references coccolithophores

8/13/2019 References coccolithophores

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Emiliania huxleyiincreases calcification but not expression of calcification-related genes in long-term exposure

to elevated temperature andpCO2

1. Ina Benner1,2. Rachel E. Diner1,3. Stephane C. Lefebvre1,,4. Dian Li1,5. Tomoko Komada1,6. Edward J. Carpenter1and7. Jonathon H. Stillman1,2

+Author Affiliations

1. 1Romberg Tiburon Center for Environmental Studies, San Francisco State University, Tiburon, CA 94920,USA

2. 2Department of Integrative Biology, University of California Berkeley, 3040 Valley Life Sciences Building no.3140, Berkeley, CA 94720, USA

+Author Notes

Present address: Microbial and Environmental Genomics, J. Craig Venter Institute, 10355 ScienceCenter Drive, San Diego, CA 92121, USA.

1. e-mail:[email protected]. e-mail:[email protected]

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Abstract

Increased atmosphericpCO2is expected to render future oceans warmer and more acidic than they are at present.

Calcifying organisms such as coccolithophores that fix and export carbon into the deep sea provide feedbacks to

increasing atmosphericpCO2. Acclimation experiments suggest negative effects of warming and acidification on

coccolithophore calcification, but the ability of these organisms to adapt to future environmental conditions is not

well understood. Here, we tested the combined effect ofpCO2and temperature on the coccolithophore Emiliania

huxleyiover more than 700 generations. Cells increased inorganic carbon content and calcification rate under

warm and acidified conditions compared with ambient conditions, whereas organic carbon content and primary

production did not show any change. In contrast to findings from short-term experiments, our results suggest that

long-term acclimation or adaptation could change, or even reverse, negative calcification responses in E. huxleyi

and its feedback to the global carbon cycle. Genome-wide profiles of gene expression using RNA-seq revealed that

genes thought to be essential for calcification are not those that are most strongly differentially expressed under

long-term exposure to future ocean conditions. Rather, differentially expressed genes observed here representnew targets to study responses to ocean acidification and warming.

coccolithophore acidification climate change RNA-seq transcriptome
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discussed at the 215 generation point, and qPCR for some genes that have been previously identified as involved

with calcification [26]was measured across all generation points.

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Table 1.

Carbonate system for each generation point in the present ocean condition (383 + 43 atmpCO2, 20.0 + 0.1C) and

future ocean condition (833 + 68 atmpCO2, 24.0 + 0.2C). DIC, dissolved inorganic carbon; TA, total alkalinity.

Each value is the mean s.d. Salinity was 33.5 0.3.

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2. Material and methods

(a) Culture conditions

Monospecific cultures of E. huxleyi(CCMP 371) from the Provasoli-Guillard National Center for Marine Algae and

Microbiota were grown in nitrate-limited chemostats (1 l volume) in duplicate under two different treatments. The

first treatment represented present ocean conditions withpCO2and temperature levels of 38343 atm and

20.00.1C, respectively (table 1). The second treatment represented future ocean conditions with elevatedpCO2

and temperature (average 833 68 atm and 24.0 0.2C, respectively;table 1). Chemostats were run with a

dilution rate (equivalent to growth rate) of 1.1 d1

using 0.2 m filtered nutrient-poor, aged seawater with a

salinity of 33.5 0.3 (collected offshore of Half Moon Bay, CA, USA; 37 29 31 N, 122 30 02 W), enriched with

phosphate (14 M), and with a metal and vitamin mix according to f/2 concentrations [33]. To archive a cell

concentration of approximately 500 000 cells ml1

, nitrate concentrations were raised to 30 M in the present

ocean condition media and 35 M in the future ocean condition. These nitrate concentrations were found in

prior tests to yield the target cell concentration. Media were augmented with sodium bicarbonate to compensatefor dissolved inorganic carbon (DIC) uptake during calcification (by 245 and 250 M for the present ocean

condition and future ocean condition media, respectively). This was done after approximately 88 generations to

adjust to the DIC uptake as calculated from the carbonate system (see below for carbonate chemistry

determination). The 5 M difference in DIC concentrations in the two media after augmentation is less than 1% of

total DIC, and therefore three to eight times lower than the DIC change that is commonly accepted for diluted

batch experiments with coccolithophores [12,34].

pCO2levels in the cultures were controlled by continuously bubbling the culture and the media reservoir with CO 2

air mixtures to achievepCO2levels of approximately 400 and 900 atm. Media reservoirs were bubbled for at least

1 day prior to use for pre-equilibration. ThepCO2concentration in gas mixtures was frequently monitored using an

infrared gas analyser (LI-820, LI-COR). Cultures were stirred gently throughout the experiment to ensure

homogeneous cell suspension and avoid possible light and nutrient gradient effects. Cultures were illuminated ona 16 L : 8 D cycle with cool-white fluorescent lamps (Vita-Lite 5500 K, DUROTEST) at 240320 mol photons m

2s

1.

Photon flux density was measured in the centre of each vessel containing E. huxleyiculture using a 4 pi

Biospherical instruments probe, model QSP170B. Cell division was synchronized to the photoperiod and a diurnal

fluctuation of cell density was found that might have caused a diurnal fluctuation in the carbonate system as well

as nutrient concentration.

(b) Sampling and analyses of cultures
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Cultures were sampled at three generation points, from 199 to 232 generations (215 generations), from 393 to

436 generations (414 generations) and from 683 to 724 generations (703 generations). Each of these samplings

occurred over the course of three to four weeks where various samples were collected on a daily basis (see the

electronic supplementary material, table S1). The reason for the extended sampling period was to avoid removing

less than 10% of the chemostat volume at any given time, thereby minimizing perturbations to the steady state

[35]. The chemostat outflow was not sampled, because it was not maintained under the same temperature,pCO2,

and light conditions as the culture. At each generation point, samples for cell density and dilution rate werecollected daily (n= 22, 27 and 28 for generation 215, 414 and 703, respectively; electronic supplementary material,

table S1). Samples for primary production, calcification rate, DIC, total alkalinity (TA), chlorophyll a(Chl a), and

nutrients (n= three per generation point) were collected approximately weekly, and samples for total particulate

carbon (TPC) and POC (n= six per generation point) were collected every third or fourth day (see the electronic

supplementary material, table S1). Samples for gene expression (n= six per generation point) were collected every

36 days (electronic supplementary material, table S1). All samples were collected 14 h after the light onset.

Allowing for multiple days to pass between sampling for physiological parameters ensured that the population of

cells had been replaced completely between collection points, given the high growth rate in our chemostats of 1.1

d1

(more than one division per day). This sampling strategy is routinely used for continuous culture experiments,

as cells several generations apart represent independent samples of the same population [13,24,31,36].

TA samples (approx. 80 ml) were filtered (combusted GF/F filters, Whatman) and stored in borosilicate glass

bottles in the dark at 4C until measurement. TA was measured on 50 ml of the sample by potentiometric titration

[37]and the endpoint determined from Gran plots [38]. DIC samples (24 ml) were sterile filtered (0.2 m syringe

filter, Nalgene) into borosilicate glass vials and stored without headspace in the dark at 4C until measurement. DIC

was measured following Friederich et al.[39], but with pure O2carrier gas instead of N2. The carbonate system

parameters were determined from DIC TA, salinity, temperature, silicate and phosphate concentrations using

CO2SYS [40]with constants from Mehrbach et al.[41]refit by Dickson & Millero [42].

Samples for determination of TPC and POC were filtered on pre-combusted GF/F filters (Whatman) (75 and 125 ml,

respectively) and dried at 55C overnight. Prior to analysis, the POC filters were acidified with 230 l of 1 N HCl to

remove inorganic carbon and dried again. TPC and POC were measured on a Costech ECS 4010 CHNSO analyser.

PIC was calculated as the difference between TPC and POC. POC and PIC values were normalized either by the

volume of water filtered or by the number of cells filtered (determined from sample volume and cell density).

Primary production and calcification rates were determined using14

C incorporation modified after Balch et al.[43].

A 20 ml subsample of the culture was spiked with 6.84 Ci of H14

CO3and incubated for 2 h. Incubations were fixed

with 5% HgCl2after 2 h and 5 ml were filtered four times onto GF/F filters (Whatman) for repeated measurements.

Half of the filters were acidified, and radioactivity was measured in Optiphase Hisafe 3 scintillation cocktail

(Perkin-Elmer Inc., USA) on a Wallac Guardian 1414 liquid scintillation counter (Perkin-Elmer Life and Analytical

Sciences Inc.). Calcification rate was calculated with the radioactivity of the acidified (primary production) and non-

acidified (total carbon production) filters.

The effect of treatment, chemostat and generation points and their interactions on all response variables was

investigated by ANOVA. TukeyHSD post-hoc test was used to characterize pairwise differences across the three

generation points in each treatment. Planned comparisons for differences between the treatments at each

generation point were performed using unpaired t-tests. Data were analysed by pooling all replicates from onetreatment (two chemostats) for each generation point. T-tests were used to test that the two replicate chemostats

for each treatment were not significantly different from each other before they were pooled together by

treatment. Outliers in each dataset were identified with the Grubbs test for outliers [44]. No more than one outlier

was removed from any dataset.

(c) Transcriptomics
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One hundred millilitres of culture was filtered onto 1.0 m polycarbonate filters, which were immediately frozen in

liquid nitrogen, then stored at 80C. Total RNA was extracted from samples using Tri Reagent (Molecular

Research Center, Inc.) according to the manufacturer's protocol. RNA quantity was measured using a Qubit v. 2.0

Fluorometer (Life Technologies) and integrity was confirmed using a Bioanalyzer (Agilent 2100) RNA assay.

RNA-seq libraries were constructed using Illumina TruSeq reagents according to the manufacturer's protocol

(Illumina, TruSeq RNA Sample Preparation Kit v. 2). Clean-up steps were performed using AMPure XP beads(Agencourt), and first-strand cDNA was synthesized using SuperScript II reverse transcriptase (Invitrogen). Prior to

sequencing, cDNA library concentrations were measured viaQubit Fluorometer and fragment size distribution was

confirmed by Bioanalyzer high-sensitivity DNA assay. Libraries were sequenced at the Vincent J. Coates Genomics

Sequencing Laboratory, University of California Berkeley on the Illumina HighSeq 2000 platform using 100 base

pair paired-end sequencing. Multiplexing was at n= 8 libraries per lane.

Raw sequence reads were trimmed for quality using the program DynamicTrim (SolexaQA_v. 2.0, [45]), eliminating

sequence with a probability below 0.05 and a quality score below 13 from the analysis. RNA-seq reads were

aligned and mapped to the E. huxleyiCCMP1516 draft genome sequence (v. 1.0, Emihu1_best_transcripts.fasta)

from the Joint Genome Institute (http://genome.jgi-psf.org/Emihu1/Emihu1.home.html), using Tuxedo Suite

software for read alignment and quantification with TopHat (v. 2.0.3, [46]), short read assembly with Bowtie (v.

0.12.2, [47]) and SamTools (v. 0.1.18, [48]). Mapped reads were annotated using the E. huxleyidraft genomesequence and supporting files (including KOG, KEGG and GO identifications). Putative transcripts with fewer than

100 mapped reads were removed from the dataset, and the remaining transcripts were tested for differential

expression using edgeR (v. 2.6.12, [49]). Statistical analyses were conducted using pair-wise comparisons of

individual chemostats within and between treatments, with a false discovery rate adjustedp-value of 0.05. Genes

that differed in at least three of four pairwise comparisons between treatments, but that did not differ in the

within-treatment comparison across replicate chemostats were considered differentially expressed in response to

present versus future ocean conditions.

Quantitative real time PCR (qPCR) verification of expression in all chemostats across all three generation points

was conducted for calcification-related transcripts, a gamma carbonic anhydrase, a cation/H+exchanger, a putative

bicarbonate transporter and proton channel, and normalized to the housekeeping gene actin using published

primer sequences (table 2)[26]. RNA was extracted from two samples per chemostat per generation point (see

electronic supplementary material, table S1) using Tri Reagent (Molecular Research Center, Inc.) according to the

manufacturer's protocol and reverse transcribed into cDNA using Improm-II reverse transcriptase (Promega).

Samples were DNAse treated and purified using the RNeasy mini kit (Qiagen). RNA quantity and purity were

assessed by NanoDrop spectrophotometer (A260and A260/A280, respectively) and integrity was assessed by agarose

gel electrophoresis. qPCR assays were conducted using SYBR green mastermix (Fermentas Maxima, Thermo

Scientific) with the passive reference dye ROX on an ABI7300 real time PCR instrument (Applied Biosystems).

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Table 2.

qPCR Primers and amplicon length.

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3. Results
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(a) Physiological responses to warm and acidified conditions

Physiological responses were not affected by the interaction between treatment and generation point (table 3).

Cells had carbon to nitrogen (C : N) ratios (figure 1)of approximately 11 in both treatments at the 215 and 703

generation points, though the ratio was lower in future ocean conditions at the 703 generation point ( t-test t8=

0.62,p= 0.55 at 215 generations; t10= 2.7,p= 0.026 at 703 generations). The C : N ratio (figure 1)at the 414

generation point was lower at approximately 8.3, but was not significantly different between the treatments (t-test t9= 0.68,p= 0.52). The sum of nitrate and nitrite concentrations in the chemostats was at all generation

points below 1 M (table 1). PIC content (figure 2a) increased by 26% under future ocean conditions at all three

generation points (215, 414 and 703 generations), though this was statistically significant only at the latter two

generation points (t-test t14= 2.0,p= 0.07 at 215 generations; t21= 4.0,p< 0.001 at 414 generations; t22= 2.9,p 100% difference in surface coverage. Altering

nieffects both the bloom and no-bloom cases. The results are relatively insensitive to varying the

ramp parameters, mrand nr. This result reflects that these parameters are describing changes ingradient which will be less prevalent, and less sensitive to atmospheric and data variations, than

the intensity data. In conclusion, the sensitivity analysis illustrates that the model parameters

should be set based on primarily analysing a range of scenes containing bloom instances. Oncethey have been set, analysing a set of no-bloom cases will allow minor adjustments to be made tothe parameters.

Fig. 6.

Sensitivity analyses results for the two bloom (solid lines) and two no-bloom (dottedlines) test cases. a) Forgetting time Tand b) the number of imagesIused in the

background model. The percentage of coccolithophore bloom pixels in the default results

are illustrated by the two thick horizontal lines (4.544.79%).

Figure options
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Fig. 7.

Sensitivity analyses results for the two bloom (solid lines) and two no-bloom (dottedlines) test cases. a) The upper intensity subtraction level mi, b) the lower intensitysubtraction level mr, c) the upper ramp subtraction level ni, and d) the lower ramp

subtraction level nr.

Figure options

5. Conclusions

The unique spectral properties and typically large spatial extent of coccolithophore blooms allowthe use of EO data to investigate their frequency and distribution. Increasingly, their frequency

and extent are of interest to the carbon cycle modeling community as they are the largest source

of calcium carbonate in the oceans and are considered to play an important role in oceaniccarbon cycles. This paper presents a novel method that builds upon previous work to

automatically detect coccolithophore blooms using spectral, spatial and temporal information,

producing maps of spatial extent. The results have been compared with the established spectralalgorithm and an extensive in situcell count database. The results have illustrated that when
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applied to multi-season and multi-year datasets, the new approach reduces false positives in shelf

seas and coastal zones. Towards verification the algorithms have been applied to 2 years of

SeaWiFS data. Validation has been achieved using 2 years of in situdata (N= 432). The resultshave shown that, for the study region during 2003 and 2004, the coccolithophore bloom coverage

in May varied between 4540674985 km2. Whereas, the coverage was more consistent in July

varying between 172022174849 km

2

. This work has been demonstrated using SeaWiFS data.However, the approach is equally applicable to other sensors, providing a suitable spectral modelexists (e.g. NASA's MODIS-Aqua). The region of study was deliberately chosen to include both

open ocean, shelf sea and coastal waters (e.g. case 1 and case 2 waters,Groom et al., 2009). This

region of the northern hemisphere can also suffer from large amounts of cloud cover. Thus, boththe original approach of BY and the new A + BY approach have been evaluated in a challenging

region containing complex waters, with the potential for high cloud cover. The A + BY approach

is based around the original approach ofBrown and Yoder (1994),which has been successfully

applied globally to produce global maps of coccolithophore bloom extent. If applied globally, theA + BY approach would be expected to perform at least as well as the BY approach, and would

be expected to improve the results in shelf sea regions. However, further analysis of a range of

regions would be needed to verify this. This new method should provide improved data for thelong term study of coccolithophore bloom spatio-temporal distribution. Further research is now

underway to apply this new method to the entire SeaWiFS time-series for the north east Atlantic

in order to studyE. huxleyivariability and environmental forcing; these findings will be reported

separately.

Acknowledgements

The authors would like to gratefully acknowledge partial funding by the Natural Environment

Research Council (NERC) through the NERC Earth Observation Data Acquisition and Analysis

Service (NEODAAS) and the Plymouth Marine Laboratory strategic research programme, a

subset of the NERC Oceans 2025 programme. All SeaWiFS data were kindly received andprocessed by the NEODAAS through the NASA SeaWiFS project (code 970.2). The authors

would also like to thank Bryan Franz, Sean Bailey and Wayne Robinson from the NASA ocean

colour research team for helpful information regarding SeaDAS and the Sir Alister HardyFoundation for Ocean Science (SAHFOS) for providing the CPR data, especially David Johns

and Martin Edwards for their helpful discussions.
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Introduction

Marine photoautotrophic organisms fix c. 55 gigatonnes of carbon yr1

which is equal to the

photosynthetic production by the terrestrial biosphere (Field et al.,1998).Coccolithophores playa major role in the global carbon cycle by contributing c. 110% to total organic carbon fixation

(Poulton et al.,2007)and providing ballast through the formation of calcite, which enhancesorganic matter sinking into the deep ocean (Thierstein et al.,1977). The globally most abundantcoccolithophore species isEmiliania huxleyi, which has the ability to form blooms up to

8 106km

2(Moore et al.,2012). Despite the global significance ofE. huxleyi, there is only a

limited understanding of important cellular processes and their response to environmentalchange.

Under present-day conditions, marine phytoplankton growth is mostly limited by low light

availability or by the insufficient supply of inorganic nutrients, such as nitrogen, phosphorus oriron (Sarmiento & Gruber,2006), while carbon dioxide (CO2) is usually not considered to be

limiting. Nevertheless, CO2diffusion rates are in most cases not high enough to account for the

photosynthetic rates seen in the majority of phytoplankton (Falkowski & Raven,2007). Thisdiscrepancy is explained by the action of carbon (or CO2) concentrating mechanisms (CCMs). In

algae these are predominantly C3 biophysical mechanisms which link carbonic anhydrases

(CAs), dissolved inorganic carbon (DIC) transporters and pH gradients to enhance [CO2] at theactive site of Ribulose-1,5-bisphosphate carboxylase oxygenase (RubisCO) (Reinfelder,2011). It

is thought that nearly all marine phytoplankton operate a CCM, although the DIC species used

(CO2and/or bicarbonate ( )), its regulation, cellular components, and DIC affinity can varysignificantly between species (Giordano et al.,2005).E. huxleyioperates a low-affinity CCM

(Rost et al.,2003). Several studies indicate that CO2is the primary source for photosynthesis,

although there are some discrepancies over the importance of , especially at lower CO2concentrations (Paasche,1964;Sikes et al.,1980;Nimer & Merrett,1992;Sekino & Shiraiwa,

1994;Herfort et al.,2002;Rost et al.,2003;Schulz et al.,2007;Bach et al.,2011). In addition toa biophysical mechanism, intracellular calcification has been proposed to act as a CCM by

providing protons (H+) as a by-product of calcification to support the dehydration of to

CO2(reviewed in; Paasche,2001). Although there are some supporting data (Nimer & Merrett,

1992;Buitenhuis et al.,1999), other studies contradict the concept (Paasche,1964;Herfort et al.,2004;Trimborn et al.,2007;Leonardos et al.,2009).

In the forthcoming centuries, ongoing uptake of anthropogenic atmospheric CO2into the oceanswill continuously change the marine carbonate chemistrya process known as ocean

acidification (Caldeira & Wickett,2003). Chemically, ocean acidification leads to a strong

decrease of the carbonate ion ( ) concentration, a slight increase in [ ] and a strongincrease in [CO2] and [H

+] (Wolf-Gladrow et al.,1999). These components are thought to affect

coccolithophores in varying ways, with [ ] influencing calcite saturation concentrations,

[H+] affecting cellular pH homeostasis, [CO2] affecting photosynthesis and [ ] influencing

calcification (and photosynthesis). The potential effects of ocean acidification on calcification

and photosynthesis byE. huxleyihave been repeatedly reported (reviewed in Riebesell & Tortell,

2011), but the importance of changes in the individual carbonate parameters for the observedresponses is still not fully understood.
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The present study disentangles the carbonate system to improve our conceptual understanding of

the acquisition of DIC and its subsequent use in calcification and photosynthesis. In particular,

we address two important questions inE. huxleyiecophysiology: how sensitive isE. huxleyitolow and elevated components of the carbonate system; and does calcification act as a CCM?

Materials and Methods

Conceptual background of the experiments

The marine carbonate system is defined by the concentrations of CO2, , ,pCO2, total

alkalinity (TA), DIC (i.e. combined CO2, and ), and pH ([H+]; Zeebe & Wolf-

Gladrow,2001). The physiologically relevant parameters of the carbonate system are CO2,

, and H+, as only these can be perceived by a cell. They are connected to each other

in the equilibrium reaction:

(Eqn 1)

As no other parameters of physiological relevance other than CO2, , and H+were

changed in the experiments (e.g. light or temperature), it is assumed that only changingconcentrations of these particular parameters can induce physiological or genetic responses. CO2,

, and H+are closely codependent (Eqn(Eqn 1))and any change in the concentration

of one will lead to changes in the others. Nevertheless, it is possible to keep one of the four

parameters constant while changing the other three. We made use of this feature and performedthree experiments where we kept either [CO2] or [H

+] constant between treatments ([H

+] was

kept constant at two different concentrations). The constant carbonate system parameter within

an experiment can be excluded from being responsible for the observed physiological or geneticresponse (Buitenhuis et al.,1999). Note that we chose to focus on CO2and H

+, as previous work

points towards a primary importance of these particular parameters forE. huxleyiphysiology

(Schulz et al.,2007;Bach et al.,2011).

Experimental design and basic setup

Three experiments were conducted to test the physiological and molecular responses of

Emiliania huxleyi(Lohmann) Hay and Mohler to changes in individual carbonate chemistryparameters. DIC was varied in all experiments, while either pHf(8.34 or 7.74 on free scale) or

CO2(16 molkg1

) was kept constant. In all experiments, cells ofE. huxleyi(strain B92/11)

were grown in monoclonal dilute batch cultures (LaRoche et al.,2010)at 15C and150 molm

2s

1incident photon flux density under a 16 : 8 h, light: dark cycle. The growth

medium was artificial seawater prepared as described in Kester et al. (1967)but without the

addition of NaHCO3, which was added in a later step (see the following section). Artificial

seawater was enriched with c. 64 molkg1

nitrate, 4 molkg1

phosphate, f/8 concentrations ofa trace metal and vitamin mixture (Guillard & Ryther,1962), 10 nmol kg

1of SeO2, and

2 ml kg1

of natural North Sea water. Concentrations of nitrate and phosphate were measured

according to Hansen & Koroleff (1999). The nutrient-enriched artificial seawater was sterile-
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filtered into polycarbonate bottles where the carbonate chemistry was manipulated. After taking

samples for carbonate chemistry measurements (see the following section), the artificial seawater

was divided carefully into three 2.3 l polycarbonate bottles before inoculation. Beforeinoculation,E. huxleyicells were acclimated to exponential growth and carbonate chemistry

conditions for at least seven generations. Approximate cell densities ranged from 50 to 300

cells ml

1

at inoculation and 40 000100 000 cells ml

1

at sampling (see description of samplinglater).

Carbonate chemistry manipulation and determination

In all experiments, target DIC concentrations were adjusted by adding calculated amounts of

NaHCO3or Na2CO3(see Bach et al.,2012for details). In the constant-CO2experiment, CO2wasset to a constant concentration of c. 16 ( 2) molkg

1through additions of calculated amounts

of HCl (3.571 molar). In the constant-pH experiments, pH was adjusted to 7.74 ( 0.004) or 8.34

( 0.008) by adding 2 mmol kg1

of 2-[-4-(2-hydroxyethyl)-1-piperazinyl]-ethanesulfonic acid

(HEPES, adjusted to target pHflevels).

Carbonate chemistry in the constant-CO2experiment was determined by measuring TA and pHf,

while in both constant-pH experiments it was determined from pHfand DIC. Carbonatechemistry samples were taken at the beginning and the end of the experiments. Samples for TA

were filtered (0.7 m), poisoned with saturated HgCl2solution (0.5 final concentration) and

stored at 4C until measured (Dickson et al.,2003). TA values higher than 4700 molkg1

wereoutside the range that can be accurately determined with the applied method and therefore

diluted with double deionized water as described in Bach et al. (2012).

Samples for DIC were sterile-filtered (0.2 m) by gentle pressure into 4ml borosilicate bottles,

made air-tight without headspace and subsequently measured as described in Stoll et al. (2001).

DIC samples lower than 1000 or higher than 3000 molkg

1

could not be reliably measured withthe applied method and were therefore either diluted or concentrated (see Bach et al.,2011,2012).

Samples for pHfwere measured potentiometrically at 15C with separate glass and reference

electrodes (METROHM) calibrated with reference seawater, certified for TA and DIC (supplied

by Prof. A. Dickson, La Jolla, CA, USA; see Bach et al.,2011,2012for details).

Carbonate chemistry parameters that were not directly measured were calculated from two

measured values (DIC and TA or DIC and pHf) and known salinity, temperature, and phosphate

concentrations with the software CO2SYS (Lewis & Wallace,1998)using equilibrium constantsdetermined by Roy et al. (1993). Biological response data are plotted against the means of the

initial and final values of the carbonate chemistry. Error bars in plotted carbonate chemistry

parameters denote the mean change of the three replicates of the particular carbonate chemistryparameter from the beginning of the experiment to the end.

Sampling, measurements and calculations of growth, organic, and inorganic carbon

production rates
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Sampling started 2 h after the onset of the light period and lasted not longer than 2.5 h. Duplicate

samples for total particulate carbon (TPC) and particulate organic carbon (POC) were filtered

(200 mbar) on to precombusted (5 h at 500C) GF/F filters. To remove HEPES from the filtersof the constant-pH experiments, samples were rinsed with 60 ml of artificial seawater medium

supersaturated with respect to calcium carbonate and free of HEPES buffer immediately after

filtration. Filters were stored at 20C until measurements were carried out. POC filters wereplaced for 2 h in a desiccator containing fuming HCl to remove all calcite and then dried for c.6 h at 60C. TPC filters were dried under the same conditions but without the acid treatment.

TPC and POC analyses were performed using an elemental analyzer (HEKATECH, Wegberg,

Germany) combined with an isotope ratio mass spectrometer (FINNIGAN, Schwerte, Germany).Particulate inorganic carbon (PIC) was calculated as the difference between TPC and POC.

Cell numbers were determined with a Coulter Counter (Beckman Coulter, Krefeld, Germany) atthe beginning and the end of the experiments c. 4 h after the onset of the light period. Growth

rates () were calculated as

(Eqn 2)where t0and tfinare the cell numbers at the beginning and the end of the experiments,

respectively, and dis the growth period in days. POC and PIC production rates were calculatedby multiplying growth rates with the cellular POC or PIC contents.

Treatments were further analyzed by scanning electron microscopy (SEM) and cross-polarizedlight microscopy to confirm the presence or absence of internal coccoliths (Bach et al.,2012).

Cells were considered to be actively calcifying if coccoliths were present.

For gene expression analysis, c. 10 million cells were filtered (200 mbar) onto polycarbonatefilters with a pore size of 0.8 m and subsequently rinsed off the filters with 1ml RNAlater

(Qiagen). This cell suspension was kept on ice until storage at 20C.

Quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR)

Quantitative reverse-transcriptase polymerase chain reaction was performed for 15 target genes

(Table1). Each sample was measured in triplicate. Experimental procedures were performed as

described previously (Mackinder et al.,2011). Primers were designed using expressed sequencetag (EST) clusters from von Dassow et al. (2009), theE. huxleyiGenome Project

(http://genome.jgi-psf.org/Emihu1/Emihu1.home.html)or from the current literature (Supporting

Information, Table S1). Efficiency curves for each primer pair were generated using serialdilutions on pooled cDNA from all samples. All primers except beta-carbonic anhydrase (CA)had efficiencies between 90 and 105% and generated curves withR

2values > 0.99.CA

efficiency remained undetermined as a result of the low cycle threshold (CT) values of pooled

cDNA even at undiluted levels. For relative expression calculations, its efficiency was assumedto be 100%. This assumption results in a potential decrease in the accuracy of the absolute fold

changes, but the trend of expression and the order of magnitude will remain unaffected. For each

sample, 220 ng of RT RNA were analyzed in technical triplicates. For each primer pair, all
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samples were analyzed across three plates, and in order to allow for the correction of between-

plate variation two standards in triplicate were run on each plate. GeNorm (Vandesompele et al.,

2002)was used to test the stability of four potential endogenous reference genes (ERGs).

Table 1. Emiliania huxleyigenetic response to carbonate system manipulations

Gene Full name

Correlation to carbonate system

parameterFunction and location

CO2

(mol

kg1

)

(mol

kg1

)

(mol

kg1

)

pHf

Putative

function

Possible

location

experimentally

or by analogy

Predicted

location by

WoLF

PSORT

(Horton

et al.,

2007)


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Gene Full name



CO2

(mol

kg1

)

(mol

kg1

)

(mol

kg1

)

pHf

Putative

function

Possible

location

experimentally

or by analogy

Predicted

location by

WoLF

PSORT

(Horton

et al.,

2007)


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Gene Full name



CO2

(mol

kg1

)

(mol

kg1

)

(mol

kg1

)

pHf

Putative

function

Possible

location

experimentally

or by analogy

Predicted

location by

WoLF

PSORT

(Horton

et al.,

2007)


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Gene Full name



CO2

(mol

kg1

)

(mol

kg1

)

(mol

kg1

)

pHf

Putative

function

Possible

location

experimentally

or by analogy

Predicted

location by

WoLF

PSORT

(Horton

et al.,

2007)


55/68


Gene Full name



CO2

(mol

kg1

)

(mol

kg1

)

(mol

kg1

)

pHf

Putative

function

Possible

location

experimentally

or by analogy

Predicted

location by

WoLF

PSORT

(Horton

et al.,

2007)


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Primer 6 in case they were not. Normality was tested with ShapiroWilk's test (P= 0.05).

Nonnormally distributed subsets were BoxCox-transformed. Subsets that remained

nonnormally distributed were analyzed with the PERMANOVA.

ANOVA: The difference of individual treatments within an experiment was tested with Tukey's

HSDpost-hoctest (Pvalues frompost-hoctests are denoted byPpost hoc). Homogeneity ofvariance was tested using Levene's test and was accepted if theP-value was > 0.05. WherePwas

smaller, the significance level (P-value of the ANOVA and thepost-hoctest) was decreased to

0.01. Subsets treated this way are marked in Table S2.

PERMANOVA: A resemblance matrix was created using the Euclidian distance function and

further processed with a one-factorial PERMANOVA design choosing type III partitioning of thesum of squares. In cases where statistically significant differences were detected, a pairwise

comparison of treatments (analog to apost-hoctest) was conducted in a second PERMANOVA

run. The numbers of permutations for each run are given in Table S2. In pairwise

PERMANOVA runs, these numbers were not sufficiently high (< 100) to get reasonable results

forP, so that an additional Monte Carlo test was conducted. Significance levels of thePERMANOVA analysis are the same as for the ANOVA, but by convention are termedP(perm)

for the permutationP-value andPpost hoc(MC) for the Monte CarloP-value to distinguish them.

Results

Growth and POC production rates are sensitive to low CO2(and ) and to low pH,

but not to elevated CO2

To determine the importance of individual components of the carbonate system forE. huxleyi

physiology, cells were grown in three separate experiments at constant pHf(7.74 and 8.34) and

constant CO2(16 molkg1

). Fig.1shows how the carbonate system changed within the threeexperiments. By maintaining relatively low cell concentrations, changes in carbonate chemistry

as a result of biological processes were kept to a minimum over the time of the experiments. This

is indicated by the error bars in Fig.1with the corresponding values in Table S3.

Figure 1. Physiologically relevant carbonate chemistry parameters in relation to dissolved

inorganic carbon (DIC). (a) pHf. (b) [ ]. (c) [ ]. (d) [CO2]. Error bars account for themean change (mean of triplicates) of the particular carbonate chemistry parameter over thecourse of the experiments. Black circles, constant pHf= 7.74; red circles, constant pHf= 8.34;

triangles, constant CO2. Note that error bars are in most cases masked by symbol size.
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Within the ranges examined, growth and POC production rates were primarily influenced by

changes in carbonate chemistry from low to intermediate (1602000 molkg1

) and CO2

(0.820 molkg1

) (Fig.2)with neither pH nor having a pronounced influence (Fig. S1).

Growth rates increased in all experiments with increasing concentrations of and CO2until

reaching maximum rates of c. 1.1 d1

where further CO2or increases had no effect on

growth rates. The constant-pH experiments allow us to differentiate between the effects of CO2

and on growth rate. CO2demonstrates a good correlation with growth rate in both

constant-pH experiments, whereas the influence of on growth rate is more variable(Fig.2a,b), suggesting that CO2is the principal factor responsible for growth inhibition below a[CO2] of c. 7.5 molkg

1(Fig.2b). No effect of pH on growth rate was observed in the constant-

pH treatments (7.74 and 8.34). However, at constant CO2, growth rates are significantly lower at

pH 7.58 than at pH 7.83 (Ppost-hoc= 0.009), which cannot be explained by a decrease in [CO2] or [

] (Fig.2a,b). Thus, below pHf7.74, [H+] appears to have a direct negative influence on

growth rate.

Figure 2. Physiological response parameters forEmiliania huxleyiin relation to [ ] (leftcolumn) and [CO2] (right column). (a, b) Growth rates; (c, d) particulate organic carbon (POC)

production; (e, f) C : N ratio; (g, h) particulate inorganic carbon (PIC) production. Black circles,

constant pHf= 7.74; red circles, constant pHf= 8.34; triangles, constant CO2. Vertical error barsdenote the standard deviation of three replicates. Horizontal error bars show the mean change in [

] or [CO2] (mean of triplicates) from the beginning to the end of the experiments.

Particulate organic carbon production rates in both constant-pH experiments were highly

sensitive to and CO2when the concentrations dropped below c. 2000 and 10 molkg1

,respectively (Fig.2c,d). The rates appear to correlate best to CO2at concentrations < c.

5 molkg1

, although there are limited data points in this range. At a constant CO2, the lowest

treatment also showed significantly lower POC production rates than at intermediate(Ppost hoc= 0.002, Fig.2c). At concentrations > c. 2000 mol kg

1POC production

rates display a slight but significant decrease of c. 20% at a constant pHfof 8.34 and 10% at a

constant pHfof 7.74 up to the highest concentrations (Fig.2c; pH 8.34,Ppost hoc< 0.001;pH 7.74,Ppost hoc(MC) = 0.004). In summary, POC production showed no clear overall

correlation with any of the carbonate chemistry parameters, but appears to be driven by CO 2in
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the very low CO2range (< c. 5 mol kg1

) and decreased by at concentrations> 2000 mol kg

1.

At low DIC, C : N ratios decreased significantly in the constant-pH experiments, which appear to

be driven primarily by a reduction in CO2(Table S2). This is supported by no significant

changes at constant CO2(Table S2). Differences in C : N between treatments probably reflectvariable cellular amounts of nitrogen-free relative to nitrogen-rich organic compounds. As 40

60% of the total cellular carbon inE. huxleyiis in the form of lipids (Fernandez et al.,1994), the

decrease in C : N is likely to reflect reduced assimilation of lipids and polysaccharides at lowDIC.

Calcification is primarily driven by and does not act as a CCM

Calcification rates (PIC production) increased similarly in all experiments with increasing [

] (Fig.2g). Maximum calcification rates at constant pHfvalues of 8.34 and 7.74 were

identical, but were reached at lower CO2and higher at a constant pH

fof 8.34, indicating

that calcification is not primarily dependent on [CO2] or [ ] (Figs2h, S1h). A limited

control of calcification by [CO2] is further supported by the decrease in calcification rates found

in the constant-CO2experiment. Here, calcification rates would have to remain constant if [CO2]

were of primary importance. No signs of calcification could be found in the two lowest

treatments at a constant pHfof 7.74 and in two replicates of the lowest treatment atconstant CO2(Table2). In these treatments, calcite saturation (calcite) is < 0.31, so post-

production dissolution could potentially have taken place. However, cross-polarized light

microscopy and scanning electron microscopy show the absence of internal coccoliths under

these conditions, indicating that the production of coccoliths is inhibited (Bach et al.,2012).

Table 2. Presence or absence of Emiliania huxleyicoccoliths from SEM investigations

Experiment (mol kg1) H+(nmol kg

1) Coccoliths found?

1. Table showing SEM analysis of individual replicates of treatments where particulateinorganic carbon (PIC) production was < 0.5 pg per cell d

1. Note that coccoliths were

found in all treatments and replicates not listed in this table.2. a

Cell concentrations were higher in this replicate at the end of the experiment (76 000

compared with 36 000 cell ml

1

in first replicate). This caused a stronger decrease in [] and [H

+].

Constant pHf= 7.74

200 18.2 No

160 18.2 No

200 18.2 No
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300 17.8 No

330 17.8 No

320 17.8 No

Constant pHf= 8.34

170 4.8 Yes

160 4.7 Yes

170 4.7 Yes

Constant CO2

520 30.9 No

510 26.3 No

490 22.9 Yesa

Table 3. Assumptions within the conceptual model for inorganic carbon uptake in Emiliania huxleyi

Assumption Basis of assumption Reference

Cellular organelle locationand approximate relative

sizes

Transmission electron micrographsM. A. Gutowska et al.

(unpublished)

CO2principal external

inorganic carbon source

for photosynthesis

14C labeling studies; membrane inlet mass

spectrometry measurements

Sikes et al. (1980);

Schulz et al. (2007)

Increasing over CO2

usage for photosynthesis

at low CO2

Membrane inlet mass spectrometry identifies

increasing : CO2uptake ratio for cells

acclimated to low-CO2conditions; up-regulation ofAEL1 at low CO2

Rost et al. (2003); this

study

pool and dual

function of AEL1 in

calcification and carbon-

concentrating mechanism

AEL1 previously shown to have a role in calcification;

up-regulation at low dissolved inorganic carbon (DIC)

Mackinder et al.

(2011); this study
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(CCM)

Up-regulation of carbonic

anhydrases (CAs) at low

DIC

Three out of five investigated CAs showed an up-

regulation in expression at low DICThis study

Location of CA at plasma

membrane

Presence of a putative membrane anchor;

localization of a dinoflagellate CA to the plasma

membrane; strong up-regulation at low CO2has also

been demonstrated in TWCA1, a CA from

Thalassiosira weissflogii; up-regulation at low DIC

Soto et al. (2006);

Lapointe et al. (2008);

McGinn & Morel

(2008); this study

Up-regulation of

extracellular CA at low DIC

Increased extracellular CA activity at low DIC/high

pH; up-regulation of CA at low DIC

Nimer et al. (1997);

this study

Localization of CA to the

chloroplast

Two CAs from diatoms have been shown to localize

to the chloroplastspecifically the pyrenoid; CA

activity in the stroma chloroplast fraction of the

coccolithophore Pl

references coccolithophores

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