noncoding and coding transcriptome responses of a marine diatom to phosphate fluctuations

7/25/2019 Noncoding and coding transcriptome responses of a marine diatom to phosphate fluctuations

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to identify genes responsive to these changes. Physiological andglobal transcriptomic changes were assessed in the model pennatediatom Phaeodactylum tricornutum during the early and latestages of Pi depletion over the course of 8 d, as well as on Piresupply. These changes were compared with cultures growing inreplete medium.

Materials and Methods

Diatom culture conditions

Axenic cultures of Phaeodactylum tricornutum (Bohlin) strainCCMP632 were obtained from the Center for the Culture ofMarine Phytoplankton (East Boothbay, ME, USA) and main-tained under continuous shaking (100 rpm) in 250 ml of filtered(0.22 lM) steam-sterilized artificial sea water (Sigma) supple-mented with f/2 nutrients, elements and vitamins (Guillard &Ryther, 1962), with the exception of silica (f/2-Si), in 1-l glassflasks. Cultures were kept at 20C under cool white fluorescent

lights at 100 lmol m2

s1

with a 12-h photoperiod. For the Pifluctuation studies, equal aliquots of 4-d-old cultures from thesame batch culture were inoculated in parallel in 250 ml of freshf/2-Si medium (control conditions) and in 250 ml of fresh f/2-Simedium without phosphate supplement (Pi depleted), and cul-tured in the same conditions as described earlier. Culture growthwas followed using a hematocytometer (Fisher Scientific,Pittsburgh, PA, USA) and the growth rate was calculated usingthe natural logarithm of the difference in cell density during thefirst 4 d of growth. P-replete and P-depleted cultures were allstarted with the same initial cell densities of c.4.59 105 cells ml1. Pi resupplementation was performed on4-d-old Pi-depleted cultures. Briefly, c. 4050 ml of 4-d-old Pi-depleted cultures were pelleted by centrifugation for 10 min at1500gand resuspended in 250 ml of fresh f/2-Si medium (start-ing cell densities of c. 29 105 cells ml1). Cells (250 ml) wereharvested always at midday (6 h of light period) by vacuum fil-tration (0.22 lM) at different treatment time points, flash frozenin liquid N2 and maintained at 80C until use. The filteredmedium was used to measure the Pi content employing aSensoLyte MG Phosphate Assay Kit (AnaSpec, Fremont, CA,USA) following the manufacturers instructions. Experimentswere performed using duplicates of Pi-depleted cultures thatwere harvested in bulk. All the experiments were repeated atleast twice.

Confocal laser microscopy

Cells were sampled for confocal laser microscopy at the sametreatment time points as used for strand-specific RNA sequencing(ssRNA-Seq). For the staining of lipids, 2 ll of a freshly preparedNile Red solution (250 lg ml1 in acetone) were added to a 1-mldiatom cell suspension. After 30 min staining in the dark at roomtemperature, cells were washed by pelleting for 10 min at 1500 gand then resuspended in 500 ll of sterile seawater (Sigma). Con-focal microscopy analysis of the dyed diatom cell suspension wasperformed using an LSM 780 laser scanning confocal microscope

(Zeiss) with excitationemission wavelengths of 594 nm forchlorophyll and 488 nm for Nile Red.

RNA extraction, library preparation and ssRNA-Seq

Total RNA was extracted from P. tricornutumflash-frozen cellpellets using the Trizol method according to the manufacturers

instructions (Invitrogen). Extracted RNA was treated withTurboDNAse I (Life Technologies AM2238, Carlsbad, CA,USA) according to product instructions and the treated RNA waspurified using an RNeasy spin column (Qiagen) with 0.5 volumesof ethanol, washed and then eluted with 50ll of room-temperature molecular-grade water (Qiagen). The quality of thepurified RNA was assessed using an Agilent 2100 Bioanalyzer(Agilent, Santa Clara, CA, USA). cDNA libraries for ssRNA-Seqwere prepared using the Illumina TruSeq Stranded mRNA Sam-ple Preparation Kit following the Low Sample (LS) Protocolguidelines (Illumina, San Diego, CA, USA) from two indepen-dent experiments.

ssRNA-Seq data assembly and analysis

ssRNA-Seq reads were mapped to the P. tricornutum genome(Phatr2) using TopHat (version 2.0.8) (Kim et al., 2013). Themapped reads were assembled using CUFFLINKS (v.2.1.1) (Trap-nell et al., 2013) with Phatr2 annotation as the reference(Nordberg et al., 2014). The assembled transcripts of eachssRNA-Seq sample were merged and annotated using CUFFCOM-PARE (v.2.1.1) (Trapnell et al., 2013). The expression levels ofeach gene were then calculated from the fragments per kilobaseof exons per million fragments mapped (FPKM) using CUFFDIFF(v.2.1.1) (Trapnell et al., 2013). The Pearson correlation coeffi-cients (PCCs) were calculated between the FPKM of two repli-cates of each five physiological states corresponding to twoindependent experiments. As the PCCs were high (> 0.9), wepooled the reads derived from the two replicates in order toincrease the depth of the reads for the increased detection of non-coding RNA transcripts. A two-fold variance in FPKM and aPvalue (Fishers exact test) of < 0.05 were used as cutoffs todefine differentially expressed genes. The reads from both repli-cates have been deposited in the Gene Expression Omnibus(GEO) databasehttp://www.ncbi.nlm.nih.gov/geo(accession no.GSE66997).

Quantitative real-time reverse transcription PCR

Total RNA was isolated and purified fromP. tricornutumcells asdescribed above. For cDNA synthesis, 500 ng of total RNA wasincubated with SuperScript III Reverse Transcriptase (Invitrogen)according to the manufacturers instructions. For quantitativereverse transcription polymerase chain reaction (RT-qPCR) anal-ysis, cDNA was amplified using SYBR Premix ExTaq (Takara,Madison, WI, USA) with specific primers (Supporting Informa-tion Table S2) picked from random genes from those most highlyexpressed under Pi depletion. Primers were designed with thePRIMER-BLAST program (http://www.ncbi.nlm.nih.gov/tools/

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primer-blast/) defining a PCR amplicon size of < 180 bp andPhaeodactylum tricornutumCCAP 1055/1 (taxid: 556484) as thereference organism to check for primer pair specificity. Quantita-tive PCR conditions were set as follows: 95C for 10 s, followedby 40 cycles of 95C for 5 s and 60C for 30 s, and a final cycleof 95C for 10 s and 60C for 5 s. Data were collected and ana-lyzed by a Bio-Rad CFX96 real-time system (BioRad, Hercules,

CA, USA).CDKAand HISTONE 4mRNA levels were used fornormalization (Siautet al., 2007).

Correlation analysis between transcription factors (TFs) andputative target genes

To predict the gene targets of selected transiently expressed heatshock factors (HSFs), the PCCs were calculated using FPKMs vsall Pi-responsive protein coding genes as well as noncoding genes.Only the positively correlated gene targets (PCC> 0 andr2 0.6) were retained. As HSFs bind to heat shock elementswithin promoter regions of their target genes (Nover et al.,

2001), only targets with the conserved sequence 50

GAAnnTTC30

in their promoter sequences (broadly defined as sequences 3 kbupstream of the transcriptional start site) were considered. Theresults of the correlation analysis were visualized using Cytoscape(v2.8.3) (Smootet al., 2011).

Identification of long intergenic nonprotein coding RNAs(lincRNAs) and characterization of their genomic features

All assembled intergenic transcription units were collected aslincRNA candidates. Candidates with a length of 200nucleotides and a predicted open reading frame (ORF) of 100amino acids were defined as lincRNAs (Liu et al., 2012). Whenconsidering gene models of protein coding genes, the best genemodels obtained from the Phatr2 annotation were used; forthose of lincRNAs, the gene models with maximum intron num-bers were used. The lengths of entire unspliced transcripts (in-cluding introns) were used to compare transcript lengthdistribution. For ORF predictions, the spliced transcripts wereused and sent to GenScan (Burge & Karlin, 1997). To comparethe length of stop codon-free sequences, the distances betweeneach stop codon of each gene in three reading frames were calcu-lated, as described previously (Niazi & Valadkhan, 2012). Mfoldwas used to calculate the free energy of the spliced transcripts(Zuker, 2003). As longer transcripts have lower free energy, to

better compare the free energy of lincRNAs and mRNAs fromprotein coding genes, we classified them into different groupsbased on sequence length. This was also performed when com-paring the free energy with the GC contents of lincRNAs andmRNAs.

To find putativecis-regulation of lincRNAs on their neighbor-ing genes, the PCCs were calculated using FPKMs of all theresponsive lincRNAs vs mRNAs encoded by their neighboringupstream and downstream genes. Only those Pi-responsiveneighboring genes withr2 0.6 (positive or negative correlation)were considered as putative gene targets of cis-regulatorylincRNAs.

Results and Discussion

Culture growth and transcriptomic responses under Pifluctuations

WhenP. tricornutumcultures were exposed to Pi depletion in themedium (Fig. S1), their exponential growth ceased rapidly when

compared with control cultures (Fig. 1a,b). Control cultures con-tinued to grow for 8 d, reaching a cell density of c.4.89 106 cells ml1, whereas cultures without Pi grew for thefirst 2 d, peaking at a maximum cell density of c.1.39 106 cells ml1, and then transitioned to stationary growth(Fig. 1a). This was accompanied by lipid accumulation that wasdetected after 4 d of Pi depletion and further increased after 8 d(Fig. 1c). Neutral lipid accumulation is a common response ofmicroalgae under unfavorable conditions, namely nutrient stress(Fieldset al., 2014). When Pi was resupplied to 4-d starved cul-tures, culture growth recovered to control rates after 4 d and lipidbodies were no longer detected (Figs 1b,c, S2). These observa-

tions allowed us to define five distinct physiological states to beused as sampling points for the comparative transcriptomic stud-ies: control 4 d (early control), Pi 4 d (early Pi depletion),control 8 d (late control), Pi 8 d (late Pi depletion) and re-covery 4 d.

ssRNA-Seq data generated from the five physiological stateswere assembled and mapped (Table S1), yielding 10 083 genescorresponding to 97% of the P. tricornutum annotated proteincoding genome (genome.jgi-psf.org/Phatr2). Globally, 6436 pro-tein coding genes were differentially expressed in response to Pifluctuations when compared with the control, with the relativeportion of up- and downregulated genes being approximately thesame (Fig. 2a). During early Pi depletion, the number of upregu-

lated genes was slightly lower than those upregulated at late Pidepletion and at recovery (1503, 1958 and 1991, respectively)(Fig. 2a). The number of downregulated genes was the lowest forrecovery (1396) and the highest for late Pi stress (2368), withearly Pi stress showing the downregulation of 2032 genes(Fig. 2a). The expression of 21 of the most responsive proteincoding genes during Pi depletion was further verified by RT-qPCR. These included genes coding for Pi transporters, alkalinephosphatases (AlkPases), heat shock proteins, HSFs and severalproteins of unknown function (Table S2). A good correlationbetween transcript abundance was found between ssRNA-Seqdata and RT-qPCR (r= 0.8,P? 0) validating the robustness of

ssRNA-Seq data (Figs 2b, S3).

The plethoric origin of the diatom P-responsive genes

A striking aspect uncovered by the sequencing of the diatomgenomes is the diverse origin of their genes. To a large extent, thisis the result of their complex evolutionary origin, making diatomsnot quite plants nor animals (Armbrustet al., 2004; Bowleret al.,2008). In order to investigate the origins of the Pi differentiallyexpressed genes, we compared their protein sequences with thosein the National Center for Biotechnology Information nonre-dundant (NCBI nr) database using BLASTp. The criteria used to

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define genes that were present in one species were those pub-lished previously (Armbrust et al., 2004; Bowler et al., 2008): 30% sequence positives; 30% alignment coverage of eitherthe query or subject sequences; and BLAST e-value of< 1e-5. Thelarger fraction of Pi differentially expressed genes (30%) corre-sponded to proteins common to plants and animals (Eukaryotes),20% were core proteins and 19.4% were exclusively of plantorigin (Fig. 2c). Shared proteins between P. tricornutum andThalassiosira pseudonana constituted < 2% of the differentiallyexpressed genes, and those found exclusively in P. tricornutumaccounted forc. 16% (Fig. 2c). The latter are probable de novogenes that have evolved since the two diatom lineages diverged c.

90 million yr ago (Bowler et al., 2008). Seventy-seven differen-tially expressed genes were exclusively found in bacteria and wereabsent in all other organisms (Fig. 2c). Many of the bacterialgenes that responded to Pi fluctuation were related to metabolismand redox processes. Interestingly, included in the Pi differen-tially expressed genes were 123 genes also present in viruses, someof which were simultaneously present in plants (four), in plantsand bacteria (19), in animals and bacteria (five) and in all thegroups (62), suggesting a possible horizontal viralhost geneexchange. These consisted largely of membrane proteins, includ-ing several putative signaling protein kinases and Pi transporters.The presence of Pi transporter genes in several virus genomes

suggested the occurrence of viral manipulation of the infectedhost capacity for Pi uptake (Monier et al., 2012). Overall, 80%of the differentially expressed protein coding genes were sharedwith plants and 50% shared with animals, amongst which a smallfraction (< 1%, 64 genes) was absent from plants. These includedannotated genes for metabolism, DNA methylation and a puta-tively secreted AlkPase (49678). Our data strongly support theview that the physiology of the P-starved diatom response resultsfrom a combination of genes of diverse origins, probably formingoriginal metabolic pathways, such as the recently dissected ureacycle (Allen et al., 2011), enabling the resilience and success ofdiatoms in a fluctuating environment.

Pi depletion and Pi resupply define distinct physiologicaland transcriptomic profiles

In order to assess the function of the differentially expressed genesunder Pi fluctuation, we performed a search on the available geneontology (GO) terms of the annotated transcripts and analyzedtheir relative over-representation in the five distinct physiologicalstates. During early Pi depletion, the upregulated protein codinggenes that were most significantly over-represented were putativephosphate transporters, revealing an active molecular strategy toincrease the efficiency of Pi uptake (Fig. 3a). Other over-

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Fig.1 Phaeodactylum tricornutumresponsesto inorganic phosphate (Pi) fluctuations. (a)Time course of cultures grown in fullysupplemented medium (closed circles) andPi-depleted medium (open circles); and (b)mean growth rates (natural logarithm, loge)of the first 4 d of culture under fully repletecontrol conditions (C), Pi depletion (Pi) andPi resupply after 4 d of Pi depletion (+Pi).Data represent SD of two independentexperiments (with at least three biologicalreplicates each). Statistically significantdifferences between treatment and controlcultures were assessed by a Studentst-test:

**,P < 0.01; *,P < 0.05. (c) Confocal lasermicroscopy of diatom cells in the five distinctphysiological states: C 4d, 4 d under controlconditions; Pi 4d, 4 d Pi depleted;Pi 8d,8 d Pi depleted;+Pi 4d, 4 d Pi resupply after4 d Pi depleted; C 8d, 8 d control conditions.Cells were stained with Nile Red (NR) tovisualize lipid bodies (green color).Chloroplasts can be visualized by thechlorophyll autofluorescence (red color).Bars, 10 lm. Chl, chlorophyllautoflorescence; DIC, differentialinterference contrast.


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represented GO enrichments were for protein coding genesbelonging to several metabolic pathways involved in carbohydratemetabolism and catabolism (Fig. 3a). This points to the occur-rence of a general shift in carbon metabolism in response to Pi

depletion. The regulation of intermediate carbon metabolism hasbeen demonstrated previously to be essential for the growth opti-mization of N-starvedP. tricornutum(Allenet al., 2011; Levitanet al., 2015), which suggests that the same adaptive metabolicprocesses also operate in response to P starvation. Under late Pidepletion, cells were probably severely P starved because of theprolonged Pi scarcity and possibly the consumption of internalreserves. Other over-represented GO enrichments in the upregu-lated genes during this stage were ubiquitin cycle-associatedterms, and genes encoding components in intracellular signalingcascades and chromatin organization (Fig. 3a). The downregu-lated genes most significantly over-represented during early Pi

depletion encoded proteins involved in the photosynthetic lightreactions, and transcripts for these genes declined further duringlate Pi depletion (Fig. 3b). The over-representation of the down-regulated genes relating to photosynthesis also occurred during

the late exponential phase when cell population growth wasentering into stationary phase (Fig. 1a). Reduction of the photo-synthetic machinery by the downregulation of genes involved inthe light reactions in photosystem II (PSII) and photosystem I(PSI) is ultimately beneficial to a cell being subjected to a nutri-tive imbalance by reducing the generation site of reactive oxygenspecies, and hence oxidative stress. A reduction in photosyntheticactivity has been reported previously to occur in P. tricornutumunder P scarcity (Yanget al., 2014), as well as under N stress(Yanget al., 2013; Levitan et al., 2015). Our data highlight theexistence of a stringent relationship between nutrient supply andthe genomic control of photosynthesis. When Pi was resupplied

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Fig.2 Genome-wide transcriptome analysis ofPhaeodactylum tricornutumresponse to inorganic phosphate (Pi) fluctuations. (a) Venn diagramsrepresenting the up- and downregulated genes in response to progressive Pi depletion and resupply. Cutoff of two-fold difference in fragments perkilobase of exons per million fragments mapped, P < 0.05, when compared with 4 d control cultures. Pi 4d, 4 d Pi depleted;Pi 8d, 8 d Pi depleted;+Pi

4d, 4 d Pi resupply after 4 d Pi depletion. (b) Correlation between strand-specific RNA-sequencing (ssRNA-Seq) and quantitative reverse transcriptionpolymerase chain reaction (RT-qPCR) in the detection of Pi-responsive Phaeodactylum tricornutumgenes. Thex-axis gives the log2value of the foldchange detected by ssRNA-Seq and they-axis gives the same value detected by RT-qPCR. Green dots represent differentially expressed (DE) genesdetected by both platforms; gray dots represent genes that do not change by more than two-fold in expression under Pi fluctuation. (c) Gene origins of the6436 Pi DE protein coding genes.Phaeodactylum tricornutumprotein sequences were compared with the National Center for Biotechnology Informationnonredundant (NCBI nr) database using BLASTp. The criteria used to define genes that were present in one species were as follows: 30% sequencepositives; 30% alignment coverage of either the query or subject sequences; and a BLASTe-value of < 1e-5. Core, proteins present in animals, plants,bacteria; Unique, proteins only found in P. tricornutum; Diatom, proteins common toThalassiosira pseudonanaandP. tricornutum.

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to the medium, the over-represented upregulated genes coded forproteins involved in unsaturated fatty acid biosynthetic/metabolic processes and DNA replication initiation and DNApackaging (Fig. 3a); these proteins are involved in the resumptionof active cell growth under recovery (Fig. 1c). Furthermore, otherover-represented upregulated genes during recovery includedthose putatively involved in epigenetic modifications, such aschromatin and nucleosome assembly, DNA packaging and chro-mosome assembly (Fig. 3a), suggesting a new acclimated epige-nomic state anticipating repeated Pi-depleted conditions.

Optimization of P scavenging under Pi depletion

Common strategies used by microorganisms and plants to opti-mize Pi scavenging in response to Pi scarcity include an increasein the number of Pi transporters and/or replacement of low-affinity transporters with higher affinity ones, and the productionof phosphatases to utilize organic P sources from the environ-ment (Clarket al., 1998; Riegman et al., 2000; Vance et al.,2003). In a recent report, five of the six annotated Pi transportergenes inP. tricornutumwere upregulated after 48 h of Pi deple-tion (Yanget al., 2014). Manual curation and analysis of con-served domains enabled us to identify several new putative Pi

transporter genes in P. tricornutum, with the number increasingto 24 (Fig. 4a). This is approximately the same number of Pitransporters as annotated in Arabidopsis thaliana (The

Arabidopsis Information Ressource, TAIR, database), whereasChlamydomonas reinhardtiihas 14 annotated putative Pi trans-porters (Grossman & Aksoy, 2015). Twelve of the Pi transportergenes inP. tricornutumwere highly upregulated under Pi deple-tion, with 11 being dramatically downregulated on Pi resupply(Fig. 4a), revealing a tight regulation of their expression level byenvironmental Pi concentration. These results suggest thatdiatoms are equipped with a highly responsive Pi transporter sys-

tem programmed to operate only when Pi is scarce. Five of thehighly induced Pi transporters have been annotated as Na+/Pi co-transporters, a type of transporter that occurs in phytoplankton,yeast and vertebrates, but which is lacking in plants. Interestingly,the five Na+/Pi co-transporters in P. tricornutum share moresequence homology to mammalian renal Pi transporters than toyeast, bacterial or green algae (Chlamydomonas) Na+/Pi co-transporters.

Also supporting the notion of optimized Pi uptake under Pidepletion was the very high induction of five genes coding for

AlkPases, with three expressed > 1000-fold under late Pi stress(Fig. 4a). Marine bacteria have been shown to have a large

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Phosphate transportNucleode-sugar metabolic processInorganic anion transport

Anion transportGlycolysisGlucose catabolic processMonosaccharide catabolic processHexose catabolic processAlcohol catabolic processCarbohydrate catabolic processCellular carbohydrate catabolic processGlucose metabolic processHexose metabolic processMonosaccharide metabolic processCellular carbohydrate metabolic processAlcohol metabolic processUbiquin cycleUnsaturated fay acid biosynthec processUnsaturated fay acid metabolic processPhosphoenolpyruvate-dependent sugar phosphotransferase systemRegulaon of metabolic processIntracellular signaling cascadeDNA replicaon iniaonDNA packagingChroman assembly or disassemblyChroman assemblyChroman organizaonProtein-DNA complex assemblyNucleosome assembly

Nucleosome organizaonChromosome organizaonDeoxyribonucleode metabolic processOrganelle organizaonRegulaon of gene expressionRegulaon of macromolecule metabolic processEstablishement of localizaonLocalizaonGene expressionTransportNitrogen compound metabolic processNucleobase, nucleoside, nucleode and nucleic acid metabolic process

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Negave regulaon of catalyc acvityNegave regulaon of molecular funconPhotosynthesisPhotosynthesis, light harvesng

Photosynthesis, light reaconAmine transportAmino acid transportSecondary metabolic processCarboxylic acid transportOrganic acid transportPorphirin biosynthec processTetrapyrrol biosynthec processTetrapyrrol metabolic processPorphyrin metabolic processIsoprenoid biosynthec processIsoprenoid metabolic processResponse to oxidave stressBranched chain family amino acid metabolic processInorganic anion transportAnion transportncRNAprocessingncRNA metabolic processRNA processingtRNAmetabolic processRNA metabolic processCyclic nucleode metabolic processCyclic nucleode biosynthec processNucleoside monophosphate biosynthec processNucleoside monophosphate metabolic processHeterocycle biosynthec process

Nucleoside phosphate metabolic processNucleode metabolic processCofactor biosynthec processCofactor metabolic processTranscriponUnsaturated fay acid metabolic processUnsaturated fay acid biosynthec processFay acid biosynthec processFay acid metabolic processDicarboxylic acid metabolic processPigment biosynthec processLipid biosynthec processCellular lipid metabolic process

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Fig.3 Gene ontology (GO) enrichment analysis of (a) upregulated and (b) downregulated genes in the transcriptome response of Phaeodactylumtricornutumto inorganic phosphate (Pi) fluctuations. The top 15 (highest odds ratio) enriched GO terms of the biological process category in each sampleare shown. The odds ratio was defined as the ratio of the proportion of a GO term in (a) upregulated and (b) downregulated genes to the proportion ofthis GO term in all diatom genes. The larger the odds ratio, the higher the relative abundance of this GO term compared with background. Multiple-testadjustedP < 0.05 was used to define statistical significance. Pi 4d, 4 d Pi depleted;Pi 8d, 8 d Pi depleted;+Pi 4d, 4 d Pi resupply after 4 d Pi depletion; C8d, 8 d control conditions.


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fraction of AlkPases secreted under Pi-deficient conditions (Luoet al., 2009). InP. tricornutum, one of the AlkPases (49678) waspredicted to be secreted. This AlkPase has been biochemicallycharacterized previously (termed PtAPase) and has been shown tobe released to the medium in response to Pi depletion (Lin et al.,2013). InT. pseudonana, several AlkPases have been shown to beupregulated on Pi depletion in both the transcriptome and pro-

teome (Dyhrman et al., 2012). Furthermore, the authors alsoshowed that AlkPase activity triggered by Pi depletion was mainlysurface associated with some intracellular location (Dyhrmanet al., 2012). This, together with our data, suggests a similar loca-tion of activity ofP. tricornutumAlkPases.

Maintenance of P homeostasis in diatoms has common anddistinct characteristics compared with higher plants

The ability to economize cellular Pi demands by the replacementof membrane phospholipids by sulfolipids is known to occur inplants (Vance et al., 2003), in Chlamydomonas (Grossman &

Aksoy, 2015) and in phytoplankton (Van Mooyet al., 2009;Martin et al., 2011; Dyhrman et al., 2012; Abidaet al., 2015).Under prolonged Pi-depleted conditions (13 d), a total disap-pearance of phospholipids, with a concomitant increase in diacyl-glyceryl-hydroxymethyl-N,N,N-trimethyl-b-alanine (DGTA),sulfoquinovosyldiacylglycerol (SQDG) and digalactosyldiacyl-glycerol (DGDG), has been reported recently in P. tricornutum(Abidaet al., 2015). Membrane phospholipids in P-starved Ara-bidopsis plants have been shown to be cleaved by phospholipasesC (Nakamuraet al., 2005; Gaude et al., 2008) and D (Cruz-Ramrez et al., 2006). In this work, two phosphatidylinositol-specific phospholipases C (PI-PLC) were specifically upregulated

on early Pi depletion, and three others were upregulated duringlate Pi stress (Fig. 4b). Two genes encoding phospholipases Dwere also upregulated throughout Pi depletion (Fig. 4b). Thissupports the occurrence of membrane phospholipid degradationunder Pi depletion, similar to that which occurs in Arabidopsis.It also shows that the process of membrane phospholipid degra-dation under Pi depletion is regulated at the transcriptional level.

Different from the observations in Arabidopsis, the polar lipidthat increases most strongly in P. tricornutummembranes underPi stress is DGTA, a betaine glycerolipid (Abidaet al., 2015).This is corroborated by our transcriptome data, where a putativeDGTA enzyme (ARF4, 42872) was expressed > 30-fold underearly Pi depletion and > 80-fold under late Pi depletion (Fig. 4b).Two genes coding for sulfolipid synthases (SQD2) were alsohighly induced during early and late Pi depletion (up to 13-foldexpression increase) and, to a lesser extent, a gene coding for amonogalactosyldiacylglycerol synthase (MGD2) (Fig. 4b). Thesedata corroborate, at the transcriptional level, previous findings(Yanget al., 2014; Abidaet al., 2015). They also confirm that

membrane remodeling events in P. tricornutumare tightly regu-lated at the transcriptional level and are related directly to Pscarcity.

Neutral lipid accumulation is a common response of microal-gae under unfavorable conditions, namely nutrient stress (Fieldset al., 2014), and, in the present study,P. tricornutumcells accu-mulated large lipid bodies after 8 d of Pi depletion (Fig. 2c). Wesuggest that the lipids resulting from the remodeling of mem-branes were shifted in the form of triacylglycerol (TAG) to thenascent lipid bodies. In Dunaliella salina, fatty acids typicallyfound in chloroplast membrane galactolipids have been detectedin storage lipids (Cho & Thompson, 1986). Membrane

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Pitransporters

47239 Na+/Pi co-transporter47666 Na+/Pi co-transporter39515 Pi transporter23830 Pi transporter

47667 Na+/Pi co-transporter22315 Pi transporter21441 Na+/Pi co-transporter33266 Na+/Pi co-transporter40433 Na+/Pi co-transporter46692 Pi transporter19030 HYP22279 HYP1277 Pi transporter14922 Na+/tricarboxylate and Pi transporter43646 HYP17265 HYP22453 Na+/tricarboxylate and Pi transporter47954 Mito Pi carrier protein462 Mito Pi carrier protein11414 Mito Pi carrier protein37916 Mito Pi carrier protein8987 Mito Pi carrier protein11866 HYP49842 Na+/Pi co-transporter

39432 Alkaline phosphatase49678 Alkaline phosphatase47869 HYP45959 Alkaline phosphatase

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42872 Putave DGTA synthesis enzyme43665 Phosphadylinositol-specific phospholipase C (PI-PLC)50356 Sulfoquinovosyldiacylglycerol 2 (SQD2)42467 Sulfoquinovosyldiacylglycerol 2 (SQD2)

9619 Monogalactosyldiacylglycerol synthase 2 (MGD2)46400 Phospholipase D (PLD)49771 Phosphadylinositol-specific phospholipase C (PI-PLC)12431 Phospholipase D (PLD)46908 Phosphadylinositol-specific phospholipase C (PI-PLC)8860 Phospholipid:diacylglycerol acyltransferase (PDAT)1000 Phosphadylinositol-specific phospholipase C (PI-PLC)1611 Phosphadylinositol-specific phospholipase C (PI-PLC)40261 Phosphadate phosphatase (PAP1)43116 Digalactosyl diacylglycerol synthase 1 (DGD1)11390 Digalactosyl diacylglycerol synthase 1 (DGD1)48445 Phosphadylinositol-specific phospholipase C (PI-PLC)54168 Monogalactosyldiacylglycerol synthase 1 (MGD1)42683 Phosphadylinositol-specific phospholipase C (PI-PLC)12884 Digalactosyl diacylglycerol synthase 1 (DGD1)14125 Monogalactosyldiacylglycerol synthase 1 (MGD1)3262 Phospholipid/glycerol acyltransferase (ACT1)36877 Phospholipase D (PLD)34555 Phospholipase D (PLD)47576 Phospholipase D (PLD)43099 Phospholipid/glycerol acyltransferase (ACT1)

50019 VTC15281 VTC48538 VTC54257 VTC

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Fig.4 Heat maps of log2fold expression changes under inorganic phosphate (Pi) fluctuation of putative (a) Pi transporters and alkaline phosphatase(AlkPase) coding genes and (b) membrane lipid metabolism and polyphosphate metabolism (PolyP) coding genes in Phaeodactylum tricornutum. Numberscorrespond to Joint Genome Institute (JGI) protein identifiers. Pi 4d, 4 d Pi depleted;Pi 8d, 8 d Pi depleted;+Pi 4d, 4 d Pi resupply after 4 d Pi depletion;C 8d, 8 d control conditions.

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phospholipids can enter the TAG metabolic pathway by directconversion to diacylglycerol (DAG) by phospholipid diacylglyc-erol acyltransferase (PDAT)-catalyzed transesterification. Thegene encoding PDAT, an acyl-CoA-independent pathwayenzyme for the production of TAGs, initially characterized inyeast (Dahlqvist et al., 2000; Oelkers et al., 2000), has anortholog in A. thaliana (Stahl et al., 2004) and in C. reinhardtii

(Merchantet al., 2012). An ortholog of PDAT is also present inP. tricornutum(8860), being specifically upregulated during earlyand late Pi stress (Fig. 4b), further supporting a role for mem-brane phospholipid recycling to the TAG pathway during Pidepletion. A recent report has shown that N depletion inP. tricornutum leads to the remodeling of membranes, and thatthe PDAT gene ortholog is concomitantly upregulated, support-ing its involvement in the movement of membrane phospholipidsto the TAG pathway (Yanget al., 2013).

Polyphosphate (PolyP), the most important phosphate reserveused on Pi depletion in yeast, is synthesized through the vacuolartransporter chaperone (VTC) complex (Ogawaet al., 2000).

Unlike plants, diatoms have VTC orthologs, and these proteinshave been shown to increase Pi allocation to PolyP in response toN deficiency (Perry, 1976) and Pi deficiency (Dyhrman et al.,2012). Genes encoding VTCs appeared to be regulated, at leastpartially, at the transcriptional level, as two genes coding forputative VTC proteins were significantly upregulated in responseto Pi deficiency in T. pseudonana (Dyhrman et al., 2012). Fourgenes encoding proteins with a VTC domain (IPR018966) weredetected inP. tricornutum, with two being highly upregulated inresponse to Pi depletion and the other two in response to Piresupply (Fig. 4b), suggesting distinct roles in PolyP metabolismin response to Pi concentration.

Long noncoding transcripts specifically induced in responseto Pi depletion

The P starvation response in plants involves the induction of sev-eral RNA transcripts with no protein coding potential, whichhave been described as having a key role in the regulation of Phomeostasis. These noncoding RNAs include several precursorsof micro-RNAs (miRNAs), such as miR399 and miR827,involved in the regulation of signaling pathways and Pi transportunder Pi depletion (Bari et al., 2006; Hsieh et al., 2009).

Although the function of miRNAs in diatoms remains to be veri-fied (Lopez-Gomollon et al., 2014; Rogato et al., 2014), gene

silencing has been shown to occur (De Riso et al., 2009). In thepresent work, two annotated miRNA precursors (pti-MIR5472and pti-MIR5471; Huanget al., 2011) were significantly upregu-lated in response to Pi stress in P. tricornutum (Table S3),although functional studies are needed to examine the relevanceof these transcripts in the diatom Pi response.

Pi starvation in plants also involves longer nonprotein codingtranscripts, such as INDUCED BY PHOSPHATESTARVATION 1 (IPS1). This transcript has a small ORF, butwas later found to be active as an RNA molecule, target mimick-ing miR399 (Franco-Zorrillaet al., 2007). IPS1 is recognized bymiR399 as a target; however, as a result of mismatches in the

recognition sequence, their binding does not lead to miR399-assisted cleavage and remains stable, which results in the fine-tuning of Pi uptake (Franco-Zorrillaet al., 2007). We have thor-oughly analyzed theP. tricornutumnoncoding transcriptome andhave identified 1510 putative lincRNAs (Table S4), 202 of whichwere specifically upregulated in response to Pi depletion anddownregulated when Pi was resupplied to the medium. The 1510

lincRNA sequences identified in this study were compared withthe 10 402 mRNAs obtained from Phatr2. PhaeodactylumtricornutumlincRNAs are significantly shorter than mRNAs withc. 90% at < 1000 nucleotides (Fig. 5a,b). Most of these diatomlincRNAs (> 70%) lack ORFs with coding potential in any of thethree possible reading frames (Fig. 5c). Nonetheless, approxi-mately 28% of the identified lincRNAs have the presence of avery short putative ORF (< 100 amino acids) (Fig. 5c,d), whichcould potentially be translated into a short peptide. The majorityof theP. tricornutumlincRNAs are intronless (90%) with only asmall fraction containing a single intron (Fig. 5e) of similar sizeto the introns found in mRNAs (Fig. 5f). The exons of lincRNAs

are shorter than those of protein coding transcripts (Fig. S4a,c)and the distance between stop codons and the longest stopcodon-free sequences are shorter in diatom lincRNAs than inprotein coding transcripts (Fig. S4d,e). LincRNAs also havelower GC content and lower free energy compared with mRNAs(Figs S4f, S5, S6). Interestingly, all of these genomic features havealso been detected in functional human lincRNAs (Niazi & Val-adkhan, 2012), suggesting conserved features of these moleculesacross kingdoms.

To search for lincRNAs with a similar function to that of IPS1in higher plants, we analyzed whether the P. tricornutum Pi-responsive lincRNAs had a predicted target mimicry function(Wuet al., 2013). No target mimicry function could be predictedin any of the Pi-responsive lincRNAs identified in this work.Using recently publically available RNA-Seq reads (accession no.SRP040703), we sought to investigate the expression changes ofthe Pi-responsive lincRNAs under 48 h N depletion (Levitanet al., 2015). Amongst the top 20 upregulated lincRNAs in Pi,only two were significantly upregulated under N (two-fold dif-ference and P< 0.05) (Fig. 6a), revealing very specific responsesof the noncoding transcriptome to stress conditions. The fact thatthese diatom lincRNAs were specifically expressed in response toPi depletion (Figs 6a, S3) suggests that at least some of these tran-scripts could have regulatory roles in P. tricornutum.

LincRNAs have been shown to associate with chromatin

remodeling complexes and to affect gene expression bycis- andtrans-action (De Lucia & Dean, 2011; Nagano & Fraser, 2011;Guttman & Rinn, 2012; Bonasio & Shiekhattar, 2014; Liuet al.,2015). We investigated the coexpression correlation between thePi-responsive lincRNA genes and their neighboring genes toexplore putativecis-regulatory functions of the lincRNAs. Severalpotential gene targets have been identified as having a correlation(positive or negative) to lincRNAs (Fig. 6b; Table S5). Theseresults can be used to further investigate the function of diatomlincRNAs in the context of Pi depletion, but also in the contextof other abiotic stresses that have putative common responsivemolecular modules, such as N stress.


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Diatom TFs as coordinators of the Pi transcriptomicresponse

The dynamic nature of the diatom transcriptomic response to Pifluctuation is ultimately controlled by a network of TFs, whoseactivity changes in response to the varying signals, thereby coor-dinating the activation of target genes. We have detected the pres-ence of 275 genes coding for putative TFs in P. tricornutum,which include all the previously annotated TFs (Rayko et al.,2010) and several other newly identified putative TFs (Table S6).These TFs have been manually curated for the presence of DNAbinding domains using INTERPRO (http://www.ebi.ac.uk/Tools/InterProScan/), although we cannot completely exclude the pres-ence of false positives. In response to Pi fluctuation, 62.5% of the

genes for putative TFs were differentially expressed, revealing avery dynamic response. Approximately 32% of the upregulated

TFs throughout Pi depletion belong to the HSF family (Fig. 7a).When Pi was resupplied to the medium, there was a switchbetween the abundance of TF families, with the Myeloblastosisfamily (MYB) being over-represented (Fig. 7a). These results sup-port a role for HSFs in the present stress response, which is inagreement with the function of this class of TFs in higher plantsand mammals (Akerfeltet al., 2010). However, as in Arabidopsis(Nover et al., 2001), the significance of the abundance of theHSF family in diatoms remains to be resolved. In Chlamy-domonas and in vascular plants, the key regulators of the Piresponse are TFs (PSR1 and PHR1, respectively) of the MYBfamily with a coiled-coil domain (MYB-CC) (Wykoffet al.,

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tricornutumlong intergenic nonproteincoding RNAs (lincRNAs). (a, b) Lengthdistribution in nucleotides (nt) of unsplicedlincRNAs and mRNAs; (c) number ofpredicted open reading frames (ORFs) and(d) length of putative ORFs in amino acids(aa) considering the three reading frames oflincRNAs and mRNAs; (e) intron number and(f) length of introns in nucleotides (nt) inlincRNAs and mRNAs.

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1999; Rubio et al., 2001). In diatoms, there are 34 annotatedMYB family TFs, but none is MYB-CC with the characteristicLHEQLE conserved motif, suggesting that this domain wasacquired after the separation of green and red algae from thecommon ancestor.

Amongst the TF genes upregulated during early Pi depletion,genes for two HSFs (HSF3.1b and HSF4.7a) returned to theircontrol levels during late Pi depletion (Fig. 7b). This was furtherconfirmed by RT-qPCR (Fig. S7), suggesting a role for these TFsin the coordination of an early response-specific gene network.

Assuming that these TFs will bind to the conserved heat shockelement (HSE) present in the upstream promoter region of puta-tive target genes (Nover et al., 2001; Akerfelt et al., 2010), wegenerated a transcription activation network between these TFsand the significantly coexpressed genes (Fig. 7c). Several signal-ing/sensing genes and other genes coding for other HSF andMYB TFs were present in this early responsive network, as wellas several lincRNA genes (Table S7). This gene regulatory model

can be used to design new studies to further dissect the relation-ship between the two transiently expressed TFs and the coex-pressed genes, to deepen our understanding of the molecularnetworks underlying diatom early physiological adaptations to Pdepletion.

Sensing and signaling of environmental Pi fluctuationsinvolves a singular mix-and-match of genes and pathways

Transmembrane or cell surface receptors in unicellular organ-isms, such as diatoms, are likely to play primordial roles in sens-ing environmental changes, and the resulting signals are then

transmitted to intracellular regulatory pathways, enabling thecell to respond, regulate and adjust its metabolism to maintaincellular homeostasis. We detected 659 genes putatively encodingsensing and signaling functions (Table S8), 42 of which werepredicted to be membrane localized and therefore to have aputative receptor/sensing function. These receptors constitute acollection of several representatives of the signaling pathwaystypically described in metazoans (G protein-coupled receptors(GPCRs), serine/threonine (Ser/Thr) receptor kinases and/ortyrosine (Tyr) receptor kinases) and bacteria (histidine kinasereceptors). Of the total putative sensing/signaling genes, 65.5%were differentially expressed under Pi fluctuation. Amongst themembrane-localized putative protein kinases were five histidinekinase (HK) domain-containing proteins, the gene of one ofwhich, with an extracellular PAS domain (a protein domainfunctioning as a signal sensor), was upregulated in response toPi stress (45485). Membrane HKs are major sensors of environ-mental changes in bacteria, regulating the activity of a second

component, through a phosphorelay between the C-terminalHK domain and the aspartate residue of the response regulator(Laub & Goulian, 2007). Several annotated genes for Tyr and/or Ser/Thr kinases were also upregulated in response to Pi deple-tion, with four such kinases being putatively membrane located.Genes encoding GPCR signaling pathway components havebeen documented to exist in diatoms (Port et al., 2013). GPCRproteins, found in most eukaryotic organisms, are cell surfacereceptors that play a major role in signal transduction, percep-tion and response to the environment (Fredriksson & Schioth,2005). Four genes coding for GPCRs of the rhodopsin/class Afamily and two of the glutamate/class C were significantly

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Fig.6 Long intergenic nonprotein codingRNAs (lincRNAs) involved inPhaeodactylumtricornutumresponses to inorganicphosphate (Pi) depletion. (a) Heat map of thetop 20 upregulated lincRNAs (P < 0.05)under early Pi depletion (4 d, this work) andearly N depletion (N) (2 d, from Levitanet al., 2015; RNA sequencing (RNA-Seq)reads obtained from accession no.SRP040703). C 8d, 8 d control conditions;Pi 4d, 4 d Pi depleted;Pi 8d, 8 d Pidepleted; +Pi 4d, 4 d Pi resupply after 4 d Pidepletion; U, significantly upregulated underN (more than two-fold,P < 0.05); D,significantly downregulated underN (more

than two-fold,P

noncoding and coding transcriptome responses of a marine diatom to phosphate fluctuations

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