RCSB Protein Data Bank: Enabling biomedical research and drug discovery

Analyses of publicly available structural data reveal interesting insights into the impact of the three‐dimensional (3D) structures of protein targets important for discovery of new drugs (e.g., G‐protein‐coupled receptors, voltage‐gated ion channels, ligand‐gated ion channels, transporters, and E3 ubiquitin ligases). The Protein Data Bank (PDB) archive currently holds > 155,000 atomic‐level 3D structures of biomolecules experimentally determined using crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy. The PDB was established in 1971 as the first open‐access, digital‐data resource in biology, and is now managed by the Worldwide PDB partnership (wwPDB; wwPDB.org ). US PDB operations are the responsibility of the Research Collaboratory for Structural Bioinformatics PDB (RCSB PDB). The RCSB PDB serves millions of RCSB.org users worldwide by delivering PDB data integrated with ～40 external biodata resources, providing rich structural views of fundamental biology, biomedicine, and energy sciences. Recently published work showed that the PDB archival holdings facilitated discovery of ～90% of the 210 new drugs approved by the US Food and Drug Administration 2010–2016. We review user‐driven development of RCSB PDB services, examine growth of the PDB archive in terms of size and complexity, and present examples and opportunities for structure‐guided drug discovery for challenging targets (e.g., integral membrane proteins).     

UV-B辐射诱导芒果叶片抗氧化响应研究

为了解增强UV-B辐射诱导芒果叶片抗氧化响应的机制,以?台农1号?芒果(Mangifera indica?Tainong No. 1?)成年树为材料,以自然光为对照(CK),设置24和96 kJ/(m~2·d)两个增强UV-B辐射处理水平,观测叶片生理生化指标的动态变化。结果表明,24k J/(m~2·d)处理的芒果叶片MDA含量、相对电导率、净光合速率、抗氧化酶活性、多酚、Vc和芒果苷含量均与对照没有显著差异,而类黄酮和还原型GSH含量显著高于对照;而96 kJ/(m~2·d)处理的芒果叶片MDA含量、相对电导率、抗氧化酶活性及多酚、类黄酮、还原型GSH、芒果苷等还原型保护成分的含量均显著高于对照,而净光合速率和Vc含量均显著低于对照。因此,24 kJ/(m~2·d) UV-B辐射未引起?台农1号?芒果成年树损伤,可能是通过提高类黄酮和还原型GSH的含量来清除活性氧自由基;96 kJ/(m~2·d)处理则引起叶片活性氧损伤,但仍可能以两种机制减轻损伤,一是通过增强抗氧化酶活性和提高还原性成分含量来清除活性氧自由基,二是利用芒果苷、类黄酮和还原型GSH等成分吸收UV-B辐射。     

农业主产区湖泊水质对湖滨带多尺度景观格局的空间响应

为分析农业主产区湖泊水环境质量对不同空间尺度上景观格局的响应关系,以洪湖为研究对象,以5种湖泊功能区为基础,利用RS和GIS软件生成7种空间尺度的湖滨带缓冲区,采用Fragstats 软件分析景观格局指数,结合冗余分析等数理统计方法与模型,研究景观格局对洪湖水质变化的空间尺度效应。结果表明: 1)景观格局在不同宽度缓冲区内对湖泊水质的影响具有空间尺度性,在200 m宽度其解释能力最大,达到86.1%,是影响水质的最有效空间尺度。2)景观配置变量(如最大斑块指数、斑块密度等)对水质的影响程度大于景观组成变量(如面积比例和均匀度指数等)。3)景观类型对水质的影响机制具有较大的差异性,农业用地受流域的地形地貌和耕作方式等因素的影响,在100～500 m小尺度的湖滨带缓冲区内对水质退化起主导作用;在远离水体的相对较大尺度(1000～5000 m),林地分布越密集、面积越大,对污染物进入水体的净化作用越明显;草地对水质的影响与林地一致;密集分布的城市用地对水质的影响与林地相反。研究结果可以从宏观尺度上为农业主产区湖泊流域水质管理和景观合理配置提供科学参考。     

Migration sources and pathways of the pest species Sogatella furcifera in Yunnan,China, and across the border inferred from DNA and wind analyses

The migration sources and pathways of Sogatella furcifera (Horváth) in topologically complex regions like Yunnan, China, and adjacent montane areas have long been a challenging task and a bottleneck in effective pest forecast and control. The present research reinvestigated this issue using a combination of mtDNA and long‐term historical wind field data in an attempt to provide new insights. Genetic analyses showed that the 60 populations of S. furcufera collected across Myanmar, Thailand, Laos, Vietnam, Yunnan, Guizhou, and Sichuan lack genetic structure and geographic isolation, while spatial analysis of haplotype and diversity indices discovered geographic relevance between populations. Migration rate analysis combined with high‐resolution 10‐year wind field analysis detected the following migration sources, pathways, and impacted areas which could explain the outbreak pattern in Yunnan. (a) Dominating stepwise northward migrations originated from northern Indochina, southern Yunnan, and central‐eastern Yunnan, impacting their northern areas. (b) Concurring summer–autumn southward (return) migration originated from nearly all latitude belts of Sichuan and Yunnan mainly impacting central and southern Yunnan. (c) Regular eastward and summer–autumn westward migrations across Yunnan. The northward migration reflects the temporal rhythm of gradual outbreaks from the south to the north in a year, while the return migration may explain the repeated or very severe outbreaks in the impacted areas. To form a better pest forecast and control network, attention must also be paid to the northern part of Yunnan to suppress the impact of return migration in summers and autumns.     

Meta‐replication,sampling bias,and multi‐scale model selection: A case study on snow leopard (Panthera uncia) in western China

Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi‐scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape‐specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles’ overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape‐specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low‐contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi‐scale response of snow leopards to environmental attributes and confirms the role of meta‐replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction.     

丙酮丁醇梭菌(Clostridium acetobutylicum)原生质体融合育种研究

为了提高丙酮丁醇梭菌(Clostridium acetobutylicum)的丁醇耐受能力和培养基总糖产丁醇的转化率,通过原生质体融合的方法,研究了溶菌酶浓度及其作用时间、再生培养基种类、55℃条件下菌体致死时间、不同PEG分子量以及作用时间、Ca^2+和Mg^2+不同的添加量对丙酮丁醇梭菌原生质体制备、融合、再生的影响,得到了一套比较系统的丙酮丁醇梭菌的原生质体融合条件,同时通过气相色谱检测了融合菌的产溶剂能力并计算总糖转化率。结果显示,最终得到的215I菌株的总糖转化率比原始菌株提高了34.7%,产丁醇能力比原始菌株提高了32.2%,并且发现1株融合菌能产生新物质。原生质体融合方法在丙酸丁醇梭菌育种方面有广泛的应用潜力,通过融合得到的菌株为丁醇生产奠定了基础。     

Five candidate biomarkers associated with the diagnosis and prognosis of cervical cancer

Purpose: Cervical cancer (CC) is one of the most general gynecological malignancies and is associated with high morbidity and mortality. We aimed to select candidate genes related to the diagnosis and prognosis of CC.Methods: The mRNA expression profile datasets were downloaded. We also downloaded RNA-sequencing gene expression data and related clinical materials from TCGA, which included 307 CC samples and 3 normal samples. Differentially expressed genes (DEGs) were obtained by R software. GO function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed in the DAVID dataset. Using machine learning, the optimal diagnostic mRNA biomarkers for CC were identified. We used qRT-PCR and Human Protein Atlas (HPA) database to exhibit the differences in gene and protein levels of candidate genes.Results: A total of 313 DEGs were screened from the microarray expression profile datasets. DNA methyltransferase 1 (DNMT1), Chromatin Assembly Factor 1, subunit B (CHAF1B), Chromatin Assembly Factor 1, subunit A (CHAF1A), MCM2, CDKN2A were identified as optimal diagnostic mRNA biomarkers for CC. Additionally, the GEPIA database showed that the DNMT1, CHAF1B, CHAF1A, MCM2 and CDKN2A were associated with the poor survival of CC patients. HPA database and qRT-PCR confirmed that these genes were highly expressed in CC tissues.Conclusion: The present study identified five DEmRNAs, including DNMT1, CHAF1B, CHAF1A, MCM2 and Kinetochore-related protein 1 (KNTC1), as potential diagnostic and prognostic biomarkers of CC.