World J Microbiol Biotechnol (2016)32:55 DOI 10.1007/s11274-016-2008-5

ORIGINAL PAPER

Identification of gene transcripts involved in lipid biosynthesis in Chlamydomonas reinhardtii under nitrogen, iron and sulfur deprivation Araceli Herna´ndez-Torres1 • Ana Laura Zapata-Morales1 • Ana Erika Ochoa Alfaro1 Ruth Elena Soria-Guerra1

•

Received: 22 June 2015 / Accepted: 4 January 2016 Ó Springer Science+Business Media Dordrecht 2016

Abstract Chlamydomonas reinhardtii is able to accumulate large amounts of triacylglycerides, the major feedstock for biodiesel production, when grown under stress conditions. In order to characterize gene transcripts induced under nitrogen, iron, and sulfur deprivation in C. reinhardtii; 583 expressed sequence tags (ESTs) were generated through a cDNA library. These sequences were subjected to contig assembly resulting in 30 contigs and 76 singletons. The comparison of the ESTs obtained with public databases allowed to assign putative functions to 66.7 % of the sequences. An important group of the identified genes are related to the lipid metabolic process. A phylogenetic analysis of these sequences identified five isoforms of diacylglycerol O-acyltransferase type 2 (DGAT-2). These genes were selected to measure their relative expression under these stress conditions by means of qRT-PCR. According to the results, the accumulation of DGTT1 mRNA increases considerably under nitrogen and iron inanition when compared to the other isoforms, which indicated that each isoform participates at different levels under each stress condition. These results can help to

Araceli Herna´ndez-Torres and Ana Laura Zapata-Morales have contributed equally to this work.

Electronic supplementary material The online version of this article (doi:10.1007/s11274-016-2008-5) contains supplementary material, which is available to authorized users. & Ruth Elena Soria-Guerra [email protected] 1

Laboratorio de Ingenierı´a de Biorreactores. Facultad de Ciencias Quı´micas, Universidad Auto´noma de San Luis Potosı´, Av. Dr. Manuel Nava 6, 78210 San Luis Potosı´, SLP, Mexico

identify potential genes to be overexpressed by genetic engineering in C. reinhardtii. Keywords cDNA library  Triglycerides  Metabolic pathways  Green microalgae

Introduction Triacylglycerides (TAGs) are the major feedstock for biodiesel production. These kinds of lipids are grouped in the storage lipids category and constituted predominately by saturated fatty acids (FAs) and some unsaturated FAs (Thompson 1996). Microalgae are a diverse group of prokaryotic and eukaryotic photosynthetic microorganisms that have useful applications in food, cosmetic, and pharmaceutical industries. In the past years, microalgae have also been recognized as a potential raw material for biodiesel production due to their easy and inexpensive culture and great capacity to accumulate biomass (Sharma et al. 2012; Coragliotti et al. 2011; Mata et al. 2010). The microalgal TAGs accumulate mainly in the form of oil droplets in the cytoplasm. Once extracted, the TAGs can be easily converted into biodiesel through transesterification reactions (Fukuda et al. 2001). In spite of these advantages, the current microalgal-biofuel production is still too expensive to be commercialized due to low TAGs productivity in some species (Hu et al. 2008). Nutrient availability is required for growth of microalgae, however; it is well established that stress caused by nutrient deprivation affects a variety of responses in cellular mechanisms leading to an accumulation of total lipid content, mainly TAGs (Juergens et al. 2015; Ramundo et al. 2014; Glaesener et al. 2013; Matthew et al. 2009; Liu

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et al. 2008). This physiological response may be useful in the development of biofuels. Microalgae have two especially iron-rich organelles, the chloroplast and the mitochondrion. In both organelles there are numerous iron-dependent proteins whose functions are essential in the electron transfer pathways. An inadequate access to this micronutrient limits the photosynthesis process leading to lipid accumulation (Glaesener et al. 2013). In green algae, sulfur deprivation causes changes in the photosynthetic activity; especially in proteins belonging to the photosystem I (PSI) and the composition of the PSII lightharvesting complex (LHC-II), which prevents the conversion of excitation energy to chemical energy in the thylakoid membrane (Matthew et al. 2009; Malnoe¨ et al. 2014). Nitrogen deprivation in green photosynthetic microalgae induces ribosome remodeling, differentiation into sexually competent gametes, and metabolic changes aimed at nitrogen recycling and carbon storage into lipid bodies; mostly composed of TAGs (Wei et al. 2014; Li et al. 2010). Among microalgae, Chlamydomonas reinhardtii is considered a good model to analyze genes involved in the lipid metabolism since this eukaryotic green alga is genetically well characterized and can modify its lipid metabolism efficiently in response to adverse conditions (Hung et al. 2013; Guschina and Harwood 2006). cDNA libraries are effective in gene discovery and characterization of expression patterns. In this article we describe the preparation and characterization of an EST library from C. reinhardtii in response to unfavorable grown conditions such as nitrogen, iron, and sulfur deprivation. Phylogenetic comparisons were made between selected sequences finding similarity in the databases with proteins involved in the triglyceride biosynthetic process. Subsequently, by means of qRT-PCR, five genes corresponding to the DGAT-2 isoforms that are differentially expressed under nutrient starvation were analyzed.

Materials and methods Strains and growth conditions Chlamydomonas reinhardtii strain CC-137 (mt?) was obtained from the Chlamydomonas Center (Duke University, Durham, NC). The cells were grown in liquid cultures under cool fluorescent light at 150 lmol photons m-2s-1 (photoperiod of 16 h light, 8 h dark) at 25 °C. The cultures were grown in Tris-acetate-phosphate (TAP) medium to 3 9 106 cells/mL, followed by transfer to TAP medium without iron, nitrogen, or sulfur as previously described by Deng et al. (2011). The cultures were grown photoheterotrophically until reaching the stationary phase at 25 °C with a photoperiod

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in a working volume of 800 mL. Temperature and pH of the culture medium were continuously monitored. Afterwards, the biomass of the cultures was harvested by centrifugation at 800g for 10 min at 25 °C and immediately frozen and stored at -70 °C for further use. cDNA library construction Total RNA was extracted from each culture grown in TAP medium without iron, nitrogen, or sulfur according to the RNAqueous kit protocol (Ambion, St. Austin, TX). Quality and concentration of RNAs were analyzed by absorbance measurements at 260 and 280 nm on a NanoDrop ND-1000 BioPhotometer (Thermo Fisher Scientific Inc., Waltham, MA). The RNA mixture (at equal concentrations) was prepared for the cDNA library construction. The firststrand cDNA was synthesized from 1 lg of total RNAs using the SMARTScribe Reverse Transcriptase Kit (Clontech, Palo Alto, CA). In order to obtain genes expressed during the stress conditions, a cDNA library was constructed using the InFusionÒ SMARTerÒ Directional cDNA Library Construction kit (Clontech, Palo Alto, CA, USA) according to the standard protocol provided by the manufacturer. The double-stranded cDNA population was cloned into the pSMART2IFD linearized vector provided with the kit and used to transform TOP-10 electrocompetent Escherichia coli cells. Plasmid DNA was obtained with WizardÒ Plus SV Minipreps DNA Purification System (Promega, Fitchburg, WI) and verified by PCR with universal oligonucleotides M13. PCR products were analyzed by electrophoresis on 1 % agarose/EtBr gels. Sequencing and bioinformatics analyses of ESTs The cloned products were sequenced using the M13 forward primer in a 3500 Genetic Analyzer sequencer (Applied Biosystems, Mulgrave, AUS). All nucleic acid sequences were screened for vector contamination using the Vector Screen program (www.ncbi.nlm.nih.gov/ VecScreen) and grouped into contigs (groups of overlapping DNA sequences) using the Sequencher 5.2 (Gene Codes Corporation, Ann Arbor, MI). Homology searches were conducted using the BLASTX program against the GenBank non-redundant (nr) databases of the National Center of Biotechnology Information (NCBI; www.ncbi. nlm.nih.gov). Functional classification analyses were performed according to the UniProtKB database (http://www. uniprot.org/). The encoded protein sequences of known or putative diacylglycerol O-acyltransferase (DGAT) genes were aligned with CLUSTALW (http://www.ebi.ac.uk/Tools/ msa/clustalw2/) and the conserved motifs were identified

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using the Prosite tool (http://prosite.expasy.org/). For phylogenetic analysis the Mega software V6.0 was used (http://www.megasoftware.net/). Differential expression analysis by quantitative RT-PCR Total RNA extraction and cDNA synthesis was performed, as previously described, for each condition. Quantitative real-time PCR (qRT-PCR) was performed using SYBR Green as fluorophore. The reaction mixture contained 5 lL of SYBR Green Master Mix reagent (Applied Biosystems, Mulgrave, AUS), 100 nM of each oligonucleotide (see Table 1) and 100 ng of cDNA in a final reaction volume of 10 lL. Real-time was performed in a 96-well format using the Applied Biosystems Step One Real-Time PCR System (Applied Biosystems, Mulgrave, AUS). The real-time PCR conditions were: 95 °C for 10 min, 40 cycles at 95 °C for 30 s, and 60 °C for 1 min. Melting curves were performed by 40 cycles of 1 min at 95 °C, 1 min at 60 °C, and 15 s at 95 °C. Analyses were performed by triplicate. Quantification was based on a cycle threshold value, with the expression level of each gene normalized to ubiquitin ligase gene (XM_001697453). Tukey’s multiple comparison test was used when the ANOVA detected significant differences (p \ 0.05) between each condition.

Results Overview of results from Chlamydomonas reinhardtii cDNA library With the aim of isolate genes expressed under stress condition of C. reinhardtii grown in TAP medium without iron, nitrogen, or sulfur; a cDNA library was constructed. In total, 583 plasmids were sequenced and assembled with Table 1 Oligonucleotides designed for qRT-PCR analysis

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Sequencher 5.2 (Gene Codes Corporation, Ann Arbor, MI) comprising a total of 76 singletons and 30 contigs. Sequence lengths varied from 102 to 1718 bases with an average read length of 438 bases. Putative function of 66.7 % ESTs were assigned using the BLASTX programs of the NCBI database (considering a maximum probability threshold per sequence to an E value of 10-2) and the UniProtKB database (http://www.uniprot.org/). The remainder sequences (33.3 %) showed no similarities, thus they were classified as unidentified sequences. Functional classification of singletons and contigs isolated from the cDNA library The sequenced clones were classified according to ontologies reported by the Uniprot database (http://www. uniprot.org/). This classification includes, in the ‘‘Molecular function’’ category, sequences related to protein binding (44.3 %), transferase activity (11.3 %), cyclase activity (5.7 %), and translation regulation (5.6 %); among others. In the ‘‘Cellular component’’ category, the most representative sequences were found in chloroplast (34 %) followed by components of membrane (8.5 %) and nucleus (6.6 %). Regarding the ‘‘Biological process’’ category, most of the genes are involved in metabolic processes (23.6 %) as well as translation and catabolic processes (13.2 and 12.3 %, respectively) (Fig. 1). A descriptive list with the gene ontologies of each sequence is available in Supplementary Information. Among 133 ESTs with putative function, 42 and 44 % of the sequences showed similarity with plants and algae, respectively; in particular for algae, the results could be matched with ‘‘green algae’’ like C. reinhardtii, Acutodesmus obliquus, Botryococcus braunii, and Ostreococcus lucimarinus; among the group of ‘‘other algae’’ a similarity with Chlorella vulgaris, Stigeoclonium helveticum, Nephroselmis olivacea, Parachlorella kessleri,

Gene

Oligonucleotide name

Oligonucleotide sequence

Ubiquitin ligase

UBI-F

50 -GTACAGCGGCGGCTAGAGGCAC-30

UBI-R

50 -AGCGTCAGCGGCGGTTGCAGGTATCT-30

DGTT1

DGTT1-F

50 -GAAGCAGGTGTTTGGCTTCT-30

DGTT1-R

50 -CAGTGCCTCCGTGTAGGTCT-30

DGTT2

DGTT2-F

50 -GCGCCGCAACATTTACATGG-30

DGTT3

DGTT2-R DGTT3-F

50 -CAGCCGTACTCGGTCTTGTG-30 50 -GTCAGAGCCAAGTGCTGGAC-30

DGTT3-R

50 -TCCACCTCCTTGTCGAACTC-30

DGTT4-F

50 -GCATGTTTGGGCAGTACGGC-30

DGTT4-R

50 -GCCTTGTGCTTGTCGTACAG-30

DGTT5-F

50 -AGTCACTGCAGCAGCTGTCG-30

DGTT5-R

50 -GCCCACACACATCATGAGCG-30

DGTT4 DGTT5

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Fig. 1 Gene Ontology annotation of ESTs from Chlamydomonas reinhardtii by functional classes. a Biological process: 1 anatomical structure formation (1.9 %); 2 catabolic process (12. %); 3 cellular component biogenesis (2.8 %); 4 cellular component organization (1.9 %); 5 cellular process (3.8 %); 6 metabolic process (23.6 %); 7 photosynthesis (7.5 %); 8 response to stimulus (4.7 %); 9 transcription (9.4 %); 10 translation (13.2 %); 11 transport (4.7 %); 12 no hits (14.1 %). b Molecular function: 1 binding (43.6 %); 2 cyclase activity (6.5 %); 3 desaturase activity (3.1 %); 4 endopeptidase activity (2.4 %); 5 glucosidade activity (2.9 %); 6 lipase activity

(2.8 %); 7 oxidoreductase activity (3.7 %); 8 structural molecules (4.8 %); 9 transcription regulator (3.1 %); 10 transferase activity (11.1 %); 11 translation regulation (4.8 %); 12 transporter activity (3.1 %); 13 no hits (8.1 %). c Cellular component: 1 cell wall (2.4 %); 2 chloroplast (32.8 %); 3 cytoplasm (13.5 %); 4 endoplasmic reticlum (2.4 %); 5 extracellular region (4.8 %); 6 glyoxysome (1.9 %); 7 golgi aparatus (4.2 %); 8 component of membrane (8.3 %); 9 microtubule (2.9 %); 10 mitochondria (4.3 %); 11 nucleus (5.3 %); 12 cell membrane (3.8 %); 13 ribosome (1.8 %); 14 no hits (11.6 %)

and some others was found. Regarding plants, the sequences could be mainly matched with Arabidopsis thaliana and Oryza sativa. Small amounts of sequences were found in genomes from bacteria and animals (Fig. 2).

genes involved in lipid biosynthesis increased during nitrogen, iron, and sulfur deprivation. As can be seen in Table 2, two contigs were identified as putative DGAT. The first one (contig 12) contained thirtyeight sequences. A phylogenetic analysis of the corresponding consensus protein with eighteen DGAT1 sequences previously reported from different organisms, showed a close relationship with DGAT1 from Arabidopsis thaliana (NP_179535); these sequences are approximately conserved in length and they co-align over large stretches with about 80 % of totally conserved residues dispersed throughout (Fig. 3). In the contig 24 (containing thirty-one sequences) a putative DGAT protein was also identified. A detailed search with bioinformatics tools and available databases allow identifying 5 type-2 DGATs. A phylogenetic tree including DGAT2 sequence of Arabidopsis thaliana (NP_566952), DGTT1 (AGO32156), DGTT2 (AGO32157), DGTT3 (AGO32158), DGTT4 (AGO32159), and DGTT5 (EDP06642) from C. reinhardtii; and ESTs Cr.54, Cr.71, Cr.74, Cr.28, and Cr.52 was constructed. As we can see in Fig. 4, there is a clear definition of each EST with an isoform of type 2 DGAT. The amino acid sequences of the predicted isoforms of DGAT2 were aligned using the Clustal W program. As shown in Fig. 5, the five clones corresponding to the ESTs Cr.54, Cr.71, Cr.74, Cr.28, and Cr.52 retain the conserve motifs including YFP, PH, PR, GGE, RGFA, VPFG, and G blocks which are found in the DGAT2 family (Hung et al. 2013; Liu et al. 2012; Cao 2011). Totally conserved residues are shaded in dark gray. In Cr.71, Cr.74, and Cr.28 (corresponding to DGTT 2, 3, and 4; respectively) the

Identification of genes induced under stress conditions An important group of the identified genes were related to the lipid metabolic process including diacylglycerol O-acyltransferase, 1-acyl-sn-glycerol-3-phosphate acyltransferase 5, acyl-[acyl-carrier-protein] desaturase, oxysterol-binding protein, sterol methyltransferase and 3-oxoacyl-[acyl-carrier-protein] synthase 1 (Table 2). These results suggest that

Fig. 2 Classification of the ESTs according to the matching organism in the non-redundant (nr) database

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Table 2 Representative genes involved in lipid metabolic process ID

Description

E-value

ID UNIPROT

Organism

Biological process

7

1-Acyl-sn-glycerol-3-phosphate acyltransferase

7.70E-05

Q9LHN4.1

Arabidopsis thaliana

Diacylglycerol biosynthetic process

22

Acyl-[acyl-carrier-protein] desaturase

9.30E-07

Q42770.1

Gossypium hirsutum

Fatty acid biosynthetic process

280

Oxysterol-binding protein-related protein

4.90E-06

Q9SW00.2

Arabidopsis thaliana

Lipid transport

283

Sterol methyltransferase-like

1.10E-07

H2E7U0.1

Botryococcus braunii

Steroid biosynthetic process

297

3-Ketoacyl-CoA synthase

3.70E-06

O65677.1

Arabidopsis thaliana

Fatty acid biosynthetic process

Contig 8

Phospholipase A1-IIbeta

9.20E-08

O82274.2

Arabidopsis thaliana

Lipid catabolic process

Contig 12

Diacylglycerol O-acyltransferase 1

2.00E-163

Q9SLD2.2

Arabidopsis thaliana

Triglyceride biosynthetic process

Contig 18

3-Oxoacyl-[acyl-carrier-protein] synthase

6.00E-05

A4S7I3

Ostreococcus lucimarinus

Fatty acid biosynthetic process

Conting 24

Diacylglycerol O-acyltransferase 2

4.00E-52

Q9ASU1

Arabidopsis thaliana

Triglyceride biosynthetic process

DGAT domains were also found; while two DGAT domains were found in Cr.52 (DGTT5) as previously reported in diacylglycerol acyl transferases (http://smart. embl.de). Furthermore, a set of ESTs with unknown functions as well as sequences with no matches in the NCBI database were identified (33.3 % of ESTs); suggesting that they might encode novel proteins or could correspond to 30 UTR regions of C. reinhardtii. It is also possible that the region of the sequence being expressed by the EST may only be a small part of a much larger protein and we might have not enough of the sequence to obtain a correct match for its predicted function from the database searches. Differentially expressed DGAT2 isoforms genes under nutrient starvation Five genes, corresponding to the DGAT2 isoform were selected to measure their relative expression under nitrogen, sulfur, and iron starvation by means of qRT-PCR. Our hypothesis was that they could possibly participate at different levels under each stress condition. The relative expression levels of all the analyzed genes were normalized to the ubiquitin ligase from C. reinhardtii. DGTT1 is mostly induced under nitrogen and iron starvation and differentially expressed when compared to sulfur inanition. Conversely, the expression of DGTT2 showed higher transcript levels under sulfur and nitrogen starvation relative to the other studied condition. DGTT4 transcript was up-regulated notoriously for nitrogen depletion. For DGTT2 and DGTT3 upper transcript levels in the sulfur depletion compared to iron starvation were observed. The relative expression levels of DGTT5 were almost the same

in all conditions (Fig. 6). Tukey’s multiple comparison test was used when the ANOVA detected significant differences (p \ 0.05) between each condition. Although the DGTT family has been widely studied, not enough information has been reported from DGTT5 under different stress conditions.

Discussion Many microalgae species can be induced to accumulate substantial quantities of lipids, particularly during nutrient shortage, thus contributing to a high oil yield. Among the nutrient stress conditions, nitrogen (N) deficiency is considered as the best trigger of effective TAG accumulation (Kajikawa et al. 2015; Fan et al. 2012). During N deprivation in algae the growth slows, an autophagy program is induced, the photosynthesis is down-regulated, and starch and lipids droplets accumulate (Juergens et al. 2015; Ramundo et al. 2014: Wang et al. 2009a, b). In C. reinhardtii cultures, the photosynthetic downregulation under N deprivation is due to a specific degradation of cytochrome b6f complexes, rather than to the photosystem II (PSII) inactivation as reported for phosphorus and sulfur deprivation (Kajikawa et al. 2015; Philipps et al. 2012). This loss in cytochrome b6f complex results from active proteolytic degradation. The cytochrome b6f complex is required both for NADPH and ATP production through photosynthetic electron flow (Wei et al. 2014). Chlorosis and protein degradation observed in nitrogen deficient cells are supposed to be caused by nitrogen recycling (Schmollinger et al. 2014). TAG accumulation is a mechanism to protect cells against oxidative damage

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Fig. 3 Phylogenetic tree of 18 DGAT1 proteins including the consensus sequence from the contig 12 of C. reinhardtii (Cr.12). The phylogenetic tree was created by Neighbor-Joining method using Mega V.6 sotware. Bootstrap support values out of 500 replicates of the data set are provided as percentages at the corresponding nodes. Sources are as follows: AtDGAT1: Arabidopsis thaliana (NP_179535.1); LjDGAT1: Lotus japonicas (AAW51456.1); JcDGAT1: Jatropha curcas (ABB84383.1); OeDGAT1: Olea europea (AAS01606.1); PfDGAT1: Perilla frutescens (AAG23696.1); NtDGAT1: Nicotiana tabacum (AAF19345.1); OsDGAT1: Oryza sativa (NP_001054869.2); SmDGAT1: Selaginella moellendorffii (XP_002964165.1); PpDGAT1: Polysphondylium pallidum (EFA85004.1); AaDGAT1: Aedes aegypti (XP_001658299); MmDGAT1: Mus musculus (NP_034176.1); PtDGAT1: Phaeodactylum tricornutum (XP_002177753.1); HsDGAT1: Homo sapiens (NP_036211.2); BtDGAT1: Bos taurus (NP_777118.2); OaDGAT1: Ovis aries (NP_001103634.1); BbDGAT1: Bubalus bubalis (AAZ22403.1); ChDGAT1: Capra hircus (ABD59375)

(Johnson and Alric 2013). Other studies have reported elevated levels of neutral lipids (palmitic, oleic, and olinoleic fatty acids) that are stored in lipid bodies under nitrogen deficiency in C. reinhardtii (Li et al. 2010; Wang et al. 2009a, b). The iron has an important role as micronutrient in microalgae; therefore these organisms have multiple pathways to assimilate it under various chemical forms. During iron starvation, the loss of photosynthetic complexes occurs by degradation of the chlorophyll protein complexes; starting with disconnection of the photosystem I followed by the loss of photosystem II (Glaesener et al. 2013; Urzica et al. 2012). Liu et al. (2008) showed that the iron deficiency is one of the main factors limiting marine algal biomass productivity and under certain culture conditions results in higher quantities of lipids. Kropat et al. (2011) observed that iron deficiency in C. reinhardtii cells

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Fig. 4 Phylogenetic tree created by Neighbor-Joining method showing the identification of isoforms of DGAT type 2 within ESTs collection. The bootstrap consensus tree was inferred from 500 replicates. The analysis was executed in Mega V.6 software. Sources are as follows: DGTT5: C. reinhardtii (EDP06642); DGTT3: C. reinhardtii (EDP06642); DGTT2: C. reinhardtii (AGO32157); DGTT4: C. reinhardtii (AGO32159); DGTT1: C. reinhardtii (AGO32156); AtDGAT2: Arabidopsis thaliana (NP_566952); EoDGAT2: Elaeis oleı´fera (ACO35365.1); HvDGAT2: Hordeum vulgare (BAJ85730.1)

accumulated TAG in parallel with inhibition of cell division. Chlamydomonas reinhardtii also accumulates larger amounts of TAGs under sulfur shortage. Specifically, it undergoes cell cycle arrest and downregulation of photosynthesis. This decrease in photosynthesis has mainly been attributed to compromised photosystem II (PSII) activity and the composition of the PSII light-harvesting complex (LHC-II), which prevents the conversion of excitation energy to chemical energy in the thylakoid membrane (Matthew et al. 2009; Malnoe¨ et al. 2014). It has also been reported that about 85 % of its chloroplast sulfolipids are recycled under sulfur limitation (Sato et al. 2014; Sugimoto et al. 2010) resulting in increased amounts of TAGs. Considering the previous information, the goal of this study was to characterize gene transcripts induced under nitrogen, iron, and sulfur deprivation conditions on the green alga C. reinhardtii through a cDNA library analysis. Most of the ESTs in our library seemed to encode proteins involved in metabolism. Among these genes a 3-oxoacyl[acyl-carrier-protein] synthase was found; this enzyme belongs to the fatty acid synthase II complex that catalyzes the acyl-ACP-dependent elongation steps in higher plants. A 3-ketoacyl-CoA synthase was also found. The first enzyme of the fatty acid elongase complex, ketoacylcoenzyme synthase (KCS), catalyzes the rate-limiting, condensation reaction of the acyl primer with malonylCoA (Boger 2003). Phosphate acyltransferase also participates in the Kennedy pathway of glycerolipid and TAG syntheses. In our

World J Microbiol Biotechnol (2016)32:55 Fig. 5 Multiple alignment of the deduced amino acid sequences of DGAT2 isoforms including Arabidopsis thaliana sequence (NP_566952) as reference. Identical residues in the proteins are indicated in dark gray. Characteristic motifs present in DGAT2 family proteins are indicated: YFP, PH, PR, GGE, RGFA, VPFG and G blocks

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AtDGAT2 Cr.54_DGTT1 Cr.71_DGTT2 Cr.74_DGTT3 Cr.28_DGTT4 Cr.52_DGTT5

MGGSREFRAEEHS-NQFHSIIAMAIWLGAIHFNVALVLCSLIFLPPS-LSLMVLGL-LSL MKWGWLIRTDLYFQSRSLRIAFPLYFYCSSLSPGDDAN--CKWKPTFRKIWPLAA---------------MH-SFWMTVLLSG---SDNNSPSDDVG---APADVRDRIDSVVND---MARGKMMGAAKAH-ARTVTLTLNG---GGEFVPNVRLYSDRIRSDARQNLLLQISDGISM MAR-RDMMAILDY-AAIAIVTENG---GGEFVDLDALALFYLFGATSPSAWLLLAA-FLA MAR-RDPPAIRPP-PGVTTVTENG---SASYILLG-----LLLGTAAGGSLLVPAP----

AtDGAT2 Cr.54_DGTT1 Cr.71_DGTT2 Cr.74_DGTT3 Cr.28_DGTT4 Cr.52_DGTT5

FIF-----IPIDHRSKYGRKLARYICKHACNYFPVS-LYVEDYEAFQPNRA--N----G-------------------------------YFPVSKLVLQKYIS-EP--------A---------------------------------YFKGS-ANLAGVLD-GG-----N-----SDYVGAPM-VVDALQGTLALPGDFNFKLWRHYFHKSFLIEE--------GGDDNR-AR-LTFTPLQV----GAPALSERIDSVVNDDAAAYFPTV--TADPEAG-DTD---------GG -------------------------------YFPSY--AEDQLPDRNRRKS-----A-G-

YFP block AtDGAT2 Cr.54_DGTT1 Cr.71_DGTT2 Cr.74_DGTT3 Cr.28_DGTT4 Cr.52_DGTT5

YVFG-YEPHSVLPIGVVALCDLTGFMPIPNIKVLA-----------------------SS YIFAEF-PHKYISEPYIFVIFPHGVIAISDWLAPAYVTLR-----CDSAFLSGVTLMLLT YIFVIF-PHGVGGIES-VVSSPSQGAAATEDNE-------ASFVRGGGEGRGATEATIMF YDFEF--PHGGGPGGPIVAGTLMQT------------------------------TVAAS YLFG-GGPHGGEGR-----GNADAFATTSPLL--------------PKERRARESPLSSD YLF----PHFVNS-----GALIS-LLSGSDNNS-------A--AAADNGAGGTTGAAGRG

AtDGAT2 Cr.54_DGTT1 Cr.71_DGTT2 Cr.74_DGTT3 Cr.28_DGTT4 Cr.52_DGTT5

AIFYTPFLRHIWTWLGLTAASRKNFTSLLDSGYSCVLVPGGV-----QETFHM------CIFWLPFWREYLVSYAHTSYDIRSLANAADKGYVVLVV-GGA-----SEAPEV------RIFGLPAFRVPAHRRARESLGSVPATTRQSHGYVVVLL-GGLFNGANGEVVVLVGGNAEL VRFYIPY-RHFITWIGSVPATPLSSKRILKKGHSCVLV-GGV-----VELIAVNS----AIFKAPIVRQLNWWLGVRIATRQSLSLIENLG-SCLLVPGGF-----QESSNM------GSFPKPASRDGARQPKAQQRDRESRQIFKQLLAGDPAVGLGLCV---VELIAVNSRGF--

PH block

PR block

GGE block

AtDGAT2 Cr.54_DGTT1 Cr.71_DGTT2 Cr.74_DGTT3 Cr.28_DGTT4 Cr.52_DGTT5

QHDAENVF---LSRRRGFVRIAM-EQGSPLVPVFCFG--------------QARVYKWWK SYYVS------LKSRAGFMR-A--GAGTSLVPVPTFGYQ-----------PTYPRPPCIR IMQSLMKYGWLLRDRFGFSRRAL-RDG-GIVPVFHFG------------ISVLDFGPQ-RLIIEN-----LVGRRGFARIAFWGAVDSIVPVYYFGQSQ---------I-VLSIFPW-LHGKELFY---LCSRLGFVRLAV-QHGEPLVPVKAIGQTRAYFLHIPGT---MLVPLW-IENAVEMG-VPLVPR-GFVR-SL-TFGPLSLPCISFRIR------------MAAGATV--

AtDGAT2 Cr.54_DGTT1 Cr.71_DGTT2 Cr.74_DGTT3 Cr.28_DGTT4 Cr.52_DGTT5

PDCDLYLKLSRAIRFTPICFWGVFGSPLPCRQPMHVVVGKPIEVTKTLK----PTDEEIA -KAAVMKVLKQKFSFSSLLSWG------FHLFGNKYVVG-PI-VT----------APIQV ----AMFTVEKRLRAALGFLYG---VIFLHIRNIYMVCGRPCPVTKTAR----CDSAFLS ----LADFTRRKLTSQKYITGG---LPVIFPIPIIMVTGKPYPVPKVARDSPEFDSGVTL ----LVERISRAAGAVLSGVTGQLLTPIVHRKPLTSVVHTPIPVPKLAPAALKANPEVSA ----GVLVLPVPISEPVMMFVGSP-IPVTEVLPAAYVTVKAIDSAFLSG---VTLMLLTC

RGFA block

VPFG block

G block AtDGAT2 Cr.54_DGTT1 Cr.71_DGTT2 Cr.74_DGTT3 Cr.28_DGTT4 Cr.52_DGTT5

KFHGQYVEALRDLFERHKSRVGYDLELKIL DKVS------TLTEAPVA-----------VVDANVIA--VMCMLQIA-----------MLDATIVE--LGEMSYAHGRI--------AVSKKSLDDLMGCYDIMLSTFGSSFELYSIVWLKLVS--YAHTSYDIRSLAKCCR----

study a 1-acyl-sn-glycerol-3-phosphate acyltransferase and a phospholipase A1 were found, these enzymes have been previously described under nitrogen deprivation (Miller et al. 2010). The phospholipases are important for the turnover or replacement of membranes during cell growth or gamete fusion (Holm et al. 2000). Two member of the sterol family were also found (oxysterol-binding protein and sterol methyltransferase). Sterols are ubiquitous among eukaryotic organisms and serve both as bulk membrane lipid components and

precursors for additional metabolites such as mammalian steroid hormones, plant brassinosteroid hormones, and insect ecdysteroids. It has been reported that the sterol methyltransferase 1 in Arabidopsis controls the level of cholesterol in plants (Diener et al. 2000). In addition to the genes involved in the synthesis of the glycerolipids themselves, fatty acid desaturase gene was annotated. It was identified as acyl-[acyl-carrier-protein] desaturase. Desaturase enzymes perform dehydrogenation reactions resulting in the introduction of double bonds into

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Fig. 6 Reverse transcriptase real-time PCR analysis of DGTT1 (a), DGTT2 (b), DGTT3 (c), DGTT4 (d) and DGTT5 (e) transcript levels in medium without sulfur (S-), iron (Fe-) and nitrogen (N-). Data are expressed as fold difference compared to the expression in wild type strain arbitrarily set to 1. Data were analyzed with the 2-DDCt method and plotted on a linear scale. Bars are mean ? 1 s.e.; n = 3, Tukey’s multiple comparison test was used when the ANOVA detected significant differences (p \ 0.05) between each condition

fatty acids that are initiated by the energy-demanding abstraction of a hydrogen from a methylene group (Buist 2004; Fox et al. 2004). The Chlamydomonas genome contains six genes coding for diacylglycerol:acyl-CoA acyltransferases (DGATs), which catalyze the last step in the Kennedy pathway of TAG biosynthesis: the acylation of diacylglycerol to TAG (Courchesne et al. 2009). Among these genes, one encodes for type 1 DGAT and the rest for 5 isoforms of type 2DGAT. In our study sequences corresponding to these diacylglycerol acyltransferases were found, identifying conserved motifs including YFP, PH, PR, GGE, RGFA, VPFG, and G blocks previously reported for the DGAT2 family (Hung et al. 2013; Liu et al. 2012; Cao 2011). The DGAT2 isoforms were selected to measure their relative expression under nitrogen, sulfur, and iron starvation by means of qRT-PCR. Our results indicate that each isoform participates at different levels under each stress condition, being up-regulated in all cases. According to our results, the accumulation of DGTT1 mRNA increases considerably under nitrogen and iron inanition relative

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to the other isoforms. These findings agree with previous studies of the response of Chlamydomonas to nitrogen starvation (Miller et al. 2010; Benning et al. 2010; Boyle et al. 2012). DGTT4, DGTT4, and DGTT5 are up-regulated under nitrogen starvation and differentially expressed when compared to other conditions. Under sulfur starvation, all the isoforms are expressed at moderate levels and remain approximately constant under this condition. The DGTT4 transcript only increases noticeable in nitrogen-starved cells. Although DGTT5 mRNA abundance is low, it was detected. Similar studies performed under nitrogen starvation have failed to detect this isoform (Benning et al. 2010; Boyle et al. 2012). In Hung et al. (2013) demonstrated that DGTT2 is the most robust isozyme in TAG accumulation, which suggests its primary involvement in TAG biosynthesis in vivo. It was proposed that DGTT1 and DGTT3 might be conditional isozymes contributing to the additional TAG biosynthesis under nitrogen starvation (Boyle et al. 2012). It is important to note that these conclusions were obtained

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using a heterologous expression system. However, orthologs of Chlamydomonas DGTT1 in yeast and Arabidopsis are established as significant contributors to oil accumulation (Boyle et al. 2012). In La Russa et al. (2012) overexpressed three promising type-2 DGAT isoforms (DGTT1, 4, and 5) in C. reinhardtii. Although the recombinant strains showed enhanced mRNA levels over the wild type, the strains did not boost the intracellular TAG accumulation or resulted in alterations of the fatty acid profiles when compared to the wild type during standard growth condition or during nitrogen or sulfur stress conditions. Future cost saving efforts for algal oil production should focus on the production method of lipid rich algae itself. Since Chlamydomonas has a complete sequenced genome with a rigorous genetic system developed, it is a powerful reference organism for metabolic manipulation through techniques such as gene knock-down or overexpression. The sequences found in this work can help us identify potential genes to be overexpressed by genetic engineering. This could have a significant impact for algal biodiesel production by increasing yields of TAGs. Some efforts on this regard are in progress in our research group. Acknowledgments This work was supported by CONACYT Grants 151480 to RESG and C14-PIFI-08-14.14. Thanks to Bioprocess CA.

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