Identification of a novel substrate motif of yeast separase and deciphering the recognition specificity using AlphaFold2 and molecular dynamics simulation.

Separase is a giant cysteine protease and has multiple crucial functions. The most well-known substrate of separase is the kleisin subunit of cohesin, the cleavage of which triggers chromosome segregation during cell division (Uhlmann et al., 1999; Kamenz and Hauf, 2016) [1,2]. Recently, separase has also been found to cleave MCL-1 or BCL-XL proteins to trigger apoptosis (Hellmuth and Stemmann, 2020) [3]. Although substrate recognition through a short sequence right upstream of the cleavage site is well established, recent studies suggested that sequence elements outside this minimum cleavage site are required for optimal cleavage activity and specificity (Rosen et al., 2019; Uhlmann et al., 2000) [4,5]. However, the sequences and their underlying mechanism are largely unknown. To further explore the substrate determinants and recognition mechanism, we carried out sequence alignments and found a conserved motif downstream of the cleavage site in budding yeast. Using Alphafold2 and molecular dynamics simulations, we found this motif is recognized by separase in a conserved cleft near the binding groove of its inhibitor securin. Their binding is mutually exclusive and requires conformation changes of separase. These findings provide deeper insights into substrate recognition and activation of separase, and paved the way for discovering more substrates of separase.

A conserved mechanism affecting hydride shifting and deprotonation in the synthesis of hopane triterpenes as compositions of wax in oat.

Triterpenoids are biologically active metabolites synthesized from a common linear precursor catalyzed by 2,3-oxidosqualene cyclases (OSCs) to form diverse triterpenoid skeletons. OSCs corresponding to many discovered triterpene alcohols in nature have not been functionally and mechanistically characterized due to the diversity of chemical structures and complexity of the cyclization mechanism. We carried out a genome-wide investigation of OSCs from Avena strigosa and discovered two triterpene synthases, namely, AsHS1 and AsHS2, using a Nicotiana benthamiana expression system. These synthases produce hopenol B and hop-17(21)-en-3ß-ol, which are components of surface wax in oat panicles and sheathes, respectively. We demonstrated that substitutions of two to three amino acid residues in AsHS1 with corresponding residues from AsHS2 allowed it to be completely converted into a hop-17(21)-en-3ß-ol synthase. AsHS2 mutants with a substitution at site 410 could synthesize hopenol B alone or mixed with a side product isomotiol. The combined quantum mechanics and molecular mechanics calculation demonstrated that the side chain size of the residue at site 410 regulated the relative orientations between the hopyl C22 cation and Phe257, leading to a difference in deprotonation positions through providing or not providing cation­π interaction between the aromatic ring of F257 and the carbocation intermediate. A similar mechanism could be applied to a hopenol B synthase from a dicotyledonous plant Aquilegia. This study provided mechanistic insight into triterpenoid synthesis and discovered key amino acid residues acting on hydride transfer and a deprotonation site to differentiate between hopane-type scaffolds in diverse plant species.

Mammographic image classification with deep fusion learning.

To better address the recognition of abnormalities among mammographic images, in this study we apply the deep fusion learning approach based on Pre-trained models to discover the discriminative patterns between Normal and Tumor categories. We designed a deep fusion learning framework for mammographic image classification. This framework works in two main steps. After obtaining the regions of interest (ROIs) from original dataset, the first step is to train our proposed deep fusion models on those ROI patches which are randomly collected from all ROIs. We proposed the deep fusion model (Model1) to directly fuse the deep features to classify the Normal and Tumor ROI patches. To explore the association among channels of the same block, we propose another deep fusion model (Model2) to integrate the cross-channel deep features using 1 × 1 convolution. The second step is to obtain the final prediction by performing the majority voting on all patches' prediction of one ROI. The experimental results show that Model1 achieves the whole accuracy of 0.8906, recall rate of 0.913, and precision rate of 0.8077 for Tumor class. Accordingly, Model2 achieves the whole accuracy of 0.875, recall rate of 0.9565, and precision rate 0.7,586 for Tumor class. Finally, we open source our Python code at https://github.com/yxchspring/MIAS in order to share our tool with the research community.

Erratum: MicroRNA-152 suppresses cisplatin resistance in A549 cells.

[This corrects the article DOI: 10.3892/ol.2019.10834.].

MicroRNA-152 suppresses cisplatin resistance in A549 cells.

The present study aimed to investigate the association between microRNA-152 and cisplatin resistance in non-small cell lung cancer. A549 and cisplatin-resistant A549 cells (A549/cis) were maintained in vitro. Reverse transcription-quantitative PCR (RT-qPCR) was performed to analyze differences in microRNA-152 levels between A549 and A549/cis cells, and changes in Bcl-2 and NF-κB expression levels were analyzed via RT-qPCR and western blot analyses. MicroRNA-152 was overexpressed in A549/cis cells via transfection of a microRNA-152 mimic. Upon treating transfected or untransfected A549/cis cells with 2 µg/l cisplatin for 24 h, a Cell Counting Kit-8 assay, morphological analysis and flow cytometry analysis were performed to evaluate the effect of microRNA-152 on the inhibition of cell proliferation and induction of apoptosis. Furthermore, changes in Bcl-2 and NF-κB expression levels in microRNA-152-overexpressing A549/cis cells were also analyzed. MicroRNA-152 was significantly downregulated and Bcl-2 and NF-κB were significantly upregulated in A549/cis cells (P<0.05). MicroRNA-152 upregulation enhanced the inhibitory effect of cisplatin on A549/cis cells. These results suggest that microRNA-152 downregulates Bcl-2 and NF-κB. MicroRNA-152 downregulation may induce cisplatin resistance in non-small cell lung cancer cells, whereas microRNA-152 upregulation may improve cisplatin sensitivity among A549/cis cells via downregulation of Bcl-2 and NF-κB.

Activation of endoplasmic reticulum stress is involved in the activity of icariin against human lung adenocarcinoma cells.

In this study, we investigated the anticancer activity of icariin (ICA) against human lung adenocarcinoma cells in vitro and in vivo and explored the role of endoplasmic reticulum (ER) stress (ERS) signaling in this process. ICA treatment resulted in a dose- and time-dependent decrease in the viability of human lung adenocarcinoma A549 cells. Additionally, ICA exhibited potent anticancer activity, as evidenced by reductions in A549 cell adhesion, migration and intracellular glutathione (GSH) levels and increases in the apoptotic index, Caspase 3 activity, and reactive oxygen species. Furthermore, ICA treatment increased the expression of ERS-related molecules (p-PERK, ATF6, GRP78, p-eIF2α, and CHOP), up-regulated the apoptosis-related protein PUMA and down-regulated the anti-apoptosis-related protein Bcl2. The down-regulation of ERS signaling using PERK siRNA desensitized lung adenocarcinoma cells to ICA treatment, whereas the up-regulation of ERS signaling using thapsigargin (THA) sensitized lung adenocarcinoma cells to ICA treatment. Additionally, ICA inhibited the growth of human lung adenocarcinoma A549 cell xenografts by increasing the expression of ERS-related molecules (p-PERK and CHOP), up-regulating PUMA, and down-regulating Bcl2. These data indicate that ICA is a potential inhibitor of lung adenocarcinoma cell growth by targeting ERS signaling and suggest that the activation of ERS signaling may represent a novel therapeutic intervention for lung adenocarcinoma.

Activation of Schwann cells in vitro by magnetic nanocomposites via applied magnetic field.

Schwann cells (SCs) are attractive seed cells in neural tissue engineering, but their application is limited by attenuated biological activities and impaired functions with aging. Therefore, it is important to explore an approach to enhance the viability and biological properties of SCs. In the present study, a magnetic composite made of magnetically responsive magnetic nanoparticles (MNPs) and a biodegradable chitosan-glycerophosphate polymer were prepared and characterized. It was further explored whether such magnetic nanocomposites via applied magnetic fields would regulate SC biological activities. The magnetization of the magnetic nanocomposite was measured by a vibrating sample magnetometer. The compositional characterization of the magnetic nanocomposite was examined by Fourier-transform infrared and X-ray diffraction. The tolerance of SCs to the magnetic fields was tested by flow-cytometry assay. The proliferation of cells was examined by a 5-ethynyl-2-deoxyuridine-labeling assay, a PrestoBlue assay, and a Live/Dead assay. Messenger ribonucleic acid of BDNF, GDNF, NT-3, and VEGF in SCs was assayed by quantitative real-time polymerase chain reaction. The amount of BDNF, GDNF, NT-3, and VEGF secreted from SCs was determined by enzyme-linked immunosorbent assay. It was found that magnetic nanocomposites containing 10% MNPs showed a cross-section diameter of 32.33±1.81 µm, porosity of 80.41%±0.72%, and magnetization of 5.691 emu/g at 8 kOe. The 10% MNP magnetic nanocomposites were able to support cell adhesion and spreading and further promote proliferation of SCs under magnetic field exposure. Interestingly, a magnetic field applied through the 10% MNP magnetic scaffold significantly increased the gene expression and protein secretion of BDNF, GDNF, NT-3, and VEGF. This work is the first stage in our understanding of how to precisely regulate the viability and biological properties of SCs in tissue-engineering grafts, which combined with additional molecular factors may lead to the development of new nerve grafts.