosphorylation events maintain proper autophagy levels to coordinate the development and pathogenicity of the rice blast fungus.

Deep profiling of potential substrate atlas of porcine epidemic diarrhea virus 3C-like protease.

Coronavirus (CoV) 3C-like protease (3CLpro) is essential for viral replication and is involved in immune escape by proteolyzing host proteins. Deep profiling the 3CLpro substrates in the host proteome extends our understanding of viral pathogenesis and facilitates antiviral drug discovery. Here, 3CLpro from porcine epidemic diarrhea virus (PEDV), an enteropathogenic CoV, was used as a model which to identify the potential 3CLpro cleavage motifs in all porcine proteins. We characterized the selectivity of PEDV 3CLpro at sites P5-P4'. We then compiled the 3CLpro substrate preferences into a position-specific scoring matrix and developed a 3CLpro profiling strategy to delineate the protein substrate landscape of CoV 3CLpro. We identified 1,398 potential targets in the porcine proteome containing at least one putative cleavage site and experimentally validated the reliability of the substrate degradome. The PEDV 3CLpro-targeted pathways are involved in mRNA processing, translation, and key effectors of autophagy and the immune system. We also demonstrated that PEDV 3CLpro suppresses the type 1 interferon (IFN-I) cascade via the proteolysis of multiple signaling adaptors in the retinoic acid-inducible gene I (RIG-I) signaling pathway. Our composite method is reproducible and accurate, with an unprecedented depth of coverage for substrate motifs. The 3CLpro substrate degradome establishes a comprehensive substrate atlas that will accelerate the investigation of CoV pathogenicity and the development of anti-CoV drugs.IMPORTANCECoronaviruses (CoVs) are major pathogens that infect humans and animals. The 3C-like protease (3CLpro) encoded by CoV not only cleaves the CoV polyproteins but also degrades host proteins and is considered an attractive target for the development of anti-CoV drugs. However, the comprehensive characterization of an atlas of CoV 3CLpro substrates is a long-standing challenge. Using porcine epidemic diarrhea virus (PEDV) 3CLpro as a model, we developed a method that accurately predicts the substrates of 3CLpro and comprehensively maps the substrate degradome of PEDV 3CLpro. Interestingly, we found that 3CLpro may simultaneously degrade multiple molecules responsible for a specific function. For instance, it cleaves at least four adaptors in the RIG-I signaling pathway to suppress type 1 interferon production. These findings highlight the complexity of the 3CLpro substrate degradome and provide new insights to facilitate the development of anti-CoV drugs.

Cleavage of HDAC6 to dampen its antiviral activity by nsp5 is a common strategy of swine enteric coronaviruses.

HDAC6, a structurally and functionally unique member of the histone deacetylase (HDAC) family, is an important host factor that restricts viral infection. The broad-spectrum antiviral activity of HDAC6 makes it a potent antiviral agent. Previously, we found that HDAC6 functions to antagonize porcine deltacoronavirus (PDCoV), an emerging enteropathogenic coronavirus with zoonotic potential. However, the final outcome is typically a productive infection that materializes as cells succumb to viral infection, indicating that the virus has evolved sophisticated mechanisms to combat the antiviral effect of HDAC6. Here, we demonstrate that PDCoV nonstructural protein 5 (nsp5) can cleave HDAC6 at glutamine 519 (Q519), and cleavage of HDAC6 was also detected in the context of PDCoV infection. More importantly, the anti-PDCoV activity of HDAC6 was damaged by nsp5 cleavage. Mechanistically, the cleaved HDAC6 fragments (amino acids 1-519 and 520-1159) lost the ability to degrade PDCoV nsp8 due to their impaired deacetylase activity. Furthermore, nsp5-mediated cleavage impaired the ability of HDAC6 to activate RIG-I-mediated interferon responses. We also tested three other swine enteric coronaviruses (transmissible gastroenteritis virus, porcine epidemic diarrhea virus, and swine acute diarrhea syndrome-coronavirus) and found that all these coronaviruses have adopted similar mechanisms to cleave HDAC6 in both an overexpression system and virus-infected cells, suggesting that cleavage of HDAC6 is a common strategy utilized by swine enteric coronaviruses to antagonize the host's antiviral capacity. Together, these data illustrate how swine enteric coronaviruses antagonize the antiviral function of HDAC6 to maintain their infection, providing new insights to the interaction between virus and host.IMPORTANCEViral infections and host defenses are in constant opposition. Once viruses combat or evade host restriction, productive infection is achieved. HDAC6 is a broad-spectrum antiviral protein that has been demonstrated to inhibit many viruses, including porcine deltacoronavirus (PDCoV). However, whether HDAC6 is reciprocally targeted and disabled by viruses remains unclear. In this study, we used PDCoV as a model and found that HDAC6 is targeted and cleaved by nsp5, a viral 3C-like protease. The cleaved HDAC6 loses its deacetylase activity as well as its ability to degrade viral proteins and activate interferon responses. Furthermore, this cleavage mechanism is shared among other swine enteric coronaviruses. These findings shed light on the intricate interplay between viruses and HDAC6, highlighting the strategies employed by viruses to evade host antiviral defenses.

Conserved and specific gene expression patterns in the embryonic development of tardigrades.

Tardigrades, commonly known as water bears, are enigmatic organisms characterized by their remarkable resilience to extreme environments despite their simple and compact body structure. To date, there is still much to understand about their evolutionary and developmental features contributing to their special body plan and abilities. This research provides preliminary insights on the conserved and specific gene expression patterns during embryonic development of water bears, focusing on the species Hypsibius exemplaris. The developmental dynamic expression analysis of the genes with various evolutionary age grades indicated that the mid-conserved stage of H. exemplaris corresponds to the period of ganglia and midgut development, with the late embryonic stage showing a transition from non-conserved to conserved state. Additionally, a comparison with Drosophila melanogaster highlighted the absence of certain pathway nodes in development-related pathways, such as Maml and Hairless, which are respectively the transcriptional co-activator and co-repressor of NOTCH regulated genes. We also employed Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the expression patterns of tardigrade-specific genes during embryo development. Our findings indicated that the module containing the highest proportion of tardigrade-specific genes (TSGs) exhibits high expression levels before the mid-conserved stage, potentially playing a role in glutathione and lipid metabolism. These functions may be associated to the ecdysone synthesis and storage cell formation, which is unique to tardigrades.

Phenazine biosynthesis protein MoPhzF regulates appressorium formation and host infection through canonical metabolic and noncanonical signaling function in Magnaporthe oryzae.

Microbe-produced secondary metabolite phenazine-1-carboxylic acid (PCA) facilitates pathogen virulence and defense mechanisms against competitors. Magnaporthe oryzae, a causal agent of the devastating rice blast disease, needs to compete with other phyllosphere microbes and overcome host immunity for successful colonization and infection. However, whether M. oryzae produces PCA or it has any other functions remains unknown. Here, we found that the MoPHZF gene encodes the phenazine biosynthesis protein MoPhzF, synthesizes PCA in M. oryzae, and regulates appressorium formation and host virulence. MoPhzF is likely acquired through an ancient horizontal gene transfer event and has a canonical function in PCA synthesis. In addition, we found that PCA has a role in suppressing the accumulation of host-derived reactive oxygen species (ROS) during infection. Further examination indicated that MoPhzF recruits both the endoplasmic reticulum membrane protein MoEmc2 and the regulator of G-protein signaling MoRgs1 to the plasma membrane (PM) for MoRgs1 phosphorylation, which is a critical regulatory mechanism in appressorium formation and pathogenicity. Collectively, our studies unveiled a canonical function of MoPhzF in PCA synthesis and a noncanonical signaling function in promoting appressorium formation and host infection.

Improved synthesis and evaluation of preclinical pharmacodynamic parameters of a new monocyclic ß-lactam DPI-2016.

Monocyclic ß-lactams are stable to a number of ß-lactamases and are the focus of researchers for the development of antibacterial drugs, particularly against Enterobacterales. We recently synthesized and reported the bactericidal activity of diverse series of aztreonam appended with amidine moieties as siderophores. One of the derivatives exhibiting the highest MIC value in vitro was selected for further preclinical studies. The compound DPI-2016 was reassessed for its synthetic routes and methods that were improved to find the maximum final yields aimed at large-scale synthesis. In addition, the results of the pharmacological studies were determined with reference to aztreonam. It has been found that the compound DPI-2016 showed comparable or slightly improved ADMET as well as pharmacokinetic parameters to aztreonam. It is estimated that the compound could be a potential lead for further clinical evaluation.

Identification of whole-cell dsRNA-binding proteins by phase separation.

Interactions between double-stranded RNA (dsRNA) and proteins play an important role in cellular homeostasis by regulating the editing, stability, and splicing of intracellular RNA. The identification of dsRNA-binding proteins (dsRBPs) is key; however, it has long been challenging to purify dsRBPs from cells. In this study, we developed a novel method, dsRBPC (dsRNA-binding protein capture), to purify cellular dsRBPs based on classic phase separation purification procedures. A global dsRNA-binding proteome of LLC-PK1 cells was obtained, and we identified 1326 dsRBPs, including 1303 putative novel dsRBPs. Functional analyses suggested that these enriched dsRBPs are mainly associated with rRNA processing, RNA splicing, transcriptional regulation, and nucleocytoplasmic transport. We also found that the ARM (armadillo/beta-catenin-like repeats) motif is a previously unknown dsRNA-binding domain, as demonstrated by biochemical experiments. Collectively, this study provides a useful approach for dsRBP identification and the discovery of a global dsRNA-binding proteome to comprehensively map the dsRNA - protein interaction network.

Computed tomography-based radiomics model to predict adverse clinical outcomes in acute pulmonary embolism.

This preliminary study investigated the feasibility of a combined model constructed using radiomic features based on computed tomography (CT) and clinical features to predict adverse clinical outcomes in acute pulmonary embolism (APE). Currently, there is no widely recognized predictive model. Patients with confirmed APE who underwent CT pulmonary angiography were retrospectively categorized into good and poor prognosis groups. Seventy-four patients were randomized into a training (n = 51) or validation (n = 23) cohort. Feature extraction was performed using 3D-Slicer software. The least absolute shrinkage and selection operator regression was used to identify the optimal radiomics features and calculate the radiomics scores; subsequently, the radiomics model was developed. A combined predictive model was constructed based on radiomics scores and selected clinical features. The predictive efficacy of the three models (radiomics, clinical and combined) was assessed by plotting receiver operating characteristic curves. Furthermore, the calibration curves were graphed and the decision curve analysis was performed. Four radiomic features were screened to calculate the radiomic score. Right ventricular to left ventricular ratio (RV/LV) ≥ 1.0 and radiomics score were independent risk factors for adverse clinical outcomes. In the training and validation cohorts, the areas under the curve (AUCs) for the RV/LV ≥ 1.0 (clinical) and radiomics score prediction models were 0.778 and 0.833 and 0.907 and 0.817, respectively. The AUCs for the combined model of RV/LV ≥ 1.0 and radiomics score were 0.925 and 0.917, respectively. The combined and radiomics models had high clinical assessment efficacy for predicting adverse clinical outcomes in APE, demonstrating the clinical utility of both models. Calibration curves exhibited a strong level of consistency between the predictive and observed probabilities of poor and good prognoses in the combined model. The combined model of RV/LV ≥ 1.0 and radiomics score based on CT could accurately and non-invasively predict adverse clinical outcomes in patients with APE.

Predictive Value of Pulmonary Artery Distensibility for Short-Term Adverse Clinical Outcomes in Patients with Acute Pulmonary Embolism.

We aimed to explore the relationship between pulmonary artery distensibility obtained from computed tomography pulmonary angiography (CTPA) and short-term adverse clinical outcomes in patients with acute pulmonary embolism (APE). We included patients who underwent retrospective electrocardiogram-gated CTPA and were subsequently diagnosed with APE. Patients were categorized into good and poor outcome groups based on short-term clinical outcomes. Pulmonary artery distensibility (AD), right ventricle/left ventricle (RV/LV) ratio, and pulmonary artery obstruction index (PAOI) were measured, and the receiver operating characteristic curves were constructed. Sixty-four patients with APE (good outcome, 46; poor outcome, 18) were enrolled. AD, RV/LV ratio, and PAOI differed significantly between groups (P < 0.05). Pulmonary artery AD in the good outcome group was greater than that in the poor outcome group (P < 0.001). The poor outcome group exhibited a higher RV/LV ratio and PAOI than the good outcome group (P < 0.05). AD and PAOI were independent predictors of adverse clinical outcomes. Areas under the curve for AD and PAOI were 0.860 (95% confidence interval [CI]: 0.750-0.934) and 0.675 (95%CI: 0.546-0.786), and the combined curve of the AD and RV/LV ratio was 0.906 (95%CI: 0.806-0.965). The calibration curve showed a combined curve superior to the other curves. The decision curve showed high clinical application value of the combined curve. Retrospective electrocardiogram-gated CTPA-derived AD could serve as an indicator for predicting short-term adverse clinical outcomes in APE. Combining AD and PAOI has a high predictive value for short-term adverse clinical outcomes.

Coinfection and nonrandom recombination drive the evolution of swine enteric coronaviruses.

Coinfection with multiple viruses is a common phenomenon in clinical settings and is a crucial driver of viral evolution. Although numerous studies have demonstrated viral recombination arising from coinfections of different strains of a specific species, the role of coinfections of different species or genera during viral evolution is rarely investigated. Here, we analyzed coinfections of and recombination events between four different swine enteric coronaviruses that infect the jejunum and ileum in pigs, including porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), and swine acute diarrhea syndrome coronavirus (SADS-CoV), and a deltacoronavirus, porcine deltacoronavirus (PDCoV). Various coinfection patterns were observed in 4,468 fecal and intestinal tissue samples collected from pigs in a 4-year survey. PEDV/PDCoV was the most frequent coinfection. However, recombination analyses have only detected events involving PEDV/TGEV and SADS-CoV/TGEV, indicating that inter-species recombination among coronaviruses is most likely to occur within the same genus. We also analyzed recombination events within the newly identified genus Deltacoronavirus and found that sparrows have played a unique host role in the recombination history of the deltacoronaviruses. The emerging virus PDCoV, which can infect humans, has a different recombination history. In summary, our study demonstrates that swine enteric coronaviruses are a valuable model for investigating the relationship between viral coinfection and recombination, which provide new insights into both inter- and intraspecies recombination events among swine enteric coronaviruses, and extend our understanding of the relationship between coronavirus coinfection and recombination.

Pursuing Impactful Quantitative Proteomics Using QC-Channels in Every Spectrum and Trend-Design in Experiment.

False changes discovered by quantitative proteomics reduce the trust of biologists in proteomics and limit the applications of proteomics to unlock biological mechanisms, which suppresses the application of proteomics techniques in the pharmaceutical industry more than it does in academic research. To remove false changes that arise during LC-MS/MS data acquisition, we evaluated the contributions of peptide abundance and number of unique peptides on reproducibility. Lower abundance and only one unique peptide have a higher risk of generating a higher coefficient of variation (CV), resulting in less accurate quantification. However, the abundance of peptides in samples is not adjustable and discarding proteins quantified by only one unique peptide is not a choice either. Indeed, a large percentage of proteins are accurately quantified by only one unique peptide. Therefore, to improve the calculations of the CV, we leverage a new function in PEAKS called QC-channels which enables technical replicates of each spectrum to be evaluated prior to calculation of the CV. While the QC-channels function in PEAKS significantly reduced the false quantification, random false changes still exist due to known or unknown reasons. To address this challenge, we present the idea of Trend-design to track trend changes rather than changes from two points to remove false quantifications and reveal consequential changes responding to a treatment or condition. The idea was confirmed by molecules with different affinity and dose in the current study. The combination of QC-channels and Trend-design enables a more impactful quantitative proteomics to allow unlocking biological mechanisms using proteomics.

Multiomics analysis reveals metabolic subtypes and identifies diacylglycerol kinase α (DGKA) as a potential therapeutic target for intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is a highly heterogeneous and lethal hepatobiliary tumor with few therapeutic strategies. The metabolic reprogramming of tumor cells plays an essential role in the development of tumors, while the metabolic molecular classification of iCCA is largely unknown. Here, we performed an integrated multiomics analysis and metabolic classification to depict differences in metabolic characteristics of iCCA patients, hoping to provide a novel perspective to understand and treat iCCA. METHODS: We performed integrated multiomics analysis in 116 iCCA samples, including whole-exome sequencing, bulk RNA-sequencing and proteome analysis. Based on the non-negative matrix factorization method and the protein abundance of metabolic genes in human genome-scale metabolic models, the metabolic subtype of iCCA was determined. Survival and prognostic gene analyses were used to compare overall survival (OS) differences between metabolic subtypes. Cell proliferation analysis, 5-ethynyl-2'-deoxyuridine (EdU) assay, colony formation assay, RNA-sequencing and Western blotting were performed to investigate the molecular mechanisms of diacylglycerol kinase α (DGKA) in iCCA cells. RESULTS: Three metabolic subtypes (S1-S3) with subtype-specific biomarkers of iCCA were identified. These metabolic subtypes presented with distinct prognoses, metabolic features, immune microenvironments, and genetic alterations. The S2 subtype with the worst survival showed the activation of some special metabolic processes, immune-suppressed microenvironment and Kirsten rat sarcoma viral oncogene homolog (KRAS)/AT-rich interactive domain 1A (ARID1A) mutations. Among the S2 subtype-specific upregulated proteins, DGKA was further identified as a potential drug target for iCCA, which promoted cell proliferation by enhancing phosphatidic acid (PA) metabolism and activating mitogen-activated protein kinase (MAPK) signaling. CONCLUSION: Via multiomics analyses, we identified three metabolic subtypes of iCCA, revealing that the S2 subtype exhibited the poorest survival outcomes. We further identified DGKA as a potential target for the S2 subtype.