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Comparative Transcriptomic Analysis of the Response of Dunaliella acidophila (Chlorophyta) to Short-Term Cadmium and Chronic Natural Metal-Rich Water Exposures

  • Environmental Microbiology
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Abstract

Heavy metals are toxic compounds known to cause multiple and severe cellular damage. However, acidophilic extremophiles are able to cope with very high concentrations of heavy metals. This study investigated the stress response under natural environmental heavy metal concentrations in an acidophilic Dunaliella acidophila. We employed Illumina sequencing for a de novo transcriptome assembly and to identify changes in response to high cadmium concentrations and natural metal-rich water. The photosynthetic performance was also estimated by pulse amplitude-modulated (PAM) fluorescence. Transcriptomic analysis highlights a number of processes mainly related to a high constitutive expression of genes involved in oxidative stress and response to reactive oxygen species (ROS), even in the absence of heavy metals. Photosynthetic activity seems to be unaltered under short-term exposition to Cd and chronic exposure to natural metal-rich water, probably due to an increase in the synthesis of structural photosynthetic components preserving their functional integrity. An overrepresentation of Gene Ontology (GO) terms related to metabolic activities, transcription, and proteosomal catabolic process was observed when D. acidophila grew under chronic exposure to natural metal-rich water. GO terms involved in carbohydrate metabolic process, reticulum endoplasmic and Golgi bodies, were also specifically overrepresented in natural metal-rich water library suggesting an endoplasmic reticulum stress response.

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References

  1. Debelius B, Forja JM, Del Valls TA, Lubián LM (2009) Toxicity of copper in natural marine picoplankton populations. Ecotoxicol 18:1095–1103

    Article  CAS  Google Scholar 

  2. Williams JJ, Dutton J, Chen CY, Fisher NS (2010) Metal (As, Cd, Hg, and CH3Hg) bioaccumulation from water and food by the benthic amphipod Leptocheirus plumulosus. Environ Toxicol Chem 29:1755–1761

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Nordstrom DK, Alpers CN (1999) Negative pH, efflorescent mineralogy and consequences from environmental restoration at the Iron Mountain Superfund site, California. PNAS 96:3455–3462

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Aguilera A, Manrubia SC, Gómez F, Rodríguez N, Amils R (2006) Eukaryotic community distribution and its relationship to water physicochemical parameters in an extreme acidic environment, Rio Tinto (SW, Spain). Appl Environ Microbiol 72:5325–5330

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Amaral-Zettler LA, Zettler ER, Theroux SM, Palacios C, Aguilera A, Amils R (2011) Microbial community structure across the tree of life in the extreme Río Tinto. ISME J 5:42–50

    Article  PubMed  Google Scholar 

  6. Volland S, Andosch A, Milla M, Stöger B, Lütz C, Lütz-Meindl U (2011) Intracellular metal compartmentalization in the green algal model system Micrasterias denticulata (Streptophyta) measured by transmission electron microscopy coupled electron energy loss spectroscopy. J Phycol 47:565–579

    Article  CAS  PubMed  Google Scholar 

  7. Andosch A, Affenzeller MJ, Lütz C, Lütz-Meindl U (2012) A freshwater green alga under cadmium stress: ameliorating calcium effects on ultrastructure and photosynthesis in the unicellular model Micrasterias. J Plant Physiol 169:1489–1500

    Article  CAS  PubMed  Google Scholar 

  8. Volland S, Schaumlöffel D, Dobritzsch D, Krauss GJ, Lütz-Meindl U (2013) Identification of phytochelatins in the cadmium-stressed conjugating green alga Micrasterias denticulate. Chemosphere 91:448–454

    Article  CAS  PubMed  Google Scholar 

  9. Forbes VE (1998) Genetics and Ecotoxicology. Taylor & Francis, Ann Arbor

    Google Scholar 

  10. Aguilera A, Amils R (2005) Tolerance to cadmium in Chlamydomonas sp. (Chlorophyta) strains isolated from an extreme acidic environment, the Tinto River (SW, Spain). Aquat Toxicol 75:316–329

    Article  CAS  PubMed  Google Scholar 

  11. Gimmler H, Weis U, Weiss C, Kugel H, Treffny B (1989) Dunaliella acidophila (Kalina) Masyuk an alga with a positive membrane potential. New Phytol lI 3:175–184

    Article  Google Scholar 

  12. González-Toril E, Llobet-Brossa E, Casamayor EO, Amann R, Amils R (2003) Microbial ecology of an extreme acidic environment, the Tinto River. Appl Environ Microbiol 69:4853–4865

    Article  PubMed  PubMed Central  Google Scholar 

  13. Brayner R, Dahoumane SA, Nguyen JN, Yéprémian C, Djediat C, Couté A, Fiévet F (2011) Ecotoxicological studies of CdS nanoparticles on photosynthetic microorganisms. J Nanosci Nanotech 11:1852–1858

    Article  CAS  Google Scholar 

  14. Okamoto OK, Asano CS, Aidar E, Colepicolo P (1996) Effects of cadmium on growth and superoxide dismutase activity of the marine microalga Tetraselmis gracilis (Prasinophyceae). J Phycol 32:74–79

    Article  CAS  Google Scholar 

  15. Bajguz A (2010) Suppression of Chlorella vulgaris growth by cadmium, lead, and copper stress and its restoration by endogenous brassinolide. Arch Environ Contam Toxicol 60:406–416

    Article  PubMed  PubMed Central  Google Scholar 

  16. Lamai C, Kruatrachue M, Pokethitiyook P, Upatham ES, Soonthornsarathool V (2005) Toxicity and accumulation of lead and cadmium in the filamentous green alga Cladophora fracta Kützing: a laboratory study. Sci Asia 31:121–127

    Article  CAS  Google Scholar 

  17. Prasad MNV, Strzalka K (1999) Impact of heavy metals on photosynthesis. In: Prasad MNV, Hagemeyer J (eds) Heavy metal stress in plants: from molecules to ecosystems. Springer, Berlin, pp 117–128

    Chapter  Google Scholar 

  18. Rivetta A, Negrini N, Cocucci M (1997) Involvement of Ca2+-calmodulin in Cd2+ toxicity during the early phases of radish (Raphanus sativus L.) seed germination. Plant Cell Environ 20:600–608

    Article  CAS  Google Scholar 

  19. Lauer C, Bonatto D, Mielniczki-Pereira AA, Schuch AZ, Dias JF, Yoneama M, Pegas JA (2008) The Pmr1protein, the major yeast Ca2+-ATPase in the Golgi, regulates intracellular levels of the cadmium ion. FEMS Microbiol Lett 285:79–88

    Article  CAS  Google Scholar 

  20. Lütz-Meindl U, Luckner M, Andosch A, Wanner G (2015) Structural stress responses and degradation of dictyosomes in algae analysed by TEM and FIB-SEM tomography. J Microsc DOI. doi:10.1111/jmi.12369

    Google Scholar 

  21. Mendoza-Cozatl DG, Moreno-Sanchez RM (2005) Cd2+ transport and storage in the chloroplast of Euglena gracilis. Biochim Biophys Acta 1706:88–97

    Article  CAS  PubMed  Google Scholar 

  22. Nassiri Y, Mansot L, Ginsburger-Vogel T, Amiard JC (1997) Ultrastructural and electron energy loss spectroscopy studies of sequestration mechanisms of Cd and Cu in the marine diatom Skeletonema costatum. Arch Environ Contam Toxicol 33:147–155

    Article  CAS  PubMed  Google Scholar 

  23. Nassiri Y, Wery J, Mansot L, Ginsburger-Vogel T (1997) Cadmium bioaccumulation in Tetraselmis suecica: an electron energy loss spectroscopy (EELS) study. Arch Environ Contam Toxicol 33:156–161

    Article  CAS  PubMed  Google Scholar 

  24. Eggert A, Raimund S, Michalik D, West J, Karsten U (2007) Ecophysiological performance of the primitive red alga Dixoniella grisea (Rhodellophyceae) to irradiance, temperature and salinity stress: growth responses and the osmotic role of mannitol. Phycologia 46:22–28

    Article  Google Scholar 

  25. Gustavs L, Eggert A, Michalik D, Karsten U (2009) Physiological and biochemical responses of green microalgae from different habitats to osmotic and matric stress. Protoplasma 243:3–14

    Article  PubMed  Google Scholar 

  26. Petrou K, Doblin MA, Smith RA, Ralph PJ, Shelly K, Beardall J (2008) State transitions and non-photochemical quenching during a nutrient induced fluorescence transient in phosphate starved Duniella tertiolecta. J Phycol 44:1204–1211

    Article  CAS  PubMed  Google Scholar 

  27. Puente-Sánchez F, Olsson S, Gómez-Rodriguez M, Souza-Egipsy V, Altamirano-Jeschke M, Amils R, Parro V, Aguilera A (2016) Solar radiation stress in natural acidophilic biofilms of Euglena mutabilis revealed by metatranscriptomics and PAM fluorometry. Protists 167:67–81

    Article  Google Scholar 

  28. Hutchinsa CM, Simon DF, Zerges W, Wilkinson KJ (2010) Transcriptomic signatures in Chlamydomonas reinhardtii as Cd biomarkers in metal mixtures. Aquat Toxicol 100:120–127

    Article  Google Scholar 

  29. Jamers A, Blust R, Coen WD, Griffin JL, Jones OAH (2013) An omics based assessment of cadmium toxicity in the green alga Chlamydomonas reinhardtii. Aquat Toxicol 126:355–364

    Article  CAS  PubMed  Google Scholar 

  30. Zhang W, Tana N, Li SF (2014) NMR-based metabolomics and LC-MS/MS quantification reveal metal-specific tolerance and redox homeostasis in Chlorella vulgaris. Mol Biosyst 10:149–160

    Article  CAS  PubMed  Google Scholar 

  31. Rippka R, Deruelles J, Waterbury J, Herdman M, Stanier R (1979) Generic assignments, strain histories and properties of pure cultures of cyanobacteria. J Gen Microbiol 111:1–61

    Google Scholar 

  32. Guillard RR, Ryther JH (1962) Studies of marine planktonic diatoms. I. Cyclotella nana Hustedt and Detonula confervacea Cleve. Can J Microbiol 8:229–239

    Article  CAS  PubMed  Google Scholar 

  33. Schreiber U, Schliwa U, Bilger W (1986) Continuous recording of photochemical and non-photochemical chlorophyll fluorescence quenching with a new type of modulation fluorometer. Photosyn Res 10:51–62

    Article  CAS  PubMed  Google Scholar 

  34. Bischof K, Hanelt D, Wiencke C (1998) UV-radiation can affect depth-zonation of Antarctic macroalgae. Mar Biol 131:597–605

    Article  Google Scholar 

  35. Sokal RR, Rohlf FJ (1995) Biometry. Springer, New York

    Google Scholar 

  36. Schmieder R, Edwards R (2011) Quality control and preprocessing of metagenomic datasets. Bioinformatics 27:863–864

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I et al (2011) Full-length transcriptome assembly from RNA-seq data without a reference genome. Nature Biotechnol 29:644–652

    Article  CAS  Google Scholar 

  38. Marcais G, Kingsford C (2011) A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27:764–770

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25

    Article  PubMed  PubMed Central  Google Scholar 

  41. Robinson MD, McCarthy DJ, Smyth GK (2010) EdgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140

    Article  CAS  PubMed  Google Scholar 

  42. Chen Y, McArthy D, Robinson M, Smyth GK (2015) edgeR: differential expression analysis of digital gene expression data., User’s guide, https://bioconductor.org/packages/3.3/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf

    Google Scholar 

  43. Conesa A, Götz S (2008) Blast2GO: a comprehensive suite for functional analysis in plant genomics. Int J Plant Genom 58:619832

    Google Scholar 

  44. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N et al (2009) The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics 25:2078–2079

    Article  PubMed  PubMed Central  Google Scholar 

  45. García-Alcalde F, Okonechnikov K, Carbonell J, Cruz LM, Götz S, Tarazona S et al (2012) Qualimap: evaluating next generation sequencing alignment data. Bioinformatics 28:2678–2679

    Article  PubMed  Google Scholar 

  46. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nuc Acid Res 25:3389–3402

    Article  CAS  Google Scholar 

  47. De Wit P, Pespeni M, Ladner J, Barshis D, Seneca F et al (2012) The simple fool’s guide to population genomics via RNA-seq: an introduction to high-throughput sequencing data analysis. Mol Ecol Resour 12:1058–1067

    Article  PubMed  Google Scholar 

  48. Gomez-Alvarez V, Teal TK, Schmidt TM (2009) Systematic artifacts in metagenomes from complex microbial communities. ISME J 3:1314–1317

    Article  PubMed  Google Scholar 

  49. Saha SK, Moane S, Murray P (2013) Effect of macro- and micro-nutrient limitation on superoxide dismutase activities and carotenoid levels in microalga Dunaliella salina CCAP 19/18. Biores Technol 147:23–28

    Article  CAS  Google Scholar 

  50. Faller P, Kienzler K, Krieger-Liszkay A (2005) Mechanism of Cd2+ toxicity: Cd2+ inhibits fotoactivation of photosystem II by competitive binding to the essential Cd2+ site. Biochim Biophys Act 1706:158–164

    Article  CAS  Google Scholar 

  51. Ben-Amotz A, Polle JEW, Rao DVS (2009) The Alga Dunaliella: biodiversity, physiology, genomics, and biotechnology. Science Publishers, Enfield

    Book  Google Scholar 

  52. García-Gomez C, Parages ML, Jimenez C, Palma A, Mata MT, Segovia M (2012) Cell survival after UV radiation stress in the unicellular chlorophyte Dunaliella tertiolecta is mediated by DNA repair and MAPK phosphorylation. J Exp Bot 63:5259–5274

    Article  PubMed  PubMed Central  Google Scholar 

  53. Gimmler H, Schiede M, Kowalski M, Zimmermann U, Pick U (1991) Dunaliella acidophila: an alga with a positive zeta potential at its optimal pH for growth. Plant Cell Environ 14:261–269

    Article  CAS  Google Scholar 

  54. Tsujia N, Hirayanagia N, Iwabea O, Nambaa T, Tagawaa M et al (2003) Regulation of phytochelatin synthesis by zinc and cadmium in marine green alga, Dunaliella tertiolecta. Phytochem 62:453–459

    Article  Google Scholar 

  55. Nikookar K, Moradshahi A, Hosseini L (2005) Physiological responses of Dunaliella salina and Dunaliella tertiolecta to copper toxicity. Biomol Engineer 22:141–146

    Article  CAS  Google Scholar 

  56. Marcano LB, Carruyo IM, Montiel XM, Morales CB, de Soto PM (2009) Effect of cadmium on cellular viability in two species of microalgae (Scenedesmus sp. and Dunaliella viridis). Biol Trace Elem Res 130:86–93

    Article  CAS  PubMed  Google Scholar 

  57. Mangold S, Potrykus J, Björn E, Lövgren L, Dopson M (2012) Extreme zinc tolerance in acidophilic microorganisms from the bacterial and archaeal domains. Extremophiles 17:75–85

    Article  PubMed  Google Scholar 

  58. Dopson M, Ossandon FJ, Lövgren L, Holmes DS (2014) Metal resistance or tolerance? Acidophiles confront high metal loads via both abiotic and biotic mechanisms. Front Microbiol 5:157

    Article  PubMed  PubMed Central  Google Scholar 

  59. Mera R, Torres E, Abalde J (2014) Sulphate, more than a nutrient, protects the microalga Chlamydomonas moewusii from cadmium toxicity. Aquat Toxicol 148:92–103

    Article  CAS  PubMed  Google Scholar 

  60. Hirata K, Tsuji N, Miyamoto K (2005) Biosynthetic regulation of phytochelatins, heavy metal binding peptides. J Biosci Bioengine 100:593–599

    Article  CAS  Google Scholar 

  61. Rea PA (2012) Phytochelatin synthase: of a protease a peptide polymerase made. Physiol Plant 145:154–164

    Article  CAS  PubMed  Google Scholar 

  62. Nishikawa K, Onodera A, Tominaga N (2006) Phytochelatins do not correlate with the level of Cd accumulation in Chlamydomonas spp. Chemosphere 63:1553–1559

    Article  CAS  PubMed  Google Scholar 

  63. Mendoza-Cózatl DG, Jobe TO, Hauser F, Schroeder JI (2011) Long distance transport, vacuolar sequestration, tolerance, and transcriptional responses induced by cadmium and arsenic. Curr Opin Plant Biol 14:554–562

    Article  PubMed  PubMed Central  Google Scholar 

  64. Jacobson T, Navarrete C, Sharma SK, Sideri TC, Ibstedt S, Priya S et al (2012) Arsenite interferes with protein folding and triggers formation of protein aggregates in yeast. J Cell Sci 125:5073–5083

    Article  CAS  PubMed  Google Scholar 

  65. Halter D, Andres J, Plewniak F, Poulain J, Da Silva C, Arsène-Ploetze F, Bertin PN (2014) Arsenic hypertolerance in the protist Euglena mutabilis is mediated by specific transporters and functional integrity maintenance mechanisms. Environ Microbioly 17:1941–1949

    Article  Google Scholar 

  66. Bérubé K, Dodge J, Ford T (1999) Effects of chronic salt stress on the ultrastructure of Dunaliella bioculata (Chlorophyta, Volvocales): mechanisms of response and recovery. J Phycol 34:117–123

    Article  Google Scholar 

  67. Perales-Vela HV, Peña-Castro JM, Cañizares-Villanueva RO (2006) Heavy metal detoxification in eukaryotic microalgae. Chemosphere 64:1–10

    Article  CAS  PubMed  Google Scholar 

  68. Siyan-Cao J, Kaufman RJ (2012) Unfolded protein response. Curr Biol 22:R622–R626

    Article  Google Scholar 

  69. Malhotra JD, Kaufman RJ (2007) Endoplasmic reticulum stress and oxidative stress: a vicious cycle or a double-edged sword? Antiox Redox Signal 9:2277–2294

    Article  CAS  Google Scholar 

  70. Ozgur R, Turkan I, Uzilday B, Sekmen AH (2014) Endoplasmic reticulum stress triggers ROS signalling, changes the redox state, and regulates the antioxidant defence of Arabidopsis thaliana. J Exp Bot 65:1377–1390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

Funding was provided by the Spanish Ministry of Economy and Competitivity (MINECO) under Grants No. CGL2011-22540 and CGL2015-69758. F. Puente-Sánchez was supported by a JAE-predoctoral fellowship Consejo Superior de Investigaciones Científicas (CSIC). We acknowledge the Data Intensive Academic Grid (DIAG) computing infrastructure (funded by National Science Foundation under Grant No. 0959894 titled MRI-R2: Acquisition of Data Intensive Academic Grid (DIAG)) as well as CSC – Finnish IT Center for Science and the Finnish grid infrastructure (FGI) for the allocation of computational resources.

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Authors and Affiliations

  1. Centro de Astrobiología (INTA-CSIC), Carretera de Ajalvir Km 4, Torrejón de Ardoz, 28850, Madrid, Spain

    Fernando Puente-Sánchez & Angeles Aguilera

  2. Present address: Systems Biology Program. Centro Nacional de Biotecnología (CSIC). c/ Darwin 3, 28049, Madrid, Spain

    Fernando Puente-Sánchez

  3. Department of Agricultural Sciences, University of Helsinki, P.O. Box 27, FI-00014, Helsinki, Finland

    Sanna Olsson

  4. Department of Forest Ecology and Genetics, INIA, Forest Research Centre, Carretera A Coruña km 7.5, 28040, Madrid, Spain

    Sanna Olsson

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  1. Fernando Puente-Sánchez
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  3. Angeles Aguilera
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Correspondence to Angeles Aguilera.

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Fig. S1

Differential Biological Process (BP) GO-Term distribution. Relative proportions of significantly up-regulated transcripts belonging to each Gene Ontology category for the three transcriptomic libraries. The x-axis contains the proportion of significantly up-regulated transcripts in each category, the y-axis shows the GO-categories. GO IDs are presented in parenthesis. (DOCX 17 kb)

Fig. S2

Differential Molecular Function (MF) GO-Term distribution. Relative proportions of significantly up-regulated transcripts belonging to each Gene Ontology category for the three transcriptomic libraries. The x-axis contains the proportion of significantly up-regulated transcripts in each category, the y-axis shows the GO-categories. GO IDs are presented in parenthesis. (DOCX 17 kb)

Fig. S3

Differential Cell Component (CC) GO-Term distribution. Relative proportions of significantly up-regulated transcripts belonging to each Gene Ontology category for the three transcriptomic libraries. The x-axis contains the proportion of significantly up-regulated transcripts in each category, the y-axis shows the GO-categories. GO IDs are presented in parenthesis. (DOCX 16 kb)

Table S1

Ion concentrations (mM) of the natural water from Río Tinto used as growth media (RTW). (DOCX 13 kb)

Table S2

Significant differentially expressed transcripts in D. acidophila with significant blast homologies and gene-ontology (GO) terms. When many isoforms from the same Trinity subcomponent shared the same blastx result, only the one with the highest expression in each condition was reported. LogFC values were obtained from Trimmed-Mean-of-M-values (TMM) - normalized expresion values by using the edgeR function “predFC”.(XLSX 503 kb)

Table S3

Significant differentially expressed transcripts in D. acidophila with significant blast homologies and gene-ontology (GO) terms. When many isoforms from the same Trinity subcomponent shared the same blastx result, only the one with the highest expression in each condition was reported. LogFC values were obtained from Trimmed-Mean-of-M-values (TMM) - normalized expresion values by using the edgeR function “predFC”.(XLSX 24.1 kb)

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Puente-Sánchez, F., Olsson, S. & Aguilera, A. Comparative Transcriptomic Analysis of the Response of Dunaliella acidophila (Chlorophyta) to Short-Term Cadmium and Chronic Natural Metal-Rich Water Exposures. Microb Ecol 72, 595–607 (2016). https://doi.org/10.1007/s00248-016-0824-7

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