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Regulatory branch points affecting protein and lipidbiosynthesis in the diatom Phaeodactylumtricornutum

L. Tiago Guerra a,b, Orly Levitan c, Miguel J. Frada c,1, Jennifer S. Sun a,Paul G. Falkowski c, G. Charles Dismukes a,*aWaksman Institute of Microbiology, Rutgers, The State University of New Jersey, 190 Frelinghuysen rd.,

Piscataway, NJ 08854, USAbDepartment of Chemistry, Princeton University, Princeton, NJ 08544, USAcEnvironmental Biophysics and Molecular Ecology Program, Institute of Marine and Coastal Sciences, Rutgers,

The State University of New Jersey, New Brunswick, NJ 08901, USA

a r t i c l e i n f o

Article history:

Received 18 March 2013

Received in revised form

14 September 2013

Accepted 2 October 2013

Available online xxx

Keywords:

Microalgae

Biofuels

Nitrogen metabolism

GS/GOGAT

Lipid

Carbon partition

Abbreviations: GS, glutamine synthetase;glutamine; GLU, glutamate; AKG, a-ketoglut* Corresponding author. Tel.: þ1 848 445 678E-mail address: [email protected]

1 Current address: Department of Plant Sc

Please cite this article in press as: Guerrdiatom Phaeodactylum tricornutum, Bioma

0961-9534/$ e see front matter ª 2013 Elsevhttp://dx.doi.org/10.1016/j.biombioe.2013.10.

a b s t r a c t

It is widely established that nutritional nitrogen deprivation increases lipid accumulation

but severely decreases growth rate in microalgae. To understand the regulatory branch

points that determine the partitioning of carbon among its potential sinks, we analyzed

metabolite and transcript levels of central carbon metabolic pathways and determined the

average fluxes and quantum requirements for the synthesis of protein, carbohydrates and

fatty acid in the diatom Phaeodactylum tricornutum. Under nitrate-starved conditions, the

carbon fluxes into all major sinks decrease sharply; the largest decrease was into proteins

and smallest was into lipids. This reduction of carbon flux into lipids together with a

significantly lower growth rate is responsible for lower overall FA productivities implying

that nitrogen starvation is not a bioenergetically feasible strategy for increasing biodiesel

production. The reduction in these fluxes was accompanied by an 18-fold increase in

a-ketoglutarate (AKG), 3-fold increase in NADPH/NADPþ, and sharp decreases in glutamate

(GLU) and glutamine (GLN) levels. Additionally, the mRNA level of acetyl-CoA carboxylase

and two type II diacylglycerol-acyltransferases were increased. Partial suppression of ni-

trate reductase by tungstate resulted in similar trends at lower levels as for nitrate star-

vation. These results reveal that the GS/GOGAT pathway is the main regulation site for

nitrate dependent control of carbon partitioning between protein and lipid biosynthesis,

while the AKG/GL(N/U) metabolite ratio is a transcriptional signal, possibly related to redox

poise of intermediates in the photosynthetic electron transport system.

ª 2013 Elsevier Ltd. All rights reserved.

GOGAT, glutamine oxoglutarate aminotransferase; GDH, glutamate dehydrogenase; GLN,arate.6; fax: þ848 445 5735.(G.C. Dismukes).

iences, Weizmann Institute of Science, P.O. B. 26, Rehovot 76100, Israel.

a LT, et al., Regulatory branch points affecting protein and lipid biosynthesis in thess and Bioenergy (2013), http://dx.doi.org/10.1016/j.biombioe.2013.10.007

ier Ltd. All rights reserved.007

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http://dx.doi.org/10.1016/j.biombioe.2013.10.007




1. Introduction

The appropriation of photosynthetically fixed carbon in

microalgae is strongly affected by environmental conditions.

Under optimal growth conditions, most fixed carbon is allo-

cated to proteins [1]. In contrast, under suboptimal conditions,

especially nitrogen limitation, cells divert most of the fixed

carbon into nitrogen deficient compounds such as lipids and/

or carbohydrates, at the expense of growth [2]. The tradeoff

between growth rate and lipid content has been one of the

biggest factors preventing the industrial production of

algal biodiesel at prices competitive with fossil sources [3].

Hence, considerable effort has gone into understanding the

Fig. 1 e Model of metabolic pathways and branching points aff

starvation. Relevant branching points are signaled in parenthes

enzymatic steps are color coded according to the fold change of

comparison to the control according to the legend. The names o

next to the corresponding step. Multistep biosynthetic pathway

arrow color refers to the DGAT step only. The chrysolaminarin s

chloroplast. Here it is represented only the cytosol pathway for s

localized in the mitochondrion, cytosol or plastid. Here they we

simplicity. Gene abbreviations are given in Table S1 and metab

Photosystem, FD e ferredoxin.

Please cite this article in press as: Guerra LT, et al., Regulatory bdiatom Phaeodactylum tricornutum, Biomass and Bioenergy (2013),

molecular mechanisms that determine the fate of photosyn-

thetically fixed carbon under stress conditions [2]. In this

paper we use a metabolic analysis to identify the regulatory

branch points in the ‘carbon decision tree’ under nitrogen

limitation in a marine diatom.

Inspection of the intermediate metabolism of eukaryotic

algae (Fig. 1) reveals several potential regulatory branch points

that could control the fate of carbon. Pyruvate (Pyr) is the first

key intermediate in this process. This 3-carbon molecule can

take several alternative paths in themetabolic network which

will determine if the carbon is deposited into amino or fatty

acids (Fig. 1). Pyruvate can be directly aminated to generate

alanine and thus proteins (denoted as step (1) in Fig. 1). More

commonly however, pyruvate undergoes decarboxylation to

ecting lipid biosynthesis in P. tricornutum under nitrogen

is and described in the introduction. Metabolites and

metabolite abundance or mRNA in the eNOL3 condition in

f the enzymes responsible for relevant reactions are given

s are noted by broken arrows. For TAG biosynthesis the

ynthesis pathway may happen in the cytosol and/or in the

implicity. The GS/GOGAT cycle proteins are predicted to be

re represented only in the mitochondrion and cytosol for

olite abbreviations are given in the legend of Fig. 2. PS e

ranch points affecting protein and lipid biosynthesis in thehttp://dx.doi.org/10.1016/j.biombioe.2013.10.007



b i om a s s a n d b i o e n e r g y x x x ( 2 0 1 3 ) 1e1 0 3

form acetyl-CoA (AcCoA), (denoted as step (2) in Fig. 1). AcCoA,

the second key intermediate, can either undergo successive

oxidation in the TCA cycle or be used by acetyl-CoA carbox-

ylase (ACCase) to form malonyl-CoA (MaCoA), which is the

first committed intermediate in the synthesis of lipids [4]. If it

enters the TCA cycle it produces a-ketoglutarate (AKG), which

can be used for assimilation of ammonium via the glutamine

synthetase/glutamine oxoglutarate aminotransferase (GS/

GOGAT) cycle, yielding glutamine (GLN) and glutamate (GLU),

(step (3) in Fig. 1) [5]. GLU, the third intermediate, can also be

produced by the NAD(P)H-dependent amination of AKG via

the reversible glutamate dehydrogenase (GDH), step (4) in

Fig. 1. However the contribution of this pathway for assimi-

lation of ammoniumwas shown to be minor in relation to the

GS/GOGAT cycle as its Michaelis constant Km for ammonium

is 1000-fold higher than GS’s [5]. Thus, AKG is an essential

carbon source for the synthesis of glutamine (GLN) and

glutamate (GLU), from which many other amino acids and

cofactors are produced. Finally, two anapleurotic pathways

exist to replenish AKG in the TCA cycle: pyruvate may un-

dergo carboxylation to form oxaloacetate via step (5) in Fig. 1,

or AKG can be derived from the deamination of glutamic acid

by the catabolism of proteins via GDH in step (4). In conclu-

sion, there are at least five key carbon branch points that can

influence the supply of intermediates, and hence the fate of

carbon, all of which intersect in a small part of the metabolic

processes centered on pyruvate and the TCA cycle.

In eukaryotic microalgae, nitrate reductase (NR) is

responsible for the NAD(P)H dependent reduction of nitrate to

nitrite, and is sequentially coupled to ferredoxin-dependent

nitrite reductase (NiR) for production of ammonium which is

used in amino acid and protein synthesis (Fig. 1) [6]. Hence,

coordinated regulation of NR by several factors including the

cellular redox poise provides the initial mechanism for con-

trolling the conversion of intracellular nitrate for downstream

biosynthesis reactions [7]. The cellular redox poise has also

been implicated in controlling pathways of carbon meta-

bolism such as lipid biosynthesis [8].

Although phylogenetically distant from diatoms, cyano-

bacteria use AKG and GLN or GLU to report the C:N status of

the cell in real time [9,10]. The levels of these metabolites are

sensed by NtcA, a global nitrogen regulator that can function

as both a transcriptional activator and a repressor. For

instance, NtcA binds and activates the promoters of glnA

(encoding glutamine synthetase), the nir operon (nitrate up-

take) and icd (isocitrate dehydrogenase) while it also represses

transcription of gifA and gifB (encoding inactivating factors of

glutamine synthetase) [10].

Based on the logic of intermediate metabolism of acetyl-

CoA, Dunahay and coworkers (1996) tried to increase carbon

flow towards lipid biosynthesis by increasing the activity of

ACCase. In the first genetic transformation of a diatom, these

researchers overexpressed ACCase in Cyclotella cryptica [11].

The transformant strain had increased ACCase activity, but

the phenotype did not show any significant change in lipid

content [2]. Similar results were achieved when ACCase of

Arabidopsis thaliana was expressed in Brassica napus and Sym-

phytum tuberosum [12,13]. These results indicate that ACCase

does not control the flux of carbon into lipids, thus, leaving the

regulatory branch point for lipid biosynthesis poorly defined.


In the present study we sought to understand the mecha-

nism of carbon partitioning under nitrate depletion in the ma-

rine diatom Phaeodactylum tricornutum. We probed changes in

intracellularmetabolite pools and transcripts of genes involved

in central carbon metabolism. For this, we compared cells

grown under nitrate replete (control), nitrate starved (�NO�3 ),

and nitrate replete with tungstate (W). In the absence or limi-

tation for molybdenum, tungsten can substitute in the active

site of nitrate reductase, rendering the enzyme catalytically

inactive [14]. Our results on the influence of nitrate assimila-

tion/deprivation on terminal products in P. tricornutum reveal

that regulation occurs at the nexus of the TCA/(GS/GOGAT)/

GDHpathways, similar to cyanobacteria, and is consistent with

the multi-functional role of AKG in microbial phototrophs.

2. Materials and methods

2.1. Culturing system and sampling

P. tricornutum was obtained from the National Center for Ma-

rine Algae and Microbiota (NCMA, formerly CCMP) accession

Pt1 8.6 (clone CCMP 632) was maintained in an artificial sea

water medium [15] supplemented with F/2 nutrients [16] and

buffered with 2 mmol L�1 Tris to pH 8 (hereafter called F/2).

Cultures were grown at 18 �C, with air bubbling, under

continuous white LED light at a photon flux density of

200 mmol m�2 s�1. Pre-inocula were grown with NaNO3

(0.88 mmol L�1) as the sole nitrogen source. Exponentially

growing pre-inocula were centrifuged (5500 g, 10 min) and

washed twice with nitrate-free F/2 medium and inoculated in

triplicate at a concentration of 2.5� 105 cellsmL�1 into fresh F/

2 medium with nitrate (0.88 mmol L�1, control), F/2 medium

without any nitrogen source (�NO�3 ) and F/2 medium with

nitrate (0.88 mmol L�1) and sodium tungstate (0.88 mmol L�1,

W) replacing molybdate in the trace metal mixture. All cul-

tures were grown for 3 days in the same conditions as above.

Known numbers of cells were then filtered, flash frozen in

liquid nitrogen, and kept at �80 �C until analysis. The only

exception was the metabolite extraction which was per-

formed on fresh samples.

2.2. Cell number, cell volume and chlorophylldetermination

Cell numbers were measured with a Coulter counter multi-

sizer 3 (Beckman Coulter Inc, Fullerton, CA, USA). After 3 days

of growth, cell volume (approximated to a prolate spheroid)

was determined by measuring the length and width of 100

representative cells of each condition with the image analysis

software imageJ (http://imagej.nih.gov/ij/) [17]. Chlorophyll a

was measured from a known amount of cells after filtration

andmechanic homogenization in a cold mixture of acetone at

90% volume fraction [18].

2.3. Fatty acid methyl esters and triacylglycerolsdetermination

For measuring total fatty acids content we transesterified the

cells’ fatty acids to get fatty acidsmethyl esters (FAMEs). 5� 107


http://imagej.nih.gov/ij/




cells were filtered onto 25 mm GF/F filters (Whatman) and

subsequently extracted and transesterified in a single step as

reported previously [19]. Analysis of the hexane fraction con-

taining the FAMEs was performed by gas chromatography as in

Ref. [14]. Helium was used as the carrier gas at 179 kPa.

Triacylglycerols (TAGs) were extracted with methyl tert-

butyl ether from 5 � 107 cells collected on GF/F filters [20]. TAG

estimationwas performed by thin layer chromatography (TLC).

Briefly, after resuspension of dried samples in a known volume

of chloroform:methanol:water mix (60 mL:30 mL:4.5 mL),

samples were spotted on silica gel 60 10 cm � 20 cm TLC

plates (Millipore) with hexane:diethylether:acetic acid mix

(80 mL:20 mL:2 mL) as running solvent. The plates were

sprayed with 50 mg L�1primuline in an 80% volume fraction

acetone solution, dried for several hours and the TAGs were

visualized under a UV lamp. ImageJ [17] was used to quantify

the intensity of the spots which were compared to spots of

known amounts of a commercial mono-, di-, and triglyceride

standard mix (1787, SigmaeAldrich).

2.4. Carbohydrate content determination

5 ∙107 cells were collected in 1.2 mm pore size polycarbonate

filters (Millipore, Billerica, MA, USA). Total carbohydrate levels

(intracellular reducing pentoses and hexoses) were measured

by reaction with anthrone [21] with a procedure adapted to

diatoms [22].

2.5. Total protein determination

For total protein determination, 2� 107 cells were filtered onto

1.2 mm pore size polycarbonate filters and re-suspended in 1�denaturing extraction buffer (300 mL), containing 140mmol L�1

Tris base, 105mmol L�1 TriseHCl, 0.5 mmol L�1 EDTA, 20 g L�1

lithium dodecyl sulfate, 10% volume fraction glycerol, and

protease inhibitor (1 mL:200 mL, P2714, SigmaeAldrich). After

re-suspension, the samples underwent two cycles of freezing

in liquid nitrogen and thawing with a Microson ultrasonic cell

disruptor XL (Qsonica, Newtown, CT, USA). After pelleting

insoluble cell debris total protein concentration was

measured using amodified Lowry assay (Bio-Rad DC 500-0111,

Hercules, CA, USA). Bovine gamma globulin was used as the

protein standard.

2.6. Metabolite extraction and LC-MS/MS

Intracellular metabolite extraction and analysis was made via

liquid chromatography mass spectrometry (LC-MS/MS).

2 � 107 cells were filtered onto a 0.45 mm pore size nylon filter

(Pall Corporation, Port Washington, NY, USA) and immedi-

ately cold extracted [23]. Samples were then analyzed on a

1200-series Agilent LC system coupled to an Agilent 6410 Tri-

ple Quadrupole (QQQ) mass spectrometer (Agilent Technolo-

gies, Santa Clara, CA, USA), using previously optimized

Selective Reaction Monitoring parameters [23]. Ion-pairing

chromatography was employed using a Pursuit XRs3 C18

(50 mm � 2 mm, Varian, Palo Alto, CA, USA). Mobile phase A

consisted of 10 mmol L�1 tributylamine (pairing agent),

11 mmol L�1 CH3OOH while mobile phase B was pure meth-

anol. The chromatography program of mixture of mobile


phase B into mobile phase A was as follows: 0 min (Volume

fraction of B: 0%), 8 min (Volume fraction of B: 40%), 10 min

(Volume fraction of B: 40%), 12.5 min (Volume fraction of B:

90%), 18 min (Volume fraction of B: 90%), 18.1 min (Volume

fraction of B: 0%). A 6min post-run equilibration period at 0%B

was used. Intracellular metabolite pools were quantified by

comparison to a calibration curve established by spiking

a standard mixture of the target compounds at

10 nmol L�1e10,000 nmol L�1 into a sample background and

determining the per-metabolite linear response of the in-

strument signals to the expected concentrations.

2.7. Metabolic analysis and real time qPCR

Genes that are involved in lipid biosynthesis and central car-

bon pathways, were selected from the literature [24] and from

both the genome (http://genome.jgi-psf.org/Phatr2/Phatr2.

home.html) [25] and the expressed sequence tag database

(http://www.diatomics.biologie.ens.fr/EST3/seq.php) [26,27].

The prediction of localization of target genes was made using

Mitoprot [28], TargetP1.1 [29] and signalP4.0 [30] online tools.

Total RNAwas extracted from 1� 108 cells collected on 1.2 mm

pore size polycarbonate filters with an RNAeasy plant mini kit

(Qiagen, Venlo, Netherlands). Ambion� Turbo� DNase (Life

Technologies, Carlsbad, CA, USA) was used to remove DNA

contamination. PCR was used before cDNA generation to

confirm that there was no DNA contamination. Total RNA

quantification and quality assessment was made spectro-

photometrically with a Nanodrop 1000 (Thermo Scientific).

cDNA generation was done using oligodT as primers and the

SuperScript� III reverse transcriptase kit (Life Technologies).

The resulting cDNA-generation reaction mixture (1 mL) was

directly used as the template for qPCR. Primers for target

genes were constructed with NCBI Primer-BLAST (http://

www.ncbi.nlm.nih.gov/tools/primer-blast/), designed to

anneal near to the 30 end of the mRNA (Table S1). Standard

molecules of known molecular weight, for copy number

calculation, were generated by cloning each amplicon onto a

TOPO�TA (Life Technologies) cloning kit. qPCR was made

using the Applied Biosystems SYBR� Green PCR Master mix

(Life Technologies) on a Mx3000P QPCR system (Agilent

Technologies). All standard curves had at least 5 points,

covered 5 orders ofmagnitude and had an R2> 0.94. Each qPCR

amplification on biological samples was then compared to its

specific calibration curve to calculate the gene copy number

present. Calculated copy numbers were normalized to total

RNA extracted.

2.8. Quantum requirement and fluxes calculations

Carbon fluxes (pmol cell�1 d�1) into proteins, carbohydrates

and fatty acids were calculated according to the equation

N � m ¼ (dN/dt), where N is moles of carbon in protein, car-

bohydrate or fatty acids measured after 3 days, m the cellular

specific growth rate and dN/dt the average flux. The average

carbon mass fraction in proteins (44%) was calculated using

the mass of carbon per mass of amino acid normalized by the

relative abundance of each amino acid according to the ge-

netic code. Themass fraction of carbon in carbohydrates (40%)

was calculated using glucose as a standard. Themass fraction


http://genome.jgi-psf.org/Phatr2/Phatr2.home.html

http://genome.jgi-psf.org/Phatr2/Phatr2.home.html

http://www.diatomics.biologie.ens.fr/EST3/seq.php

http://www.ncbi.nlm.nih.gov/tools/primer-blast/

http://www.ncbi.nlm.nih.gov/tools/primer-blast/




of carbon in fatty acids (76%) was calculated using themass of

carbon per mass of fatty acid normalized by the abundance of

each fatty acid measured in this study. The quantum

requirement for each pool (4�1) was calculated according to

[31] using the values for a* and Ek values reported in Ref. [14].

3. Results

3.1. Physiological responses to nitrate limitation

The control condition presented a growth rate of

0.86 d�1 � 0.04 d�1, while the growth rate of the eNO�3 and the

W cultures were 0.36 and 0.76-fold of the control cultures,

respectively (Table 1). Chlorophyll a (Chl a) content, which

generally reflects total biosynthetic nitrogen accumulation at a

constant irradiance, was lower for both eNO�3 and W cultures

by 0.83 and 0.50-fold, respectively, vs. the control condition

(0.12 pg� 0.02 pg cell�1) (Table 1). The volume of the cells in the

eNO�3 cultures did not change significantly in relation to the

control, while the ones in the W condition increased their

volume by approximately 1.18-fold (p-value < 0.01).

Regarding themain carbon sinks, the eNO�3 cultures, had a

1.21-fold increase in levels of FA per cell accompanied by a

0.74-fold decrease in proteins and a 0.29-fold decrease in the

carbohydrates relative to the control. In the W condition, the

FA per cell increased by 1.14-fold, while the protein levels

decreased by 0.40-fold and the total carbohydrate levels did

not change relative to the control. TAGs constituted a slightly

larger mass fraction of the total measured FA in the eNO�3

(93%) and W (82%) compared to the control (76%) (Table 1).

3.2. Changes in intracellular metabolite pools inresponse to nitrate limitation

In order to obtain further insight into the metabolic state of

cells, the intracellular metabolite pools were measured by

Table 1 e Physiological parameters of P. tricornutum after3 days of growth in nitrate replete (control), nitratelimited (LNOL

3 ) and tungstate (W) conditions. Inparentheses are the values as a fraction of the control setto 100. Here and elsewhere, the mean and one standarddeviation of biological triplicates are shown.

Control �NO�3 W

m (d�1) 0.86 � 0.04 (100) 0.31 � 0.01 (36) 0.66 � 0.03

(76)

Cell volume (mm3) 74.0 � 22.9 (100) 70.8 � 23.4 (96) 87.6 � 33.3

(118)

Chl a (pg cell�1) 0.12 � 0.02 (100) 0.02 � 0.01 (17) 0.06 � 0.01

(50)

Protein (pg cell�1) 13.6 � 0.1 (100) 3.6 � 0.6 (26) 8.2 � 0.6 (60)

Carbohydrate

(pg cell�1)

7.7 � 0.3 (100) 5.5 � 0.9 (71) 8.2 � 0.7

(106)

FAMEs (pg cell�1) 2.9 � 0.1 (100) 3.5 � 0.09 (121) 3.3 � 0.04

(114)

Mass fraction of

FAMEs as TAG

76 � 4 93 � 6 82 � 2

RNA (pg$cell�1) 0.06 � 0.01 (100) 0.02 � 0.01 (33) 0.14 � 0.02

(233)


LC-MS/MS (Fig. 2). The eNO�3 condition produced an overall

decrease of several metabolites in comparison to the control.

Most significantly, the nitrogen carriers for biosynthesis, GLU

andGLNwere reduced 7 and 55-fold, respectively, in theeNO�3

case compared to the control condition. As these metabolites

are formed from AKG and ammonium, we looked at in-

termediates of the TCA cycle. The AKG level increased by

18-fold compared to the control condition, while other TCA

metabolites downstream such as succinate increased nearly

3-fold, while fumarate and malate remained unchanged.

These data provide definitive evidence for control occurring at

(GS/GOGAT)/GDH (steps (3) and (4) in Fig. 1).

The large increase in AKG suggests either increased flux

into AKG from the upstream portion of the TCA cycle, greater

input through amino acid catabolism via GDH, or decreased

output of AKG into the GS/GOGAT pathway. To further

constrain the source of AKG, we examined the levels of the

TCA metabolites upstream prior to the typically irreversible

step at isocitrate dehydrogenase. This analysis revealed a

3-fold decrease in levels of citrate, acetyl-CoA (AcCoA) and

pyruvate under eNO�3 condition, suggestive of either faster

depletion or reduced input into these pools. AcCoA is the

immediate precursor to malonyl-CoA (MaCoA) for FA biosyn-

thesis. MaCoA was significantly decreased (10-fold), in the

eNO�3 condition.

As expected, the total pool sizes of adenosine phosphates

and both pyridine nucleotide pairs were also highly decreased

in the eNO�3 case (Fig. 2). However, the adenylate cell energy

charge (CEC) decreased, from 0.74 � 0.03 in the control to

0.63 � 0.06 in the eNO�3 condition (p-value < 0.05) (Table 2).

Regarding the cellular pyridine nucleotide redox poise, the

NADH/NADþ ratio was unchanged, while the NADPH/NADPþ

ratio increased 3-fold in the eNO�3 condition vs. the control (p-

value <0.01) (Table 2). This significant increase in the ratio of

NADPH/NADPþ is consistent with lower nitrate reduction to

ammonium and lower activity of other sinks such as the GS/

GOGAT cycle and carbon fixation.

In general, theW condition presented fewer changes in the

metabolite pools than the eNO�3 condition in comparison to

the control (Fig. 2). The levels of AKG, AcCoA, MaCoA, aden-

osine phosphates, NADH and NADþ were unchanged, while

the level of NADPþ decreased by about 60% relative to the

control. The CEC and the NADH/NADþ redox poise, were also

unchanged for the W condition in comparison to the control.

The GLU and GLN levels decreased approximately 1.7 and

12-fold, respectively, indicating some degree of nitrogen lim-

itation. The NADPH/NADPþ redox poise showed a statistically

significant increase, albeit much smaller in magnitude than

that of the eNO�3 condition (Table 2).

3.3. mRNA abundance of genes of the central carbonmetabolism in response to nitrate limitation

In order to relate the metabolite data to the genetic response

of cells, themRNA abundance of key genes involved in the key

branch points were measured by real-time RT-qPCR (Fig. 3).

The total RNA (ribosomal þ messenger þ transfer) measured

in the eNO�3 condition, was only 44% of that of the control

(p-value < 0.01, n ¼ 6). In contrast, the total RNA levels

extracted from the W condition were 2.3-fold higher than




Fig. 2 e Ratio of abundance of key cellular metabolites at

steady state growth determined by LC-MS/MS. The

abundance of each metabolite in the control condition was

used as reference and set to 1. **Student t test p-

value < 0.01, *Student t test p-value < 0.05. AA e amino-

acids; FA e fatty acids; CEC e adenylate cell energy charge;

Pyr Nuc e Pyridine nucleotides; UDP-Gluc e UDP-glucose;

G1P e Glucose-1-phosphate; R5P e Ribulose-5-phosphate;

X5P e Xilulose-5-Phosphate; F6P e Fructose-6-Phsphate;

FBP e Fructose bis-phosphate; DHAP e Dihydroxyacetone;

GAP e Glyceraldehyde-3-phosphate; 3 PG e 3-

phosphoglycerate, PEP e Phosphoenolpyruvate; AcCoA e

Acetyl-CoA; AKG e a-ketoglutarate; GLN e Glutamine; GLU

e Glutamate; MaCoA e Malonyl-Co; AMP, ADP, ATP e

adenosyl-(mono,di,tri)phosphate; NADD, NADH e

Table 2 e Adenylate Cell Energy Charge (CEC) andPyridine nucleotide ratios in the 3 conditions tested.Adenylate CEC was calculated according to the formula([ATP] D ½[ADP])/([AMP] D [ADP] D [ATP]). *Student t-testp-value < 0.05.**Student t-test p-value < 0.01.

Control �NO�3 W

Adenylate CEC 0.74 � 0.03 0.63 � 0.06* 0.75 � 0.06

NADH/NADþ 1.22 � 0.21 1.16 � 0.10 1.27 � 0.06

NADPH/NADPþ 1.2 � 0.06 3.7 � 0.9** 1.6 � 0.2*



those of the control condition (p-value < 0.01, n ¼ 6) (Table 1).

For all 18 genes tested, there was a general increase in the

abundance of their mRNA levels in both conditions compared

to the control. In the eNO�3 condition, genes involved in TCA

cycle were amongst the ones that presented highest in-

creases. Specifically, the highest increase (65-fold) was

observed in isocitrate dehydrogenase (Isocitrate DH)mRNA. In

respect to lipid biosynthesis genes, a 35-fold increase in the

ACCase mRNA abundance was observed in the eNO�3 condi-

tion, while the mRNA levels of diacylglycerol-acyltransferase

(DGAT)2B and DGAT2D were increased 3- and 8-fold, respec-

tively, in comparison to the control. The W condition gener-

ally had higher fold changes than those of the nitrogen-

starved condition. The mRNA levels of isocitrate dehydroge-

nase increased 90-fold, ACCase increased 28-fold, while the

DGAT2B and DGAT2D increased 8 and 20-fold respectively. A

very large increase in mRNA abundance of nitrate reductase

(NR) was also observed in response to nitrogen starvation (26-

fold) and W conditions (248-fold).

4. Discussion

4.1. GS/GOGAT/GDH are important regulatory branchpoints

The results of this study strongly suggest that the key branch

point in lipid biosynthesis in P. tricornutum centers on the

metabolism of AKG (Fig. 1). In the eNO�3 condition, the general

decrease in metabolite pools is consistent with lower overall

metabolic activity due to the global translational limitation

this nitrogen deprivation inevitably imposes. Nonetheless, the

changes in the levels of glutamate (GLU), glutamine (GLN), and

a-ketoglutarate (AKG) indicate that the GS/GOGAT/GDH

branch points, steps (3) and (4) of Fig. 1, the shift the flux of

carbon from protein into lipid biosynthesis. The observed

large decrease in the pool sizes of GLU and GLN, in parallel

with the 18-fold increase in AKG and 3-fold increase in

NADPH/NADPþ ratio, are consistent with an arrest of the

GS/GOGAT cycle due to ammonium depletion at step (3). The

18-fold increase in AKG is likely also due to recycling of amino

acids from protein catabolism, including chlorophyll associ-

ated proteins [a large decrease in chlorophyll a and protein

levels were observed in this condition, (Table 1)] through the

GDH pathway. This pathway is readily reversible and, because

Nicotinamide adenine dinucleotide; NADPD, NADPH -

Nicotinamide adenine dinucleotide phosphate.




Fig. 3 e mRNA abundances of target genes as measured by

real-time RT-qPCR. Logarithm of the ratio of change of

mRNA abundance of target genes in the nitrate depleted

and tungstate conditions relative to the control condition

whose copy number was set to 1. The calculated copy

number for each gene was normalized to total RNA. Gene

name abbreviations are given in Table S1.


of the high Km for ammonium, it operates primarily to convert

GLU to AKG. Analogously, this pathwaywas suggested to have

a mainly catabolic role in Chlamydomonas reinhardii [32].

Interestingly, the mRNA level of the icd gene, which codes

for isocitrate DH (responsible for synthesizing AKG) was

increased 65-fold under nitrate deprivation. Yet, it remains to

be clarified if the higher mRNA levels observed in our experi-

ments are translated into higher protein levels. Our results

strongly suggest that blockage of the GS/GOGAT branch point

due to low ammonium availability is responsible for the

decrease in protein content observed. The system attempts to

compensate for this by elevating the icd gene abundance,

attempting to make more AKG, which is not in shortage. As a

consequence, the system redirects newly fixed carbon into

lipids (via AcCoA and MaCoA) which requires no nitrogen for

its biosynthesis and, in addition, is a more effective way to

relieve the stronger reducing intracellular environment [3].

The observed redirection of carbonmetabolism into FA and

TAGs under eNO�3 conditions is consistent with the increases


in the mRNA levels of ACCase, DGAT2B and DGAT2D, which

are key steps for FA and TAG biosynthesis pathways [33,34].

Increased mRNA levels of the chloroplast ACCase were also

recently reported in nitrogen depleted P. tricornutum cultures,

albeit with a lower magnitude [35].

The replacement of Mo by W generated an intermediary

response between the control and the eNO�3 condition, likely

due to the incomplete inactivation of NR activity. Nitrogen

limitation in this condition was apparent by the decrease in

GLN and GLU levels which are in agreement with the 40%

lower proteins per cell, relative to the control. The AKG level

was, however similar to that of the control. This result is

consistent with an incomplete inactivation of NR activity by

W, which would still allow some nitrogen assimilation by the

GS/GOGAT cycle, preventing the accumulation of AKG.

The FA and TAGs per cell were also increased in the W

conditions, but not as much as in nitrogen-starved. This is

consistent with the slight but significant increase in the

NADPH/NADPþ ratio observed and with an incomplete NR

inactivation by W. Lastly, the changes in mRNA levels of iso-

citrate DH, NR, ACCase, DGAT2B and DGAT2D were, in gen-

eral, larger than what was observed in nitrogen starved

conditions. This result is somewhat unexpected, as W causes

only amild nitrogen limitation. Together with the fact that we

observed a 2.3-fold increase in total RNA in the W condition

and a 1.18-fold increase in cell volume, relative to the control,

this indicates that there are unspecific effects of tungstate in

cells. Furthermore, a specific deregulation of nitrate reductase

mRNA by tungstate was previously reported in the higher

plant Nicotiana tabacum [36]. RNAi NR knock-downs could

further clarify the importance of this enzyme on the fate of

carbon, circumventing the unspecific effects of tungstate in

cellular physiology.

4.2. Putative nitrogen sensing mechanisms in diatoms

Taking the eNO�3 and the W conditions together, we suggest

that the cell senses the ratio of AKG to GLN or GLU (GL(N/U)) in

addition to its overall redox state. FA and TAG synthesis have

a higher NADPH requirement in comparison with carbohy-

drates and proteins. Consistent with this requirement, the

ratio of NADPH/NADPþ, which is generally tightly regulated,

was increased 3-fold relative to the control, implying a

significantly more reducing intracellular environment,

including a more reduced plastoquinone (PQ) pool. The con-

trol of microalgal nuclear genes involved in photosynthesis,

carbon fixation, carbohydrate metabolism and nitrogen

assimilation (including nitrate reductase) has been previously

proposed to be controlled, at least in part, by the redox state of

the PQ pool [7,37,38]. The increase in the NADPH/NADPþ ratio

observed could then, not only facilitate lipid biosynthesis as a

substrate, but also be a sign of a reduced PQ pool that can

regulate nuclear genes for lipid biosynthesis.

Under mild nitrate limitation the decrease in the pools of

GLN and GLU are responsible for the AKG/GL(N/U) ratio in-

crease. However, under nitrate starvation both the increase of

AKG and the decrease of GL(N/U) are responsible for the large

ratio increase. In N. tabacum leaves, it was suggested that the

transcription level of NR was antagonistically controlled by

AKG (activator) and GLN (repressor). The ratio of these





metabolites was proposed to be more important for nitrogen

sensing than their individual concentrations [39]. In cyano-

bacteria, similar changes in AKG, GLU and GLN concentration

were reported to take place upon nitrogen limitation [9]. These

metabolites signal the nitrogen availability and start a cascade

of responses, through the global nitrogen regulator NtcA, that

leads to the increase in expression of several genes including

isocitrate DH, NR, GS/GOGAT and several nitrate transporters

[10]. Interestingly, both isocitrate DH and NR mRNA were also

over-represented in our experimental conditions, and there is

expressed sequence tag indication that the mRNA levels for

nitrate transporters and GS/GOGAT genes are also increased

under nitrogen limitation (Table S2). Our results suggest that a

similar nitrogen sensing mechanism that responds to the

AKG/GL(N/U) ratio may exist in P. tricornutum. A similar

conclusion was reached by analyzing the protein expression

levels in the diatom Thalassiosira pseudonana in response to

nitrogen starvation [40]. However, no ortolog of NtcA could be

found in the genome of P. tricornutum, implying that the signal

transduction between AKG/GL(N/U) and gene expression

must use a different protein or mechanism.

The general increase in mRNA abundance of nitrogen

assimilation genes seems contradictory to the arrest of the

GS/GOGAT cycle observed here under eNO�3 conditions,

although it is unclear if the increased mRNA levels are

translated into higher protein levels or increased enzymatic

activity (untested). In the diatom T. pseudonana these proteins

were observed to be increased in response to nitrogen star-

vation and it was suggested that they could serve, together

with the urea cycle, to more efficiently recycle nitrogen rich

compounds from catabolic processes [40]. This is similar to

what is observed in cyanobacteria which also have an urea

cycle [41].The physiological result of this putative sensing

mechanism is however, different e nitrate starvation leads to

accumulation of high levels of carbohydrates in cyanobacteria

[42], and to high lipid accumulation in diatoms.

4.3. Fluxes and quantum requirements of the maincarbon pools

The average flux into each major carbon pool as well as the

quantum requirement for placing carbon into each pool was

calculated as described in the methods section. These values

Table 3 e Quantum requirements and flux of carbon into for pand W conditions. The fluxes and 4L1 was calculated as descrcarbohydrate or lipid data from Table 1

Protein 4�1 (mol$mol�1)

Flux Cprotein (pmol cell�1 d�1)

Mass fraction fluxProteina

Carbohydrate 4�1 (mol mol�1)

Flux Ccarbohydrate (pmol cell�1 d�1)

Mass fraction flux Ccarbohydratea

Fatty acid 4�1 (mol mol�1)

Flux Cfatty acid (pmol cell�1 d�1)

Mass fraction fluxfatty acida

a Assumes that the sum of fluxes of carbon for protein, carbohydrate an


allow the quantification of the carbon that is placed into each

sink per unit time and the energetic cost of that flux. The flux

into each pool decreases exponentially with the increase of its

quantum requirements (Table 3, Fig. 4). This robust relation-

ship does not differentiate between carbon pools (protein,

carbohydrate or FA) or growth conditions (control, �NO�3 or

W). In the control condition, protein has the largest influx of

carbon and the lowest quantum requirement, while FA has

the highest quantum requirement and the lowest carbon

influx. In the eNO�3 condition, the quantum requirement for

all three carbon pools increased significantly relative to the

control: 7-fold for proteins, 2.6-fold for carbohydrates and 1.5-

fold for FA. This translates into a quantitatively related

reduction of total carbon flux into these pools: 10-fold for

proteins, 3.7-fold for carbohydrates and 2-fold for FA. This

overall lower total carbon flux is in agreement with the lower

growth rate and general lower levels of metabolite in-

termediates measured by LC-MS/MS. Despite the measured

increase in the mass fraction of carbon deposited into FA in

the eNO�3 condition relative to the control (41% vs. 20%,

respectively) the total carbon flux into FA is still 2-fold lower

than in the control. This lower total flux can also explain the

2.7 and 10-fold lower levels of AcCoA and MaCoA relative to

the control. Nonetheless, it is possible that the decrease of

AcCoA and MaCoA is being overestimated as the local con-

centration of AcCoA andMaCoA inside the chloroplast may be

considerably higher than the average cellular concentration.

This means that the global productivity of FA in a eNO�3 cul-

ture is severely diminished relative to the control, since both

the flux of carbon to FA per cell and the number of cells is

decreased. Thus, this treatment is not a good option for

biotechnological production of biodiesel.

The addition of W to the media affects mainly protein

biosynthesis and consequently cell growth. The quantum

requirement for protein synthesis increased 1.8-fold and

leads to a 2-fold decrease of carbon flux into proteins. The

quantum requirements for FA and carbohydrates were

similar to the control and thus the carbon fluxes into those

pools were also indistinguishable from those of the control

condition. This is consistent with the levels of AcCoA and

MaCoA that remained stable in this treatment, while GLU and

GLN levels decreased sharply as described above. Similarly to

the eNO�3 case, the lower levels of proteins and the lower

rotein, carbohydrates and fatty acids in the control, eNOL3

ibed in the methods section using the m, protein,

Control �NO�3 W

75 � 17 532 � 109 137 � 40

0.43 � 0.02 0.04 � 0.01 0.2 � 0.02

53 25 38

146 � 37 383 � 77 151 � 46

0.22 � 0.02 0.06 � 0.01 0.18 � 0.02

27 34 35

204 � 50 317 � 19 197 � 45

0.16 � 0.01 0.07 � 0.01 0.14 � 0.01

20 41 28

d fatty acid is equal to 100.




Fig. 4 e Relationship between carbon fluxes and quantum

requirements. Values of quantum requirements and fluxes

are indicated in Table 3. An exponential decay equation

was fitted to the points with a correlation coefficient of

0.97. The markers used for each condition are given in the

inset table.


growth rates will limit the productivity of cultures treated

with W in the presence of nitrate, even if the flux of carbon to

FA remains unchanged. The trends observed here for FAs

fluxes and accumulation are consistent with the ones

calculated previously under similar conditions [14]. However,

in that study these parameters were not calculated for pro-

teins or carbohydrates.

5. Conclusions

In conclusion, here we demonstrated that under nitrogen

starvation all fluxes of carbon into the major carbon sinks are

considerably decreased. The addition of tungstate mimicked

mild nitrogen limitation. Our metabolite data strongly sug-

gests that the GS/GOGAT/GDH pathways are key branch

points controlling the allocation of carbon and the recycling of

proteins, in P. tricornutum. The ratio of AKG/GL(N/U) likely re-

ports the nitrogen availability in the cell triggering the gene

expression responses observed, by an unknown signal

pathway. The high NADPH/NADPþ ratio may facilitate lipid

biosynthesis and implies a more reduced cellular environ-

ment, which could trigger previously proposed nuclear gene

expression mechanisms. These putative signal transduction

cascades (both AKG/GL(N/U) sensitive and the redox sensitive)

deserve further investigation in diatoms, as they may provide

new targets for inducing lipid biosynthesis in actively growing

cells. Thus, future studies may focus on controlling the AKG/

GL(N/U) ratio by genetically knocking down nitrate reductase

or proteins in the GDH/GS/GOGAT pathways, while simulta-

neously promoting higher fluxes of carbon towards lipid

biosynthesis. This potentially could be achieved by over

expressing ACCase in conjunction with DGATs, while

increasing the NADPH/NADPþ ratio by over expressing the

ferredoxin:NADPH oxidoreductase.


Acknowledgments

This work was supported by the DOE-EERE, grant number DE-

EE0003373. The authors acknowledge Dr. Jorge Dinamarca

Cerda for assistance with TAG analysis, as well as Dr. Sang

Hoon Lee for initial experimental planning. LTG was sup-

ported by a doctoral fellowship FCT-MCTES (reference code

SFRH/BD/61387/2009). OL and MJF were funded by a gift by

James Gibson to PGF. We would like to acknowledge assis-

tance from Rutgers University, the Aresty Research Center for

Undergraduates, and the Funding Unit for JSS support. The

authors acknowledge Agilent Technologies, Inc. for their

partnership and support in LC/MS method development and

instrumentation support.

Appendix A. Supplementary data

Supplementary data related to this article can be found online

at http://dx.doi.org/10.1016/j.biombioe.2013.10.007.

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