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Development of Novel Microsatellite Markers for Strain-Specific Identification of Chlorella vulgaris
Development of Novel Microsatellite Markers for Strain-Specific Identification of Chlorella vulgaris
Journal of Microbiology and Biotechnology. 2014. Sep, 24(9): 1189-1195
Copyright © 2014, The Korean Society For Microbiology And Biotechnology
  • Received : May 20, 2014
  • Accepted : June 09, 2014
  • Published : September 28, 2014
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About the Authors
Beom-Ho Jo
Bureau of Ecological Conservation Research, National Institute of Ecology (NIE), Seocheon 325-813, Republic of Korea
Chang Soo Lee
Environmental Biotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 305-806, Republic of Korea
Hae-Ryong Song
Bureau of Ecological Conservation Research, National Institute of Ecology (NIE), Seocheon 325-813, Republic of Korea
Hyung-Gwan Lee
Environmental Biotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 305-806, Republic of Korea
Hee-Mock Oh
Environmental Biotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 305-806, Republic of Korea
heemock@kribb.re.kr

Abstract
A strain-specific identification method is required to secure Chlorella strains with useful genetic traits, such as a fast growth rate or high lipid productivity, for application in biofuels, functional foods, and pharmaceuticals. Microsatellite markers based on simple sequence repeats can be a useful tool for this purpose. Therefore, this study developed five novel microsatellite markers (mChl-001, mChl-002, mChl-005, mChl-011, and mChl-012) using specific loci along the chloroplast genome of Chlorella vulgaris . The microsatellite markers were characterized based on their allelic diversities among nine strains of C. vulgaris with the same 18S rRNA sequence similarity. Each microsatellite marker exhibited 2~5 polymorphic allele types, and their combinations allowed discrimination between seven of the C. vulgaris strains. The two remaining strains were distinguished using one specific interspace region between the mChl-001 and mChl-005 loci, which was composed of about 27 single nucleotide polymorphisms, 13~15 specific sequence sites, and (T)n repeat sites. Thus, the polymorphic combination of the five microsatellite markers and one specific locus facilitated a clear distinction of C. vulgaris at the strain level, suggesting that the proposed microsatellite marker system can be useful for the accurate identification and classification of C. vulgaris .
Keywords
Introduction
Exploring alternative energy sources has become a serious concern owing to the rapid depletion of fossil fuels as a result of increased industrialization and urbanization [4] . To cope with this energy crisis, sustainable biofuel production using microalgae has been put forward as one of the most feasible and environmentally friendly solutions, since microalgae can grow fast with high lipid production in the cells, while also reducing greenhouse gases such as carbon dioxide [6 , 16] .
Among microalgae, Chlorella , a unicellular green alga, is regarded as one of the best representative microalgal species for the production of biofuel [20] . However, Chlorella is found in various aquatic environments, including fresh and marine water, and has highly diverse morphological and physiological traits, which hinders the accurate identification and classification of Chlorella spp. [3] . Therefore, it is important to secure specific Chlorella strains with the proper physiological characteristics for effective microalgal biofuel production, including rapid growth and high lipid productivity.
One solution to this problem is the recent development and application of molecular genetic markers, which can be used to identify and classify target organisms owing to their distinct genetic polymorphisms at a species or strain level. Thus, different genetic traits can be analyzed using different methods, such as RFLP (restriction fragment length polymorphism), RAPD (randomly amplified polymorphic DNA), AFLP (amplified fragment length polymorphism), ISSR (inter-simple sequence repeat), and SNP (single nucleotide polymorphism) [15 , 22] . Among the various genetic markers, a microsatellite, known as a simple sequence repeat (SSR) or short tandem repeat (STR), is highly effective for distinguishing a target organism from closely related species, where its discrimination power is based on its polymorphic distribution in specific loci [12 , 14] . In particular, the specific flanking regions near the microsatellite can provide a precise genotyping of inter- or intra-specific hybrids with a single primer set [5 , 21]
As a result, several microalgal microsatellite markers have already been developed to classify Chlamydomonas [10] , detect the toxic dinoflagellate Alexandrium causing mass fish deaths in red tide [17 , 18] , and identify the ecological and geographical distribution of the freshwater benthic diatom Sellaphora [9] . Cho et al . [7] also suggested that microsatellite markers could be used to track the migration route of Prorocentrum micans and analyze its population genetic structure in Korea. However, little is known about the microsatellite markers for Chlorella despite its widespread distribution in aquatic environments and extensive use in the field of microalgal biofuel production. Therefore, the present study developed and evaluated novel microsatellite markers to distinguish Chlorella vulgaris at the strain level. It is anticipated that the proposed microsatellite marker system will help to secure and manage useful genetic resources of C. vulgaris isolated from domestic and foreign aquatic environments.
Materials and Methods
- Chlorella Strains, Culturing, and DNA Extraction
A total of nine strains of Chlorella vulgaris were obtained from two culture collection centers. Four strains of C. vulgaris , UTEX 265, 396, B1803, and 1809, were obtained from the Culture Collection of the University of Texas at Austin (UTEX). Five strains of C. vulgaris , NIES 641, 642, 686, 1269, and 2170, were obtained from the Microbial Culture Collection of the National Institute for Environmental Studies (NIES) in Japan.
Each of the nine C. vulgaris strains was cultivated in a 1L glass bottle containing BG11 medium on a shaking incubator at 25 ± 2℃ under 12 h light/12 h dark conditions (120 ± 5 μmol photons/m 2 /s) for 2 weeks. The BG11 medium contained NaNO 3 , 1.5 g; K 2 HPO 4 , 40 mg; MgSO 4 ·7H 2 O, 75 mg; Na 2 CO 3 , 20.2 mg; CaCl 2 ·7H 2 O, 36 mg; citric acid, 6 mg; ammonium ferric citrate, 6 mg; Na 2 ·EDTA, 1m g; H 3 BO 3 , 2.86 mg; MnCl 2 ·4H 2 O, 1.81 mg; ZnSO 4 ·7H 2 O, 0.22 mg; Na 2 MoO 4 ·2H 2 O, 0.39 mg; CuSO 4 ·5H 2 O, 0.08 mg; and Co(NO 3 ) 2 ·6H 2 O, 0.05 mg/l [24] .
The cultured C. vulgaris cells were harvested from the media by centrifugation and their genomic DNAs were subsequently extracted using a DNeasy plant mini kit (Qiagen, Germany) according to the manufacturer’s instructions. The partial 18S ribosomal RNA genes of the nine C. vulgaris strains were amplified using the extracted DNAs as templates and a C. vulgaris -specific primer pair (forward, 5’-CGACTTCTGGAAGGGACGTA-3’; reverse, 5’-GAATCAACC TGACAAGGCAAC-3’) [23] , followed by taxonomical confirmation based on the 18S rRNA sequences using the Basic Local Alignment Search Tool (BLAST).
- Screening of Microsatellites and Design of Specific Primers
The whole-genome sequence of the chloroplast of C. vulgaris C-27 (AB001684) was archived from the National Center for Biotechnology Information (NCBI) database ( http://www.ncbi. nlm.nih.gov/ ) and candidates for the microsatellite motifs were screened using the Gramene Simple Sequence Repeat Identification Tool (SSRIT, http://www.gramene.org/db/markers/ssrtool ) [26] under the search options of di-pentamer motif-lengths at a minimum frequency of three repeats [27] . C. vulgaris strain-specific primers were then designed based on the upstream/downstream flanking sequences of the screened microsatellite motifs.
- PCR Amplification and Genotyping
The PCR amplification was performed in a 20 μl reaction mixture containing 10-20 ng of the extracted genomic DNA of C. vulgaris , 0.5 pmole of each primer set, 200 μM of each dNTP, 2 mM of MgCl 2 , 0.5 units of Taq DNA polymerase, and 1× supplied buffer, using a GeneAmp system 2700 thermal cycler (Applied Biosystems, Foster City, CA, USA). The PCR amplification conditions were 95℃ for 5 min, followed by 35 cycles at 95℃ for 30 sec, 54℃ or 55℃ for 30 sec, and 72℃ for 30 sec, with a final extension at 72℃ for 7 min.
The PCR products were analyzed by electrophoresis to assess the polymorphic diversity of each microsatellite marker and determine the genotypes of the nine C. vulgaris strains. The PCR products were mixed with equal volumes of 2× STR loading buffer (10 mM NaOH, 95% formamide, 0.05% bromophenol blue, 0.05% xylene cyanol FF) (Promega, USA). After heating at 95℃ for 3 min, the mixtures were immediately chilled by dipping in ice. The electrophoresis was performed using a 5% denaturing polyacrylamide gel (acrylamide:bis-acrylamide = 19:1; thickness: 0.4 mm × length: 40 cm) containing 7 M urea in 1× TBE buffer at a constant voltage of 1,600 V for 2~4 h. The DNA bands were visualized using a DNA silver staining kit (Promega, USA) [2] . The sizes and repeat structures of the alleles were then determined by eluting the PCR bands from the silver-stained gels, amplifying the secondary PCR products, and sequencing the PCR products after purification. The alleles were arbitrarily named according to the size of the PCR bands and number of repeat motifs.
- Analysis of Specific Loci between mChl-001 and mChl-005 Microsatellite Markers
The interspace region between the mChl-001 and mChl-005 microsatellite markers was analyzed after the PCR amplification using a primer pair (mChl-001 forward primer, 5’-CCTATTGCTCTATGTTAACATATG-3’; and newly designed specific reverse primer, 5’-ACTGTGCGTTGGCTTGCTGTGCACGCATTAGC-3’). The conditions of the PCR amplification were 95℃ for 5 min, followed by 35 cycles at 95℃ for 30 sec, 60℃ for 30 sec, and 72℃ for 1 min, with a f inal e xtension at 72℃ f or 1 0 min. The PCR products were confirmed as single band amplicons by gel electrophoresis under 1.2% agarose, followed by a sequence analysis using a pGEM-T vector system (Promega, USA)
Results and Discussion
- Microsatellite Marker Design
A total of 234 repeat structures were screened from the chloroplast genome sequence of C. vulgaris C-27. The observed frequencies of the di-, tri-, tetra-nucleotides, and other repeats were 74% (174), 23% (54), 2.1% (5), and 0.9% (2), respectively ( Table 1 ). Thus, the predominance of dinucleotide repeats in the chloroplast of C. vulgaris was found to be notable when compared to the predominance of trinucleotide repeats (more than 57%) with the microsatellite distributions of crop plants, such as barley, maize, rice, and wheat [11] . Therefore, among the 234 microsatellite candidates, five novel primer pairs were selected that incorporated the proper nucleotide size (20-25 bp), optimal melting temperature for a PCR (50~65℃), and relatively short PCR amplicon size (100~300 bp) ( Table 2 ).
Characterization of repeat structures for identification of microsatellites.
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Characterization of repeat structures for identification of microsatellites.
Allelic structures of polymorphic microsatellite markers inC. vulgaris.
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P and N indicate the length of primer sequence and non-repeated flanking sequence, respectively. Sequence file supplied for supplementary data.
- Genotyping of C. vulgaris Strains using Microsatellite Markers
The genetic polymorphisms of nine C. vulgaris strains were examined using the five microsatellite markers. The sequence analysis of the PCR bands showed that the mChl-001 marker had (TTA) n repeat structures, where three alleles were detected and named allele 3, allele 5, and allele 7 according to the number of repeated (TTA) n motifs. The mChl-002 marker had (GAA) n repeat structures, where five alleles were detected and named allele 4-09, allele 5-10, allele 5-11, allele 6-12, and allele 10-12 according to the number of repeated (GAA) n motifs and length of (A) in the flanking sequences. In the case of allele 10-12, an additional sequence of (AAAGAC) was inserted between (GAA) 7 and (GAA) 2 . The mChl-005 marker had (AAAAAAAAAG) n repeat structures, where five alleles were detected and named allele 2, allele 3, allele 3.5, allele 4.5, and allele 5-5. In the case of ‘allele 5-5’, the number of repeated (AAAAAAAAAG) n motifs and the length of the flanking sequence were both different when compared with those of allele 2. All the PCR bands for the mChl-011 maker had the same (GTT) 4 repeat structures, yet only single nucleotide polymorphisms in their flanking sequences that were named allele A, allele T, and allele G. The mChl-012 marker yielded polymorphism lengths based on the difference of the length of the (AAG) n repeat motif and the length of the flanking sequences. The UTEX 396 and B1803 strains were not detected by the mChl-012 marker and named allele 0 ( Table 2 ).
All the C. vulgaris strains were distinguished based on the combination of the developed microsatellite markers, except for strains UTEX 265 and UTEX 1809, due to their identical genotype of 7,7-6-12,6-12-2,2-T-2,2. All the genotypes were regarded as homozygous, except for the mChl-005 loci of strains UTEX 396 and UTEX B1803 (bands 2 and 3 in Fig. 1 C). The double bands in the mChl-012 loci were regarded as band-splitting due to slightly different motilities between the sense and antisense strands of the homozygous alleles during the gel electrophoresis ( Fig. 1 E).
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Polymorphisms of microsatellite markers and genotyping of nine C. vulgaris strains. Numbers around each gel indicate strain (top) or allele (right) for (A) mChl-001, (B) mChl-002, (C) mChl-005, (D) mChl-011, and (E) mChl-012 microsatellite markers.
- Locus-Specific Genotyping using the Interspace Region between mChl-001 and mChl-005
The chloroplast genome revealed five microsatellite loci in the order of mChl-012, mChl-001, mChl-005, mChl-002, and mChl-011, where mChl-001 and mChl-005 were located close to each other at a distance of about 2.3 kb (Fig. S1). However, since the whole 2.3 kb sequence between these two loci could not be analyzed owing to the high frequency of AT repeats, a fragment of about 0.9 kb at the beginning of the 2.3 kb fragment was sequenced using a reverse primer designed in this study (5’-ACTGTGCGTTGGCTTGCTGTGCACGCATTAGC-3’). As a result, 17 simple sequence repeats were identified, including the (TTA) n repeat structure of the mCh1-001 microsatellite marker and different nucleotide compositions, such as tandem (T) repeat sequences ( Table 3 ). Hence, the total sequence difference was more than 10% within the 0.9 kb amplicon of the interspace region, providing a supplementary discrimination power between the two identical genotypes (7,7-6-12,6-12-2,2-T-2,2) of UTEX 265 and UTEX 1809 when using the five microsatellite markers ( Fig. 1 ).
Nucleotide compositions of nineC. vulgarisstrains in the interspace region between the mChl-001 and mChl-005 loci.
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Nucleotide compositions of nine C. vulgaris strains in the interspace region between the mChl-001 and mChl-005 loci.
Further investigation revealed that the three microsatellite markers mChl-012, mChl-002, and mChl-011 were located within open reading frames, where mChl-012 and mChl-002 were located in unknown genes, while mChl-011 was located in a postulated minD gene that is known to regulate cell division by coding a topological specificity factor [8] . Moreover, the interspace region between mChl-001 and mChl-005 was located in the family operon of the psbJ , psbL , psbF , and psbE genes to assign proteins for regulating the electron flow to the plastoquinone pool of photosystem II in photosynthetic organisms such as plants and algae [19 , 25] .
Previous genetic markers for identifying microalgae have mostly been developed based on noncoding ribosomal genes, such as 18S rRNA, small-subunit RNA (SSU), large-subunit RNA (LSU), and internal transcribed spacers (ITS). However, owing to the highly conserved gene diversities of noncoding RNA genes, this makes accurate discrimination of target organisms more difficult at lower taxonomical levels, such as species and strain. Yet, noncoding ribosomal genes can also be amplified from other symbiotic organisms, such as fungi or bacteria, owing to the difficulty of establishing axenic microalgae cultures. Furthermore, when compared with noncoding RNA genes, the high occurrence of microsatellites in the untranslated regions of expressed sequence tags can be a potentially useful source of geneassociated polymorphisms [1 , 13] . Therefore, molecular genotyping using the proposed five novel microsatellite markers and one specific interspace region is suggested to be more powerful than traditional genetic markers, such as 18S rRNA and ITS, in related fields of studies, such as genetic variation and quantitative trait mapping.
Acknowledgements
This study was supported by the Advanced Biomass R&D Center (ABC) of the Global Frontier Project funded by the Korean Ministry of Science, ICT and Future Planning (2010-0029719) and a grant from the KRIBB (Korea Research Institute of Bioscience and Biotechnology) Research Initiative Program.
References
Anti V , Jan N , Craig RP. 2005 Expressed sequence tag-linked microsatellites as a source of gene-associated polymorphisms for detecting signatures of divergent selection in Atlantic salmon (Salmo salar L.). Mol. Biol. Evol. 22 1067 - 1076    DOI : 10.1093/molbev/msi093
Bassam BJ , Caetano-Anollés G , Gresshoff PM. 1991 Fast and sensitive silver staining of DNA in polyacrylamide gels. Anal. Biochem. 196 80 - 83    DOI : 10.1016/0003-2697(91)90120-I
Bock C , Krienitz L , Pröeschold T. 2011 Taxonomic reassessment of the genus Chlorella (Trebouxiophyceae) using molecular signatures (barcodes), including description of seven new species. Fottea 11 293 - 312
Boyle G. 2004 Renewable Energy. Oxford University Press UK.
Chambers GK , MacAvoy ES. 2000 Microsatellites: consensus and controversy. Comp. Biochem. Physiol. B Biochem. Mol. Biol. 126 455 - 476    DOI : 10.1016/S0305-0491(00)00233-9
Chisti Y. 2007 Biodiesel from microalgae. Biotechnol. Adv. 25 294 - 306    DOI : 10.1016/j.biotechadv.2007.02.001
Cho SY , Nagai S , Han MS. 2009 Development of microsatellite markers in red-tide causative species Prorocentrum micans (Dinophyceae). Conserv. Genet. 10 1151 - 1153    DOI : 10.1007/s10592-008-9730-y
de Boer PA , Crossley RE , Rothfield LI. 1989 A division inhibitor and topological specificity factor coded for by the minicell locus determine proper placement of the division septum in E. coli. Cell 56 641 - 649    DOI : 10.1016/0092-8674(89)90586-2
Evans KM , Chepurnov VA , Mann DG. 2009 Ten microsatellite markers for the freshwater diatom Sellaphora capitata. Mol. Ecol. Resour. 9 216 - 218    DOI : 10.1111/j.1755-0998.2008.02383.x
Kang TJ , Fawley MW. 1997 Variable (CA/GT)n simple sequence repeat DNA in the alga Chlamydomonas. Plant Mol. Biol. 35 943 - 948    DOI : 10.1023/A:1005897400357
Kantety RV , La Rota M , Matthews DE , Sorrells ME. 2002 Data mining for simple sequence repeats in expressed sequence tags from barley, maize, rice, sorghum and wheat. Plant Mol. Biol. 48 501 - 510    DOI : 10.1023/A:1014875206165
Kim J , Jo BH , Lee KL , Yoon ES , Ryu GH , Chung KW. 2007 Identification of new microsatellite markers in Panax ginseng. Mol. Cells 24 60 - 68
Kim YO , Cho HK , Park EM , Nam BH , Hur YB , Lee SJ , Cheong J. 2008 Generation of expressed sequence tags for immune gene discovery and marker development in the sea squirt, Halocynthia roretzi. J. Microbiol. Biotechnol. 18 1510 - 1517
Li S , Zhang X , Yin T. 2010 Characteristics of microsatellites in the transcript sequences of the Laccaria bicolor genome. J. Microbiol. Biotechnol. 20 474 - 479
Mahmudul IN , Bian YB. 2010 Efficiency of RAPD and ISSR markers in differentiation of homo- and heterokaryotic protoclones of Agaricus bisporus. J. Microbiol. Biotechnol. 20 683 - 692    DOI : 10.4014/jmb.0906.06031
Mata TM , Martins AA , Caetano NS. 2010 Microalgae for biodiesel production and other applications: a review. Renew. Sust. Energ. Rev. 14 217 - 232    DOI : 10.1016/j.rser.2009.07.020
Nagai S , Lian C , Hamaguchi M , Matsuyama Y , Itakura S , Hogetsu T. 2004 Development of microsatellite markers in the toxic dinoflagellate Alexandrium tamarense (Dinophyceae). Mol. Ecol. Notes 4 83 - 85    DOI : 10.1046/j.1471-8286.2003.00576.x
Nagai S , McCauley L , Yasuda N , Erdner DL , Kulis DM , Matsuyama Y 2006 Development of microsatellite markers in the toxic dinoflagellate Alexandrium minutum (Dinophyceae). Mol. Ecol. Notes 6 756 - 758    DOI : 10.1111/j.1471-8286.2006.01331.x
Ohad I , Dal Bosco C , Herrmann RG , Meurer J. 2004 Photosystem II proteins PsbL and PsbJ regulate electron flow to the plastoquinone pool. Biochemistry 43 2297 - 2308    DOI : 10.1021/bi0348260
Phukan MM , Chutia RS , Konwar BK , Kataki R. 2011 Microalgae Chlorella as a potential bio-energy feedstock. Appl. Energy 88 3307 - 3312    DOI : 10.1016/j.apenergy.2010.11.026
Roder MS , Plaschke J , König SU , Börner A , Sorrells ME , Tanksley SD , Ganal MW. 1995 Abundance, variability and chromosomal location of microsatellites in wheat. Mol. Gen. Genet. 246 327 - 333    DOI : 10.1007/BF00288605
Semagn K , Bjørnstad Å , Ndjiondjop MN. 2007 An overview of molecular marker methods for plants. Afr. J. Biotechnol. 5 2540 - 2568
Shin SY , Jo BH , Lee HG , Oh HM. 2013 Physiological and ecological characteristics of lipid-producing Botryococcus isolated from the Korean freshwaters. Korean J. Environ. Biol. 31 288 - 294    DOI : 10.11626/KJEB.2013.31.4.288
Stanier RY , Kunisawa R , Mandel M , Cohen-Bazire G. 1971 Purification and properties of unicellular blue-green algae (order Chroococcales). Bacteriol. Rev. 35 171 - 205
Suorsa M , Regel RE , Paakkarinen V , Battchikova N , Herrmann RG , Aro EM. 2004 Protein assembly of photosystem II and accumulation of subcomplexes in the absence of low molecular mass subunits PsbL and PsbJ. Eur. J. Biochem. 271 96 - 107    DOI : 10.1046/j.1432-1033.2003.03906.x
Temnykh S , DeClerck G , Lukashova A , Lipovich L , Cartinhour S , McCouch S. 2001 Computational and experimental analysis of microsatellites in rice (Oryza sativa L.): frequency, length variation, transposon associations, and genetic marker potential. Genome Res. 11 1441 - 1452    DOI : 10.1101/gr.184001
Ware D , Jaiswal P , Ji J , Pan X , Chang K , Clark K 2002 Gramene: a resource for comparative grass genomics. Nucleic Acids Res. 30 103 - 105    DOI : 10.1093/nar/30.1.103