2019环境生物技术专刊序言

环境生物技术,作为一门由现代生物技术与环境工程相结合的新兴交叉学科,已经在环境污染治理、环境监测中得到了广泛的应用,环境友好、高效地处理有机及无机污染,同时变废为宝生产高值化合物为从根本上解决环境问题提供了希望与支持。本专刊报道了环境生物技术在多环芳烃、抗生素、石油基塑料等环境污染物降解领域的基础与应用研究,介绍了吲哚、微生物铁载体等分子在生物修复中的应用,为全面认识环境污染现状、深入开展环境生物技术研究并制定综合治理策略等提供参考。     

基于文献计量分析的珊瑚礁研究现状与热点

珊瑚礁生态系统在全球海洋生态中扮演着重要角色,它为热带海洋动物提供栖息地,为人类提供食物药物资源,是全球生产力最高的生态系统之一。为了解当前国内外珊瑚相关研究的现状与热点,利用文献计量的方法统计分析了珊瑚的相关研究。文章分别以WEB OF SCIENCE数据库和中国期刊全文数据库(CNKI)中期刊论文为国际和国内的数据源,从文献计量的角度出发,利用Excel按年份统计论文的发文数量,通过Bibexcel得出高频词共词矩阵,并用Ucinet和Netdraw得出共词网络可视化图谱。利用SPSS进行聚类分析,分别将国内外相关研究分为四大类,分析珊瑚相关研究趋势与热点。研究表明:①国际与国内的珊瑚研究除个别年份有所回落,均基本成逐年上升趋势,大致于20世纪90年代开始进入成熟阶段,但国内的研究略迟于国际;②国际上对珊瑚的研究更倾向于探究珊瑚礁退化的原因,而国内则以提高珊瑚礁的造礁能力为研究热点;③通过共词分析得出,国际研究高频词中的coral reefs,corals,climate change,sedimentation,一定程度上也可视为研究热点;④通过聚类分析,国内外的珊瑚研究有一定的相似性,主要集中在珊瑚礁生态系统、影响珊瑚的环境因子、气候因子等几个方面,但国内外研究又各有侧重。总结得出,有关珊瑚、珊瑚礁研究在国内外均以珊瑚礁为重点,近年来和未来珊瑚礁研究注重于珊瑚礁修复或帮助珊瑚礁生态系统自行恢复。     

药用白及资源再生策略初探

白及为兰科白及属植物。作为著名中药,白及功效多样、用途广泛,具有较高的药用价值和经济价值。随资源利用强度的增加,野生白及资源日渐萎缩,人工规模化种植是实现白及药用资源可持续利用的必由之路。优良种质及繁育技术是种植业的关键问题。为了更好地推动白及资源研究和可持续利用,本文就白及种质及快繁技术研究进展作一综述,并就白及资源再生策略进行初步探讨,为相关研究和生产提供参考。     

益生菌黏附能力评估模型的研究进展

益生菌的黏附能力是益生菌在宿主肠道中稳定定殖的关键,也是益生菌发挥作用的前提。研究者常以益生菌的黏附能力作为筛选益生菌菌种的重要标准,因此建立稳定的益生菌黏附能力评估模型一直是该领域的研究热点。着重介绍了益生菌黏附能力评估模型的种类和检测方法,旨在为益生菌黏附能力评估模型的研究及应用提供参考。     

协同分布式实验2.0 (CDE 2.0):生态学野外研究新方法

全球野外实验网络是近年来兴起的生态学实验方法,产生了“协同分布式实验”(CDE)、“分布式协作实验”(DCE)的野外实验网络和英国生物学记录中心(BRC)的野外观察网络等具体方法,但均存在尺度小、周期短或数据偏差问题.野外实验网络的协议设计应秉持实验优于观察测量、数据数量优于数据质量和尺度优于操作的原则.综合上述方法,本研究提出利用公众科学(citizen science)获得大范围、多尺度和长周期的数据,采用环境因子作为协变量对公众参与者的实验数据集进行验证后,将其作为后验概率与作为主观概率的生态学家实验数据集进行比对,以完成数据有效性验证,克服公众参与者数据质量瑕疵,并提出了相应的统计学模型.讨论了生态学实验数据中应用先验概率、先验与后验概率的逻辑关系以及后验概率发现演化过程新关系的可能性.这种方法更符合统计学采样规范,并增加了大尺度时空的样本量.该方法有望为生态学研究所寻找的一般性理论提供方法支持,新方法可称之为“协同分布式实验2.0”(CDE 2.0).     

Current methods for the maturation of induced pluripotent stem cellderived cardiomyocytes

Induced pluripotent stem cells(iPSCs) were first generated by Yamanaka and colleagues over a decade ago. Since then, iPSCs have been successfully differentiated into many distinct cell types, enabling tissue-, disease-, and patientspecific in vitro modelling. Cardiovascular disease is the greatest cause of mortality worldwide but encompasses rarer disorders of conduction and myocardial function for which a cellular model of study is ideal. Although methods to differentiate iPSCs into beating cardiomyocytes(iPSC-CMs) have recently been adequately optimized and commercialized, the resulting cells remain largely immature with regards to their structure and function,demonstrating fetal gene expression, disorganized morphology, reliance on predominantly glycolytic metabolism and contractile characteristics that differ from those of adult cardiomyocytes. As such, disease modelling using iPSC-CMs may be inaccurate and of limited utility. However, this limitation is widely recognized, and numerous groups have made substantial progress in addressing this problem. This review highlights successful methods that have been developed for the maturation of human iPSC-CMs using small molecules,environmental manipulation and 3-dimensional(3 D) growth approaches.     

Site fertility drives temporal turnover of vegetation at high latitudes

Experimental evidence shows that site fertility is a key modulator underlying plant community changes under climate change. Communities on fertile sites, with species having fast dynamics, have been found to react more strongly to climate change than communities on infertile sites with slow dynamics. However, it is still unclear whether this generally applies to high‐latitude plant communities in natural environments at broad spatial scales. We tested a hypothesis that vegetation of fertile sites experiences greater changes over several decades and thus would be more responsive under contemporary climate change compared to infertile sites that are expected to show more resistance. We resurveyed understorey communities (vascular plants, bryophytes, and lichens) of four infertile and four fertile forest sites along a latitudinal bioclimatic gradient. Sites had remained outside direct human disturbance. We analyzed the magnitude of temporal community turnover, changes in the abundances of plant morphological groups and strategy classes, and changes in species diversity. In agreement with our hypothesis, temporal turnover of communities was consistently greater on fertile sites compared to infertile sites. However, our results suggest that the larger turnover of fertile communities is not primarily related to the direct effects of climatic warming. Furthermore, community changes in both fertile and infertile sites showed remarkable variation in terms of shares of plant functional groups and strategy classes and measures of species diversity. This further emphasizes the essential role of baseline environmental conditions and nonclimatic drivers underlying vegetation changes. Our results show that site fertility is a key determinant of the overall rate of high‐latitude vegetation changes but the composition of plant communities in different ecological contexts is variously impacted by nonclimatic drivers over time.     

基于计量学方法分析数字PCR技术的临床应用现状与技术热点

近年来数字PCR技术作为第三代PCR技术迅猛发展,已被应用于无创产前筛查、病毒核酸检测及肿瘤液体活检等领域。以中国生物医学文献数据库、PubMed医学文献检索服务系统及Incopat专利数据库收录的与“数字PCR技术临床应用”相关的中英文论文和专利文献为数据源,利用计量学方法分析了数字PCR临床应用现状与技术热点趋势,明确该技术的主要研究机构包括美国弗雷德-哈钦森肿瘤研究中心、哈佛医学院丹娜法伯癌症研究所和Bio-Rad公司等。中文文献发表机构中检验检疫部门和疾控中心占比较高。国内外数字PCR技术研究主要聚焦于肿瘤伴随诊断、病毒检测和基因表达分析等方面。中国数字PCR技术研究热情较高,专利申请已展现出国际领先趋势。     

篮状菌属微生物次级代谢产物研究进展

天然产物的主要来源之一是微生物,不同于其他的生物资源,真菌菌种相对容易选育和保藏、适应力较强,可通过大规模发酵获取产物,更具有利于自然资源的可持续发展性和利用价值。篮状菌（Talaromyces sp.）及其次级代谢产物在天然色素上的研究受到科学家的青睐,同时在食品、环境、农业和医药等方面发挥了重要作用,尤其是海洋来源的篮状菌及其次级代谢物表现出显著的生物活性,例如杀虫、抗肿瘤、抗菌、抗病毒等。近来研究表明,篮状菌次级代谢产物根据生物合成的方式可以分为六大类：萜类（terpenes）、生物碱类（fumiquinazolines）、聚酮类（polyketides）、聚酯类（lactones）、醌类（quinones）和甾体类（steroids）,这些活性物质对促进药物的先导物质挖掘与开发具有重要意义。本文通过对文献和资料的查阅,总结了近年来篮状菌及其次级代谢物的研究开发进展,希望为后续研究和应用提供参考。     

Applications of a new subspace clustering algorithm (COSA) in medical systems biology

A novel clustering approach named Clustering Objects on Subsets of Attributes (COSA) has been proposed (Friedman and Meulman, (2004). Clustering objects on subsets of attributes. J. R. Statist. Soc. B 66, 1–25.) for unsupervised analysis of complex data sets. We demonstrate its usefulness in medical systems biology studies. Examples of metabolomics analyses are described as well as the unsupervised clustering based on the study of disease pathology and intervention effects in rats and humans. In comparison to principal components analysis and hierarchical clustering based on Euclidean distance, COSA shows an enhanced capability to trace partial similarities in groups of objects enabling a new discovery approach in systems biology as well as offering a unique approach to reveal common denominators of complex multi-factorial diseases in animal and human studies. Doris Damian, Matej Orešič, and Elwin Verheij contributed equally to this work.