川中丘陵地区大豆根瘤菌遗传多样性与系统发育关系

【目的】研究分离自川中丘陵地区大豆根瘤菌的遗传多样性和系统发育。【方法】采用16S rDNA PCR-RFLP和16S rRNA基因、glnII、共生基因(nodC)系统发育分析的方法进行研究。【结果】供试未知菌的16S rDNA用4种限制性内切酶(HaeⅢ、HinfⅠ、MspⅠ及TaqⅠ)酶切后获得5种16S遗传图谱类型。16S rDNA PCR-RFLP结果表明,所有供试菌株在83%水平分为慢生根瘤菌属(Bradyrhizobium)和中华根瘤菌属(Sinonrhizobium)两大类群,而75%的菌株为中华根瘤菌。6个代表菌株的16S rDNA、glnII和nodC三个位点基因的系统发育结果基本一致,4株与S.fredii USDA205T相似度最高;有2株分别与B.yuanmingense CCBAU10071T、B.diazoefficiens USDA110T相似度最高。4个Sinonrhizobium代表菌株16S rDNA、glnII序列相似度分别为98.3%-99.9%、98.2%-100%,但它们的nodC基因序列完全相同。【结论】川中丘陵地区大豆根瘤菌具有较丰富的遗传多样性,S.fredii为优势种。     

黄河三角洲滨海湿地微生物多样性及其驱动因子

微生物在湿地的生物地球化学循环和生态功能调节中发挥着重要作用,对全球气候变化具有重大影响,对维持全球生态系统的健康至关重要。以黄河三角洲滨海湿地为研究对象,通过采集代表性植被群落的土壤表层和部分植物根系,探究土壤微生物群落组成、根际微生物、环境因子及其内在的关联性和影响机制。研究结果表明不同植被覆盖地区微生物多样性存在差异,芦苇区和柽柳区微生物丰度高于泥滩区、碱蓬区和棉田,海漫滩微生物丰度高于河漫滩地和泥滩。土壤微生物菌群结构和多样性显著高于根际：土壤细菌的香农指数约为4-5.5,根际微生物的香农指数约为0-4。土壤细菌主要为厚壁菌门、变形菌门、拟杆菌门和放线菌门,占样品总数的90%以上;而根际细菌主要是蓝藻门、变形菌门和放线菌门,二者在属水平上的菌群结构差异更加明显。环境因子的含量与生境类型有关,SO₄^2-和NO₃^-的相关性最高,植被覆盖区土壤中Mn⁴⁺、Fe³⁺和水解氮的含量低于滩涂裸地。冗余分析（RDA）表明,pH值在小空间尺度上对湿地土壤中细菌群落的影响较小,环境因子在门和属水平的解释率分别为89.7%和86.8%,其中K（23.4%）、NO₂^-（11.8%）、Mn⁴⁺（9.8%）和Na（8.0%）是解释门水平微生物区系结构变化和组成的主要因子。研究为理解湿地微生物多样性与湿地生态系统功能之间的影响机制提供了一个生态学视角,有助于了解黄河三角洲滨海湿地土壤和植物根际的细菌分布特征,对黄河三角洲退化滨海湿地的生物修复具有重要的指导意义。     

温度感受器TRPV1调节疼痛

2021年诺贝尔生理学或医学奖由戴维·朱利叶斯(David Julius)和阿德姆?帕塔普蒂安(Ardem Patapoutian)共同获得,以表彰二人分别在温度感受器辣椒素受体(TRPV1)和触觉感受器PIEZO1/2方面做出的杰出贡献.此项工作有助于阐明神经系统如何感知冷、热和机械刺激的机制,以及开发治疗疼痛的药物...     

Identification,Design and Bio-Evaluation of Novel Hsp90 Inhibitors by Ligand-Based Virtual Screening

Heat shock protein 90 (Hsp90), whose inhibitors have shown promising activity in clinical trials, is an attractive anticancer target. In this work, we first explored the significant pharmacophore features needed for Hsp90 inhibitors by generating a 3D-QSAR pharmacophore model. It was then used to virtually screen the SPECS databases, identifying 17 hits. Compound S1 and S13 exhibited the most potent inhibitory activity against Hsp90, with IC₅₀ value 1.61±0.28 μM and 2.83±0.67 μM, respectively. Binding patterns analysis of the two compounds with Hsp90 revealed reasonable interaction modes. Further evaluation showed that the compounds exhibited good anti-proliferative effects against a series of cancer cell lines with high expression level of Hsp90. Meanwhile, S13 induced cell apoptosis in a dose-dependent manner in different cell lines. Based on the consideration of binding affinities, physicochemical properties and toxicities, 24 derivatives of S13 were designed, leading to the more promising compound S40, which deserves further optimization.     

Identification of cancer hallmark‐associated gene and lncRNA cooperative regulation pairs and dictate lncRNA roles in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Numerous cancers share ten common traits (“hallmarks”) that govern the transformation of normal cells into cancer cells. Long non‐coding RNAs (lncRNAs) are important factors that contribute to tumorigenesis. However, very little is known about the cooperative relationships between lncRNAs and cancer hallmark‐associated genes in OSCC. Through integrative analysis of cancer hallmarks, somatic mutations, copy number variants (CNVs) and expression, some OSCC‐specific cancer hallmark‐associated genes and lncRNAs are identified. A computational framework to identify gene and lncRNA cooperative regulation pairs (GLCRPs) associated with different cancer hallmarks is developed based on the co‐expression and co‐occurrence of mutations. The distinct and common features of ten cancer hallmarks based on GLCRPs are characterized in OSCC. Cancer hallmark insensitivity to antigrowth signals and self‐sufficiency in growth signals are shared by most GLCRPs in OSCC. Some key GLCRPs participate in many cancer hallmarks in OSCC. Cancer hallmark‐associated GLCRP networks have complex patterns and specific functions in OSCC. Specially, some key GLCRPs are associated with the prognosis of OSCC patients. In summary, we generate a comprehensive landscape of cancer hallmark‐associated GLCRPs that can act as a starting point for future functional explorations, the identification of biomarkers and lncRNA‐based targeted therapy in OSCC.     

LNRLMI: Linear neighbour representation for predicting lncRNA‐miRNA interactions

LncRNA and miRNA are key molecules in mechanism of competing endogenous RNAs(ceRNA), and their interactions have been discovered with important roles in gene regulation. As supplementary to the identification of lncRNA‐miRNA interactions from CLIP‐seq experiments, in silico prediction can select the most potential candidates for experimental validation. Although developing computational tool for predicting lncRNA‐miRNA interaction is of great importance for deciphering the ceRNA mechanism, little effort has been made towards this direction. In this paper, we propose an approach based on linear neighbour representation to predict lncRNA‐miRNA interactions (LNRLMI). Specifically, we first constructed a bipartite network by combining the known interaction network and similarities based on expression profiles of lncRNAs and miRNAs. Based on such a data integration, linear neighbour representation method was introduced to construct a prediction model. To evaluate the prediction performance of the proposed model, k‐fold cross validations were implemented. As a result, LNRLMI yielded the average AUCs of 0.8475 ± 0.0032, 0.8960 ± 0.0015 and 0.9069 ± 0.0014 on 2‐fold, 5‐fold and 10‐fold cross validation, respectively. A series of comparison experiments with other methods were also conducted, and the results showed that our method was feasible and effective to predict lncRNA‐miRNA interactions via a combination of different types of useful side information. It is anticipated that LNRLMI could be a useful tool for predicting non‐coding RNA regulation network that lncRNA and miRNA are involved in.