Investigation of how diatoms cope with the rapid fluctuations in iron bioavailability in marine environments may facilitate a better understanding of the mechanisms underlying their ecological success, in particular their ability to proliferate rapidly during favorable conditions. In this study, using in vivo biochemical markers and whole-cell iTRAQ-based proteomics analysis, we explored the cellular responses associated with reactive oxygen species (ROS) production and cell fate decision during the early response to Fe limitation in the centric diatom Thalassiosira pseudonana. Fe limitation caused a significant decrease in Photosystem (PS) II photosynthetic efficiency, damage to the photosynthetic electron transport chain in PS I, and blockage of the respiratory chain in complexes III and IV, which could all result in excess ROS accumulation. The increase in ROS likely triggered programmed cell death (PCD) in some of the Fe-limited cells through synthesis of a series of proteins involved in the delicate balance between pro-survival and pro-PCD factors. The results provide molecular-level insights into the major strategies that may be employed by T. pseudonana in response to Fe-limitation: the reduction of cell population density through PCD to reduce competition for available Fe, the reallocation of intracellular nitrogen and Fe to ensure survival, and an increase in expression of antioxidant and anti-PCD proteins to cope with stress.
Investigation of how diatoms cope with the rapid fluctuations in iron bioavailability inpan> marinpan>e enpan>vironments may facilitate a better understanding of the mechanisms underlying their ecological success, in particular their ability to proliferate rapidly during favorable conditions. In this study, using in vivo biochemical markers and whole-cell iTRAQ-based proteomics analysis, we explored the cellular responses associated with reactive oxygen species (ROS) production and cell fate decision during the early response to Fe limitation in the centric diatom Thalassiosira pseudonana. Fe limitation caused a significant decrease in Photosystem (PS) II photosynthetic efficiency, damage to the photosynthetic electron transport chain in PS I, and blockage of the respiratory chain in complexes III and IV, which could all result in excess ROS accumulation. The increase in ROS likely triggered programmed cell death (PCD) in some of the Fe-limited cells through synthesis of a series of proteins involved in the delicate balance between pro-survival and pro-PCD factors. The results provide molecular-level insights into the major strategies that may be employed by T. pseudonana in response to Fe-limitation: the reduction of cell population density through PCD to reduce competition for available Fe, the reallocation of intracellular nitrogen and Fe to ensure survival, and an increase in expression of antioxidant and anti-PCD proteins to cope with stress.
Entities:
Keywords:
Fe-limitation stress; diatom; iTRAQ-based proteomics; phytoplankton; programmed cell death (PCD); reactive oxygen species (ROS)
Diatoms are believed
to be the most important primary producers
in the ocean,[1] accounting for approximately
40% of total marine primary productivity.[2] These organisms are extensively distributed, are oftenpan> dominpan>ant
inpan> well-mixed coastal and openpan>-ocean upwellinpan>g regions,[3] warm oligotrophic gyres,[4] and the Southern and Arctic Oceans,[5] and
are evenpan> adapted to the subzero hypersaline conditions of brine channels
within polar ice.[6] Diatoms also grow rapidly
with high turnover rates and often form massive blooms.[1,7] It is of great interest to understand how and why diatoms have been
able to achieve such remarkable prominence in contemporary oceans.
It has been suggested that the ecological success of diatoms can be
at least partially attributed to the unique mechanisms through which
they cope with the wide range of fluctuations in the complex marine
environment, such as variations in the supply of nutrients (most notably
nitrogen, phosphorus, silicon, and iron).The critical roles
of iron (Fe) in diatom growth and primary production
are now well established. Phytoplankton growth in major high-nutrient,
low-chlorophyll (HNLC) waters can be limited by Fe deficiency (e.g.,
Martin et al., 1991).[8] Open ocean Fe-enrichment
experiments in HNLC areas[9−11] together with laboratory studies
have demonstrated that diatoms have multilevel strategies to endure
long-term (or chronic) Fe limitation (herein referred to as acclimated
response). For low Fe quota diatom species such as Phaeodactylum
tricornutum, Thalassiosira oceanica, and Pseudo-nitzschia multiseries, several studies have indicated
their unique high tolerance to chronic Fe-limitation stress and rapid
responses to replenishment.[12−16] However, Thalassiosira pseudonana, as a high Fe
quota diatom species, has exhibited distinctive tolerance and different
adaptation mechanisms in response to Fe-limitation conditions.[13,17] For example the enhancement of photorespiration and pentose phosphate
pathways have been proposed to be employed to acclimate to long-term
Fe limitation (10 generations, almost 10 days), based on proteomics
data.[18] Another study has indicated that T. pseudonana cells display an early stress response at
the onset of Fe limitation (the first 3 or 4 days) and then “acclimate”
to Fe limitation on the following days, showing thus a physiological
adjustment to Fe limitation from an early stress response to latter
acclimated response.[19] To date, although
many studies have focused on the fundamental cellular response of
diatoms to various Fe conditions such as Fe long-term stress, Fe-acclimation,
Fe-spiking, and Fe-enrichment (see list of previous studies in Nunn
et al, 2013[18]), studies of early stress
responses in diatoms is very limited. Notwithstanding, it is likely
that they often suffer from short-term Fe limitation (defined here
as early stress response), particularly during bloom progression when
they are likely to be subjected to rapid nutrient fluctuations, including
rapid variations in Fe bioavailability.[7,20] Therefore,
it is necessary to investigate the cellular response and metabolic
mechanisms through which diatoms respond to short-term iron limitation,
which will help us elucidate how diatom cells control their life and
death during blooms (termed cell-fate decisions). Despite the previous
investigations of early morphological, and physiological responses[21] as well as expression profiles of putative Fe-responsive
genes (such as ferredoxin and flavodoxin)[22] in early Fe-limited T. pseudonana cells, a molecular
basis for early Fe-limited stress response has remained unclear. Actually,
whole-cell proteomic profiling could be a powerful additional tool
to describe the pathways and protein products involved in the early
stress response to Fe-limitation, which could be district from acclimated
responses.Additionally, the response of T. pseudonana to
Fe bioavailability suggests that Fe starvation and culture age can
initiate programmed cell death (PCD).[21] PCD is an irreversible, caspase-mediated, autocatalytic, and genetically
controlled form of cell suicide that is accompanied by distinct morphological
changes and an energy-dependent biochemical mechanism,[23] which is consistent with the markers of apoptosis
in multicellular organisms.[21] Over the
past several decades, an increasing number of studies have noted that
light limitation, nutrient starvation, and/or the accumulation of
ROS can also induce a PCD process in unicellular phytoplankton,[24−29] including in the diatom species Ditylum brightwellii,[30]Thalassiosira weissflogii,[28,31] and Skeletonema costatum.(32) Actually, a PCD response to Fe limitation
is interesting given the importance of this trace metal in the regulation
of diatom growth and primary productivity,[24] particularly during late-phase diatom blooms. In addition, it has
been suggested that PCD resulting from Fe limitation is one of the
main causes for the decline phase of phytoplankton (including of diatoms)
blooms.[33,34]Related to PCD, the production of
reactive oxygen species (ROS)
has also been noted as a response to environmental stress.[7] Despite the fact ROS exhibit several concentration-dependent
functions,[35,36] intermediate ROS concentrations
are considered to be toxic and to be able to trigger PCD.[37,38] For instance, Vardi et al. (1999) reported that CO2 limitation
results in the formation of ROS to a level that induces PCD in the
dinoflagellate Peridinium gatunense.[25] ROS accumulation induced by Fe limitation was also demonstrated
to be involved in the triggering of PCD in T. pseudonana.[19] Moreover, the colocalization of PtNOA
(nitric oxide-associated protein) and Mn-superoxide dismutase (MnSOD)
in the chloroplast of the diatom P. tricornutum is
likely to be of relevance for ROS metabolism.[26,39] Although the diatom responses to various adverse environmental factors
may show some commonalities, ROS generation triggered by various stresses
is generally attributed to different mechanisms.[40] Therefore, it is necessary to investigate the mechanisms
of ROS production triggered by early stress of Fe limitation and their
role in governing decisions related to cell-fate in diatoms.As a complement to previous studies of cellular responses to Fe
availability inpan> T. pseudonana, a proteomics analysis
was employed here to investigate its cellular responses associated
with ROS production and cell-fate decisions during the early stress
response phase of Fe limitation. Because PCD has also been found to
be initiated in aging cultures,[21] cells
in the exponential phase of growth were chosen for the proteomics
analysis. We combined in vivo biochemical markers with the well-developed
iTRAQ-based (isobaric tags for relative and absolute quantitation)
proteomics approach[41,42] for the detection of the concomitant
induction of ROS, caspase-specific activity, externalization of phosphatidylserine,
cell death, and the suite of proteins involved in ROS production and
cellular responses to oxidative stress. Our results address the biochemical
machinery of ROS production triggered during the early stages of Fe
limitation and the related cell-fate decision mechanisms, which is
based on the balance of the functions of antioxidant and anti-PCD
proteins and PCD-induced proteins. Furthermore, the data also provide
a molecular-level understanding of the early stress response to Fe-limitation
in T. pseudonana.
Materials and Methods
Culture
Conditions
Thalassiosira pseudonana (Hust.)
Hasle et. Heimdal (strainpan> CCMP 1335) was obtained from the
Provasoli-Guillard National Center for Marine Algae and Microbiota
(NCMA, formerly known as the CCMP, https://ncma.bigelow.org/). The culture was grown in f/2 medium at 18 °C under exposure
to 60 micromol photons m–2 s–1 in a 12-h light/12-h dark regime. A starter culture of T.
pseudonana was grown in f/2 medium to the midexponential
phase (∼3.0 × 106 cells mL–1). The cells were then pelleted via centrifugation (10 000×g, 18 °C, 10 min) and washed once with filtered (0.45
μm pore-size) autoclaved seawater (FSW) for inoculation of duplicate
4-L cultures of either replete f/2 medium (Fe-replete, +Fe) or f/2
medium without added iron (Fe-limited, -Fe) at a cell concentration
of 1.5 × 105 cells mL–1. Seawater
was collected from far offshore of Xiamen harbor and the seawater
contained dissolved-Fe at very low concentrations. The duration of
the experimental phase was 7 days.
Analysis of Physiological
Parameters
Triplicate samples
were collected daily and assessed for cell abundance and photosynthetic
health. Cell numbers were counted using an Olympus microscope and
a Qiujing hemocytometer at the same time every day.[43] The cell density (cells mL–1) was calculated
as follows: CD = (N/80) × 400 × 104, where CD is the cell density, and N is the cell abundance
counted in 80 grids on the slide.The photochemical quantum
yield of photosystem (PS) II (Fv/Fm) was measured by XE-PAM (Waltz, Germany).
The measurements were performed in duplicate. Fifteen microliters
of cells were harvested onto 2-μm-pore-size polycarbonate filters,
snap frozen in liquid nitrogen, and stored at −80 °C until Fv/Fm analysis. Ten
milliliters of the filtered medium (0.45-μm pore size) was sampled
daily and stored at −20 °C for determination of nutrient
concentrations.
Determination of Nitrogen, Phosphorus, and
Silicon Concentrations
The concentrations of N—NO3–, P—PO43– and Si—SiO32– in the medium
were measured daily according
to classic colorimetric methods using a Technicon AA3 Auto-Analyzer
(BRAN+LUEBBE, GmbH, Germany). N—NO3– was analyzed using the copper–cadmium column reduction method
(Method No. G-172-96 Rev.7, BRAN+LUEBBE, Germany), P—PO43– was determined by the molybdenum blue
method (Method No. G-175-96 Rev.8, BRAN+LUEBBE, Germany), and Si—SiO32– was measured using silicon–molybdenum
blue spectrophotometry (Method No. G-177-96 Rev.5, BRAN+LUEBBE, Germany).
The detection limits for N—NO3–, P—PO43– and Si—SiO32– were 0.015, 0.024, and 0.03 μmol
L–1, respectively.
Transmission Electron Microscopy
(TEM)
The internal
cell morphology of T. pseudonana cells was observed
daily from day 2 by transmission electron microscopy (TEM). The cells
were collected via centrifugation (4 °C, 10 000×g, 5 min) and fixed in 500 μL of 2.5% glutaraldehyde
fixative (pH 7.4) for 2 h. The cells were then rinsed once, resuspended
in 0.1 M PBS (pH 7.4), and stored at 4 °C (for less than 1 week)
prior to the next treatment. The fixed cells were rinsed three times
for 15 min in 0.1 M PBS (pH 7.4), postfixed for 2–3 h in 1%
buffered OsO4, and washed three times with 0.1 M PBS (pH 7.4). After
the supernatant was removed by centrifugation (4 °C, 10 000×g, 5 min), the pellets were dehydrated through a graded
series of ethanol and then with propylene oxide. The cells were then
embedded in an Epon812 Embedding medium (3 g of DDSA 3 g, 7 g of MNA,
and 10 g of Epon812 in 0.32 mL of DMP). Sections were cut using a
PowerTomo-XL ultramicrotome (RMC, U.S.A.), collected on 200-mesh copper
grids, and stained with uranyl acetate and lead citrate. The stained
sections were visualized and photographed using a H-7560 electron
microscope (HITACHI, Japan).
In Vivo Cell Staining and Flow Cytometry
Cells were
collected daily from day 2, pelleted via centrifugation (10 000×g, 10 min, 4 °C), resuspended in buffer, and stainpan>ed
with the followinpan>g: SYTOX greenpan> (1 μM; Invitrogenpan>) to visualize
live/dead cells, z-VAD-FMK-FITC (20 μM; CaspACE; Promega, Madison,
WI, U.S.A.) to detect activated caspases, Annexin V (10 μL/100
μL cells; Invitrogen) to detect the externalization of phosphatidylserine,
and CM-H2DCFDA [5 μM; 5-(and-6)-chloromethyl-2′,7′-dichlorodihydrofluorescein
diacetate, acetyl ester; Invitrogen] to detect intracellular ROS.
The detailed protocol was previously described.[19] The percentage of positively stained cells (from a total
of 10 000 cells) was determined at 520 nm after excitation
with a 488 nm laser using a flow cytometer (BD Fortessa, U.S.A.).
The gating and data analysis were performed using FlowJo analytical
software.
Protein Extraction and Preparation
According to the
physiological and biochemical results obtainpan>ed for T. pseudonana during previous experiments, day 4 (middle exponential phase of
growth) was chosen as the sampling time point for the iTRAQ-based
proteomics analysis. Protein extraction was conducted according to
the methods described by Du et al. (2014).[44] Briefly, approximately 1 L of culture was collected through a 2
μm pore-size filter membrane for each sample. Cells on the membrane
were then resuspended with 10 mL medium into a 15 mL centrifugal tube.
After the cell pellets were collected by centrifuging at 3000×g for 5 min, 10 mL of TRIzol Reagent (Invitrogen, Life Technologies)
was added, and the protein was then extracted according to the manufacturer’s
recommendations.For protein preparation, the proteinpan> pellets
were suspended inpan> lysis buffer (7 M urea, 2 M thiourea, 4% CHAPS,
40 mM Tris-HCl, pH 8.5), then incubated with 10 mM DTT at 56 °C
for 1 h to reduce the disulfide bonds. After that, 55 mM IAM was added
(final concentration), and the samples were incubated for 1 h in the
dark to block the cysteine residues of the proteins (alkylate). The
reduced and alkylated protein mixtures were precipitated by adding
4× volume of chilled acetone at −20 °C overnight.
After centrifugation on at 4 °C, 30 000×g, the pellet was dissolved in 0.5 M TEAB (triethylammonium bicarbonate,
Applied Biosystems, Milan, Italy) and sonicated in ice. After centrifuging
at 30 000×g at 4 °C, an aliquot
of the supernatant was taken for determination of protein concentration
by Bradford Protein Assay Kit according to the manufacturer’s
protocol. The proteins in the supernatant were kept at −80
°C until further analysis.
iTRAQ Labeling and SCX
Fractionation
A total of 100
μg proteins from each sample were digested with Trypsin Gold
(Promega, Madison, WI, U.S.A.) with the ratio of protein/trypsin =
30:1 at 37 °C for 16 h. After trypsin digestion, peptides were
dried by vacuum centrifugation. Peptides were reconstituted in 0.5
M TEAB and processed according to the manufacture’s protocol
for 8-plex iTRAQ reagent (Applied Biosystems, Foster City, CA, U.S.A.).
Four samples (two biological replicates for Fe-replete and Fe-limited,
respectively) were labeled with different iTRAQ tags: 113- and 114-iTRAG
tags for Fe-replete replicate 1 and 2, respectively; and 119- and
121-iTRAG tags for Fe-limited replicate 1 and 2, respectively. The
peptides were labeled with the isobaric tags, and then incubated at
room temperature for 2h. The labeled peptide mixtures were then pooled
and dried by vacuum centrifugation.SCX (Strong Cationic Exchange)
chromatography was performed using a Shimadzu LC-20AB HPLC pump system
(Shimadzu, Kyoto, Japan). The fractionated peptides were first reconstituted
inpan> 4 mL of buffer A (25 mM NaH2PO4 in 25% ACN,
pH 2.7) and then loaded onto a 4.6 × 250 mm2 Ultremex
SCX column containing 5-μm particles (Phenomenex). The peptides
were eluted at a flow rate of 1 mL/min with a gradient of buffer A
for 10 min, 5–60% buffer B (25 mM NaH2PO4, 1 M KCl in 25% ACN, pH 2.7) for 27 min, 60–100% buffer B
for 1 min. The system was then maintained at 100% buffer B for 1 min
before equilibrating with buffer A for 10 min before the next injection.
Elution was monitored by measuring the absorbance at 214 nm, and fractions
were collected every minute. The eluted peptides were then pooled
into 20 fractions, desalted with a Strata X C18 column (Phenomenex),
and vacuum-dried.
LC-ESI-MS/MS Analysis
Each fraction
was resuspended
in solution A (2% ACN, 0.1%FA) and cenpan>trifuged at 20 000×g for 10 minpan>. The finpan>al concenpan>tration of peptide was about
0.5 μg/μL on average. Ten μL supernatant was then
loaded on a Shimadzu LC-20AD nano HPLC by the autosampler onto a C18
trap column, and the peptides were eluted onto an analytical C18 column
(inner diameter of 75 μm) packed in-house. The samples were
collected at a rate of 8 μL/min for 4 min. A 44 min gradient
was then run at a rate of 300 nL/min starting from 2% to 35% solution
B (98% ACN and 0.1% FA), followed by a 2 min linear gradient to 80%
solution B, maintenance at 80% solution B for 4 min, and return to
5% in 1 min.The peptide samples were then subjected to nanoelectrospray
ionization for tandem mass spectrometry (MS/MS) inpan> a Q Exactive (Thermo
Fisher Scientific, San Jose, CA, U.S.A.) coupled onlinpan>e to the HPLC.
Intact peptides were detected inpan> the Orbitrap at a resolution of 70 000.
The peptides were chosen for MS/MS using the high-energy collision
dissociation (HCD) operating mode with a normalized collision energy
setting of 27.0 and a stepped NCE of 12.0%. The ion fragments were
detected in the Orbitrap at a resolution of 17 500. A data-dependent
procedure that alternated between one MS scan followed by 15 MS/MS
scans was applied for the 15 most abundant precursor ions above a
threshold ion count of 20 000 in the MS survey scan with subsequent
dynamic exclusion duration of 15 s. The electrospray voltage applied
was 1.6 kV. Automatic gain control (AGC) was used to optimize the
spectra generated by the Orbitrap. The AGC target for full MS was
3e6 and 1e5 for MS2. For MS scans, the m/z scan range was 350 to 2000 Da. For MS2 scans, the m/z scan range was 100–1800.
Proteomic
Data Analysis
Raw data files acquired from
the Orbitrap were converted into MGF files using Proteome Discoverer
1.2 (PD 1.2, Thermo), and the MGF file was searched. The peptide and
proteinpan> idenpan>tifications were performed through the Mascot search enpan>ginpan>e
(ver. 2.3.02; Matrix Scienpan>ce, London, U.K.) againpan>st Joinpan>t Genpan>ome Institute
database for the T. pseudonana genome (http://genome.jgi-psf.org/Thaps3/Thaps3.home.html, October, 2012, which contains a total of 34 736 sequences
including the Thaps3 finished chromosomes and Thaps3_bd unmapped sequence
data (386 sequences)) and NCBI.For protein identification,
a mass tolerance of 0.05 Da (the tolerance was “ ± 0.05
Da”) was permitted for intact peptide masses and ±0.1
Da for fragmented ions, with allowance for one missed cleavage in
the trypsin digests. Gln → pyro-Glu (N-term Q), Oxidation (M),
Deamidated (NQ) as the potential variable modifications, and Carbamidomethyl
(C), iTRAQ 8plex (N-term), iTRAQ 8plex (K) as fixed modifications.
The charge states of peptides were set to +2 and +3. For reducing
the probability of false peptide identification, only peptides at
the 95% confidence interval by a Mascot probability analysis greater
than “identity” were counted as identified.For
protein quantitation, it was required that a protein contains
at least two unique peptides. The quantitative protein ratios were
weighted and normalized by the median ratio in Mascot. The student’s t test was performed using the Mascot 2.3.02 software. We
only used ratios with p-values <0.05, and only
fold changes of >1.5 were considered as significant.
Function Annotation
Description
Functional annotations
of the proteins were conducted using Blast2GO program againpan>st the
nonredundant proteinpan> database (NR; NCBI). GO (Gene Ontology) enrichment
analysis was carried out for the differentially regulated proteins
to determine the affected cellular metabolism. Cluster of Orthologous
Groups(COG, http://www.geneontology.org), a system for
automated detection of homologues among the annotated genes of several
completely sequenced eukaryotic genomes, was used to compare identified
proteins to COG database for predicting the function of identical
proteins and for functional classification and statistics.[45,46] The analysis was performed by matching the responsive proteins to
the proteins annotated with a COG term and then comparing the frequencies
of the responsive proteins in each COG term subset to determine the
statistical authenticity of the involvement of that COG term in the
Fe-limited responses. A P-value of 0.05 was set as
the threshold. KEGG pathway database (KEGG, http://www.genome.jp/kegg/), a collection of manually drawn pathway maps representing knowledge
on molecular interaction and reaction networks, was used for protein
functional and interaction analysis in different metabolic pathways.
Quantitative RT-PCR Analysis
The expression of 11 randomly
selected genpan>es enpan>codinpan>g idenpan>tified proteinpan>s was performed by quantitative
RT-PCR analysis. The primers were designed using Primer-BLAST (Supporting Information, SI, Table S1).[47] Each primer pair was designed to span at least
one exon–exon junction such that genome DNA digestion was not
needed. At day 4, approximately 30 mL of culture was filtered for
Fe-replete and Fe-limited conditions. Samples were rapidly placed
in liquid nitrogen with the filter, ground to powder in a precooled
traditional mortar, and immediately transferred to TRIzol Reagent
(Invitrogen, Life Technologies). Total RNA was then extracted according
to the manufacturer’s recommendations. The cDNA was synthesized
immediately after the RNA was extracted (ReverTra Ace qPCR RT Kit,
TOYOBO, Japan). Quantitative PCR was performed with a Rotor-Gene 6000
system (Corbett Life Science) using the SYBR Green Real-time PCR Master
Mix (TOYOBO, Japan). Each gene was detected in triplicate simultaneously
with an inner control gene.
Results and Discussion
General
Physiological and Biochemical Responses
The
cells were cultured under Fe-limited conditions (f/2+Si medium without
Fe added) and Fe-replete conditions (f/2+Si medium). The photosynthetic
efficiency of PSII (Fv/Fm), an indicator of Fe limitation in the laboratory,[13] was used as a rapid measure of the physiological
status of T. pseudonana. On day 4, which corresponds
to the exponential phase (Figure 1A), the value
of Fv/F of the cells exposed to Fe-limitation conditions was markedly
reduced, being 20% lower (∼0.50) compared to Fe-replete cells
(∼0.63). After day 4, the value of Fv/Fm slightly increased, indicating that
the cells were exhibiting some physiological adjustment to Fe limitation
on days 5 and 6. The growth rate and maximum cell abundances of the
Fe-limited cells on day 4 were much lower than those of the Fe-replete
cells: 17% lower growth rate (∼0.50 in limited versus ∼0.63
in replete) and 41% fewer cells (∼2.33 × 106 in limited versus ∼3.93 × 106 in replete),
respectively (Figure 1B).
Figure 1
Growth, photosynthetic
efficiency, and nutrient concentrations
in Fe-replete and Fe-limited culture conditions. Photochemical quantum
yield of photosystem II (Fv/Fm) (A) and cell growth (B) of T. pseudonana Fe-replete and Fe-limited cultures. The error bars represent the
standard errors from duplicate measurements. Concentrations of N—NO3–, P—PO43–, and Si—SiO32– in media from T. pseudonana cells cultured under Fe-replete (C) and Fe-limited
(D) conditions. The error bars represent the standard errors from
triplicate measurements.
Growth, photosynthetic
efficiency, and nutrient concentrations
inpan> Fe-replete and Fe-limited culture conditions. Photochemical quantum
yield of photosystem II (Fv/Fm) (A) and cell growth (B) of T. pseudonanaFe-replete and Fe-limited cultures. The error bars represent the
standard errors from duplicate measurements. Concentrations of N—NO3–, P—PO43–, and Si—SiO32– in media from T. pseudonana cells cultured under Fe-replete (C) and Fe-limited
(D) conditions. The error bars represent the standard errors from
triplicate measurements.The notable differenpan>ces inpan> the degree of inpan> vivo cell stainpan>inpan>g
for ROS production (oxidative stress), externalization of phosphotidylserine
(a morphological characteristic of the early stages of PCD), caspase
activity (caspases are a specific class of intracellular cysteinyl
aspartate-specific proteases that initiate and execute PCD in metazoans[48]), and cell mortality (visualization of live/dead
cells) between cells exposed to Fe-replete and -limiting conditions
during days 2–7 are shown in Figure 2 and Table 1. After 4 days of exposure, 24%
of the Fe-limited cells stained positive for ROS compared with 6%
of the Fe-replete cells (Figure 2A). This observation
indicates that Fe-limitation caused a most marked increase in ROS
(more than 4-fold) on day 4 compared with the Fe-replete cells, although
the percent of positive stained cells for intracellular ROS was not
the highest on day 4. This result was consistent with the most marked
decrease in Fv/Fm data on day 4 shown in Figure 1A,
which indicates that the cells suffered from acute oxidative stress
(early stress response) before attempting to physiologically adjust
to the Fe-limited conditions after day 4. Correspondingly, the percent
of positively stained cells for the externalization of phosphatidylserine
(Annexin) (16%) and caspase activity (CaspACE) (25%) increased significantly
by around 3-fold on day 4 in the Fe-limited cultures (Figure 2B,C). However, the ratio of dead cells was not significantly
different between the Fe-limited and the Fe-replete cultures from
days 2–6 (Figure 2D). These findings
suggest that some cells were undergoing PCD due to intense oxidative
stress on day 4 but were not actually dead.
Figure 2
Examination of ROS production
and PCD in cells grown in Fe-replete
and Fe-limited conditions. In vivo detection of ROS (CM-H2DCFDA) (A),
externalization of phosphatidylserine (Annexin V) (B), caspase activity
(CaspACE) (C), and dead cells (SYTOX) (D) using flow cytometry. T. pseudonana cells were analyzed from days 2 to 7 after
growth in either Fe-replete or Fe-limited media. The numbers above
the columns represent the ratios of positive cells between Fe-limited
and Fe-replete cultures.
Table 1
Percentage of Cells Positively-Stained
for Intracellular ROS, Externalization of Phosphatidylserine, Caspase
Activity, and Dead Cells Based on the in Vivo Staining of T. pseudonana Cells from Days 2 to 7 in Fe-Replete (+Fe)
or Fe-Limited (−Fe) Conditions
time (D)
culture
ROS (%)
annexin (%)
caspases
(%)
SYTOX (%)
2
+Fe
4.1
2.6
6.5
11.9
–Fe
5.5
8.6
10.2
13.2
3
+Fe
5.1
4.8
7.0
10.3
–Fe
6.6
5.7
20.0
13.0
4
+Fe
5.7
5.1
9.6
26.6
–Fe
24.4
16.0
25.4
22.5
5
+Fe
18.8
15.5
35.5
28.1
–Fe
40.4
28.0
47.8
31.7
6
+Fe
13.8
12.6
39.2
30.7
–Fe
49.3
31.1
65.2
32.7
7
+Fe
24.0
18.6
55.7
29.5
–Fe
31.9
49.0
61.6
49.9
Examination of ROS production
and PCD in cells grown in Fe-replete
and Fe-limited conditions. In vivo detection of ROS (CM-H2DCFDA) (A),
externalization of phosphatidylserine (Annexin V) (B), caspase activity
(CaspACE) (C), and dead cells (SYTOX) (D) using flow cytometry. T. pseudonana cells were analyzed from days 2 to 7 after
growth in either Fe-replete or Fe-limited media. The numbers above
the columns represent the ratios of positive cells between Fe-limited
and Fe-replete cultures.To find further evidence that ROS
inpan>duced PCD on day 4, we examined
morphological changes based on TEM observations. The most common hallmarks
of PCD previously recorded in T. pseudonana,[21] such as marked vacuolization, internal degradation
(unrecognizable organelles with integral membranes), and chromatin
condensation, were indeed observed, as shown in Figure 3E. Morphological characteristics of PCD were also found in
the cells on day 7 (Figure 3C,F) under both
Fe-replete and Fe-limiting conditions, due to the fact that culture
age also induces PCD.[21] However, the nucleosomal
laddering of DNA, the strongest evidence for PCD in higher eukaryotes,
could not be detected (data not shown), which is consistent with the
absence of ladders observed in previous studies of PCD in the same
species,[21] the dinoflagellate Peridinium
gatunense,(25) and yeast.[49]
Figure 3
Electron micrographs of cells grown in Fe-replete and
Fe-limited
conditions. Morphological changes in T. pseudonana cells grown in Fe-replete conditions on day 2 (A), day 4 (B) and
day 7 (C), and Fe-limited conditions on day 2 (D), day 4 (E), and
day 7 (F). n: nucleus; c: chloroplast; m: mitochondria; d: dictyosome;
v: vacuole; a: autophagosome; and bars: 1 μm.
Electron micrographs of cells grown in Fe-replete and
Fe-limited
conditions. Morphological changes in T. pseudonana cells grown in Fe-replete conditions on day 2 (A), day 4 (B) and
day 7 (C), and Fe-limited conditions on day 2 (D), day 4 (E), and
day 7 (F). n: nucleus; c: chloroplast; m: mitochondria; d: dictyosome;
v: vacuole; a: autophagosome; and bars: 1 μm.
General Results from the iTRAQ Analysis
To unravel
the cellular responses associated with ROS production and cell-fate
decision during the early stress response to Fe limitation, we harvested
cells for iTRAQ-based proteomics analysis on day 4. We labeled and
mixed two biological replicates of Fe-replete and Fe-limited samples
directly for proteomic analysis. Reproducibility of the proteomics
analysis for two comparison samples is shown in Figure S1 (SI), and Pearson correlation coefficients were
used to evaluate the similarity between the two replicates. The delta
error in the figure represents the difference between the quantitative
values of two biological replicates of each treatment (Fe-replete
or Fe-limited). The difference was plotted against the percentage
of proteins identified, and the comparisons showed that approximately
50% of the proteins had differences with a delta error of less than
0.1, and more than 95% of the proteins had differences of less than
0.5 in both treatments, suggesting good analytical reproducibility
(SI Figure S1).A total of 883 differenpan>tially
regulated proteinpan>s betweenpan> the Fe-replete and Fe-limited conditions
were confidently identified in both biological replicates using the
criteria described in the experimental methods (SI Table S2). Among these proteins, 510 were subjected to
Cluster of Orthologous Groups (COG) enrichment analysis to determine
the cellular metabolisms most impacted by Fe limitation (data shown
in SI Table S3; 75 out of 510 proteins
have more than one description). Functional classification of the
proteins identified showed that they were involved in almost every
aspect of T. pseudonana metabolism (Figure 4). Several key cellular processes, such as post-translational
modification, protein turnover, and chaperones (14.9%), energy production
and conversion (13.9%), translation, ribosomal structure and biogenesis
(10.8%), and amino acid transport and metabolism (10.3%) were significantly
affected by the Fe-limiting conditions. Furthermore, most of the “translation,
ribosomal structure, and biogenesis” proteins identified were
found to decrease in abundance, suggesting an overall slowdown of
protein biosynthesis and a possible slowdown of metabolism.
Figure 4
Functional
category (COG) coverage of the proteins identified in T. pseudonana under Fe-limited conditions based on the iTRAQ-LC–MS/MS
analysis.
Functional
category (COG) coverage of the proteinpan>s idenpan>tified inpan> T. pseudonana under Fe-limited conditions based on the iTRAQ-LC–MS/MS
analysis.Using a significance cutoff of
1.5-fold change and a P-value less than 0.05 to assess
changes in abundance, we determined
that a total of 127 proteins showed significant differences. Of these,
41 and 86 unique proteins, respectively, were found to be present
in significantly higher and lower relative abundances in the Fe-limited
cells compared with the cells exposed to Fe-replete conditions (SI Table S4). The most interesting proteins are
summarized in SI Table S5.
Quantitative
RT-PCR Analysis
A subset of 11 genes encoding
the proteins detected in iTRAQ analysis was selected for quantitative
RT-PCR analysis. The genes were selected based on the abundance levels
of their encoded proteins to ensure that genes with a wide range of
expression levels were included, as well to cover a range of important
regulatory processes. According to the iTRAQ proteomics analysis,
the abundance of seven of the proteins encoded by the seven genes
were decreased (i.e., Thaps3|255232, Thaps3|2152, Thaps3|8571, Thaps3|25206,
Thaps3|24591, and Thaps3|1669), and four of the proteins encoded by
the selected genes were increased in abundance (i.e., Thaps3|20362,
Thaps3|21534, Thaps3|3353, and Thaps3|2404). Eight of our quantitative
RT-PCR results (Thaps3|255232, Thaps3|2152, Thaps3|8571, Thaps3|25206,
Thaps3|24591, Thaps3|3353, Thaps3|2404, and Thaps3|1669) were somewhat
consistent with the iTRAQ data, whereas three (Thaps3|20362, Thaps3|21534,
and Thaps3|11118) were not (Figure 5), indicating
that their protein levels may not necessarily correlate with their
mRNA levels. In particular, death-specific protein 1 (Thaps3|11118),
an important protein associated with cell death and PCD regulation
in phytoplankton (see below), was found at increased mRNA levels but
decreased protein abundance. Another two proteins, a cyclin-dependent
kinase (Thaps3|20362) and an RNA-binding protein (RRM domain) (Thaps3|21534),
both showed decreased abundance of mRNA and increased abundance of
protein.
Figure 5
Comparison of iTRAQ and qPCR results for 11 genes. Comparison of
the protein (iTRAQ) and mRNA (qPCR) levels of Thaps3|11118, Thaps3|20362,
Thaps3|255232, Thaps3|2152, Thaps3|8571, Thaps3|25206, Thaps3|24591,
Thaps3|21534, Thaps3|3353, Thaps3|2404, and Thaps3|1669 under Fe-limited
conditions. β-actin was used as a housekeeping marker. Fold
changes of either more than 1 or less than 1 from iTRAQ and qPCR indicate
that they are consistent (red dotted line).
Comparison of iTRAQ and qPCR results for 11 genes. Comparison of
the proteinpan> (iTRAQ) and mRNA (qPCR) levels of Thaps3|11118, Thaps3|20362,
Thaps3|255232, Thaps3|2152, Thaps3|8571, Thaps3|25206, Thaps3|24591,
Thaps3|21534, Thaps3|3353, Thaps3|2404, and Thaps3|1669 under Fe-limited
conditions. β-actin was used as a housekeeping marker. Fold
changes of either more than 1 or less than 1 from iTRAQ and qPCR indicate
that they are consistent (red dotted line).
Metabolic Mechanisms Involved in ROS Production
Downregulation
of Photosynthesis and Accumulation of ROS
Light-harvesting
complexes (LHCs) are generally used to harvest and
transfer light enpan>ergy inpan>to the reaction cenpan>ters to drive photosynpan>thesis.[50] Diatoms contain a branch of genes encoding the
LHC superfamily known as fucoxanthin-chlorophyll a/c-binding proteins
(FCPs).[51] In the present study, Fe limitation
induced the increased abundance of almost all of the FCPs, especially
FCP 2 (Thaps3|30605, 1.60-fold, p > 0.05) and
green
algal LI818-like clade (annotated as LHCX in diatoms)[51,52] (Thaps3|17894, 1.60-fold, Thaps3|12096, 1.48 fold). Recent studies
have demonstrated that LHCX protein members have a dual role in light
energy harvesting and excess light energy dissipation.[51,52] Moreover, the increased protein abundance and transcript level of
FCP in Fe-limited T. oceanica cultures have been
hypothesized by Lommer et al. (2012)[12] to
be associated with light-mediated oxidative stress. One gene of the
LHCX family was also found to be significantly up-regulated in Fe-limited P. tricornutum cells.[13] Thus,
the increased levels of these FCP proteins could infer that Fe-limited T. pseudonana cells were undergoing oxidative stress.The abundance of proteins involved in PS II, such as photosystem
II reaction center protein D2 (Thaps3|bd|1272, 1.39 fold, p > 0.05), photosystem II oxygen-evolvinpan>g complex 23K
proteinpan>
(Thaps3|2185, 1.22 fold, p > 0.05), and photosystem
II 44-kDa reaction center proteinpan> (Thaps3_bd|1244, 1.23 fold), were
inpan>creased slightly inpan> our study (Figure 6),
resultinpan>g potentially inpan> a slight enhancement of PS II activity. The
electrons produced inpan> PS II must then be transferred to PS I by plastoquinone
and the cytochrome b6f complex (cyt b6f), to ultimately lead to ATP production. However, in this study,
most of PS I-related proteins and cytochrome f, a
component of cyt b6f (Thaps3_bd|106, 0.64 fold, p > 0.05), were decreased in abundance in the Fe-limited T. pseudonana cells. In addition, the abundance of ferredoxin-NADP+ reductase (Thaps3|25892), which catalyzes the last electron
transfer from PS I to NADP,[53] also decreased
0.56-fold. Therefore, the photosynthetic electron transport chain
could be damaged in PS I, which could result in the accumulation of
electrons and a concomitant increase in ROS generation. Furthermore,
the abundance of some proteins associated with photosynthesis were
also found to be slightly decreased, such as oxygen-evolving enhancer
protein 1 precursor (Thaps3|16430, 0.29 fold, p >
0.05), high light-induced protein 2 (Thaps3|21467, 0.65 fold, p > 0.05), and ferredoxin (Thaps3_bd|1258, 0.55-fold),
which
further supports the existence of inefficient photosynthetic electron
transport in Fe-limited T. pseudonana cells. In other
words, Fe limitation caused the downregulation of photosynthesis and
may block electron flow in PS I to result in the excess production
of highly toxic ROS, which is consistent with previous results from
the diatom P. tricornutum.[13]
Figure 6
Hypothetical
cellular pathways and processes in the diatom T. pseudonana under iron-limited growth conditions. All
red words or arrows represent proteins with increased abundance or
enhanced pathways, respectively. All green words or arrows represent
proteins with decreased abundance or inhibited pathways, respectively.
Lhc: Light harvesting complex, PS: Photosystem; OEM: Oxygen-evoling
complex; Cyt: Cytochrome; FNR: Ferredoxin-NADP+ reductase;
Fd: Ferredoxin; Fd-NiR: Ferredoxin nitrite reductase; ROS: Reactive
oxygen species; PCD: Programmed cell death; RUBP: Ribulose-1,5-bisphosphate;
TCA: Tricarboxylic acid cycle; FET3: Ferroxidase; FTR1: Iron permease;
TpDSP: T. pseudonana death-specific protein; COX6B1:
Cytochrome c oxidase subunit 6B1; EC 5.3.1.1: Triosephosphate
isomerase; EC 2.7.2.3:3-phosphoglycerate kinase; EC 1.2.4.1: Pyruvate
dehydrogenase (E1) component; EC 2.3.3.1: Citrate synthase; EC 1.1.1.37:
Malate/lactate dehydrogenases; EC 1.6.5.3: NADH-ubiquinone reductase;
EC 1.10.2.2: Cytochrome c1; EC 3.6.3.14: ATP synthase;
EC 6.3.5.5: Carbamoyl-phosphate synthase; EC 6.3.4.5: Argininosuccinate
synthase; and EC 3.5.3.1: Arginase.
Hypothetical
cellular pathways and processes in the diatom T. pseudonana under iron-limited growth conditions. All
red words or arrows represent proteins with increased abundance or
enhanced pathways, respectively. All green words or arrows represent
proteins with decreased abundance or inhibited pathways, respectively.
Lhc: Light harvesting complex, PS: Photosystem; OEM: Oxygen-evoling
complex; Cyt: Cytochrome; FNR: Ferredoxin-NADP+ reductase;
Fd: Ferredoxin; Fd-NiR: Ferredoxin nitrite reductase; ROS: Reactive
oxygen species; PCD: Programmed cell death; RUBP: Ribulose-1,5-bisphosphate;
TCA: Tricarboxylic acid cycle; FET3: Ferroxidase; FTR1: Iron permease;
TpDSP: T. pseudonana death-specific protein; COX6B1:
Cytochrome c oxidase subunit 6B1; EC 5.3.1.1: Triosephosphate
isomerase; EC 2.7.2.3:3-phosphoglycerate kinase; EC 1.2.4.1: Pyruvate
dehydrogenase (E1) component; EC 2.3.3.1: Citrate synthase; EC 1.1.1.37:
Malate/lactate dehydrogenases; EC 1.6.5.3: NADH-ubiquinone reductase;
EC 1.10.2.2: Cytochrome c1; EC 3.6.3.14: ATP synthase;
EC 6.3.5.5: Carbamoyl-phosphate synthase; EC 6.3.4.5: Argininosuccinate
synthase; and EC 3.5.3.1: Arginase.
Response of Cellular Respiration and ROS Accumulation
Under Fe-limited conditions, it was found that the three proteinpan>s
inpan>volved inpan> glycolysis, through which glucose is broken down into
pyruvate with generation of a small amount of ATP and NADH, were markedly
increased in abundance (Figure 6). These proteins
are triosephosphate isomerase (EC 5.3.1.1, Thaps3|16639, 1.68-fold)
which catalyzes the reversible interconversion of the triose phosphate
isomers dihydroxyacetone phosphate and d-glyceraldehyde 3-phosphate,
and 3-phosphoglycerate kinase (EC 2.7.2.3, Thaps3|14980, 1.55-fold
and Thaps3|256275, 1.54-fold), an enzyme that catalyzes the reversible
transfer of a phosphate group from 1,3-bisphosphoglycerate (1,3-BPG)
to adenosine diphosphate (ADP) and then produces 3-phosphoglycerate
(3-PG) and ATP. Thus, it could be inferred that more pyruvate would
enter the mitochondrion and be fully oxidized to produce GTP, FADH2, and NADH through the TCA cycle. At the same time, three
proteins related to the TCA cycle were also significantly increased
in protein abundance in the Fe-limited cells, including pyruvate dehydrogenase
E1 (Thaps3|15834, 1.51-fold), citrate synthase (Thaps3|11411, 1.79-fold),
and malate/lactate dehydrogenases (Thaps3|20726, 1.57-fold). The first
protein (Thaps3|15834) is a component of the pyruvate dehydrogenase
complex (PDC), which converts pyruvate into acetyl-CoA and links the
glycolysis metabolic pathway to the TCA cycle. Citrate synthase catalyzes
the first step of the TCA cycle, and the last protein, namely malate/lactate
dehydrogenase, is an enzyme that reversibly catalyzes the oxidation
of malate to oxaloacetate by the reduction of NAD+ to NADH.
The increased abundance of these proteins could suggest that T. pseudonana may prefer to produce more NADH and FADH2 and other bioenergy molecules by accelerating the decomposition
of glucose in response to iron-limited stress.The respiratory
chainpan> consists of a series of protein complexes that transfer electrons
from NADH (or FADH2) to O2 via redox reactions.
This chain includes coenzyme Q, cytochrome c, and
four membrane-bound complexes (Complexes I, II, III, and IV) (Figure 6). In the present study, it was found that NADH-ubiquinone
reductase (H+-translocating) (EC 1.6.5.3, Thaps3_bd|1380)
in Complex I was markedly increased in abundance (1.7-fold), which
may suggest that more electrons could be delivered to the respiratory
chain in Fe-limited cells. However, both abundance of cytochrome c1 (Thaps3|25564, 0.56-fold) of Complex III and a possible
cytochrome c oxidase subunit 6B1 (COX6B1, Uniprot_Swissprot,
Thaps3|1996, 0.48-fold) of Complex IV were significantly decreased,
which could indicate that Complexes III and IV were inhibited and
thus that the respiratory chain was blocked and electrons were undeliverable.
In general, the major sites for ROS generation are Complexes I and
III of the electron transport chain.[55,56] Previous studies
have also indicated that the oxidation of either Complex I or Complex
II substrates when Complex III is inhibited by antimycin A may increase
ROS accumulation.[57,58] Thus, it can be proposed that
under the Fe-limited conditions in the present study, increases in
ROS production are likely to occur when Complex III is inhibited.
Although cytochrome c oxidase is not a source of
ROS,[59,60] the inhibition of cytochrome c oxidase due to the decreased abundance of COX6B1 may facilitate
ROS production from Complex I or III.[61,62] Therefore,
our findings also suggest that the observed decreased abundance of
COX6B1 could also be considered to be related with the overproduction
of ROS. It was found that mitochondrial alternative oxidase (AOX)
is used as an alternative electron acceptor to remove excess electrons
in Fe limited P. tricornutum cells because it uses
less iron.[13] However, we did not find AOX
protein expression in this Fe limited T. pseudonana based on our proteomic data.In addition, the decrease in
ATP production via the respiratory
chain coincided with the blockage of the respiratory chain when T. pseudonana suffered from Fe-limited stress. In contrast,
the abundance of three proteins belonging to the F1 region of FoF1-type
ATP synthase (an important enzyme that catalyzes the synthesis of
ATP) were found to increase in response to Fe-limited stress in this
study, indicating an increase in ATP production. These proteins are
F0F1-type ATP synthase α subunit (Thaps3|13863, 1.52-fold),
δ subunit (Thaps3|17981, 1.67-fold, p >
0.05),
and ϵ subunit (Thaps3_bd|1254, 1.60-fold, p > 0.05), and all possess the core catalytic functions for the
synthesis
of ATP. Thus, it could be concluded that the increase in ATP synthesis
observed in the present study may be a compensatory mechanism in response
to the decrease in ATP production through the respiratory chain.To conclude, evidence for the accumulation of ROS under Fe-limited
conditions has been found to stem from inefficient activity of the
electron transport chains in both the photosynthetic and respiratory
processes (Figure 6). These results coincide
with the high levels of intracellular ROS detected in vivo (Figure 2A), indicating that the cells were in a state of
oxidative stresses.
Response to Oxidative Stress and Cell Fate
Decision
Response to oxidative stress
Because oxidative stress
can trigger PCD,[37,38]T. pseudonana must have effective mechanisms for removing excess electrons and
for scavenging ROS. On the other hand, due to Fe limitation, some
typical ROS defense proteins that require iron as a cofactor showed
limited abundance or even a decreased abundance. For example, superoxide
dismutase (SOD, Thaps3|17168, 0.95-fold), which is a cambialistic
(Fe/Mn)-SOD that has been previously cloned and characterized in the
diatom Thalassiosira weissflogii,[63] and catalase (peroxidase I) (Thaps3|257595, 0.68-fold),
which is a tetramer of four polypeptide chains containing four porphyrin
heme (iron) groups that allow the enzyme to react with hydrogen peroxide,[64] both showed decreased abundance. Notwithstanding,
some other iron-free antioxidant enzymes were found to increase in
abundance, presumably to replace these ROS scavenging functions. These
included peroxiredoxins (Thaps3|32681, 1.64-fold), a ubiquitous family
of antioxidant enzymes (peroxidases) to detoxify various peroxide
substrate,[65] which notably represent the
second most highly abundant group of proteins found in this proteomics
analysis. Moreover, glutaredoxin-related proteins (Thaps3|261282,1.26-fold)
are thiol-disulfide oxidoreductases that can combat oxidative stress
by detoxifying H2O2 to H2O using
glutathione and NADPH, and some members have been shown to exert anti-apoptotic
effects.[66] The expression of thiol–disulfide
isomerase and thioredoxins (Thaps3|5491, 1.47-fold, Thaps3|23961,
1.22-fold), the key antioxidant proteins in T. pseudonana,[67] were also elevated, which is consistent
with the upregulation of the genes detected by Thamatrakoln et al.
(2012).[19] Our results indicate rather that
an iron-free ROS scavenging machinery replaced the iron-rich systems
to respond to the oxidative stress caused by Fe limitation.In addition, some heat shock proteins showed differenpan>ces inpan> their
expression levels under Fe-limited conditions. For example, chaperonin
GroES (HSP10) (Thaps3|24914, 0.29-fold), molecular chaperone GrpE
(Thaps3|18072, 0.64-fold), and some coexpression proteins, such as
FKBP-type peptidyl-prolyl cis–trans isomerase 1 (Thaps3|18543, 0.43-fold) and trypsin-like serine proteases
(Thaps3|875, 0.59-fold), all decreased in abundance. The decreased
abundance of these proteins could reduce the tolerance of T. pseudonana cells to Fe limitation, inhibit growth, and
other physiological processes, and eventually induce PCD. However,
the increased abundance (1.56-fold) of chaperonin GroEL (HSP60 family,
Thaps3|13537) suggested that this anti-apoptotic protein is also present
in the Fe-limited cells to resist the apoptotic process induced by
Fe limitation. Furthermore, chaperonin GroEL, which is involved in
protein folding after its post-translational translocation to the
mitochondrion/chloroplast, has been suggested to play a key role in
preventing the stress response[68] and apoptosis[69] in the cytoplasm.Photorespiration is
thought to play an important role inpan> excess
energy dissipation under stress conditions, such as high light or
low temperature.[70] A similar function was
also detected in Fe-limited cells of P. tricornutum.[13] Ribulose-1,5-bisphosphate carboxylase/oxygenase
(RuBisCO), the key enzyme used to fix CO2 in photosynthesis,[71] also participates in photorespiration by consuming
the O2 created by photosynthesis (O2 is a competitive
inhibitor of CO2).[72] In the
present study, the abundance of RuBisCO large subunit (Thaps3_bd|1265)
(that has catalytic activity) increased (1.33-fold, p > 0.05), whereas the abundance of the RuBisCO small subunit (Thaps3_bd|1314)
(that can functions as a CO2 reservoir[73]) decreased (0.87-fold, p > 0.05). This
finding indicates that photorespiration may be strengthened to alleviate
oxidative stress under Fe limitation.
PCD Induction
Internally triggered cell death has been
identified in unicellular organisms[74] and
may play a major role in phytoplankton bloom succession and collapse.[24−26] ROS are one of the factors that can induce PCD. When oxidative stress
exceeds the antioxidant capacity of cells, PCD pathways can be induced.
In this study, based on the in vivo staining data and TEM observations,
a markedly higher number of cells underwent PCD under Fe-limited conditions
compared with Fe-replete conditions. Moreover, some proteins that
are closely related to PCD processes were also detected in Fe-limited T. pseudonana cells.As a case in point, the family
of serine proteases comprises enzymes that cleave peptide bonds in
proteins[75] and exhibit caspase-specific
activity.[76] Our results showed that a serine
protease inhibitor (Thaps3|23814) decreased in abundance (0.56-fold),
which could suggest an increase in caspase-specific activity and the
induction of PCD under Fe-limited conditions. In addition, the protein
adenine nucleotide translocator has received much attention due to
its participation in altering the integrity of the mitochondrial membrane,
which promotes apoptosis.[77] The increased
abundance (1.6-fold) of adenine nucleotide translocator (Thaps3|260967)
found in this study was in accordance with the typical features of
PCD, as determined based on our morphological TEM observations (Figure 3E). Therefore, the protein data further confirmed
that some cells were undergoing PCD in response to Fe limitation on
day 4.Furthermore, death-specific protein (DSP), which was
first identified
in the diatom S. costatum, has beenpan> suggested to
play a role inpan> the molecular mechanism of PCD in phytoplankton under
stress.[32]T. pseudonana has two DSP-like proteins (TpDSPs, namely TpDSP1 and TpDSP2), both
of which have a transmembrane domain and calcium-binding EF-hand motifs.[19] A recent investigation indicated that TpDSPs
have a dual role in stress-acclimation and cell death based on the
finding that the transcript levels of TpDSP1 and TpDSP2 genes are
all markedly increased in response to sublethal and lethal ROS.[19] Only one TpDSP, namely TpDSP1 (Thaps3|11118),
was detected in this study. Together with the in vivo staining results,
which showed no difference in the ratio of dead cells between Fe-limited
and Fe-replete cultures on day 4, the decreased abundance (0.72-fold, p > 0.05) of TpDSP1 implied that the TpDSP1 protein may
play a role in cell death under Fe-limited conditions. According to
the different expression patterns obtained for the TpDSP1 gene[19] and protein (this study), which are also supported
by our quantitative RT-PCR findings, we hypothesize that TpDSP may
be subject to post-transcriptional regulation. However, more work
is needed to confirm this hypothesis.Unicellular organism PCD
is considered an altruistic adaptation
designed to benefit a population, as has been demonstrated in bacteria
and yeast.[78−81] Bidle et al. (2004) suggested that PCD may also have evolved in
phytoplankton cells as a strategy to relieve a population from nutrient
stress and remove aging and/or damaged cells from a population to
ensure that they do not become a burden,[24] further supported by studies in P. tricornutum (Vardi
et al. 2006). Therefore, in our study, PCD may be employed as a strategy
to reduce the number of cells in the population, thereby decreasing
the Fe demands of the whole population. Ultimately, the surviving
cells would be able to grow better with an increased Fe supply under
what would otherwise be Fe-limited conditions.
Other Cellular
Responses to Fe Limitation
Intracellular Nitrogen Metabolism in Fe-Limited
Cells
The use of nitrate can be restricted by Fe bioavailability
because
the enzymes involved in nitrate assimilation (nitrate reductase and
nitrite reductase), require Fe as a cofactor. However, analysis of
the nitrogen content in the medium showed that the assimilation of
nitrate was not influenced by Fe limitation in our study, even showed
an increase according to the consumption of per cell (Figure 1C,D). The proteomics data nonetheless showed that
the abundance of ferredoxin subunits of nitrite reductase (Thaps3|2673)
were significantly decreased (0.60-fold), whereas the nitrate reductase
of T. pseudonana was not detected (only one nitrate
reductase [NADH] fragment (Thaps3|24484) was detected and showed a
slightly increased abundance (1.24-fold)). It can be inferred that T. pseudonana cells exposed to early Fe limitation stress
may continue to take up nitrate despite the decrease in reducing power
(inactive nitrite reductase) and build up an internal pool of NO2–, which is in agreement with the findings
reported by Milligan and Harrison (2000)[82] and Allen et al. (2008).[13] Furthermore,
it is well-known that nitrite reductase requires five Fe atoms per
active enzyme, whereas nitrate reductase only requires two. Thus,
we speculate that nitrite reductase is affected prior to nitrate reductase
upon exposure of T. pseudonana cells to early Fe
limitation stress, whereas both enzymes may be affected during chronic
Fe limitation.[18] However, the genes for
nitrate assimilation, such as nitrate reductase, two forms of nitrite
reductase, and a plastid-targeted nitrite transporter, were all down
regulated in Fe-limited P. tricornutum cells,[13] suggesting differences in the responses of individual
species to Fe limitation.Moreover, some enzymes involved in
intracellular amino acid metabolism, specifically cysteine synpan>thase
(Thaps3|14952, 1.82-fold, p > 0.05), methenpan>yltetrahydrofolate
cyclohydrolase (Thaps3|24746, 1.56-fold, p > 0.05),
and glutamate dehydrogenpan>ase/leucinpan>e dehydrogenpan>ase (Thaps3|262098,
1.63-fold, p > 0.05), were found to inpan>crease inpan>
abundance
inpan> Fe-limited T. pseudonana cells. In addition, multiple
aminotransferases, such as ornithine/acetylornithine aminotransferase
(Thaps3|14668, 1.69-fold), aspartate/tyrosine/aromatic aminotransferase
(Thaps3|14577, 1.63-fold), and serine-pyruvate aminotransferase/archaeal
aspartate aminotransferase (Thaps3|22208, 1.58-fold), which are involved
in amino acid reorganization and intracellular recycling, were also
found to increase in abundance. The increased expression of the above-mentioned
proteins could suggest that the intracellular recycling of N-containing
compounds may be enhanced due to Fe-limitation stress. It is interesting
that the aminotransferases detected in this study are totally different
from the types of aminotransferases found in T. pseudonana cells when they underwent chronic Fe limitation stress.[18] Thus, it can be hypothesized that different
intracellular nitrogen-containing compounds may be reallocated due
to different responses between the early and the acclimated stress
response to Fe limitation.Three enzymes associated with the
ornithine-urea cycle (OUC) were
also detected, specifically carbamoyl phosphate synthase large subunit
(Thaps3|12265, 0.96-fold, p > 0.05), argininosuccinate
synthase (Thaps3|25328, 1.27- fold), and arginase (Thaps3|16456, 1.78-fold, p > 0.05). However, other enzymes such as ornithine transcarbamoylase
and argininosuccinase were not detected, and only arginase was found
to be significantly increased in abundance in Fe-limited cultures
compared with Fe-replete cultures. Arginase is an enzyme that catalyzes
the final step in the urea cycle and converts l-arginine
into l-ornithine and urea.[100,83] In addition,
the difference in the expression levels of the urease enzyme between
the Fe-replete and Fe-limited cultures was not significant. Thus,
the accumulation of urea may be as a nitrogen reserve to alleviate
nitrogendeficiency caused by iron limitation in T. pseudonana based on the hypothesis that urea can also provide nitrogen to diatoms.[84] However, arginase was not detected and carbamoyl
phosphate synthase was found to increase in abundance when T. pseudonana was acclimated to Fe limitation.[18] These different responses of the OUC between
the early stress response and the acclimated response indicate that
different cellular strategies are employed.
Intracellular Iron Metabolism
in Fe-Limited Cells
Fe
acquisition by T. pseudonana occurs via a Fe(II)
ferroxidase/permease pathway, the molecular components of which consist
of two ferric reductases (FRE1 and FRE2), two iron permeases (FTR1
and FTR2), a ferroxidase (FET3), and the divalent metal transporter
NRAMP.[15,19] However, only the plasma membrane iron permease
(FTR1, Thaps3|20774) was detected and found to increase in abundance
(1.54-fold) in this early stress response of Fe-limited cells, which
is consistent with the acclimation response of T. pseudonana to Fe limitation[18] (Nunn et al, 2013).
This result suggests that a similar cellular strategy may be employed
between these two responses, namely that T. pseudonana could increase production of FTR1 for Fe acquisition by endocytic
recycling when limited by Fe.[18]Moreover,
the cells reduced their iron proteinpan> demands by using iron-free proteins
with similar functions, e.g., ferredoxin was replaced by flavodoxin.
In addition, proteins that do not require heme as a coenzyme or iron
as a cofactor were found to increase in abundance during the antioxidant
and anti-apoptotic processes reported here. Thus, we propose that
the cell regulates its own protein expression to reduce the consumption
of iron such that it is able to adapt to the environmental stress
associated with iron limitation.
Intracellular Silicon Metabolism
in Fe-Limited Cells
It is interesting that silicon uptake
was also found to be enpan>hanced
by Fe-limitation (Figure 1). A higher silicon
concentration in the medium was consumed under Fe-limited compared
to Fe-replete conditions on day 4. Even the medium of Fe-replete cultures
was completely depleted of silicon by day 5, while approximately 100
μm of silicon was still present in the medium of Fe-limited
cultures. More silicon was taken up by Fe-limited cells than by Fe-replete
cells on day 5, which was calculated based on the cell number. Our
result is consistent with the previous finding that Fe limitation
induced silica deposition in T. pseudonana, as demonstrated
by the upregulation of the gene encoding silaffin 1 (a protein associated
with silica deposition, SIL 1), as well as with the observation that
the frustules of Fe-limited cells are thicker and more heavily silicified
than Fe-replete cells (Mock et al, 2008).[17] Our finding therefore support a possible link between iron bioavailability
and silica deposition (Mock et al., 2008).[17]
Conclusions
In this study, iTRAQ proteomic profiles,
inpan> vivo biochemical markers
and physiological characteristics represent not only a comprehensive
systematic analysis of the early stress response of diatoms to Fe
limitation, but also a large amount of information about previously
uncharacterized cellular metabolism processes and proteins involved
in ROS accumulation and PCD induction in response to short-term Fe
limitation. Our observations provide a new molecular view about the
diatom response to oxidative stress and control of cell fate: reduction
of the cell population by PCD to reduce the consumption of Fe, enhancement
of the turnover and reallocation of intracellular nitrogen and Fe
into key cellular components to ensure the most basic survival and
defense, and the increased abundance of antioxidant and anti-PCD proteins
to ensure cell survival. These results significantly increase our
understanding of how diatom cells control their life and death during
blooms, and the molecular mechanism of diatoms involved in their survival
and competition strategies to cope with trace metal fluctuations in
the marine environment.
Authors: Assaf Vardi; Kay D Bidle; Clifford Kwityn; Donald J Hirsh; Stephanie M Thompson; James A Callow; Paul Falkowski; Chris Bowler Journal: Curr Biol Date: 2008-06-05 Impact factor: 10.834
Authors: Ben P Diaz; Ben Knowles; Christopher T Johns; Christien P Laber; Karen Grace V Bondoc; Liti Haramaty; Frank Natale; Elizabeth L Harvey; Sasha J Kramer; Luis M Bolaños; Daniel P Lowenstein; Helen F Fredricks; Jason Graff; Toby K Westberry; Kristina D A Mojica; Nils Haëntjens; Nicholas Baetge; Peter Gaube; Emmanuel Boss; Craig A Carlson; Michael J Behrenfeld; Benjamin A S Van Mooy; Kay D Bidle Journal: Nat Commun Date: 2021-11-17 Impact factor: 14.919