Structure and mechanism of a eukaryotic ceramide synthase complex.

Ceramide synthases (CerS) catalyze ceramide formation via N-acylation of a sphingoid base with a fatty acyl-CoA and are attractive drug targets for treating numerous metabolic diseases and cancers. Here, we present the cryo-EM structure of a yeast CerS complex, consisting of a catalytic Lac1 subunit and a regulatory Lip1 subunit, in complex with C26-CoA substrate. The CerS holoenzyme exists as a dimer of Lac1-Lip1 heterodimers. Lac1 contains a hydrophilic reaction chamber and a hydrophobic tunnel for binding the CoA moiety and C26-acyl chain of C26-CoA, respectively. Lip1 interacts with both the transmembrane region and the last luminal loop of Lac1 to maintain the proper acyl chain binding tunnel. A lateral opening on Lac1 serves as a potential entrance for the sphingoid base substrate. Our findings provide a template for understanding the working mechanism of eukaryotic ceramide synthases and may facilitate the development of therapeutic CerS modulators.

Mortality among papillary thyroid cancer patients by detection route: a hospital-based retrospective cohort study.

Background: Incidence rates of papillary thyroid cancer (PTC) have increased rapidly, with incidentally detected cancers contributing a large proportion. We aimed to explore the impact of incidental detection on thyroid cancer-specific and competing mortality among PTC patients. Methods: We conducted a retrospective cohort study of PTC patients at a cancer center in Guangzhou. Baseline information on detection route and other covariates were collected between 2010 and 2018, and death outcome was followed up for each patient. Cumulative incidence functions were used to estimate the mortality risk of thyroid cancer and competing risk. Cause-specific hazard models were then utilized to explore the association between detection routes and PTC-specific and competing mortality. Results: Of the 2874 patients included, 2011 (70.0%) were detected incidentally, and the proportion increased from 36.9% in 2011 to 82.3% in 2018. During a median follow-up of 5.6 years, 42 deaths occurred, with 60% of them due to competing causes. The probability of competing mortality at 5 years in the non-incidental group and incidental group was 1.4% and 0.4%, respectively, and PTC-specific mortality in the non-incidental group and incidental group was 1.0% and 0.1%, respectively. After adjusting for covariates, the HRs of incidental detection were 0.13 (95% CI: 0.04-0.46; P = 0.01) and 0.47 (95% CI: 0.20-1.10; P = 0.10) on PTC-specific mortality and competing mortality, respectively. Conclusions: Incidental detection is associated with a lower risk of PTC-specific and competing mortality. Under the context of increasing magnitude of overdiagnosis, incorporation of detection route in clinical decision-making might be helpful to identify patients who might benefit from more extensive or conservative therapeutic strategies.

Cryo-EM structures of the human surfactant lipid transporter ABCA3.

The adenosine 5'-triphosphate (ATP)-binding cassette (ABC) transporter ABCA3 plays a critical role in pulmonary surfactant biogenesis. Mutations in human ABCA3 have been recognized as the most frequent causes of inherited surfactant dysfunction disorders. Despite two decades of research, in vitro biochemical and structural studies of ABCA3 are still lacking. Here, we report the cryo-EM structures of human ABCA3 in two distinct conformations, both at resolution of 3.3 Å. In the absence of ATP, ABCA3 adopts a "lateral-opening" conformation with the lateral surfaces of transmembrane domains (TMDs) exposed to the membrane and features two positively charged cavities within the TMDs as potential substrate binding sites. ATP binding induces pronounced conformational changes, resulting in the collapse of the potential substrate binding cavities. Our results help to rationalize the disease-causing mutations in human ABCA3 and suggest a conserved "lateral access and extrusion" mechanism for both lipid export and import mediated by ABCA transporters.

Enhancing Cancer Driver Gene Prediction by Protein-Protein Interaction Network.

With the advances in gene sequencing technologies, millions of somatic mutations have been reported in the past decades, but mining cancer driver genes with oncogenic mutations from these data remains a critical and challenging area of research. In this study, we proposed a network-based classification method for identifying cancer driver genes with merging the multi-biological information. In this method, we construct a cancer specific genetic network from the human protein-protein interactome (PPI) to mine the network structure attributes, and combine biological information such as mutation frequency and differential expression of genes to achieve accurate prediction of cancer driver genes. Across seven different cancer types, the proposed algorithm always achieves high prediction accuracy, which is superior to the existing advanced methods. In the analysis of the predicted results, about 40 percent of the top 10 candidate genes overlap with the Cancer Gene Census database. Interestingly, the feature comparison indicates that the network based features are still more important than the biological features, including the mutation frequency and genetic differential expression. Further analyses also show that the integration of network structure attributes and biological information is valuable for predicting new cancer driver genes.

Structural basis of substrate recognition and translocation by human ABCA4.

Human ATP-binding cassette (ABC) subfamily A (ABCA) transporters mediate the transport of various lipid compounds across the membrane. Mutations in human ABCA transporters have been described to cause severe hereditary disorders associated with impaired lipid transport. However, little is known about the mechanistic details of substrate recognition and translocation by ABCA transporters. Here, we present three cryo-EM structures of human ABCA4, a retina-specific ABCA transporter, in distinct functional states at resolutions of 3.3-3.4 Å. In the nucleotide-free state, the two transmembrane domains (TMDs) exhibit a lateral-opening conformation, allowing the lateral entry of substrate from the lipid bilayer. The N-retinylidene-phosphatidylethanolamine (NRPE), the physiological lipid substrate of ABCA4, is sandwiched between the two TMDs in the luminal leaflet and is further stabilized by an extended loop from extracellular domain 1. In the ATP-bound state, the two TMDs display a closed conformation, which precludes the substrate binding. Our study provides a molecular basis to understand the mechanism of ABCA4-mediated NRPE recognition and translocation, and suggests a common 'lateral access and extrusion' mechanism for ABCA-mediated lipid transport.

A network-based deep learning methodology for stratification of tumor mutations.

MOTIVATION: Tumor stratification has a wide range of biomedical and clinical applications, including diagnosis, prognosis and personalized treatment. However, cancer is always driven by the combination of mutated genes, which are highly heterogeneous across patients. Accurately subdividing the tumors into subtypes is challenging. RESULTS: We developed a network-embedding based stratification (NES) methodology to identify clinically relevant patient subtypes from large-scale patients' somatic mutation profiles. The central hypothesis of NES is that two tumors would be classified into the same subtypes if their somatic mutated genes located in the similar network regions of the human interactome. We encoded the genes on the human protein-protein interactome with a network embedding approach and constructed the patients' vectors by integrating the somatic mutation profiles of 7344 tumor exomes across 15 cancer types. We firstly adopted the lightGBM classification algorithm to train the patients' vectors. The AUC value is around 0.89 in the prediction of the patient's cancer type and around 0.78 in the prediction of the tumor stage within a specific cancer type. The high classification accuracy suggests that network embedding-based patients' features are reliable for dividing the patients. We conclude that we can cluster patients with a specific cancer type into several subtypes by using an unsupervised clustering algorithm to learn the patients' vectors. Among the 15 cancer types, the new patient clusters (subtypes) identified by the NES are significantly correlated with patient survival across 12 cancer types. In summary, this study offers a powerful network-based deep learning methodology for personalized cancer medicine. AVAILABILITY AND IMPLEMENTATION: Source code and data can be downloaded from https://github.com/ChengF-Lab/NES. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Safflower yellow alleviates osteoarthritis and prevents inflammation by inhibiting PGE2 release and regulating NF-κB/SIRT1/AMPK signaling pathways.

BACKGROUND: Safflower yellow (SY) is the main active ingredient of safflower, with various pharmacological effects such as anticoagulating, antioxidant, and anti-arthritis effects. PURPOSE: To investigate the anti-inflammatory and chondrocyte protecting role of SY, which subsequently leads to the inhibition of cartilage degradation. METHODS: Rat chondrocytes were stimulated with tumor necrosis factor α (TNF-α) with or without SY treatment. Following this, CCK-8 assay was performed to detect cytotoxicity. RT-qPCR, Western blotting, and immunofluorescence staining were used to detect the gene/protein expression of typical cartilage matrix genes and related inflammatory markers. Subsequently, EdU assay was used to evaluate cell proliferation. RNA sequencing, online target prediction, and molecular docking were performed to determine the possible molecular targets and pathways. RESULTS: The results showed that SY restored the TNF-α-induced up-regulation of IL-1ß, PTGS2, and MMP-13 and down-regulation of COL2A1 and ACAN. Furthermore, it recovered cell proliferation by suppressing TNF-α. Gene expression profiles identified 717 differentially expressed genes (DEGs) in the cells cultured with or without SY under TNF-α stimulation. After pathway enrichment, PI3K-Akt, TNF, Cytokine-cytokine receptor interaction, NF-κB, NOD-like receptor, and Chemokine signaling pathways were notably selected to highlight NFKBIA, CCL5, CCL2, IL6, and TNF as potential targets in osteoarthritis (OA). SY inhibited TNF-α-induced activation of NF-κB and endoplasmic reticulum (ER) stress by promoting AMPK phosphorylation along with SIRT1 expression. Further, SY reduced MMP-13 expression and targeted COX-2 for decreasing PGE2 release. In addition, anterior cruciate ligament transection-induced OA was ameliorated by local administration of SY. CONCLUSION: These results demonstrate that SY protects chondrocytes and inhibits inflammation by regulating the NF-κB/SIRT1/AMPK pathways and ER stress, thus preventing cartilage degeneration in OA.

Ursolic acid protects chondrocytes, exhibits anti-inflammatory properties via regulation of the NF-κB/NLRP3 inflammasome pathway and ameliorates osteoarthritis.

Inflammation and poor viability of chondrocytes result in the degradation of cartilage as osteoarthritis (OA) progresses. The purpose of the present study was to investigate whether ursolic acid (UA) can protect chondrocytes and alleviate OA. Following stimulation with tumor necrosis factor-α (TNF-α), 5 µM UA displayed no cytotoxicity and reversed the up-regulation of the inflammatory factors MMP13, IL-1ß, IL-6 and PTGS2, and down-regulation of the cartilaginous genes/proteins type II collagen and Aggrecan. RNA sequencing identified 533 common deferentially expressed genes (DEGs) of which TNF, PI3K-AKT, NOD-like receptor, cytokine receptor interaction and NF-κB pathways were of potential importance. Further notable DEGs in the most-highly expressed 10 pathways contributed to maintenance of cartilaginous ECM homeostasis and were involved in an inflammatory response. The expression of these most-enriched DEGs was reversed by UA following stimulation with TNF-α. Additional investigation demonstrated that treatment with UA inhibited TNF-α-induced nuclear translocation of p65 and phosphorylation of IκBα and AKT, and reversed TNF-α-induced up-regulation of P20, ACS and NLRP3. Furthermore, rat anterior cruciate ligament transection (ACLT) induced-OA was ameliorated by treatment with UA. In conclusion, these results suggest that UA activates chondrocytes through the NF-κB/NLRP3 inflammasome pathway, thus preventing cartilage degeneration in osteoarthritis.

Prevalence of Enteropathogens in Outpatients with Acute Diarrhea from Urban and Rural Areas, Southeast China, 2010-2014.

Acute diarrhea is an important public health issue. Here, we focused on the differences of enteropathogens in acute diarrhea between urban and rural areas in southeast China. Laboratory- and sentinel-based surveillance of acute diarrhea (≥ 3 loose or liquid stools/24 hours) was conducted at 16 hospitals. Fecal specimens were tested for bacterial (Aeromonas sp., Campylobacter sp., diarrheagenic Escherichia coli, Plesiomonas shigelloides, non-typhoidal Salmonella, Shigella sp., Vibrio sp., and Yersinia sp.) and viral (adenovirus, astrovirus, Norovirus, Rotavirus, and Sapovirus) pathogens. Descriptive statistics were used. Between January 1, 2010, and December 31, 2014, 4,548 outpatients with acute diarrhea were enrolled (urban, n = 3,220; rural, n = 1,328). Pathogens were identified in 2,074 (45.6%) patients. Norovirus (25.7%), Vibrio parahaemolyticus (10.2%), enteroaggregative Escherichia coli (EAEC) (8.8%), group A Rotavirus (7.0%), and enterotoxigenic Escherichia coli (ETEC) (5.6%) were the most common pathogens. Enteropathogens were less common in urban than in rural areas (42.0% versus 54.4%, P < 0.001). In urban areas, EAEC and ETEC were more common in high-income than in middle-income regions. Interventions targeting the most common enteropathogens can substantially reduce the burden of acute diarrhea in southeast China.