塔拉海洋科考队探索浮游生物的多样性

  海洋覆盖了地球面积的三分之二,是30多亿年前生命诞生的地方。海洋发挥着强大的碳汇作用,吸收了人类活动排放的二氧化碳的近30%,浮游植物的光合作用主导着该过程。浮游生物是一种肉眼观测不到的生物体,在碳(地球上产生的氧气有一半来自海洋)、氮、磷、硫等元素的主要生物地球化学循环中起重要作用。然而,参与这些循环过程的微生物并不为人知。塔拉海洋科考队成立了一个国际科学联盟,为探索海洋中这类未知的生物制定了准确的采样和分析方案,生成高精度数据并进行分析。经过三年在地球海洋的航行和研究,塔拉海洋科考队的科学家们揭示了真核单细胞生物(又称原生生物)鲜为人知的多样性。近10亿的基因条形码测序从根本上改变了我们对浮游生物的种类和功能多样性的认知,明确了浮游生物对地球生态系统运作的关键意义。

1. 探索地球上最大的生态系统

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-浮游生物个体图片
图1. 浮游生物图片。 [来源:Christian Sardet/法国科学研究中心(CNRS)/塔拉科考团/知识共享署名-相同方式国际协议(CC BY-SA 4.0)]

  海洋是地球上最大的连续生态系统,海洋生物的生物量大部分由肉眼不可见的生物组成,即海洋微生物。其中最主要的类群是“浮游生物”。“浮游生物”(plankton)一词来自希腊语planktos,即wanderer(流浪者),指生活在水体中,不能逆流游动的生物。因此,海洋浮游生物包括原生生物(单细胞真核生物)、细菌、古生菌、病毒以及较大生物的幼虫阶段(如鱼类或甲壳类动物的幼体)(图1)。

  21世纪零零年代中期,高通量DNA测序技术的出现实现了全球海洋微生物群落多样性和分布的可量化,并为大空间尺度采样提供技术支持。事实上,浮游生物的分布高度依赖于非生物因素,如光照、营养物质、湍流、温度、盐度或pH值;也受到生物因素的影响,如捕食者或共生生物。尽管浮游生物的数量存在水平和垂直空间以及季节间的差异,但该类群广泛存在于海洋中。

浮游生物对地球的重要性是多方面的:

  • 浮游生物是食物链的基础,它们占地球每年初级生产力(光合作用)的50%[1]
  • 浮游生物的生产代谢对碳、氧、氮、磷和硫的主要生物地球化学循环过程起重要作用。
  • 海洋吸收了近30%人类活动产生的二氧化碳(一种温室气体),这一强大碳吸收功能主要得益于浮游植物通过光合作用物捕获二氧化碳的能力(参见“人类活动对碳循环的破坏”)。

2. 塔拉海洋科考

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-塔拉海洋科考期间使用的塔拉号帆船
图2.塔拉海洋科考期间使用的塔拉号帆船。[照片来源: 塔拉海洋萨夏·波莱基金会]

  自2006年以来,塔拉号帆船上的科学家们进行了一系列科学考察活动(图2):

  • 塔拉北极项目(2006-2008年):塔拉号在浮冰上漂流近两年,科学家们收集了大气、冰以及海洋数据。塔拉号在冰中停留了504天,最终到达了船只(破冰船除外)所能到达的最北位置:北纬88°32′10″ N。
  • 塔拉海洋项目(2009-2013年):这是一次前所未有的大规模浮游生物研究,塔拉号行驶了14万公里,穿越地球上所有海洋。塔拉海洋极圈探险也是塔拉海洋项目的一部分,该项目绕极圈进行了为期6个月的任务,是历史上第一次在一年内跨越北极东北和西北航道。
  • 塔拉地中海项目(2014年):评估了微塑料对地中海生态系统健康和功能的影响。
  • 塔拉太平洋项目(2016-2018年):探索了珊瑚礁在面对全球变化时抵抗、适应和恢复的潜力。
  • 塔拉微塑料项目(2019年):历经欧洲4个海岸,从9条主要河流采集样本,以追踪塑料污染的来源。
环境百科全书-塔拉海洋科考队探索浮游生物的多样性-塔拉号帆船的航行路线
图3.塔拉号帆船的航行路线。航线超过14万公里,于20个生物地理区的210个站点共采集了4万份海水和浮游生物样本。[图片来源: 塔拉基金会的南北极项目(https://oceans.taraexpeditions.org)]

  也就是说,塔拉海洋科考队探索了全球海洋表层(0-200米深)和中层(200-1000米深)水体中种类繁多的浮生物(从病毒到鱼类幼体)。

  该项目从20个生物地理区的210个站点共收集了4万份海水和浮游生物样本,并探明以下问题:

  • 海洋中浮游生物多样性程度如何?
  • 哪些生物承担着最重要的生态功能
  • 环境参数和生物的相互作用对海洋生态系统有何影响

  为了回答这些问题,塔拉海洋科考队汇集了来自世界各地的250多名科学家。他们在这艘36米长的帆船上进行了长达三年的高度标准化取样

  塔拉海洋项目使用了许多新技术分析工具,建立了第一个将生物地理学、生态学、遗传学和形态学结合在一起的全球数据收集工作,汇集了来自不同学科的国际团队:海洋生态学家、微生物学家、海洋学家、统计学家、生物地球化学家、计算机科学家和进化生物学家。

  制定标准的取样方案旨在研究多样的海洋生态系统:上升流、生物多样性热点、低pH值或贫氧区等。为了将浮游生物的形态和基因样本置于环境背景中,研究人员总共设定了210个站点(图3),并对这些监测站进行了更精确的环境特征分析。

3. 样品收集的主要原则

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-塔拉海洋考察期间使用的采样方法
图4.塔拉海洋科考期间使用的采样方法。使用合适的设备按个体大小差异收集生物样本。蓝色背景表示为了获得足够的生物量进行分析所过滤的海水体积。[来源: Eric Karsenti蒂等人和塔拉海洋联盟,知识共享署名国际协议(CC BY 4.0),通过维基共享](Sampling strategy 采样方法;volume filtered 体积过滤;seawater 海水;Niskin botttles 尼斯金采水瓶;Total Sea Water 海水总量;Filtration 过滤装置;GPSS 通用系统模拟器;Nets 网;mesh 孔径;Sizefractions collected:分粒径大小范围采样;Virus 病毒;Girus 巨病毒;Bacteria 细菌;Protists 原生生物;Zoopplankton 浮游动物;cell/body size:细胞或个体尺寸)

  塔拉海洋科考对210个站点中的大部分(图3)都进行了三个深度的采样。

  • 第一个水层是表层(SUR),为水面以下3至7米深的水层。
  • 第二个水层被称为“叶绿素最大值层”(DCM),为光合浮游生物丰度最大的水层,一般由荧光法测定叶绿素浓度来确定。浮游植物生长所必需的两种条件是光线和较冷的深层海水向上补充的营养物质,这个最大值的存在由这两个条件共同来决定。
  • 第三个水层为“弱光层”,该水层位于DCM之下,是阳光能到达的最大深度,平均深度为700米。

  在每一个站点,分别对不同大小范围的生物采样(图4)[2]

  在塔拉海洋科考期间收集的浮游生物大小包括六个量级,分别是:

  • 病毒和巨型病毒(giant viruses,也称为giruses)(参见:“海洋病毒”);
  • 原核生物(细菌和古生菌);
  • 单细胞真核生物(原生生物、真菌和微藻);
  • 多细胞真核生物(桡足类)。

  单细胞真核生物的直径在0.8到2000微米之间。使用适当网目大小的网建立几个尺寸范围:0.8-5微米,5-20微米,20-180微米,180-2000微米。

  视频1:塔拉海洋(包括下图)浮游生物采样。浮游生物过滤(通用系统模拟器)。

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-基于样本个体大小的形态分析方法
图5.基于样本个体大小的形态分析方法(从左至右):流式细胞技术、高通量显微镜、流式细胞摄像系统(FlowCam)和浮游动物图像扫描分析系统(ZooScan)。[来源: Eric Karsenti蒂等人和塔拉海洋联盟,知识共享署名国际协议(CC BY 4.0),通过维基共享](protists:原生生物;prokaryotes 原核生物;metazoa:后生动物;viruses:病毒;Flow Cytometry:流式细胞技术;High-Throughput Microscopy:高通量显微镜; FlowCam:流式细胞摄像系统; ZooScan:浮游动物图像扫描分析系统)

  在每个站点,对不同尺寸范围的样本进行形态学分析(图5):

  • 一方面,通过自动识别系统,如流式细胞摄像系统(FlowCam)[3]和浮游动物图像扫描分析系统(ZooScan)[4],能够对20微米到几厘米的生物多样性进行定量测定。
  • 另一方面,通过三维共聚显微镜和透射电子显微镜可以对小型原生生物的超微结构进行分析。

4. 浮游生物的基因多样性分析

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-样本的遗传分析方法
图6.样本的基因分析方法。[图片来源:Eric Karsenti等人和塔拉海洋联盟,知识共享署名国际协议(CC BY 4.0)](protists:原生生物;prokaryotes 原核生物;metazoan 后生生物;viruses 病毒;Total DNA 总脱氧核糖核酸片段;Total organismal diversity 总生物多样性;Metagenomics 宏基因组学;Total gene diversity 总基因多样性;Total RNA总核糖核酸片段;cDNA total 总的互补脱氧核糖核酸; cDNA messenger 互补脱氧核糖核酸序列;Metatranscriptomics 元转录组学;PCR:聚合酶链式反应;18S,28S,16S,CO1:分别为18S rDNA,28S rDNA,16S rDNA,CO1测序;Active organismal diversity活性生物多样性;Expressed gene diversity 基因表达多样性)

  对于每个监测站点,过滤水样获得样品后,运用不同的基因分析方法(图6),让我们了解谁(何种生物)在其中,它们在做什么,它们各有何种功能或潜力:

  • 通过对16S和18S rDNA(元条形码)的测序,编码核糖体RNA的基因:谁在其中
  • 元转录组学: 测定不同生物体在将基因转录成蛋白质的过程中产生的所有RNA:它们在做什么?
  • 宏基因组学:环境样本中所有的基因特征:它们能做什么?

  “条形码”、“转录组学”和“基因组学”等术语中添加的前缀“元”表示,这些分子分析不是对单个物种进行的,而是对来自环境样本生物群落进行的。高通量DNA测序[5][6]为定性和半定量地探索环境样本的基因多样性打开了大门。

4.1. 谁在其中?

  利用不同的分子技术来探索样品的遗传多样性

  分子条形码(DNA条形码):长期以来,微生物的系统发育是基于形态学和生化特征。近年来,分子标记(条形码)被用来重建生物的进化史,其简化的技术思维是,即两个生物在进化上的距离越远,它们的基因组序列之间的差异就越大。

  严格来说,DNA条形码与一个基因组的标准部分相比是一个短序列(通常为100至400个碱基对),例如:18S核糖体DNA。DNA条形码可用于识别物种,类似超市中使用的条形码,它可以确定产品(序列)和价格(物种的识别)之间的关系(参见描述生物多样性的DNA条形码)。这个序列是根据精确的标准选择的[7]

  • 种内变异性必须:这一序列必须在同一物种的所有生物中几乎相同;
  • 种间变异性必须,才能根据它们的序列区分两个不同的物种。
环境百科全书-塔拉海洋科考队探索浮游生物的多样性-真核生物rDNA的结构
图7.真核生物rDNA的结构。真核生物中rDNA簇的典型结构。18S、5.8S和28S基因编码核糖体RNA;ITS1和ITS2是内部转录间隔体。基因间间隔体(IGS)将这些重复的基因分隔开。V9为PCR引物的位置。(IGS 基因间间隔体;primers 引物)

  用于系统发育重建最常用的DNA分子标记是编码核糖体亚基rRNA的基因,即rDNAs。在大多数真核生物中,18S rRNA存在于核糖体小亚基中,而大亚基包含3个rRNA分子(哺乳动物为5S, 5.8S, 28S,植物为25S)。编码rRNAs的基因通常聚在一起,由内部转录间隔(ITS1和ITS2)和基因间间隔(IGS)分隔(图7)[8]

  元条形码。条形码作为一种分子工具,其作用不仅是对已知物种建立高分辨率系统发育,还应用于:保护、发现物种,以及群落生态学[9],[10]。随着高通量测序的出现,分子条形码(DNA条形码)以一种元条形码的方式被广泛应用于真核生物(和原核生物!)群落生态学研究。

  更正式地说,DNA元条形码是指从包含完整生物体的单一样本或包含降解DNA(来自土壤、水、粪便等)的环境样本中自动识别多个物种。用于分子元条形码研究的一个合理条形码(如18S rDNA)应该:

(i)在同一物种的个体中几乎相同的基因中的一部分,但在不同物种之间有所不同;

(ii) 适用于研究中的所有物种;

(iii) 允许在不同的水平上进行分类[6]

  样本DNA被提取后通过PCR(聚合酶链式反应)进行扩增。PCR是一种将以下状态下的DNA(或RNA)序列大量复制(增殖因子为十亿级)的技术:

  • 少量的核酸(数量级低至几个皮克);
  • 被称为“通用”引物的特定核苷酸引物,例如V9[12]序列,它可以特异性地扩增存在于所有个体中的特定部分DNA(扩增子,例如18S rDNA)。

  因此,扩增后得到的最终PCR产物是测试样本中所有生物体的V9序列的混合物。

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-图8
图8.大西洋(左,蓝色)和印度洋(右,粉色)样本之间共享丰富的条形码。在每个样本中,水平线表示测序获得的V9 rDNA条形码,灰色条形码对每个样本都是通用的(超过总条形码的31%),而蓝色和粉色条形码是具有区域特异性的。摘自参考文献[12]。(Shared V9 rDNA barcode richness 共享V9 rDNA条形码丰富性;Barcodes shared between Indian and Atlantic stations 印度和大西洋站点共享的条形码;Barcodes specific to Atlantic stations 大西洋采样站特有的条形码; Barcodes specific to Indian stations 印度采样站特有的条形码)

  在第二步中,对扩增的副本进行测序:这样我们就得到了样本V9序列的全部多样性(图 8)[13]。具有足够相似性的序列被分组为操作分类单元(OTU)[14]。DNA序列的相似性阈值常使用97%。一个物种必须与每个OTU相匹配。

  该分类的任务是通过比较样本的OTU和参考生物数据库来完成的。该方法的主要思路是查看OTU与哪个已知序列最接近,相似比例如何。相似程度会在一定程度上确定一个物种、属或科:如果一个OTU的序列与一个已知名称的物种100%相同,那么通过这个OUT即可被确定为该种类。

  但有时序列不够相似,对物种的鉴定只能达到属的层面,而不能准确至种的层面。

  但最大的障碍是,塔拉海洋调查所获得样品的OTU超过40%是全新的,与任何已知物种都不对应。我们只知道它们是真核生物,但几乎不可能把它们放在系统发育树中。能够发现未知的物种也令人兴奋!

4.2. 他们在做什么?

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-68个采样点获得的真核生物样本中转录组的数量
图9. 68个采样点获得的真核生物样本中转录组的数量。左图:每个大小范围真核生物的转录组片段数量;右图:按真核生物大小范围分组后,每个样本中转录组数量的分布情况(小横线)。摘自参考文献[16](Estimated number of transcriptomes 转录组的数量; Estimated number of transcriptomes per sample 每个样本转录组的数量)

  除了提供现存物种的详细目录,塔拉海洋科考队的采样还使用“元转录组学”技术。这有助于通过测序信使RNA(mRNA)来解释样本中表达的基因[15]

  为了专门研究真核生物转录组,可以只选择真核生物的mRNA(图9)[16][17]。这些mRNA在逆转录酶的作用下被逆转录:即获得的互补DNA并用于测序,然后将它们的序列与参考数据库中存在的序列进行比较,这种方法可以同时获得功能注释(这些转录本来自哪些基因,它们有什么用途?)和分类信息(这些转录本来自哪些生物种类?)。这就说明了“谁做什么”,详见Carradec等人发表的文章[17]

4.3. 它们能做什么?

  如今,基因组分析关注全基因组测序或宏基因组学,主要应用于原核生物样品[18]。全基因组分析对环境样本中的所有基因组进行测序,而不是使用特定的PCR引物(参见上文的元条形码)。

  • 提取DNA后,第一步是将样本中的所有DNA片段分成非常短的片段,然后进行测序;这被称为随机序列,或称散弹枪序列。
  • 随后,序列片段从重叠区域以生物信息学的方式组装,重建原始基因组。
环境百科全书-塔拉海洋科考队探索浮游生物的多样性-浮游生物样本
图10.浮游生物样本中所有的DNA都被测序,并与已知的基因组序列相对比。(Echantillon de plankton 浮游生物样本; Fragments d’AND DNA碎片;Extraction &fragmentation de l’AND 提取和片段化DNA;Séquences 序列;Séquençage global 整体测序;Séquences des génomes connus 已知基因组序列;Alignement des différentes séquences avec celle des génomes connus 将不同的序列与已知的基因组序列对齐)

  因此,宏基因组测序解释了所有未表达但存在于样本中的基因。这种类型的测序提供了关于样本中生物群落的基因潜力的信息,这就是“它们能做什么”,但不一定真的要去做。这种方法具有巨大的应用潜力但面临着许多技术的限制

  在塔拉海洋科考期间,能够用于高通量测序的DNA片段的数量刚刚超过500个碱基对。例如,如果我们考虑硅藻(一类大量存在的浮游植物)的基因组,它至少有3000万个碱基对的长度,这意味着必须对至少6万个DNA片段进行测序,才能重新构建这个完整的基因组(图10)。在实际操作中,分析从来不会对单个个体进行,而是对不同个体的混合DNA片段进行。

  在实际操作中,我们的测序不可能限制于在这6万个片段中随机进行,因为一旦这么做,硅藻基因组的某些部分将被多次重复测序,而其它部分则根本没有被测序,因此重建的基因组将会有“缺陷”。DNA的重叠片段也需要重建序列顺序。

  为了解决这个问题,测序过程不仅对单个基因组(60,000个片段)进行,而是对20个基因组(1,200,000个片段!)进行。

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-生物信息学方法
图11. 生物信息学方法结合高通量基因方法提供了关于基因和生物网络的功能解读,以及生态系统中物种空间分布的模型。[来源:Eric Karsenti等人和塔拉海洋联盟,知识共享署名国际协议(CC BY 4.0)](Community metabolome mapping 群落组织映射;Taxa/Gene network analysis 分类单元/基因网络分析;Ecosystem stochastic modeling 生态系统随机模型)

  在塔拉海洋考察中,对水体内成百上千的物种的基因组进行测序似乎是一项艰巨的任务。但完成该任务具有重要意义:大多数被识别的基因(>50%)与现有数据库中已有的基因没有同源性,这引发了很多思考。对基因序列进行组装[19]和注释[20]的挑战是巨大的,但每年都在进步。

  结合定量图像,使用这些高通量测序方法不仅可以理解基因的结构、位置和功能,而且最重要的是,可以探索浮游生物的多样性。利用基于生物信息学的强大方法,这些分析提供了生物之间的进化、代谢和相互作用的数据(参见:海洋生物碳泵),并实现了群落代谢组、基因和生物网络以及物种空间分布模型的重建(图11)。

5. 惊人的多样性:浮游原生生物

环境百科全书-塔拉海洋科考队探索浮游生物的多样性-原生生物
图12.原生生物形成了一个与单细胞真核生物相对应的多系类群。左图为真核生物系统发育树(改编自Lecointre和Guyader, 2016);右图是一些浮游原生生物,包括硅藻、甲藻、绿藻和放射虫。[来源:Plankton mix©克里斯蒂安·萨德(C.Sardet )&诺亚·萨德(N.Sardet)浮游生物编年史(Chroniques du plancton), 塔拉海洋基金会](Archéoplastidés 古质体科;Glaucophytes 绿藻;Rhodophytes红藻;Archéoplastidés (= lignée verte) 古质体科;Bicontes 比康斯;Chloroplastidés 叶绿体;Excavates 挖掘;Hacrobiés 哈克罗比斯;Rhizariens 根瘤菌;Foraminifères 有孔虫;Radiolaires 放射虫;Eucaryotes 真核生物;Chromoalvéolés 色球泡;Clade SAR 进化枝;Straménopiles 藻类;Apicomplexés 顶复合物;Ciliophores 纤毛细胞;Alvéolates 蜂窝状;Phéophycées 褐藻科;Oomycètes 卵菌纲;Bacillanophycees 芽孢杆菌;Amoebozoaires 变形虫;Unicontes 单体;Opisthocontes 奥皮斯特霍斯特;Holomycetes 完整菌纲;Champignons 蘑菇;Choanoflagelles 鞭毛虫;Metazoaires 元动物;Nuclearides 核化物;Eumycetes 真菌纲;Microsporidies 微孢子)

  经过三年的航行和对海洋中受光照上层水体至底层的研究,塔拉海洋项目的研究人员发现了真核单细胞生物(也称为原生生物)巨大的多样性(图12)[21]。对近10亿个基因条形码的测序表明,原生生物的多样性远超过细菌或动物,它们中的大多数种类鲜为人知,包括了寄生虫、共生体和捕食者等所有群体。这些结果从根本上改变了我们对世界浮游生物的种类和功能多样性的看法,浮游生物是我们生物圈运作的关键生态系统。

  • 在“海洋之家(Maison des Océans)”上展示塔拉海洋的科考成果

  在这项研究中,研究人员仅从46个采样点就破译和分析了近10亿个核糖体DNA序列。这些序列被用作真核生物多样性的标志(参见:“什么是生物多样性?”以及“生物多样性不是奢侈品,而是必需品”),标记从最小的单细胞生物(小于1微米)到几毫米大小的浮游动物[22]

  生成的大量基因条形码首先使我们能够分析透光水层中几乎所有的真核浮游生物特征,鉴定出15万种遗传类型的真核浮游生物,与迄今为止所描述的1.1万种生物相比,这是一种未曾预料到的多样性。所列出的绝大多数基因类型在目前的基因数据库中似乎没有相似的参照物,说明这些生物大多是未被记录和不可培养的。其中三分之一的基因多样性与当今已知的任何主要真核生物系无关联。

  在现有的真核生物谱系中可分类的的基因类型中,大多数种类与单细胞生物(或原生生物)相对应,其生物类群多样性惊人,包括了寄生虫、共生物种和捕食者等。光合作用生物的多样性少得多,体型小得多,生物量也少得多。

  到目前为止,有100多篇论文是直接从塔拉海洋科考队的数据分析中得出的,包括五篇原创发表于2015年《科学》杂志“塔拉海洋”特刊的文章(仅使用“塔拉海洋”一词查询2009-2019年ISI Web of Science数据库;2020年10月2日)。

6. 要记住的信息

  • 经过三年的环球航行,塔拉海洋科考队的研究人员对浮游生物进行了详尽的研究,从而能够全面了解全球浮游生物生态系统
  • 这个项目已经从4万多个海水样本中发现了1.5亿个海洋基因、10万个基因定义物种以及决定浮游生物群落的分布的因素。还揭示了原生生物(单细胞真核生物)未知的多样性
  • 在领先期刊上发表的100多篇科学论文来自于对塔拉海洋科考队所获数据的直接分析结果。所有科学家都可以在公共数据库中免费获得这些数据。
  • 在开展这些研究活动的同时,塔拉海洋项目还旨在提高公众对气候变化相关问题的认识,其方法是通过开展大量工作坊、船上访问、提供教育工具等,这些途径都经由科学家验证,在其网站上可以获取。
  • 由此产生的科学也被用于气候治理:作为联合国的特别观察员,塔拉海洋科考队动员了最高层的政治决策者。
  • 塔拉海洋最初的科学组织: EMBL科学主任埃里克·卡森提(Eric Karsenti)、塔拉科考总监艾蒂安·布尔吉斯(Etienne Bourgois)、塔拉科考秘书长罗曼·特鲁布雷(Romain Troublé)、EMBL的斯蒂芬妮·坎德尔斯·刘易斯(Stephanie Kandels Lewis)和DVIP 咨询公司业务经理迪迪埃·韦拉尤东(Didier Velayoudon)。
  • 塔拉海洋科学协调员: 这一跨学科的国际小组制定了采样战略和总体计划,确定了总体考察和项目目标,领导了考察工作,并在过去十年中对大部分结果进行了分析。见参考文献 [23]

 


参考资料及说明

封面照片:[G.Bounaud; C.Sardet; La Niak;塔拉海洋基金会]

[1] Field CB. 1998. Primary production of the biosphere: integrating terrestrial and oceanic components, Science 281, 237-240.

[2] 用多聚甲醛保存的水样用于高分辨率显微镜。

[3] FlowCam https://www.embrc-france.fr/fr/prestation/flowcam

[4] ZooScan https://www.embrc-france.fr/fr/prestation/zooscan

[5] 在塔拉海洋科考期间收集的浮游生物的DNA和RNA在国家基因测序中心进行了分析。该中心创建于1996年,用于参与人类基因组计划并在法国开发基因组计划,而后研究环境基因组学和宏基因组学。

[6] Dardel F. & Képès F., 2002, Bioinformatics: genomics and post-genomics, Éditions de l’École Polytechnique 153-180 p. (ISBN 978-2-7302-0927-4, 在线阅读).

[7] Valentini A, Pompanon F, Taberlet P. 2009. DNA barcoding for ecologists, Trends in Ecology & Evolution, 24, 110-117.

[8] Zagoskin M, Lazareva V, Grishanin A & Mukha D. 2014. Phylogenetic information content of Copepoda ribosomal DNA repeat units: ITS1 and ITS2 impact. BioMed Research International, 926342. https://doi.org/10.1155/2014/926342

[9] Kress WJ, Erickson DL, Uriarte M & Garcı C. 2015. DNA barcodes for ecology, evolution, and conservation. Trends in Ecology & Evolution, 30, 25-35.

[10] Bucklin A, Lindeque PK, Rodriguez-Ezpeleta N, Albaina A & Lehtiniemi M. 2016. Metabarcoding of marine zooplankton: prospects, progress and pitfalls. Journal of Plankton Research, 38, 393-400.

[11] Taberlet P, Coissac E, Pompanon F, Brochmann C & Willerslev E. 2012. Towards next generation biodiversity assessment using DNA metabarcoding, Molecular Ecology, 21, 2045-2050.

[12] 通过比较不同生物体之间已知的18S rDNA序列,确定了一个名为V9的区域。它有130个碱基对长,它的末端在所有已知的生物中都高度保守。因此,在PCR过程中,该序列的末端可以作为引物的锚点。

[13] Villar E. et al (2015) Environmental characteristics of Agulhas rings affect interocean plankton transport. Science DOI:10.1126/science.1261447

[14] Blaxter M, Mann J, Chapman T, Thomas F, Whitton C., Floyd R & Eyualem A. 2005. Defining operational taxonomic units using DNA barcode data. Philosophical Transactions of the Royal Society B: Biological Sciences, 360, 1935-1943.

[15] 信使RNA或mRNA是对应于一个或多个基因的部分DNA的短暂拷贝。信使RNA被细胞用作蛋白质合成的媒介。在细胞中,mRNA群与表达的基因相对应,然后被翻译成蛋白质。

[16] 这些是所谓的多腺苷化mRNA:它们存在于由一系列腺苷组成的尾部的3 ‘部分,而原核生物中没有(见参考文献[6])。

[17] Carradec Q. et al. 2018. A global ocean atlas of eukaryotic genes. Nature Communications 9, 1038.

[18] 萨查·舒茨(Sacha Schutz)元基因组学简介

[19] 组装包括对长序列的DNA或RNA片段进行比对和/或融合,以便使用生物信息学工具重建原始序列。组装的问题可以比作将一本书从之前被撕成小块的几份中重新构建文本的问题。

[20] 基因组注释是对构成原始信息的核苷酸序列进行分析,提取生物信息。它一方面可以定位基因和编码区域,另一方面可以识别或预测它们的生物学功能(这是功能注释)。这两个步骤最初是基于使用复杂的算法工具,其发展是生物信息学的一个领域。

[21] Lecointre G & Le Guyader H. 2016. Classification phylogénétique du vivant – Tome 1, Éditions Belin, Collection Nature, 584 pp. (法语)

[22] by Vargas C, Audic S, Henry N, Decelle J, Mahe F, Logares R, Lara E, Berney C, Le Bescot N, Probert I, Carmichael M, Poulain J, Romac S, Colin S, Aury JM, Bittner L, Chaffron S, Dunthorn M, Engelen S, Flegontova O, Guidi L, Horak A, Jaillon O, Lima-Mendez G, Lukes J, Malviya S, Morard R, Mulot M, Scalco E, Siano R, Vincent F, Zingone A, Dimier C, Picheral M, Searson S, Kandels-Lewis S, Acinas SG, Bork P, Bowler C, Gorsky G, Grimsley N, Hingamp P, Iudicone D, Not F, Ogata H, Pesant S, Raes J, Sieracki ME, Speich S, Stemmann L, Sunagawa S, Weissenbach J, Wincker P & Karsenti E. 2015. Eukaryotic plankton diversity in the sunlit ocean. Science, 348, 1261605.

[23] 塔拉海洋的科学协调员包括:
Silvia Acinas, Department of Marine Biology and Oceanography, Institut de Ciències del Mar (CSIC), Barcelona, Catalonia, Spain.
Peer Bork, Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg,Germany.
Emmanuel Boss, School of Marine Sciences, University of Maine, Orono, Maine 04469, USA.
Chris Bowler, PSL Research University, Institut de Biologie de l’Ecole Normale Supérieure (IBENS), CNRS UMR 8197, INSERM U1024, 46 rue d’Ulm, F-75005 Paris, France.
Colomban de Vargas, CNRS, UMR 7144, EPEP & Sorbonne Universités, UPMC Université Paris 06, Station Biologique de Roscoff, 29680 Roscoff, France.
Mick Follows, Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
Gaby Gorsky, Sorbonne, UPMC Université Paris 06, CNRS, Laboratoire d’oceanographie de Villefranche (LOV), Observatoire Océanologique, 06230 Villefranche-sur-Mer, France.
Nigel Grimsley, CNRS, UMR 7232, BIOM, Avenue du Fontaulé, 66650 Banyuls-sur-Mer, France.
Pascal Hingamp, Aix Marseille Univ, Université de Toulon, CNRS, IRD, MIO, Marseille, France.
Daniele Iudicone, Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy.
Olivier Jaillon, Genoscope, Institut de biologie François Jacob, Commissariat à l’Energie Atomique (CEA), CNRS, Université Evry, Université Paris-Saclay, Evry, France
Lee Karp-Boss, School of Marine Sciences, University of Maine, Orono, Maine 04469, USA.
Uros Krkic, Cell Biology and Biophysics, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
Fabrice Not, CNRS, UMR 7144, Sorbonne Universités, UPMC Université Paris 06, Station Biologique de Roscoff, 29680 Roscoff, France.
Hiroyuki Ogata, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-001, Japan.
Stephane Pesant, MARUM, Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany.
Jeroen Raes, Department of Microbiology and Immunology, Rega Institute, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
Emmanuel Reynaud, Earth Institute, University College Dublin, Dublin, Ireland.
Christian Sardet, Sorbonne Université UPMC Université Paris 06, CNRS, Laboratoire d’oceanographie de Villefranche (LOV), Observatoire Océanologique, 06230 Villefranche-sur-Mer, France.
Mike Sieracki, National Science Foundation, Arlington, VA 22230, USA.
Sabrina Speich, Laboratoire de Physique des Océans, UBO-IUEM, Place Copernic, 29820 Plouzané, France.
Lars Stemmann, Sorbonne, UPMC Université Paris 06, CNRS, Laboratoire d’oceanographie de Villefranche (LOV), Observatoire Océanologique, 06230 Villefranche-sur-Mer, France.
Matthew Sullivan, Department of Microbiology, The Ohio State University, Columbus, OH 43214, USA.
Shini Sunagawa, Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg, Germany.
Jean Weissenbach, Genoscope, Institut de biologie François Jacob, Commissariat à l’Energie Atomique (CEA), CNRS, Université Evry, Université Paris-Saclay, Evry, France
Patrick Wincker, Genoscope, Institut de biologie François Jacob, Commissariat à l’Energie Atomique (CEA), CNRS, Université Evry, Université Paris-Saclay, Evry, France


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The Tara Oceans expedition explores the diversity of plankton

The oceans cover two thirds of our planet, and they are where life was born more than 3 billion years ago. The ocean is a formidable pump that absorbs nearly 30% of the carbon dioxide emissions due to human activities, notably thanks to the phytoplankton that captures it during photosynthesis. Plankton, made up of organisms invisible to the naked eye, play a major role in the major biogeochemical cycles of carbon, (half of the oxygen produced on Earth comes from the oceans), nitrogen, phosphorus and sulphur, amongst others. However, the micro-organisms that participate in these cycles are still largely unknown to us. The Tara Oceans expedition has set up an international scientific consortium to develop high-resolution sampling protocols, analyze the samples, generate data and analyze them to explore this unknown world. After three years of navigation and study of our planet’s oceans, scientists from the Tara Oceans expedition have revealed an unsuspected diversity of eukaryotic single-celled organisms (also called protists). The sequencing of close to a billion genetic barcodes has made it possible to radically change our vision of the biological and functional diversity of the world’s plankton, which populates an ecosystem that is key to the functioning of our biosphere.

1. Exploring the largest ecosystem on Earth

Figure 1. Images of plankton. Source: © Christian Sardet/CNRS/Tara expeditions / CC BY-SA 4.0]

The ocean represents the largest continuous ecosystem on Earth, and the majority of its biomass is made up of organisms that are invisible to the naked eye: marine microorganisms, many of which make up “plankton”. The term “plankton” comes from the Greek word planktos, or “wanderer”, and refers to organisms that live in the water column and are unable to swim against the current. Marine plankton is thus composed of protists (unicellular eukaryotes), bacteria, archaea, viruses, but also the larval stages of larger organisms, such as the larvae of fish or crustaceans (Figure 1).

Exploration of the global distribution of marine microbial communities and diversities became quantitative with the advent of high throughput DNA sequencing technologies in the mid-2000s, paving the way for large spatial scale sampling campaigns. Indeed, the distribution of plankton is highly dependent on abiotic factors, such as light, nutrients, turbulence, temperature, salinity or pH, as well as biotic factors, such as the presence of other organisms including predators or symbionts. Although the local abundance of plankton varies horizontally, vertically and seasonally, planktonic organisms are present throughout the oceans.

The importance of plankton on a global scale is manifold:

  • Plankton are at the base of food chains and they account for 50% of the annual primary productivy (photosynthesis) on Earth [1].
  • Plankton metabolism plays a major role in the major biogeochemical cycles of carbon, oxygen, nitrogen, phosphorus and sulphur.
  • The ocean is also a formidable pump that absorbs nearly 30% of the carbon dioxide emissions (a greenhouse gas) caused by human activities, in particular thanks to phytoplankton that capture carbon dioxide during photosynthesis (See A carbon cycle disrupted by human activities).

2. The Tara Oceans Expedition

Figure 2. The schooner Tara during the Tara Oceans expedition. [Source: Photo © Sacha Bollet Fondation Tara Ocean]
Since 2006, a series of scientific expeditions have been carried out by scientists on board the schooner Tara (Figure 2):

  • Tara Arctic (2006-2008) during two years of drifting on the ice pack, scientists onboard the schooner collected data on the atmosphere, the ice and the ocean. Caught in the ice for 504 days, Tara reached the northernmost position ever reached by a ship (excluding icebreakers): 88°32’10” N.
  • Tara Oceans (2009-2013) made it possible to carry out a study of unprecedented scope on plankton, during a 140,000 kilometre journey across all the oceans of the planet. The Tara Oceans Polar Circle expedition was also part of the Tara Oceans project, a 6-month mission around the Polar Circle and the first in history to pass through the Northeast and Northwest Passages during the same year.
  • Tara Méditerranée (2014) assessed the impact of micro-plastics on the health and functioning of ecosystems in the Mediterranean.
  • Tara Pacific (2016-2018) explored the potential for resistance, adaptation and resilience of coral reefs in the face of global change.
  • Tara Microplastics (2019) travelled the 4 European sea fronts and took samples from the 9 main European rivers to trace the origins of plastic pollution.

Figure 3. Track of the schooner Tara. A total of 40,000 seawater and plankton samples were collected at 210 stations in 20 biogeographic provinces over 140,000 km. [Source: Schematic © be-poles for Fonds Tara (https://oceans.taraexpeditions.org)]
The Tara Oceans expedition thus explored the wide variety of planktonic organisms (from viruses to fish larvae) in the surface (0-200 m) and mesopelagic (200-1000 m) oceans worldwide.

A total of 40,000 seawater and plankton samples were collected from 210 stations in 20 biogeographic provinces. Many questions animated this expedition:

  • What is the extent of plankton diversity in our oceans?
  • Which organisms carry out the most important functions?
  • What are the effects of environmental parameters and biotic interactions on the ocean ecosystem?

In order to answer these questions, the Tara Oceans expedition brought together more than 250 scientists from around the world and carried out highly standardized sampling for more than three years on the 36-metre-long schooner.

The Tara Oceans project used many new technologies and analytical tools to establish the first global data collection effort that couples biogeography, ecology, genetics and morphology, bringing together an international community of scientists from many different disciplines: marine ecologists, microbiologists, oceanographers, statisticians, biogeochemists, computer scientists, and evolutionary biologists.

The standard sampling programme was designed to study a wide variety of marine ecosystems: upwellings, biodiversity hotspots, low pH or oxygen-poor zones, etc. A total of 210 stations were defined (Figure 3) on which a more precise environmental characterisation was conducted in order to contextualise the morphological and genetic sampling of plankton.

3. Main principles of sampling

Figure 4. Sampling method used during the Tara Oceans expedition. Organisms were sampled by size fractions using suitable devices. The blue background represents the volume of water filtered in order to obtain sufficient biomass for analysis. [Source: Eric Karsenti et al & the Tara Oceans Consortium, CC BY 4.0, via Wikimedia Commons]
For most of the 210 stations of the Tara Oceans expedition (Figure 3), sampling was conducted at three depths:

  • The first is the surface water layer (SUR), defined as the layer three to seven metres below the surface.
  • The second is the so-called “deep chlorophyll maximum” (DCM) layer, which corresponds to the zone of maximum abundance of photosynthetic plankton, determined by measuring the chlorophyll concentration by fluorimetry. The existence of this maximum can be explained by a compromise between the two conditions necessary for phytoplankton growth: the presence of light and the supply of nutrients from cold deep water.
  • The third sampling was carried out in the so-called “mesopelagic” zone, below the DCM and where light from the surface no longer passes, on average at a depth of 700 metres.

For each station, sampling was done on several organism size fractions (Figure 4) [2].

The plankton collected during the Tara Oceans expedition covers six orders of magnitude in terms of size that correspond to :

  • Viruses and giant viruses (also known as giruses) (See Focus Ocean Viruses);
  • prokaryotes (bacteria and archaea);
  • unicellular eukaryotes  (protists, fungi and microalgae);
  • multi-cellular eukaryotes (such as copepods).

Unicellular eukaryotes measure between 0.8 and 2000 microns. Nets of appropriate mesh sizes were used to create several size fractions: 0.8-5 microns, 5-20 microns, 20-180 microns, 180-2000 microns.

Video 1: Tara Oceans (with photo below): plankton sampling. Plankton filtration (GPSS).

Figure 5. Methods of morphological analysis of samples as a function of sample size; from left to right: Flow Cytometry, High Throughput Microscopy, FlowCam and ZooScan. [Source: Eric Karsenti et al & the Tara Oceans Consortium, CC BY 4.0, via Wikimedia Commons]
For each station, a morphological analysis (Figure 5) was performed for different classes of organisms:

  • On the one hand, automated recognition systems, such as the FlowCam [3] and the ZooScan [4], have enabled quantitative measurements of the biodiversity of organisms ranging from 20 microns to a few centimetres.
  • On the other hand, 3D confocal microscopy and transmission electron microscopy have enabled detailed ultra-structural analyses of small protists.

4. Analysis of the genetic diversity of plankton

Figure 6. Methods of genetic analysis of samples. [Source: Diagram © Eric Karsenti et al & the Tara Oceans Consortium / CC BY 4.0]
For each station, the water samples were filtered and then subjected to different genetic analyses (Figure 6), allowing us to understand who is there, what do they do, and who has the potential to do what:

  • Sequencing of 16S and 18S rDNA (metabarcoding), the genes encoding ribosomal RNA: Who’s there?
  • Metatranscriptomics: Determination of all the RNAs produced – the transcriptome – by the different organisms collected during the process of transcribing a gene into a protein: What do they do?
  • Metagenomics: characterization of all the genes present in the environmental sample: Who can do what?

The prefix “meta” added to the terms “barcoding”, “transcriptomics” and “genomics” expresses the idea that these molecular analyses are performed not on a single species but on a set of species from environmental samples. High-throughput DNA sequencing [5],[6] has opened the door to exploring, both qualitatively and semi-quantitatively, the genetic diversity of environmental samples.

4.1. Who’s there?

The exploration of the genetic diversity of samples was based on the use of different molecular technologies.
Molecular barcoding (DNA barcoding). The phylogeny of microorganisms has long been based on morphological and biochemical characteristics. Recently, molecular markers (barcodes) have been used to reconstruct the evolutionary history of living organisms, based on the – simplified – idea that the further apart two organisms are evolutionarily, the greater the difference between their genomic sequences.
Strictly speaking, a DNA barcode is a short sequence (typically 100 to 400 base pairs) corresponding to a standard portion of the genome (e.g. 18S ribosomal DNA), which can be used to identify species, such as a barcode used in the supermarket that allows the relationship between the product (the sequence) and its price (the identification of the species) to be made (See: DNA barcode to characterize biodiversity). This sequence is chosen on the basis of precise criteria [7]:

  • intra-species variability must be low: this sequence must be almost identical in all organisms of the same species;
  • inter-species variability must be high so that two different species can be differentiated on the basis of their sequence.
Figure 7. Structure of eukaryotic rDNA. Typical organization of a cluster of rDNA in eukaryotes. The 18S, 5.8S and 28S genes encode ribosomal RNAs; ITS1 and ITS2 are internal transcribed spacers. Intergenic spacers (IGS) separate the many copies of these genes. V9 indicates the location of the primers for PCR.

The most commonly used DNA molecular markers for phylogenetic reconstruction are the genes encoding the rRNAs of the ribosomal subunits, the rDNAs. In the majority of eukaryotes, 18S rRNA is present in the small ribosomal subunit, while the large subunit contains three rRNA molecules (5S, 5.8S, 28S in mammals and 25S in plants). The genes encoding the rRNAs are often grouped in a cluster, separated by internal transcribed spacers (ITS1 and ITS2) and an intergenic spacer (IGS) (Figure 7) [8].

Metabarcoding. The impact of barcoding as a molecular tool goes far beyond a higher resolution phylogeny of known species: conservation, species discovery, and community ecology benefit from it [9],[10]. With the advent of high-throughput sequencing, molecular barcoding (DNA barcoding) has become a widespread tool for the ecology of eukaryotic (and prokaryotic!) communities through a method known as metabarcoding.

More formally, DNA metabarcoding refers to the automated identification of multiple species from a single sample containing whole organisms, or an environmental sample containing degraded DNA (from soil, water, faeces, etc.) [11]. A good barcode for a molecular metabarcoding study (such as 18S rDNA) should :

(i) correspond to a portion of nearly identical genes within individuals of the same species, but which differ between species;

(ii) be usable for all species considered in the study;

(iii) allow taxonomic assignment at different taxonomic levels [6].

Once extracted, the sample DNA is amplified by PCR (polymerase chain reaction). PCR is a technique that allows a specific DNA (or RNA) sequence to be duplicated in large numbers (with a multiplication factor of the order of a billion) from:

  • a small amount (of the order of a few picograms) of nucleic acid;
  • specific nucleotide primers called “universal” primers, such as the sequence called V9 [12], which makes it possible to specifically amplify the selected portion of DNA (the amplicon, for example, 18S rDNA) of all the organisms present.

The final PCR product obtained after amplification is therefore a mixture of all the V9 sequences of the organisms in the test sample.

Figure 8. Richness of barcodes shared between two samples from stations in the Atlantic Ocean (left, blue) and Indian Ocean (right, pink). Within each sample, the horizontal lines represent sequenced V9 rDNA barcodes, with grey barcodes being common to each sample (over 31% of the barcodes), while blue and pink barcodes are region-specific. Reproduced from ref. [12]

In a second step, each of the copies is then sequenced: we thus obtain the whole diversity of the V9 sequences of our sample (Figure 8) [13]. Sequences showing a sufficient degree of similarity are grouped into operational taxonomic units (OTU) [14]. The threshold of 97% similarity of DNA sequences is often used. A species must then be matched to each OTU.

This taxonomic assignment is made by comparing the OTU of the sample with databases of reference organisms. The idea is to see which known sequence the OTU is closest to, and in what proportion. The degree of similarity will give with some degree of certainty a species, genus, or family name: if a OTU has a sequence 100% identical to a species with a known name, it is assigned the identity of that species.

But sometimes the sequences are not similar enough, so identifications can only be made at the genus level and not at the species level.
The only snag is that more than 40% of the OTUs determined from the Tara Oceans expedition are totally new and do not correspond to any known species. We simply know that they are Eukaryotes but it is almost impossible to place them in a phylogenetic tree. Exciting!

4.2. Who does what?

Figure 9. Estimated number of transcriptomes in eukaryotic samples collected from 68 sampling stations. Left: distribution of the total number of transcriptomes estimated for each size fraction; right: distribution of the number of transcriptomes in each sample (small dashes) grouped by size fraction. Reproduced from ref. [16]
In addition to providing an inventory of the species present, the sampling carried out by the Tara Oceans expedition also used so-called “metatranscriptomic” techniques. These make it possible to account for the genes expressed in the sample by sequencing messenger RNA (mRNA). [15]

To specifically study eukaryotic transcripts, it is possible to select only eukaryotic-specific mRNAs (Figure 9) [16],[17]. These mRNAs are then retrotranscribed in the presence of a reverse transcriptase: the complementary DNAs obtained are sequenced and their sequences compared with those present in reference databases, which can make it possible to specify both a functional (which genes do these transcripts come from, what can they be used for?) and taxonomic (from which organisms do these transcripts come from?) annotation. This is the “who does what”, detailed in Carradec et al [17].

4.3. Who can do what?

Today, and mainly for the prokaryotic domain, genomic analyses focus on whole genome sequencing, or metagenomics [18]. Instead of using specific PCR primers (see Metabarcoding above), all the genomes in the environmental sample are then sequenced.

  • The first step, after extraction of the DNA, is to fragment all the DNAs present in the sample into very short pieces and then sequence them; this is called shotgun sequencing or random sequencing.
  • Subsequently, the sequenced fragments are assembled bioinformatically from the overlapping regions to reconstruct the original genomes.
Figure 10. All the DNA present in a plankton sample is sequenced and aligned with the sequences of known genomes

The “metagenomic” sequencing thus accounts for all the genes not expressed but present in the sample. This type of sequencing provides information on the genetic potential of the community of organisms in the sample, it is the “who can do what”, but does not necessarily do it. This approach with huge potential faces many technical limitations.

At the time of the Tara Oceans expedition, the size of DNA fragments that could be sequenced at high throughput was just over 500 base pairs. If we consider, for example, the genome of a diatom (abundant phytoplankton), which is at least 30 million base pairs long, this means that at least 60,000 DNA fragments must be sequenced to reconstitute this complete genome (Figure 10). In practice, analyses are never carried out on a single individual, but from a mixture of DNA fragments from different individuals.

In reality, it is not possible to limit ourselves to sequencing 60,000 fragments at random, because otherwise some parts of our diatom genome will have been sequenced several times, but others not at all, and the reconstructed genome will therefore have “holes”. Overlapping fragments of DNA are also needed to reconstruct the sequence order.

To overcome this problem, we sequence the equivalent not of a single genome (60,000 fragments) but, for example, of twenty genomes (or 1,200,000 fragments!).

Figure 11. Bioinformatics methods combined with high-throughput genetic approaches provide functional knowledge about networks of genes and organisms, as well as models of the spatial distribution of species within ecosystems. [Scheme © Eric Karsenti et al. & the Tara Oceans Consortium / CC BY 4.0]
At the time of the Tara Oceans expedition, sequencing the genomes of several hundred or thousands of species present in a water sample seemed a daunting task. And for good reason: the majority of the genes identified (> 50%) have no homology with the genes listed in current databases, raising many questions. The challenges in terms of assembly [19] and annotation [20] are enormous, but progress is being made every year.

Coupled with quantitative imagery, these high-throughput sequencing approaches allow not only an understanding of the structure, location and function of genes, but also, and most importantly, an exploration of the diversity of plankton. Using powerful methods based on bioinformatics, these analyses provide data on the evolution, metabolism and interactions between organisms (See: Focus The ocean’s biological carbon pump), and enable the reconstruction of community metabolomes, gene and organism networks, and models of the spatial distribution of species (Figure 11).

5. Unsuspected diversity: plankton protists

Figure 12. Protists form a polyphyletic group corresponding to unicellular eukaryotes. On the left, phylogenetic tree of eukaryotes (adapted from Lecointre & Guyader, 2016); on the right, some plankton protists, including diatoms, dinoflagellates, green algae, and radiolarians. [Source: Plankton mix © C.Sardet & N.Sardet_Chroniques du plancton, Fondation Tara Océan]
After three years of navigation and study of the light-bathed zones of the planetary oceans, the Tara Oceans researchers have revealed an unsuspected diversity in eukaryotic unicellular organisms also called protists (Figure 12) [21]. The sequencing of nearly one billion genetic barcodes has shown that protists are far more diverse than bacteria or animals, and that most of them belong to little-known groups of parasites, symbionts, and predators of all kinds. These results radically change our vision of the biological and functional diversity of the world’s plankton, a key ecosystem for the functioning of our biosphere.

  • Presentation of Tara Oceans results at the “Maison des Océans”

In this study, researchers deciphered and analyzed nearly one billion ribosomal DNA sequences from only 46 sampling sites. These sequences are used as markers of eukaryotic biodiversity (See What is biodiversity? and Biodiversity is not a luxury but a necessity), from the smallest unicellular organisms (<1 micron) to planktonic animals a few millimetres in size [22].

The large quantity of genetic barcodes generated made it possible first of all to characterize almost all the eukaryotic species of plankton in the photic zone analysed. 150,000 genetic types of eukaryotic plankton were identified, which represents an unsuspected diversity compared to the 11,000 species described so far. It appeared that the vast majority of the genetic types listed have no close reference in current genetic databases, demonstrating that these organisms are mostly unrecorded and uncultivatable. One third of the genetic diversity could not be associated with any of the major eukaryotic lines recognized today.

Among the genetic types that can be classified in the tree of eukaryotic life, most have been found to correspond to unicellular or protist organisms, with a phenomenal diversity of parasites, symbiotic species, and predators of all kinds. Photosynthetic organisms were much less diverse, smaller, and would represent a much lower biomass.

To date, more than 100 publications have resulted directly from the analysis of the data generated by the Tara Oceans expedition, including five founding articles that were the subject of a special “Tara Oceans” issue of the journal Science in 2015 (query of the ISI Web of Science database over the period 2009-2019 using the terms “Tara Oceans” alone; October 2, 2020).

6. Messages to remember

  • After three years of sailing around the globe, the researchers of the Tara Oceans expedition carried out the most exhaustive study of plankton possible and made it possible to take an overall picture of the world’s planktonic ecosystem.
  • This work has led to the discovery of 150 million marine genes, 100,000 genetically-defined species and the determination of the distribution factor of planktonic communities from more than 40,000 seawater samples. In particular, they revealed an unsuspected diversity in protists (single-celled eukaryotic organisms).
  • More than 100 scientific publications in leading journals are a direct result of the analysis of the data generated by the Tara Oceans expedition. These data are freely available to all scientists in public databases.
  • In parallel with these research activities, the Tara Oceans project also aimed to raise public awareness of the issues related to climate change, through numerous workshops, on-board visits, educational tools available on their website and validated by scientists.
  • The science thus generated was also put at the service of climate governance: as a special observer at the UN, the Tara Oceans expedition mobilized political decision-makers at the highest level.

Initial scientific organisation of Tara Oceans: Eric Karsenti, EMBL, Scientific Director, Etienne Bourgois Director of Tara Expeditions, Romain Troublé Secretary General of Tara Expeditions – Stephanie Kandels Lewis (EMBL) & Didier Velayoudon (DVIP consulting) Operational Managers

Tara Oceans scientific coordinators: This interdisciplinary and international group developed the sampling strategy and overall plan, set the overall expedition and project objectives, led the expedition and carried out most of the analysis of the results over the past ten years. See reference [23].


Notes and References

Cover image. [Source: Photo © G.Bounaud_C.Sardet_La Niak_Fondation Tara Océan]

[1] Field CB. 1998. Primary production of the biosphere: integrating terrestrial and oceanic components, Science 281, 237-240.

[2] Water samples preserved with paraformaldehyde were used for high-resolution microscopy.

[3] FlowCam https://www.embrc-france.fr/fr/prestation/flowcam

[4] ZooScan https://www.embrc-france.fr/fr/prestation/zooscan

[5] DNA and RNA from plankton collected during the Tara Oceans expedition were anaysed at the National Sequencing Centre – Genoscope. Created in 1996 to participate in the Human Genome project and to develop genomics programs in France. It then set its sights on environmental genomics and metagenomics.

[6] Dardel F. & Képès F., 2002, Bioinformatics: genomics and post-genomics, Éditions de l’École Polytechnique 153-180 p. (ISBN 978-2-7302-0927-4, read online).

[7] Valentini A, Pompanon F, Taberlet P. 2009. DNA barcoding for ecologists, Trends in Ecology & Evolution, 24, 110-117.

[8] Zagoskin M, Lazareva V, Grishanin A & Mukha D. 2014. Phylogenetic information content of Copepoda ribosomal DNA repeat units: ITS1 and ITS2 impact. BioMed Research International, 926342. https://doi.org/10.1155/2014/926342

[9] Kress WJ, Erickson DL, Uriarte M & Garcı C. 2015. DNA barcodes for ecology, evolution, and conservation. Trends in Ecology & Evolution, 30, 25-35.

[10] Bucklin A, Lindeque PK, Rodriguez-Ezpeleta N, Albaina A & Lehtiniemi M. 2016. Metabarcoding of marine zooplankton: prospects, progress and pitfalls. Journal of Plankton Research, 38, 393-400.

[11] Taberlet P, Coissac E, Pompanon F, Brochmann C & Willerslev E. 2012. Towards next generation biodiversity assessment using DNA metabarcoding, Molecular Ecology, 21, 2045-2050.

[12] By comparing the already known 18S rDNA sequences between various organisms, a region called V9 was identified. It is 130 base pairs long and its ends are highly conserved in all known organisms. The ends of this sequence can therefore serve as an anchor point for primers during PCR.

[13] Villar E. et al (2015) Environmental characteristics of Agulhas rings affect interocean plankton transport. Science DOI:10.1126/science.1261447

[14] Blaxter M, Mann J, Chapman T, Thomas F, Whitton C., Floyd R & Eyualem A. 2005. Defining operational taxonomic units using DNA barcode data. Philosophical Transactions of the Royal Society B: Biological Sciences, 360, 1935-1943.

[15] Messenger RNA or mRNA is a transient copy of a portion of DNA corresponding to one or more genes. The mRNA is used as an intermediary by cells for protein synthesis. In a cell, the mRNA population corresponds to the expressed genes and is then translated into proteins.

[16] These are so-called polyadenylated mRNAs: they present in the 3′ part of a tail made of a succession of adenosines, absent in prokaryotes (see ref [6]).

[17] Carradec Q. et al. 2018. A global ocean atlas of eukaryotic genes. Nature Communications 9, 1038.

[18] Sacha Schutz Introduction to metagenomics

[19] Assembly consists of aligning and/or fusing DNA or RNA fragments from a longer sequence in order to reconstruct the original sequence using bioinformatics tools. The problem of assembly can be compared to the problem of reconstructing the text of a book from several copies of the book, previously shredded into small pieces.

[20] Genome annotation involves analyzing the nucleotide sequence that constitutes the raw information to extract the biological information. It makes it possible, on the one hand, to locate genes and coding regions and, on the other hand, to identify or predict their biological function (this is functional annotation). These two steps are initially based on the use of sophisticated algorithmic tools, the development of which is one of the fields of bioinformatics.

[21] Lecointre G & Le Guyader H. 2016. Classification phylogénétique du vivant – Tome 1, Éditions Belin, Collection Nature, 584 pp. (in french)

[22] by Vargas C, Audic S, Henry N, Decelle J, Mahe F, Logares R, Lara E, Berney C, Le Bescot N, Probert I, Carmichael M, Poulain J, Romac S, Colin S, Aury JM, Bittner L, Chaffron S, Dunthorn M, Engelen S, Flegontova O, Guidi L, Horak A, Jaillon O, Lima-Mendez G, Lukes J, Malviya S, Morard R, Mulot M, Scalco E, Siano R, Vincent F, Zingone A, Dimier C, Picheral M, Searson S, Kandels-Lewis S, Acinas SG, Bork P, Bowler C, Gorsky G, Grimsley N, Hingamp P, Iudicone D, Not F, Ogata H, Pesant S, Raes J, Sieracki ME, Speich S, Stemmann L, Sunagawa S, Weissenbach J, Wincker P & Karsenti E. 2015. Eukaryotic plankton diversity in the sunlit ocean. Science, 348, 1261605.

[23] Scientific coordinators Tara Oceans:
Silvia Acinas, Department of Marine Biology and Oceanography, Institut de Ciències del Mar (CSIC), Barcelona, Catalonia, Spain.
Peer Bork, Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg, Germany.
Emmanuel Boss, School of Marine Sciences, University of Maine, Orono, Maine 04469, USA.
Chris Bowler, PSL Research University, Institut de Biologie de l’Ecole Normale Supérieure (IBENS), CNRS UMR 8197, INSERM U1024, 46 rue d’Ulm, F-75005 Paris, France.
Colomban de Vargas, CNRS, UMR 7144, EPEP & Sorbonne Universités, UPMC Université Paris 06, Station Biologique de Roscoff, 29680 Roscoff, France.
Mick Follows, Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
Gaby Gorsky, Sorbonne, UPMC Université Paris 06, CNRS, Laboratoire d’oceanographie de Villefranche (LOV), Observatoire Océanologique, 06230 Villefranche-sur-Mer, France.
Nigel Grimsley, CNRS, UMR 7232, BIOM, Avenue du Fontaulé, 66650 Banyuls-sur-Mer, France.
Pascal Hingamp, Aix Marseille Univ, Université de Toulon, CNRS, IRD, MIO, Marseille, France.
Daniele Iudicone, Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy.
Olivier Jaillon, Genoscope, Institut de biologie François Jacob, Commissariat à l’Energie Atomique (CEA), CNRS, Université Evry, Université Paris-Saclay, Evry, France
Lee Karp-Boss, School of Marine Sciences, University of Maine, Orono, Maine 04469, USA.
Uros Krkic, Cell Biology and Biophysics, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
Fabrice Not, CNRS, UMR 7144, Sorbonne Universités, UPMC Université Paris 06, Station Biologique de Roscoff, 29680 Roscoff, France.
Hiroyuki Ogata, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-001, Japan.
Stephane Pesant, MARUM, Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany.
Jeroen Raes, Department of Microbiology and Immunology, Rega Institute, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
Emmanuel Reynaud, Earth Institute, University College Dublin, Dublin, Ireland.
Christian Sardet, Sorbonne Université UPMC Université Paris 06, CNRS, Laboratoire d’oceanographie de Villefranche (LOV), Observatoire Océanologique, 06230 Villefranche-sur-Mer, France.
Mike Sieracki, National Science Foundation, Arlington, VA 22230, USA.
Sabrina Speich, Laboratoire de Physique des Océans, UBO-IUEM, Place Copernic, 29820 Plouzané, France.
Lars Stemmann, Sorbonne, UPMC Université Paris 06, CNRS, Laboratoire d’oceanographie de Villefranche (LOV), Observatoire Océanologique, 06230 Villefranche-sur-Mer, France.
Matthew Sullivan, Department of Microbiology, The Ohio State University, Columbus, OH 43214, USA.
Shini Sunagawa, Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg, Germany.
Jean Weissenbach, Genoscope, Institut de biologie François Jacob, Commissariat à l’Energie Atomique (CEA), CNRS, Université Evry, Université Paris-Saclay, Evry, France
Patrick Wincker, Genoscope, Institut de biologie François Jacob, Commissariat à l’Energie Atomique (CEA), CNRS, Université Evry, Université Paris-Saclay, Evry, France


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