Molecular data for Davis 14/15 ocean acidification minicosm experiment metadata

Experimental Design
A six-level, dose-response ocean acidification experiment was run on a natural microbial community from nearshore Antarctica, between 19th November and 7th December 2014. Seawater was collected from approximately 1 km offshore of Davis Station, Antarctica (68◦ 35’ S, 77◦ 58’ E), pre-filtered (200 μm), and transferred into six 650 L tanks (minicosms) located in a temperature-controlled shipping container. Six CO2 levels were achieved by altering the fugacity of carbon dioxide (ƒCO2) within each minicosms. The ƒCO2 was adjusted stepwise to the target concentrations for each minicosm (343, 506, 634, 953, 1140, 1641 μatm) over a five-day period using 0.2 μm filtered seawater enriched with CO2. This acclimation to CO2 was conducted at low light (0.9 ± 0.2 μmol m−2 s−1) so there was low growth of the phytoplankton. Light levels were then increased over a further two days to 90.52 ± 21.45 μmol m−2 on a 19:5 light/dark non-limiting light cycle. After this acclimation period, the microbial community was allowed to grow for 10 days (days 8-18), during which the ƒCO2 levels within each minicosm was adjusted daily to maintain the target ƒCO2 level for each minicosm, and light levels were kept constant. No nutrients were added during the experiment.

For a more detailed description of minicosm set-up, lighting and carbonate chemistry see;
Davidson, A. T., McKinlay, J., Westwood, K., Thomson, P. G., van den Enden, R., de Salas, M., Wright, S., Johnson, R., and Berry, K.:Enhanced CO2 concentrations change the structure of Antarctic marine microbial communities, Mar. Ecol. Prog. Ser., 552, 93-113, 2016.
Deppeler, S. L., Petrou, K., Westwood, K., Pearce, I., Pascoe, P., Schulz, K. G., and Davidson, A. T. Ocean acidification effects on productivity in a coastal Antarctic marine microbial community, Biogeosciences, 15(1), 2018.

Sample Collection
Samples of 40-400 L were collected and sequentially size-fractionated filtered onto 293 mm biomass filters with 3.0 and 0.1 μm pore-sized polyethersulfone membrane filters (Pall XE20206 Disc 3.0 μm Versapor 293 mm and 656552 Disc 0.1 μm Supor 293 mm) using the design of the Global Ocean Sampling expedition (Rusch et al., 2007). Samples were collected on days 0 (immediately after seawater collection), 12 (mid-exponential growth) and 18 (end of experiment). On day 0, 400 L of seawater was collected from the reservoir tank (pre-filtered 200 μm), from which all the minicosms were filled, to allow characterisation of the initial community. This sample was collected from the reservoir, and not the minicosms, due to the large volume needed to collect sufficient microbial biomass on the filters. On day 12 and 18, 40 L was collected from each minicosm for filtration. The later samples were of a smaller volume due to the increase in biomass in the minicosms during the experiment, meaning less volume of water was required to gain sufficient material on the filters to perform molecular analysis. The filter membranes containing the concentrated microbial biomass were stored in 15 mL of storage buffer, flash frozen in liquid nitrogen and stored at - 80◦C. The storage buffer was freshly prepared on each sampling day with a mixture of 2.5 mM EGTA, 2.5 mM EDTA, 0.1 mM Tris-EDTA, RNA Later (0.5x house prepared), 1 mM PMSF and Protease Inhibitor Cocktail VI (Ng et al., 2010). Between samples the filtration apparatus was sequentially washed with 2 x 25 L 0.1 M NaOH, 2 x 25 L 0.07% Ca(OCl)2 and 2 x 25 L fresh water.
All samples were stored and transported at -80◦C to the Australian Antarctic Division, Hobart, Australia for DNA extraction.

DNA Extraction and Sequencing
The DNA was extracted from half of each filter (3.0 and 0.1 μatm per sample) via the method described in Rusch et al. (2007). In short, the filters were cut into small pieces and agitated in a lysozyme and sucrose buffer for 60 minutes and underwent three freeze/thaw cycles in a Proteinase K solution. This was followed by a gentler agitation at 55◦C for 2 hrs to remove all contents from the filter membranes. DNA was then separated using buffer saturated phenol, pelleted and washed in alcohol. The final DNA pellet was dissolved and stored in a 3 M sodium acetate (pH 8.0) and 100% ethanol solution and stored at - 80◦C. The DNA was transported and stored at 4◦C to the University of Queensland, St Lucia, Australia for sequencing within two months of extraction.
Eukaryotic 18S rRNA genes (V8-V9 regions) were amplified using polymerase chain reaction (PCR) with the primers V8f (5’ - AT AAC AGG TCT GTG ATG CCC T - ’3) and 1510r (5’ - CCT TCY GCA GGT TCA CCT AC - ’3) (Bradley, 2016). The 16S rRNA genes V8 region were amplified using PCR and primers 926F (5’-AAA CTY AAA KGA ATT GAC GG-3’) and 1392wR (5’-ACG GGC GGT GTG RC-3’) (Engelbrektson et al., 2010). PCR was performed using 1 or 1.5 μL of sample DNA, 2.5 μL 1x PCR buffer minus Mg+2 (Invitrogen), 0.75 μL MgCl2, 0.5 μL deoxynucleoside triphosphate (dNTPs, Invitrogen), 0.125 μL U Taq DNA Polymerase (Invitrogen), 0.625 μL of forward/reverse primer and made up to the final volume of 25 μL using molecular biology grade water. Forward and reverse primers were modified at the 5’-end to contain an Illumina overhang adaptor with P5 and i7 Nextera XT indices, respectively. The PCR thermocycling conditions were as follows: 94◦C for 3 min, 35 cycles of 94◦C for 45 sec, 55◦C for 30 sec, 7◦C for 10 min and a final extension of 72◦C for 10 min. Amplifications were performed using a Vertiti®96-well Thermocycler (Applied Biosystems) and success, amplicon size and quality was determined by gel electrophoresis.
The resultant amplicons were purified using Agencourt AMPure magnetic beads (Axygen Biosciences), dual indexed using Nextera XT Index Kit (Illumina). The indexed amplicons were purified using Agencourt AMPure XP beads and quantified using PicoGreen dsDNA Quantification Kit (Invitrogen). Equal concentrations of each sample were pooled and sequenced on an Illumina MiSeq at the University of Queensland’s School for Earth and Environmental Science using 30% PhiX Control v3 (Illumina) and a MiSeq Reagent Kit v3 (600 cycle; Illumina).

Bioinformatics
Sequencing data and runs were merged to produced single FASTQ file for 16S and 18S rDNA per sample and imported in QIIME2 (v2019.9) (Caporaso et al., 2010). A modified version of the UPARSE analysis pipeline was used to analyse the data. Specifically, the primer sequences were removed from forward reads of the 16S rDNA and reverse complement of the 18S rDNA Illumina read pairs, and chimeras removed using UCHIME2 (Edgar, 2016). These were then trimmed to a length of 200 bp and high-quality sequences identified using USEARCH (v10.0.240) (Edgar, 2010). Duplicate sequences were removed and a set of unique operational taxonomic units (OTUs) were generated using USEARCH employing a 97% OTU similarity radius. Mitochondrial and chloroplast OTUs were classified and removed from the 16S rDNA sequence data using the BIOM tool suite (McDonald et al., 2012). Representative OTU sequences were assigned taxonomy using SILVA132 (Quast et al., 2012) and PR2 (Guillou et al., 2012) for the eukaryotic group Bacillariophyceae (diatoms). Taxonomic assignments were validated against microscopy identifications conducted on the same samples (Chapter 3, Hancock et al. 2018) as well as phylogenetic trees built in iTOL (Letunic and Bork, 2006). Residual eukaryotic chloroplast and mitochondrial sequences were removed from the 16S rDNA data. Other obvious contaminants were removed manually including: Escherichia-Shigella (16S rDNA OTU75) and Saccharomycetales (18S rDNA OTU7, 146 and 160). Escherichia-shigella was removed as this group likely represents external contamination, similarly Saccharomycetales are yeast and are obvious skin-driven contaminants. A total of 9448 OTUs were identified from the 16S rDNA reads and 232 OTUs from the 18S rDNA read data. The number of reads were rarefied to 1300 and 1200 reads per sample for the 18S and 16S rDNA datasets respectively.
The following samples were removed due to lack of extracted, amplified and/or sequenced DNA, or due to low quality reads and/or low read numbers:
18S, 3.0 μm, day 18, 634 μatm ƒCO2 treatment
18S, 0.1 μm, day 12, 343 μatm or control ƒCO2 treatment
18S, 0.1 μm, day 18, 343 μatm or control ƒCO2 treatment
16S, 0.1 μm, day 18, 506 μatm ƒCO2 treatment

Statistical Analysis
The minicosm experiment was based on a repeated measure design, therefore due to being a dose-response experiment with no replication, no formal statistics could be undertaken on the interactions between time and ƒCO2. The richness (number of taxa) and evenness (equivalent to abundances within a sample) of the eukaryotic and prokaryotic microbial communities within each minicosm over time was estimated using three different alpha diversity indexes: observed number of OTUs (Sobs) (DeSantis et al., 2006), the Chao1 estimator of richness (Colwell et al., 2004), and Simpson’s diversity index and Berger-Parker index which account for both richness and evenness (Simpson, 1949; Berger and Parker, 1970) using QIIME2.
Clustering and ordinations were performed on Bray-Curtis resemblance matrices of the rarefied, square-root transformed OTU data as per Chapter 3 (Hancock et al., 2018). In brief, hierarchical agglomerative cluster analyses were performed using group-average linkage, and significantly different clusters were determined using similarity profile permutations method (SIMPROF) (Clarke et al., 2008). Both unconstrained (non-metric multidimensional scaling, nMDS) and constrained (canonical analysis of principal coordinates, CAP) ordinations were performed using the Bray-Curtis resemblance matrixes (Kruskal, 1964a,b; Oksanen et al., 2017). The constraining variables in the CAP analysis were ƒCO2, Si, P and NOx. All cluster and ordination analyses were performed using R v.1.1.453 (R Core Team, 2016) and the add-on package Vegan v.2.5-3 (Oksanen et al., 2017).

A full description of the statistical methods used for this paper is described in;
Hancock, A. M., Davidson, A. T., McKinlay, J., McMinn, A., Schulz, K. G., and van den Enden, R. L. Ocean acidification changes the structure of an Antarctic coastal protistan community, Biogeosciences, 15(1), 2018.

实验设计
本实验为六梯度剂量响应型海洋酸化实验，实验对象为采自南极近岸的天然微生物群落，实验周期为2014年11月19日至12月7日。海水采集自南极戴维斯站（Davis Station）附近约1 km海域（南纬68°35′，东经77°58′），经200 μm预过滤后，转移至置于控温集装箱内的6个650 L微型生态模拟罐（minicosms）中。通过调节每个微型生态模拟罐内的二氧化碳逸度（ƒCO₂）设置6个CO₂浓度梯度。实验前5天，使用经0.2 μm过滤且富集CO₂的海水，将ƒCO₂逐步调节至各罐的目标浓度：343、506、634、953、1140、1641 μatm。此CO₂驯化阶段于低光照条件下进行（光照强度0.9 ± 0.2 μmol·m⁻²·s⁻¹），以抑制浮游植物生长。随后2天内将光照强度提升至90.52 ± 21.45 μmol·m⁻²·s⁻¹，采用19:5的光暗周期（非光照限制型）。驯化阶段结束后，微生物群落继续培养10天（第8至18天），期间每日调节各罐内ƒCO₂以维持目标浓度，并保持光照强度恒定。实验过程中未添加任何营养盐。

关于微型生态模拟罐的设置、光照条件与碳酸盐化学的详细描述参见以下文献：
Davidson, A. T., McKinlay, J., Westwood, K., Thomson, P. G., van den Enden, R., de Salas, M., Wright, S., Johnson, R., and Berry, K.: Enhanced CO₂ concentrations change the structure of Antarctic marine microbial communities, Mar. Ecol. Prog. Ser., 552, 93-113, 2016.
Deppeler, S. L., Petrou, K., Westwood, K., Pearce, I., Pascoe, P., Schulz, K. G., and Davidson, A. T. Ocean acidification effects on productivity in a coastal Antarctic marine microbial community, Biogeosciences, 15(1), 2018.

样品采集
采集40~400 L海水样品，参照全球海洋采样计划（Global Ocean Sampling expedition, Rusch et al., 2007）的滤膜设计，使用孔径分别为3.0 μm和0.1 μm的聚醚砜膜滤器（Pall XE20206 Disc 3.0 μm Versapor 293 mm与656552 Disc 0.1 μm Supor 293 mm），依次按粒径分级过滤至293 mm生物质滤膜上。样品采集时间为第0天（海水采集后即刻）、第12天（指数生长中期）与第18天（实验结束时）。第0天时，从用于填充所有微型生态模拟罐的储水罐中采集400 L预过滤（200 μm）海水，以表征初始微生物群落。由于需在滤膜上收集足够的微生物生物量，该样品取自储水罐而非微型生态模拟罐。第12天和第18天时，从每个微型生态模拟罐中采集40 L海水用于过滤。后续样品体积较小，因为实验过程中微型生态模拟罐内的生物量增加，仅需较少体积的海水即可在滤膜上获得足够用于分子分析的样品。将载有浓缩微生物生物量的滤膜置于15 mL储存缓冲液中，经液氮快速冷冻后保存于-80℃。储存缓冲液于每次采样当日新鲜配制，成分为：2.5 mM EGTA、2.5 mM EDTA、0.1 mM Tris-EDTA、0.5倍体积自制RNA Later、1 mM PMSF与蛋白酶抑制剂鸡尾酒VI（Ng et al., 2010）。样品采集间隙，过滤装置依次用2×25 L的0.1 M NaOH、2×25 L的0.07% Ca(OCl)₂与2×25 L的新鲜水进行清洗。
所有样品均保存并运输至澳大利亚霍巴特的澳大利亚南极分部（Australian Antarctic Division）进行DNA提取，运输过程中保持-80℃。

DNA提取与测序
从每个滤膜的一半（分别对应3.0 μm和0.1 μm粒径分级的样品）中提取DNA，方法参照Rusch et al. (2007)。简要步骤为：将滤膜剪碎，置于溶菌酶蔗糖缓冲液中振荡60分钟，随后在蛋白酶K溶液中经历3次冻融循环；接着于55℃温和振荡2小时，以完全洗脱滤膜上的样品。随后用饱和酚缓冲液分离DNA，经酒精沉淀、洗涤后，将最终的DNA沉淀溶解于3 M乙酸钠（pH 8.0）与100%乙醇的混合液中，保存于-80℃。提取的DNA在2个月内运输并保存在4℃条件下，送至澳大利亚圣卢西亚的昆士兰大学进行测序。
使用聚合酶链式反应（PCR）扩增真核生物18S rRNA基因的V8-V9区，引物为V8f（5’-ATAACAGG TCTGTGATGCCCT-3’）与1510r（5’-CCTTCYGCAGGTTCACCTAC-3’）（Bradley, 2016）。扩增原核生物16S rRNA基因的V8区所用引物为926F（5’-AAACTYAAAKGAATTGACGG-3’）与1392wR（5’-ACGGGCGGTGTGRC-3’）（Engelbrektson et al., 2010）。PCR反应体系如下：1或1.5 μL样品DNA、2.5 μL 1×不含Mg²+的PCR缓冲液（Invitrogen）、0.75 μL MgCl₂、0.5 μL 脱氧核苷三磷酸（dNTPs，Invitrogen）、0.125 μL U Taq DNA聚合酶（Invitrogen）、0.625 μL上下游引物，用分子生物学级纯水定容至25 μL。上下游引物的5’端分别修饰有Illumina接头适配序列与P5、i7 Nextera XT索引序列。PCR热循环条件为：94℃预变性3分钟，35个循环（94℃变性45秒、55℃退火30秒、72℃延伸10分钟），最后72℃终延伸10分钟。PCR扩增使用Vertiti®96孔热循环仪（Applied Biosystems），通过凝胶电泳验证扩增成功与否、扩增子大小与质量。
所得扩增子用Agencourt AMPure磁珠（Axygen Biosciences）纯化，使用Nextera XT索引试剂盒（Illumina）进行双索引标记。索引后的扩增子用Agencourt AMPure XP磁珠纯化，并通过PicoGreen dsDNA定量试剂盒（Invitrogen）定量。将各样品按等浓度混合后，在昆士兰大学地球与环境科学学院使用Illumina MiSeq测序仪进行测序，测序时添加30%的PhiX Control v3（Illumina），使用MiSeq Reagent Kit v3（600循环，Illumina）。

生物信息学分析
将测序数据与测序reads合并，为每个样品生成16S和18S rDNA的单个FASTQ文件，导入QIIME2（v2019.9）（Caporaso et al., 2010）。使用改良版UPARSE分析流程处理数据：具体步骤为，去除16S rDNA正向reads与18S rDNA反向互补的Illumina双端reads中的引物序列，使用UCHIME2（Edgar, 2016）去除嵌合体序列；随后将序列修剪至200 bp长度，使用USEARCH（v10.0.240）（Edgar, 2010）识别高质量序列；去除重复序列，使用USEARCH以97%的相似性阈值生成唯一的操作分类单元（Operational Taxonomic Unit, OTU）。使用BIOM工具套件（McDonald et al., 2012）对16S rDNA序列数据中的线粒体和叶绿体OTU进行分类并移除。使用SILVA132数据库（Quast et al., 2012）与PR2数据库（Guillou et al., 2012）为代表OTU序列分配分类学信息，其中真核生物类群硅藻门（Bacillariophyceae）的分类信息需单独验证。分类学分配结果通过同一样本的显微镜鉴定结果（Hancock et al. 2018，第3章）以及在iTOL中构建的系统发育树（Letunic and Bork, 2006）进行验证。从16S rDNA数据中进一步移除残留的真核生物叶绿体与线粒体序列，手动移除其他明显的污染物序列：包括埃希氏菌-志贺氏菌属（Escherichia-Shigella，16S rDNA OTU75）与酵母菌目（Saccharomycetales，18S rDNA OTU7、146和160）。埃希氏菌-志贺氏菌属的移除是因为该类群大概率为外源污染物，而酵母菌目为真菌，属于典型的皮肤源性污染物。最终从16S rDNA测序reads中鉴定得到9448个OTU，从18S rDNA测序reads中鉴定得到232个OTU。对18S和16S rDNA数据集分别进行抽平至每个样品1200和1300条reads。
由于以下样品存在DNA提取、扩增和/或测序失败，或测序读长质量差、reads数量过低，故予以移除：
18S, 3.0 μm, 第18天, 634 μatm ƒCO₂处理组
18S, 0.1 μm, 第12天, 343 μatm或对照ƒCO₂处理组
18S, 0.1 μm, 第18天, 343 μatm或对照ƒCO₂处理组
16S, 0.1 μm, 第18天, 506 μatm ƒCO₂处理组

统计分析
本微型生态模拟罐实验采用重复测量设计，且为无重复的剂量响应实验，因此无法对时间与ƒCO₂的交互作用进行正式统计分析。使用三种不同的α多样性指数估算每个微型生态模拟罐内真核与原核微生物群落的丰富度（类群数量）与均匀度（样品内丰度分布均等性）：观测OTU数量（Sobs）（DeSantis et al., 2006）、Chao1丰富度估计值（Colwell et al., 2004），以及同时考虑丰富度与均匀度的Simpson多样性指数和Berger-Parker指数（Simpson, 1949; Berger and Parker, 1970），所有分析均通过QIIME2完成。
对抽平后的、经平方根转换的OTU数据，基于Bray-Curtis相似性矩阵进行聚类与排序分析，方法参照Hancock et al. (2018)第3章。简要步骤为：使用组平均连接法进行分层凝聚聚类分析，通过相似性轮廓置换法（SIMPROF）（Clarke et al., 2008）确定显著差异的聚类簇。使用Bray-Curtis相似性矩阵分别进行无约束排序（非度量多维标度分析，nMDS）与约束排序（主坐标典范分析，CAP）（Kruskal, 1964a,b; Oksanen et al., 2017）。CAP分析中的约束变量为ƒCO₂、硅（Si）、磷（P）与氮氧化物（NOₓ）。所有聚类与排序分析均通过R v.1.1.453（R Core Team, 2016）及其扩展包Vegan v.2.5-3（Oksanen et al., 2017）完成。
本研究所用统计方法的完整描述参见：
Hancock, A. M., Davidson, A. T., McKinlay, J., McMinn, A., Schulz, K. G., and van den Enden, R. L. Ocean acidification changes the structure of an Antarctic coastal protistan community, Biogeosciences, 15(1), 2018.