Chromosome-level genome assembly and characterization of Sophora Japonica

Sophora japonica is a medium-size deciduous tree belonging to Leguminosae family and famous for its high ecological, economic and medicinal value. Here, we reveal a draft genome of S. japonica, which was ∼511.49 Mb long (contig N50 size of 17.34 Mb) based on Illumina, Nanopore and Hi-C data. We reliably assembled 110 contigs into 14 chromosomes, representing 91.62% of the total genome, with an improved N50 size of 31.32 Mb based on Hi-C data. Further investigation identified 271.76 Mb (53.13%) of repetitive sequences and 31,000 protein-coding genes, of which 30,721 (99.1%) were functionally annotated. Phylogenetic analysis indicates that S. japonica separated from Arabidopsis thaliana and Glycine max ∼107.53 and 61.24 million years ago, respectively. We detected evidence of species-specific and common-legume whole-genome duplication events in S. japonica. We further found that multiple TF families (e.g. BBX and PAL) have expanded in S. japonica, which might have led to its enhanced tolerance to abiotic stress. In addition, S. japonica harbours more genes involved in the lignin and cellulose biosynthesis pathways than the other two species. Finally, population genomic analyses revealed no obvious differentiation among geographical groups and the effective population size continuously declined since 2 Ma. Our genomic data provide a powerful comparative framework to study the adaptation, evolution and active ingredients biosynthesis in S. japonica. More importantly, our high-quality S. japonica genome is important for elucidating the biosynthesis of its main bioactive components, and improving its production and/or processing.     

PARP inhibitor olaparib enhances the efficacy of radiotherapy on XRCC2-deficient colorectal cancer cells

The use of PARP inhibitors in combination with radiotherapy is a promising strategy to locally enhance DNA damage in tumors. Loss of XRCC2 compromises DNA damage repairs, and induced DNA damage burdens may increase the reliance on PARP-dependent DNA repairs of cancer cells to render cell susceptibility to PARP inhibitor therapy. Here we tested the hypothesis that XRCC2 loss sensitizes colorectal cancer (CRC) to PARP inhibitor in combination with radiotherapy (RT). We show that high levels of XRCC2 or PARP1 in LARC patients were significantly associated with poor overall survival (OS). Co-expression analyses found that low levels of PARP1 and XRCC2 were associated with better OS. Our in vitro experiments indicated that olaparib+IR led to reduced clonogenic survival, more DNA damage, and longer durations of cell cycle arrest and senescence in XRCC2-deficient cells relative to wild-type cells. Furthermore, our mouse xenograft experiments indicated that RT + olaparib had greater anti-tumor effects and led to long-term remission in mice with XRCC2-deficient tumors. These findings suggest that XRCC2-deficient CRC acquires high sensitivity to PARP inhibition after IR treatment and supports the clinical development for the use of olaparib as a radiosensitizer for treatment of XRCC2-deficient CRC.Subject terms: Colorectal cancer, Prognostic markers     

一株产絮凝剂不动杆菌的筛选及其絮凝特性

从活性污泥中筛选出一株高效的微生物絮凝剂产生菌,鉴定为鲍曼不动杆菌.蚕豆根尖细胞微核试验未显示该菌株所产絮凝剂具有遗传毒性.该菌产絮凝剂的最佳碳源和氮源分别为葡萄糖和酵母浸出汁,培养时间为24 h.在絮凝体系中加入Ca2 能明显提高发酵液的絮凝率.在pH为8.0时对高岭土悬浊液和污水具有良好的絮凝效果.     

DeepMHADTA: Prediction of Drug-Target Binding Affinity Using Multi-Head Self-Attention and Convolutional Neural Network

Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and development. With the rapid advancement of deep learning, computational methods are increasingly applied to screen drug-target interactions. Many methods consider this problem as a binary classification task (binding or not), but ignore the quantitative binding affinity. In this paper, we propose a new end-to-end deep learning method called DeepMHADTA, which uses the multi-head self-attention mechanism in a deep residual network to predict drug-target binding affinity. On two benchmark datasets, our method outperformed several current state-of-the-art methods in terms of multiple performance measures, including mean square error (MSE), consistency index (CI), rm2, and PR curve area (AUPR). The results demonstrated that our method achieved better performance in predicting the drug–target binding affinity.     

Time-Series Clustering of lncRNA-mRNA Expression during the Adipogenic Transdifferentiation of Porcine Skeletal Muscle Satellite Cells

Skeletal muscle satellite cells (SMSCs), which are multifunctional muscle-derived stem cells, can differentiate into adipocytes. Long-chain non-coding RNA (lncRNA) has diverse biological functions, including the regulation of gene expression, chromosome silencing, and nuclear transport. However, the regulatory roles and mechanism of lncRNA during adipogenic transdifferentiation in muscle cells have not been thoroughly investigated. Here, porcine SMSCs were isolated, cultured, and induced for adipogenic differentiation. The expressions of lncRNA and mRNA at different time points during transdifferentiation were analysed using RNA-seq analysis. In total, 1005 lncRNAs and 7671 mRNAs showed significant changes in expression at differential differentiation stages. Time-series expression analysis showed that the differentially expressed (DE) lncRNAs and mRNAs were clustered into 5 and 11 different profiles with different changes, respectively. GO, KEGG, and REACTOME enrichment analyses revealed that DE mRNAs with increased expressions during the trans-differentiation were mainly enriched in the pathways for lipid metabolism and fat cell differentiation. The genes with decreased expressions were mainly enriched in the regulation of cell cycle and genetic information processing. In addition, 1883 DE mRNAs were regulated by 193 DE lncRNAs, and these genes were related to the controlling in cell cycle mainly. Notably, three genes in the fatty acid binding protein (FABP) family significantly and continuously increased during trans-differentiation, and 15, 13, and 11 lncRNAs may target FABP3, FABP4, and FABP5 genes by cis- or trans-regulation, respectively. In conclusion, these studies identify a set of new potential regulator for adipogenesis and cell fate and help us in better understanding the molecular mechanisms of trans-differentiation.     

长白山西坡小叶章侵入苔原带过程及影响

长白山西坡岳桦林带的草本植物(以小叶章为代表)侵入了苔原带,形成了独特的植物入侵现象。在光谱及影像分析的基础上,结合GPS(Global Positional System)定位技术,并依据小叶章与牛皮杜鹃的光谱差异及其反演的NDVI(Normalized Difference Vegetation Index)植被指数,揭示小叶章侵入苔原带的过程;通过对不同侵入时间、强度的斑块进行群落调查及土壤测试,探究小叶章侵入苔原带的生态后果。结果显示小叶章侵入苔原带始于20世纪80年代后期,由低海拔向高海拔推进,进入21世纪后逐渐形成了稳定的以小叶章为优势物种的植物群落结构。目前,低海拔处的小叶章斑块经过多年扩张已连接成片,而高海拔处的斑块正处于扩张的初期阶段。从生物多样性变化可以看出,小叶章侵入苔原带导致植物群落多样性升高和物种数量的增加,苔原带原有的灌木数量明显减少,草本植物逐渐增多。植被的改变影响了土壤的理化性质,C/N比下降,土壤腐殖质含量和全氮含量下降,但速效氮和土壤持水能力上升,土壤养分的高效利用又进一步推动了小叶章的侵入。小叶章侵入苔原带已经造成了严重的生态后果。     

Discovery and SAR analysis of 5-chloro-4-((substituted phenyl)amino)pyrimidine bearing histone deacetylase inhibitors

Histone deacetylases (HDACs) are validated targets for the development of anticancer drugs in epigenetics. In the discovery of novel HDAC inhibitors with anticancer potency, the 5-chloro-4-((substituted phenyl)amino)pyrimidine fragment is assembled as a cap group into the structure of HDAC inhibitors. The SAR revealed that presence of small groups (such as methoxy substitution) is beneficial for the HDAC inhibitory activity. In the enzyme inhibitory selectivity test, compound L20 exhibited class I selectivity with IC₅₀ values of 0.684 µM (selectivity index of >1462), 2.548 µM (selectivity index of >392), and 0.217 µM (selectivity index of >4608) against HDAC1, HDAC2 and HDAC3 compared with potency against HDAC6 (IC₅₀ value of >1000 µM), respectively. In the antiproliferative assay, compound L20 showed both hematological and solid cancer inhibitory activities. In the flow cytometry, L20 promoted G0/G1 phase cell cycle arrest and apoptosis of K562 cells.     

环境因子和干扰强度对高寒草甸植物多样性空间分异的影响

采用样带与样地结合的方法在三江源自然保护区的核心区沿海拔梯度在阴坡、阳坡分别进行草本植被调查,通过因子分析和偏相关分析研究丰富度指数、多样性指数与环境梯度（包括海拔梯度、裸斑面积、坡度、土壤总碳、总氮含量、土壤pH值、土壤总可溶性盐含量）和干扰强度（鼠类干扰强度、放牧强度）之间的关系。研究结果表明：杂类草丰富度指数（DMa杂）与总物种丰富度指数（DMa总）极显著相关（P<0.01）;阳坡DMa杂和DMa总均呈现“中海拔膨胀”现象,阴坡DMa杂和DMa总与海拔梯度呈正相关,莎草科和禾本科的丰富度指数（DMa莎和DMa禾）随海拔升高并无明显规律;通过主成分分析,及偏相关分析,第一主成分（裸斑面积、鼠类干扰和放牧强度）与除莎草科Margalef丰富度指数、禾本科Simpson指数和禾本科Pielou均匀度指数外的其他草地多样性指数均显著相关,是影响阳坡草地植物多样性的主要因子,土壤总碳、总氮含量对阳坡禾本科类群的多样性指数和均匀度指数有极显著影响,土壤pH值、TDS含量和坡度对阳坡莎草科类群的丰富度有显著影响;海拔梯度、土壤总碳、总氮以及pH值对阴坡草本植物群落的多样性影响较大。研究结论认为,植物群落生物多样性的空间分异特征是地理环境、土壤环境以及干扰强度等因素综合作用的结果。无干扰或干扰较弱时,物种多样性主要受土壤环境状况所影响;而在强干扰存在条件下,干扰强度对物种丰富度和多样性的影响比环境因子更显著;遏制高寒草甸植物多样性降低应首先控制放牧及鼠类等强干扰活动。     

工业园区氮代谢——以江苏宜兴经济开发区为例

以江苏宜兴经济开发区为例,基于物质流分析构建了工业园区的氮代谢网络和分析方法,解析了工业园区中产业系统和污水处理系统的氮代谢途径和通量。研究表明,氮物质流系统的源和汇比磷物质流系统多,流通量大且较为集中;氮肥生产、纺织印染和食品加工行业是宜兴经济开发区的主要氮排放源;企业自备处理设施除氮效果较好,去除率约79%,而污水处理厂由于设计和运行等原因氮去除率较低,约57%;生活污水氮去除率低;直接排入水体的降水造成的水体负荷约28%。由此,建议企业继续完善企业内处理设施,对集中污水处理厂进行脱氮除磷提标改造,同时加强对园区内生活污水、生活垃圾和企业固体排放物的管理。