Effect of heavy metals on the methanogenic activity of starch-degrading granules

Summary Heavy metals in electroplating effluent inhibited specific methanogenic activity (SMA) of anaerobic starch-degrading granules. The SMA of granules on the degradation of starch were reduced by 50% when each gram of biomass was in contact individually with 105 mg of zinc, 120 mg of nickel, 180 mg of copper, 310 mg of chromium, or >400 mg of cadmium. Granules had higher toxicity-resistance than flocculent sludge, due to their layered structure.     

旋毛虫肌幼虫ES抗原的基因克隆及高效表达

作者对编码旋毛虫肌幼虫ES抗原的部分结构基因进行了克隆、鉴定和表达。用RNA PCR技术直接从旋毛虫肌幼虫总RNA中反转录并扩增出0．7kh的靶DNA,酶切分析后将其克隆到融合表达载体pEx3lC中。SDS—PAGE电泳表明,含重组子的大肠杆菌能够表达出一分子量为37kDa的融合蛋白(P37),后者占菌体总蛋白的22%以上,并以包含体形式存在于菌体中。经对纯化后表达蛋白的ELlSA检测,证明它能被猪旋毛虫病阳性血清和抗旋毛虫单克隆抗体识别。研究结果揭示,重组蛋白P37对于研制旋毛虫病诊断抗原和免疫抗原具有潜在的应用价值。     

沙打旺组织培养中脱分化细胞的超微结构及细胞核的动态变化

对沙打旺的下胚轴、子叶、幼叶组织培养中脱分化细胞进行了超微结构观察,并着重讨论了细胞核的动态变化。脱分化细胞的细胞质中线粒体墙加,嵴明显;多聚核糖体增多;高尔基体增加;质体中积累淀粉。核仁与核内异染色质之间有一个动态过程。此过程暂称“核仁物质喷射“现象。在致有以下：１．核体出现,半嵌在增大的核仁上,核内异染色质沿核膜凝聚;２．异染色质移向核仁,并与核仁接触,核体消失,部分异质进入核仁;３．核仁物质     

cⅠ857基因的体外定位同义突变

 ｃⅠ８５７基因的体外定位同义突变陈南春,高辉,陈苏民,杨萍,刘新平（西安第四军医大学分子生物学研究所,西安７１００３２）外源基因要在大肠杆菌中获得高表达,需要合适的ＳＤ序列和可调控的强启动子［１］。ＰＬ启动子在原核启动子中属强启动子,它受ｃⅠ基因产物...     

促髓细胞分化的锌指基因单向PCR扩增直接测序的研究

锌指基因是一种造血调节基因,编码锌指结构蛋白,主要在髓细胞中表达,促进髓细胞分化,在急性早幼粒白血病维甲酸治疗中,促使病情缓解。本文报道了我们从基因分子上研究锌指基因作用中,探索并建立了单向聚合酶链反应（ＰＣＲ）扩增特定单链ＤＮＡ,直接测序的新方法。它能产生质和量均佳的单链ＤＮＡ,无需纯化即可直接用于测序,使复杂的测序研究简便易行,可在２,３天内完成。这种单向ＰＣＲ扩增特定单链ＤＮＡ直接测序的方法,经对锌指基因的ｃＤＮＡ测序,得到验证。此法不仅适用于疾病研究中的ＤＮＡ测序,还可制各单链ＤＮＡ探针,更利于基因结构组成的研究。     

在条锈菌侵染早期小麦初生叶内多聚核糖体水平与蛋白质合成能力的变化

小麦初生叶接种条锈菌毒性生理小种（ＣＹ２９）及其弱毒突变菌系（ＣＹ２９－ｍｕｔ３）后,呈不亲和反应的寄主叶片可溶性蛋白质合成能力在接种后２４ｈ显著高于未接种对照,但其后逐渐降低,直至接近对照;而呈亲和性反应的寄主叶片可溶性蛋白质合成在侵染早期与对照相近,但与膜结合蛋白质在９６ｈ时大大高于对照。对接种叶中核糖体的密度梯度分析证实：呈不亲和反应寄主叶片游离多聚核糖体及亲和反应的寄主内与膜结合多聚核糖体均有特异性增加。上述结果表明寄主的抗病和感病反应均与蛋白质合成能力的变化有关。     

Identification of a purC gene from Streptococcus pneumoniae.

A gene encoding 5'-phosphoribosyl-5-aminoimidazole-4-N-succinocarboxamide synthetase was identified in Streptococcus pneumoniae as a 708-bp segment of the genome encoding a 27,001-Da protein with strong similarity to known PurC proteins. The S. pneumoniae purC gene, found immediately adjacent to the competence induction genes, comAB, was cloned and sequenced. The predicted protein product of purC displayed substantial (> 40%) identity to the entire sequence of the PurC proteins of Bacillus subtilis and Escherichia coli. Function of the S. pneumoniae gene product was demonstrated by complementation of E. coli purC mutations.     

The detection and attribution of extreme reductions in vegetation growth across the global land surface

Negative extreme anomalies in vegetation growth (NEGs) usually indicate severely impaired ecosystem services. These NEGs can result from diverse natural and anthropogenic causes, especially climate extremes (CEs). However, the relationship between NEGs and many types of CEs remains largely unknown at regional and global scales. Here, with satellite-derived vegetation index data and supporting tree-ring chronologies, we identify periods of NEGs from 1981 to 2015 across the global land surface. We find 70% of these NEGs are attributable to five types of CEs and their combinations, with compound CEs generally more detrimental than individual ones. More importantly, we find that dominant CEs for NEGs vary by biome and region. Specifically, cold and/or wet extremes dominate NEGs in temperate mountains and high latitudes, whereas soil drought and related compound extremes are primarily responsible for NEGs in wet tropical, arid and semi-arid regions. Key characteristics (e.g., the frequency, intensity and duration of CEs, and the vulnerability of vegetation) that determine the dominance of CEs are also region- and biome-dependent. For example, in the wet tropics, dominant individual CEs have both higher intensity and longer duration than non-dominant ones. However, in the dry tropics and some temperate regions, a longer CE duration is more important than higher intensity. Our work provides the first global accounting of the attribution of NEGs to diverse climatic extremes. Our analysis has important implications for developing climate-specific disaster prevention and mitigation plans among different regions of the globe in a changing climate.     

Climate–ecosystem modelling made easy: The Land Sites Platform

Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.     

Long-term changes in Noctiluca scintillans blooms along the Chinese coast from 1933 to 2020

Noctiluca scintillans is one of the most common harmful algal species and widely known due to its bioluminescence. In this study, the spatial distribution, seasonal variations, and long-term trends of N. scintillans blooms in China and the related drivers were analyzed and discussed. From 1933 to 2020, a total of 265 events of N. scintillans blooms were recorded in Chinese coastal waters, with a total duration of 1052 days. The first N. scintillans bloom occurred in Zhejiang in 1933, and only three events were recorded before 1980. From 1981 to 2020, N. scintillans caused harmful algal blooms (HABs) almost every year, both the average duration and the proportion of multiphase HABs showed an increasing trend. 1986–1992, 2002–2004, and 2009–2016 were the three peak periods with a frequency of no less than five events of N. scintillans blooms per year. In terms of spatial distribution, N. scintillans blooms spread from the Southeast China Sea to the Bohai Sea after 2000, Guangdong, Fujian, and Hebei were the three provinces with the highest numbers of recorded events of N. scintillans blooms. Moreover, 86.8% of the events of N. scintillans blooms occurred in spring (March, April, and May) and summer (June, July, and August). Among environmental factors, the dissolved inorganic phosphate, dissolved silicate and chemical oxygen demand were significantly correlated with the cell density of N. scintillans during N. scintillans blooms, and most of N. scintillans blooms were recorded in the temperature range of 18.0–25.0°C. Precipitation, hydrodynamics, water temperature, and food availability might be the main factors affecting the spatial–temporal distribution of N. scintillans blooms along the Chinese coast.