微生物生态：科学问题与实验设计

1、致谢 周集中 李筱婧 陈永健 束浩月 邝嘉良 花正双Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019Microbial Ecology in Genomics Era: Challenges and OpportunitiesZhongshan University, Guangzhou, November 5, 2015. Jizhong (Joe) Z; 405-3

2、25-6073School of Environment, Tsinghua University, BeijingEarth Science Division, Lawrence Berkeley Laboratory, Berkeley, CA专 业：生态学答辩人：李筱婧导 师：黄立南 教授 中山大学硕士学位论文答辩采样量与估算方法对细菌物种丰富度估算的影响研究背景稳健的微生物物种丰富度评价对于研究微生物多样性及微生物群落的组成与功能的是必不可少的1微生物个体数目巨大，多样性极高，占据了地球生物多样性的绝大部分 (Whitman et al., 1998 ;

3、Torsvik et al., 2002)；2微生物的物种丰富度与组成一定程度上决定微生物群落功能(Bell et al., 2005)，并在地球生物化学循环中扮演核心角色 (Prosser et al., 2007)；3不同丰度水平的物种对细菌群落水平的多样性有着不同程度的贡献，且在微生物群落中有着不同的角色和功能 (Shade & Handelsman, 2011; Campbell et al., 2011)。材料与方法采样理化Miseq测序多样性分析细胞密度序列处理1234567提取DNAqPCR验证采样样品准备数据分析采样 采样地：广东大宝山矿区多金属矿采样时间：2014年9月25-

4、26日采样水量：1 ml、5 ml、10 ml、50 ml、100 ml、500 ml、1 L、5 L和10 L等9个水平（每个水平10个重复）采样操作：1 原位收集微生物细胞2 原位测定温度、pH值、溶氧值和Eh值3 保存适量水样用于细胞计数和理化测定采样量的影响整体上单个样品所检测到的OTUs数目数目与采样量成正比成正比，但采样量间OTUs数目无显著性差异无显著性差异；当采样量超过超过100 ml，OTUs数目逐渐稳定在同一水平,主要类群分布相似主要类群分布相似1图3-1 不同采样量间AMD细菌群落的OTUs分布图3-2 不同采样量间AMD细菌群落的主要类群分布Sample Volume采

5、样量的影响(测序量100000)物种丰富度与组成 测序量的影响图3-4 不同测序量间AMD细菌群落的主要类群分布测测序序深深度度100010000100000门门10major - 92.1%7.9% unassigned13major - 89.4%9.1% unassigned23major- 90.3%9.6% unassigned纲纲152334目目254268科科2651115属属1971% unassigned5376% unassigned30476% unassignedOTUsOTUs15125453790216322432测序量的影响物种丰富度与组成整体上单个样品所检测到的

6、物种门类和丰富度物种门类和丰富度与测序量成正成正比比，但测序量间主要类群分布主要类群分布无显著性差异无显著性差异。1表3-1 不同测序量间AMD细菌群落的物种组成分布测序量的影响（500ml样品）常见种和稀有种的覆盖度随着测序量的上升，新增的常见种逐渐减少，而稀有种的增幅不一；测序量超过超过10000条条即可检测到50%的常见种，而测序量需超过超过50000才可检测到50%的稀有种。3图3-6 AMD细菌群落中常见种和稀有种的数目（柱图表示新增数目，折线图表示累积数目）98%80% 97% cutoff Three runs of MiSeqOTU Overlaps among Three T

7、ags with MiSeq 54 soil samples Same DNAs from each sample amplified and sequenced by three tags 10,000 sequences per technical replicate 1%) but vary slightly among samplesFungal assemblages are phylum-poor (3 phyla consisted most of all fungal sequences) but vary remarkably among samples1.4 Species

8、-accumulation curvesNumber of OTUs tended to be asymptotic to the upper bound value as number of samples increase, implying that few newly observed species were detected towards the end of our samplingTedersoo et al., Science 201440 soil cores from natural communities in each of 365 sites across the

9、 worlda mixture of six ITS3 primers and ITS4ngsfive half-plates 454 Maps of global samplingSampling32 forests192 sites3 replications/siteGradients Geography Climate Vegetation Elevation Soil Env.Scales10 m 3,000 km3. Conclusions The most likely lower-bound estimated OTUs number is 39,244 (95% confid

10、ence interval (CI) = 39,221 39,274) and 14,223 (95% CI = 14,221 14,225) for bacteria and fungi, respectively.Niche-based environmental control processes dominantly govern soil bacterial community assembly, whereas dispersal-based spatial processes appear to be the main driver of soil fungal communit

11、y assembly.Similar belowground soil microbial community composition is accompanied by similar aboveground plant community composition.CEE结论 对格局的研究而言，样品多多益善 大样地研究，500个样品是基本数量 样品数量的重要性，远高于测序深度的重要性 对于最复杂的土壤样品，3000-5000有效序列足够 对于一个和几个样品的情况，3000-5000有效序列也足够，但一定要结合宏基因组/宏转录组/宏蛋白组/宏代谢组/SIP等/单细胞基因组等深度研究与个性化分析

12、 What are the functional activities of a microbial community? What are the relationships between microbial community functional structure and ecosystem functioning? How does microbial community functional structure respond to environmental changes such as climate warming?From structure to functions

13、Open format detection Could not assure the same genes/proteins/organisms can be compared across different samples. The results could be expected and thus are open High throughput Sequencing 454 sequencing, Illumina, PacBio Proteomics, Metabolomics Functional metagenomics Single cell genomics Closed

14、format Ensure that the same genes/proteins/organisms can be compared across different samples. The results can be expected, and thus are close. BioLog Plates PhyloChip: 16S genes GeoChip: functional genesI. High Throughput Omic Technologies 97% cutoff 1 run of pyrosequencing11.73.3%13.33.3%7.42.1%9.

15、12.5%24.3%6.0%25.1%5.8%24.3%6.0%25.1%5.8%24.3%6.0%25.1%5.8%20.1%8.8%20.3%9.1%20.1%8.8%20.3%9.1%20.1%8.8%20.3%9.1%(A)(C)(B)(D)Forward primer Singletons not removedForward primer Singletons removedReverse primer Singletons not removedReverse primer Singletons removedOTU Overlaps among Three Tags with

16、pyrosequencing 24 samples, warming vs nonwarming 60 tags 80K Reads), and shotgun sequencing (10 Gb per sample). Sorensen similarity: Qualitative; Bray-Curtis: Quantitative35Replicates! Replicates! Replicates!Increasing sampling efforts Ameliorating the potential problem of low reproducibilityZhou, e

17、t al. 2015. High-Throughput Metagenomic Technologies for Complex Microbial Community Analysis: Open and Closed Formats. mBio 6(1):e02288-14 CEE评论 对于任何实验研究，重复都是必须的 对于生态学调查，重复一般是以环境梯度/样品的空间分布替代的 永远不要混样 Microarrays: Glass slides or other solid surface containing thousands of genes arrayed by automated

18、equipment. FGAs contain probes from the genes involved in various geochemical, ecological and environmental processes. C, N, S, P cylcings Organic contaminant degradation Metal resistance and reduction Antibiotic resistanceTypical format: 50mer oligonucleotide arraysUseful for studying microbial com

19、munities Functional gene diversity and activity Limited phylogenetic diversity.GeoChip or Functional Gene Arrays(FGAs)GeoChip: A high throughput tool for linking community structure to functionsHe, Z, TJ Gentry, CW Schadt, L Wu, J Liebich, SC Chong, Z Huang, W Wu, B Gu, P Jardine, C Criddle, and J.

20、Zhou. 2007. GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes. The ISME J. 1: 67-77.Highlighted by: A press release by Nature Press OfficeReported by many Newspapers National Ecology Observatory Networks (NEON), Roadmap National Academy of S

21、ciences, Metagenomics reportR & D 100, among most outstanding 100 technological innovations and breakthrough in 2009 R & D 100, among most outstanding 100 technological innovations and breakthrough in 2009R&D 100 AwardGeoChip Roadmap2402 Genes24,243 Probes150 Gene Families28,000 Probes292 Gene Famil

22、ies83,992 Probes549 Gene Families268,059 Probes2,433 Gene FamiliesThe most comprehensive high throughput metagenomic technology for characterizing microbial community functional structure and activities.Summary of GeoChip 5.0 probe information by functional gene categoryGene categoryNo. of genes in

23、categoryNo. of probes designedNo. of covered sequencesCarbon cycling 1714499787764Nitrogen 401150324631Sulphur 28850312657Phosphorus 637837141Antibiotic resistance 352293459141Metal Resistance 14556552134681Organic Remediation 3493079659064Stress 1233411987270Algal virus 1915382981Bacteria phage 411

24、0952083Energy Process 1112561647Environ toxins 36191794Fungi function 109860411457Pigments 3632294910Protists 8329944017Soil benefit 50955914424Soil borne pathogenirulence 898879222532Virus 4438629462other category 511184719874Total2,433268,059 570,042 Detecting functions: Geochemical p

25、rocesses, ecological processes Broad detection: 2500 functional gene categories of importance to ecology, geochemistry and environmental sciences Higher resolution: Species-strain level resolution Quantitative: no PCR is involved Low cost: 700 draft and finished reference genomes . Spearman r = 0.82

26、, P 0.001 Inferring metagenomes from a broader range of habitats Habitats : mammalian guts, soils from diverse geographic locations and a phylogenetically complex hypersaline mat community NSTI : the nearest sequenced taxon index Result : The accuracy of PICRUSt in general decreased with increasing NSTI across all samples (Spearman r = 0.4, P 0.001) and within each microbiome type (Spearman