新医学是解决人类健康问题的真正钥匙——需“精准”理解奥巴马的“精准医学计划”

2015年年初,美国总统奥巴马在国情咨文中提出了一个预算2.15亿美元的“精准医学计划”,希望以此“引领一个医学时代”。新闻一经发布,“精准医学”立刻成为了媒体和百姓嘴边的热词,受此影响国内亦有不少人士纷纷为美国总统的这一计划点“赞”。有人用“医学革命”来形容它,有人用“开创性”来抬高它,还有一个传闻,受奥巴马“精准医学计划”的影响,中国将在15年内投入600亿元人民币启动并发展中国版的“精准医学计划”。对此,有人提出了质疑,美国版精准医学计划是否符合中国国情?是否存在“水土不服”的可能?直接套用美国总统的智慧能否解决具有中国特色的实际问题?争论由此引发一个让人思考的问题,究竟什么才是现代医学的核心?在盲目堆钱的行动前,我们确实有必要从科学和临床应用的角度来探讨和思考一下现代医学的发展方向。 为了能“精准”地看到问题的实质,我将从当下时髦并且相关的词汇谈起,通过梳理,期待找出解决人类健康问题的真正钥匙。     

大气CO2浓度和气温升高对麦田节肢动物群落的影响

为了预测气候变化对麦田节肢动物群落多样性的影响, 本研究在麦田开放环境中设置4种处理, 分别是高温(高于当时气温2℃和当前CO₂浓度)、高CO₂浓度(500 μL/L和当时气温)、高温+高CO₂浓度和对照(当前CO₂浓度和气温)等, 采用定期随机抽样方法调查节肢动物群落的多样性, 用经典的多样性指数对整体节肢动物群落以及不同食性节肢动物群落多样性进行分析。共采到节肢动物3纲10目42科52种。仅“高温”和“高温+高CO₂”处理显著增大节肢动物群落的均匀度, 其余处理均无显著影响。“高温+高CO₂”处理的影响随小麦生长发育期不同而略有差异, 在苗期可增大Shannon-Wiener多样性指数, 而在后期使该指数减小; “高温+高CO₂”与“高温”处理的群落多样性较为相似。对不同食性节肢动物群落的分析表明, 与对照相比, 植食性昆虫群落在“高CO₂”下丰富度显著增大; 寄生性昆虫群落的多度在“高温”下显著增大; 腐食性等节肢动物群落的多度在“高CO₂+高温”和“高温”处理下有所增大、均匀度在“高温”下略降低, 但均未达统计上的显著水平; 捕食性节肢动物群落不受影响。本研究说明, CO₂浓度和气温升高不同程度地影响麦田节肢动物群落的物种多样性, 两类因素同时升高与各自单独升高的影响不完全一致。     

2021年中国植物科学重要研究进展

2021年中国植物科学家在国际综合性学术期刊及植物科学主流期刊发表的论文数量相比2020年显著增加, 在雌雄细胞识别与受精、干细胞命运决定、菌根共生、光合膜蛋白复合体、氮磷养分利用、先天免疫、作物从头驯化与基因组设计等方面取得了重要研究进展,“异源四倍体野生稻快速从头驯化”入选2021年度“中国生命科学十大进展”。该文总结了2021年度我国植物科学研究取得的成绩, 简要介绍了30项重要进展, 以帮助读者了解我国植物科学的发展态势, 思考如何更好地将植物科学研究与国家重大需求有效衔接。     

我国“干细胞及转化研究”重点专项的组织实施及思考

“十三五”期间,我国设立了国家重点研发计划“干细胞及转化研究”重点专项(以下简称“专项”)。通过五年实施,专项取得了显著进展。通过对专项立项和实施情况的回顾,总结管理中的经验和不足,为“十四五”干细胞研究部署提出相关建议,以进一步增强我国干细胞及转化研究的核心竞争力,加快推进干细胞研究成果惠及人民健康。     

“地衣”词考

本文考证了中国先秦时期到清末古籍中对“地衣”的解释;其中有共生学意义的“地衣”一词,是在清代李善兰的《植物学》一书中被提出的。     

“教学、实践、科研、临床”四位一体的医学遗传学教学体系建设探索与实践

医学遗传学课程介于基础医学和临床医学之间,是一门应用性很强的学科,在现代医学教育体系中有着重要的地位。教学团队在多年的医学遗传学教学实践中,在建设省级精品课程的过程中,构建了“教学、实践、科研、临床”四位一体的医学遗传学教学体系,主要内容包括“课堂教学、社会实践、科学研究、临床应用”四者之间相互渗透、相互补充、相互促进,以课堂教学为基础,用社会实践补充教学,科学研究提升教学,临床应用促进教学。“四位一体”教学体系为基础课程与临床课程的有机整合探索了一条切实可行的路子。实施几年来,课程建设收到了良好效果,学科团队科研水平、社会声誉、医疗服务能力也有明显提高。     

中国草原/荒漠植物多样性监测网 模式植物群落监测方案

“模式群落”是指能够反映某种植被分类单元基本特征, 并可作为准确描述该植被类型“标准”的典型植物群落。中国生物多样性监测网络——草原/荒漠植物多样性监测网旨在统一监测方法和技术规范的基础上, 在草原/荒漠植被主要群系分布的典型地段建立模式植物群落监测固定样方, 定期复查, 长期监测草原和荒漠的植物多样性变化。文章强调了典型植物群落监测是生物多样性监测的重要组成部分, 阐述了模式群落的概念, 介绍了草原/荒漠植物多样性监测网的总体思路和布局, 以及主要监测内容、方法、指标和预期产出。     

植物群落稀有种维持机制与土壤反馈的研究进展

自Janzen-Connell (J-C)假说提出后半个世纪以来, 生态学家在热带及亚热带森林对该假说开展的大量实证研究表明, 由专性天敌导致的J-C效应所引起的负密度制约是维持森林多样性和决定群落组成的重要驱动力, 该假说成功地解释了热带及亚热带森林的丰富多样性。土壤病原真菌所引起的植物-土壤负反馈是J-C效应最主要的表现形式。然而, 对于植物-土壤负反馈是否能够维持森林群落中的大量稀有种仍然存在许多争议。基于当代物种共存理论的“稀有种优势”假说认为, 只有在满足“可入侵准则” (即物种在稀有时具有种群增加的趋势)的前提下, 稀有种才能在群落中与其他物种长期共存。然而, 当前基于土壤反馈的实验结果与该理论预测相悖, 因此在稀有种的维持机制方面仍存在较大的分歧。本文通过介绍植物-土壤反馈理论, 整合了可能对稀有种维持有较大影响的因素, 包括共生菌根真菌、土壤养分以及植物细根性状等在影响土壤负反馈方面的相关研究, 并对这些因素如何影响群落中物种多度和稀有种在群落中的维持进行了探讨。最后, 我们也从其他角度探讨了一些对稀有种维持的研究。我们认为在未来对稀有种的研究中, 探讨使其长期存续的“优势”和制约其种群扩大的“限制”同等重要, 将当代物种共存理论与新技术、新方法相结合对于探究稀有种的维持机制具有重要的意义, 可为稀有种保护提供理论依据。     

围小丛壳Glomerella cingulata子囊孢子交配繁殖、生物学特性及致病性

炭疽叶枯病（Glomerella leaf spot）是我国苹果上新发现的一种病害。为了解围小丛壳Glomerella cingulata子囊孢子的交配方式、生物学特性和致病性,从安徽砀山、山东牟平等地采集病害样品,经分离培养和纯化获得单孢菌株。在适宜条件下单孢菌株可产生子囊和子囊孢子,经过毛细管破子囊壁后单孢分离,获得12个子囊,每个子囊有8个子囊孢子。其中10个子囊中有4个“正”孢子（+）和4个“负”孢子（-）,2个子囊中只有“负”孢子。子囊孢子单孢菌株培养72h,“正”菌株菌落白色,以营养生长为主;“负”菌株菌落灰白色,直径略小于正菌株,菌丝稀疏,边缘菌丝白色,中部有大量橙色的分生孢子堆。“正”、“负”菌株异宗配合后,可产生大量可育子囊壳;单独的“正”菌株有性生殖产生稀疏丛簇状的可育子囊壳;单个的“负”菌株只能产生分散且不育的子囊壳。“正”、“负”菌株菌落的生长速度没有差异,对温度、营养、光照和pH值的敏感性也没有差异,但“正”、“负”菌株的致病性存在差异。正菌株的有性生殖没有导致rDNA-ITS、β-tubulin基因碱基序列变异。     

我国植物种级水平分类学研究刍议

对洪德元先生最近在《生物多样性》(2016年第24卷第3期)发表的《关于提高物种划分合理性的意见》一文中的部分观点进行了进一步阐述。强调我国植物确实还存在大量种级水平的分类学问题有待解决, 我国植物分类学研究在一些重要发展阶段(如系统阶段和物种生物学阶段)上存在明显缺失, 需要弥补。指出分类学发展到今天, 不宜再强调“经典分类学”和“实验分类学”之分, 应采用多学科手段解决分类学问题; 我国应加强植物分类专著水平的研究工作, 注意培养年轻一辈植物分类学专著工作者; 在分类处理中应用居群概念和统计学方法时应特别谨慎; 在系统植物学中接受物种概念的多元性是必要的, 但要向达到广义的生物学种概念努力, 不宜以有所谓的“归并派”和“细分派”之分为借口而完全主观地划分物种。     

Where Next for Microbiome Research?

The development of high-throughput sequencing technologies has transformed our capacity to investigate the composition and dynamics of the microbial communities that populate diverse habitats. Over the past decade, these advances have yielded an avalanche of metagenomic data. The current stage of “van Leeuwenhoek”–like cataloguing, as well as functional analyses, will likely accelerate as DNA and RNA sequencing, plus protein and metabolic profiling capacities and computational tools, continue to improve. However, it is time to consider: what’s next for microbiome research? The short pieces included here briefly consider the challenges and opportunities awaiting microbiome research.

This Perspective is part of the “Where next?” Series.

Soon, we will enter an era when “the number of population genomes deposited in public databases will dwarf those from isolates and single cells” (Gene Tyson). Clearly, as all authors noted in the following, our focus will move from describing the composition of microbial communities to elucidating the principles that govern their assembly, dynamics, and functions. How will such principles be discovered? Elhanan Borenstein proposes that a systems biology–based approach, particularly the development of mathematical and computational models of the interactions between the specific community components, will be critical for understanding the function and dynamics of microbiomes. Evolutionary biologists Howard Ochman and Andrew Moeller want to decipher how microbial assemblies evolve but challenge us to also consider the role of microbial communities in organismal evolution, and they make the exciting prediction that microbes will be implicated in the evolution of eusociality and cooperation. Brett Finlay underscores the need for deciphering the mechanistic bases—particularly the chemical/metabolite signals—for interactions between members of microbial communities and their hosts. He emphasizes how this knowledge will enable creation of new tools to manipulate the microbiota, a key challenge for future investigation. Heidi Kong also encourages deciphering the mechanisms that underlie associations between particular skin surfaces and disorders and their respective microbiota. Jeffrey Gordon considers several intriguing opportunities as well as challenges that manipulation of the gut microbiota presents for improved human nutrition and health. Finally, Karen Nelson, Karim Dabbagh and Hamilton Smith suggest that using synthetic genomes to create novel microbes or even synthetic microbiomes offers a new way to engineer the microbiota. Overall, future microbiome research regarding the molecules and mechanisms mediating interactions between members of microbial communities and their hosts should lead to discovery of exciting new biology and transformative therapeutics.     

Metagenomic analysis reveals a functional signature for biomass degradation by cecal microbiota in the leaf-eating flying squirrel (Petaurista alborufus lena)

ABSTRACT: BACKGROUND: Animals co-evolve with their gut microbiota; the latter can perform complex metabolic reactions that cannot be done independently by the host. Although the importance of gut microbiota has been well demonstrated, there is a paucity of research regarding its role in foliage-foraging mammals with a specialized digestive system. RESULTS: In this study, a 16S rRNA gene survey and metagenomic sequencing were used to characterize genetic diversity and functional capability of cecal microbiota of the folivorous flying squirrel (Petaurista alborufus lena). Phylogenetic compositions of the cecal microbiota derived from 3 flying squirrels were dominated by Firmicutes. Based on end-sequences of fosmid clones from 1 flying squirrel, we inferred that microbial metabolism greatly contributed to intestinal functions, including degradation of carbohydrates, metabolism of proteins, and synthesis of vitamins. Moreover, 33 polysaccharide-degrading enzymes and 2 large genomic fragments containing a series of carbohydrate-associated genes were identified. CONCLUSIONS: Cecal microbiota of the leaf-eating flying squirrel have great metabolic potential for converting diverse plant materials into absorbable nutrients. The present study should serve as the basis for future investigations, using metagenomic approaches to elucidate the intricate mechanisms and interactions between host and gut microbiota of the flying squirrel digestive system, as well as other mammals with similar adaptations.     

Genomics, environmental genomics and the issue of microbial species

A microbial species concept is crucial for interpreting the variation detected by genomics and environmental genomics among cultivated microorganisms and within natural microbial populations. Comparative genomic analyses of prokaryotic species as they are presently described and named have led to the provocative idea that prokaryotes may not form species as we think about them for plants and animals. There are good reasons to doubt whether presently recognized prokaryotic species are truly species. To achieve a better understanding of microbial species, we believe it is necessary to (i) re-evaluate traditional approaches in light of evolutionary and ecological theory, (ii) consider that different microbial species may have evolved in different ways and (iii) integrate genomic, metagenomic and genome-wide expression approaches with ecological and evolutionary theory. Here, we outline how we are using genomic methods to (i) identify ecologically distinct populations (ecotypes) predicted by theory to be species-like fundamental units of microbial communities, and (ii) test their species-like character through in situ distribution and gene expression studies. By comparing metagenomic sequences obtained from well-studied hot spring cyanobacterial mats with genomic sequences of two cultivated cyanobacterial ecotypes, closely related to predominant native populations, we can conduct in situ population genetics studies that identify putative ecotypes and functional genes that determine the ecotypes' ecological distinctness. If individuals within microbial communities are found to be grouped into ecologically distinct, species-like populations, knowing about such populations should guide us to a better understanding of how genomic variation is linked to community function.     

Systematic Identification of Gene Families for Use as “Markers” for Phylogenetic and Phylogeny-Driven Ecological Studies of Bacteria and Archaea and Their Major Subgroups

With the astonishing rate that genomic and metagenomic sequence data sets are accumulating, there are many reasons to constrain the data analyses. One approach to such constrained analyses is to focus on select subsets of gene families that are particularly well suited for the tasks at hand. Such gene families have generally been referred to as “marker” genes. We are particularly interested in identifying and using such marker genes for phylogenetic and phylogeny-driven ecological studies of microbes and their communities (e.g., construction of species trees, phylogenetic based assignment of metagenomic sequence reads to taxonomic groups, phylogeny-based assessment of alpha- and beta-diversity of microbial communities from metagenomic data). We therefore refer to these as PhyEco (for phylogenetic and phylogenetic ecology) markers. The dual use of these PhyEco markers means that we needed to develop and apply a set of somewhat novel criteria for identification of the best candidates for such markers. The criteria we focused on included universality across the taxa of interest, ability to be used to produce robust phylogenetic trees that reflect as much as possible the evolution of the species from which the genes come, and low variation in copy number across taxa.We describe here an automated protocol for identifying potential PhyEco markers from a set of complete genome sequences. The protocol combines rapid searching, clustering and phylogenetic tree building algorithms to generate protein families that meet the criteria listed above. We report here the identification of PhyEco markers for different taxonomic levels including 40 for “all bacteria and archaea”, 114 for “all bacteria (greatly expanding on the ∼30 commonly used), and 100 s to 1000 s for some of the individual phyla of bacteria. This new list of PhyEco markers should allow much more detailed automated phylogenetic and phylogenetic ecology analyses of these groups than possible previously.     

Signal Processing for Metagenomics: Extracting Information from the Soup

Traditionally, studies in microbial genomics have focused on single-genomes from cultured species, thereby limiting their focus to the small percentage of species that can be cultured outside their natural environment. Fortunately, recent advances in high-throughput sequencing and computational analyses have ushered in the new field of metagenomics, which aims to decode the genomes of microbes from natural communities without the need for cultivation. Although metagenomic studies have shed a great deal of insight into bacterial diversity and coding capacity, several computational challenges remain due to the massive size and complexity of metagenomic sequence data. Current tools and techniques are reviewed in this paper which address challenges in 1) genomic fragment annotation, 2) phylogenetic reconstruction, 3) functional classification of samples, and 4) interpreting complementary metaproteomics and metametabolomics data. Also surveyed are important applications of metagenomic studies, including microbial forensics and the roles of microbial communities in shaping human health and soil ecology.     

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao''s estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics (‘Hill diversities''), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao''s estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.     

Metagenomics,paratransgenesis and the Anopheles microbiome: a portrait of the geographical distribution of the anopheline microbiota based on a meta-analysis of reported taxa

Anophelines harbour a diverse microbial consortium that may represent an extended gene pool for the host. The proposed effects of the insect microbiota span physiological, metabolic and immune processes. Here we synthesise how current metagenomic tools combined with classical culture-dependent techniques provide new insights in the elucidation of the role of the Anopheles-associated microbiota. Many proposed malaria control strategies have been based upon the immunomodulating effects that the bacterial components of the microbiota appear to exert and their ability to express anti-Plasmodium peptides. The number of identified bacterial taxa has increased in the current “omics” era and the available data are mostly scattered or in “tables” that are difficult to exploit. Published microbiota reports for multiple anopheline species were compiled in an Excel^® spreadsheet. We then filtered the microbiota data using a continent-oriented criterion and generated a visual correlation showing the exclusive and shared bacterial genera among four continents. The data suggested the existence of a core group of bacteria associated in a stable manner with their anopheline hosts. However, the lack of data from Neotropical vectors may reduce the possibility of defining the core microbiota and understanding the mosquito-bacteria interactive consortium.     

Modelling spatial patterns in host-associated microbial communities

Microbial communities exhibit spatial structure at different scales, due to constant interactions with their environment and dispersal limitation. While this spatial structure is often considered in studies focusing on free-living environmental communities, it has received less attention in the context of host-associated microbial communities or microbiota. The wider adoption of methods accounting for spatial variation in these communities will help to address open questions in basic microbial ecology as well as realize the full potential of microbiome-aided medicine. Here, we first overview known factors affecting the composition of microbiota across diverse host types and at different scales, with a focus on the human gut as one of the most actively studied microbiota. We outline a number of topical open questions in the field related to spatial variation and patterns. We then review the existing methodology for the spatial modelling of microbiota. We suggest that methodology from related fields, such as systems biology and macro-organismal ecology, could be adapted to obtain more accurate models of spatial structure. We further posit that methodological developments in the spatial modelling and analysis of microbiota could in turn broadly benefit theoretical and applied ecology and contribute to the development of novel industrial and clinical applications.