ISSN (print) 0868-8540, (online) 2413-5984
logoAlgologia
  • 4 of 9
Up
Algologia 2017, 27(4): 403–414
https://doi.org/10.15407/alg27.04.403
Physiology, Biochemistry, Biophysics

Rapid method for simultaneous discrimination of microalgae and determination on biochemical composition based on vibrational spectroscopy

Sureshkumar P.1, Thomas J.1, Sivasubramanian J.2
Abstract

Fourier-transform infrared (FT-IR) spectroscopy is a high-resolution spectroscopic method used in whole-organism molecular fingerprinting. This analysis helps for the characteristic determination of macromolecular spectrum in intact cells. Spectral analysis can discriminate, classify, and identify the microorganisms as composition of macromolecules is different between strains of the same species. In the present investigation, four different microalgae were studied for their variations in spectral data, which showed striking differences on their major macromolecules. Scenedesmus obliquus (Turp.) Kütz. have intense peaks in the lipids and protein spectral regions when compared to the other species. Chlorella vulgaris Beij., Ch. pyrenedosa Chick and Euglena gracilis Klebs possessed moderate and less intense peaks in sub sequential order in all the five spectral regions. Using FT-IR spectra, hierarchical clustering analyses resulted in a dendrogram with clear discrimination between species according to their phenotype variations. To support this, phylogenetic analysis using 16S rDNA microbial barcode sequences of these microalgal strains was evaluated and the resulting phylogram showed the same cluster pattern as revealed by FT-IR based dendrogram. Hence, this study concludes that the combination of phylogenetic analysis and the FT-IR spectra provides an effective way of distinguishing the species as well as the advantage of simultaneous determination of biochemical composition of the species.

Keywords: FT-IR spectra, microalgae, cluster analysis, phylogenetic analysis, species discrimination, fingerprint, biochemical composition

Full text: PDF (Rus) 222K

References
  1. Bradford M.M. A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 1976. 72: 248. https://doi.org/10.1016/0003-2697(76)90527-3
  2. Cakmak G., Togan I., Severcan F. 17-Estradiol induced compositional, structural and functional changes in rainbow trout liver, revealed by FT-IR spectroscopy: A comparative study with nonylphenol. Aquat. Toxicol. 2006. 77: 53–63. https://doi.org/10.1016/j.aquatox.2005.10.015 https://www.ncbi.nlm.nih.gov/pubmed/16325934
  3. de Moraes G.P., Vieira A.A.H. Fourier Transform Infrared with Attenuated Total Reflectance Applied to the Discrimination of Freshwater Planktonic Coccoid Green Microalgae. PloS One. 2014. 9(12): 1–21. https://doi.org/10.1371/journal.pone.0114458 https://www.ncbi.nlm.nih.gov/pubmed/25541701 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4277285
  4. Dean A.P., Martin M.C., Sigee D.C. Resolution of codominant phytoplankton species in a eutrophic lake using synchrotron-based Fourier transform infrared spectroscopy. Phycologia. 2007. 46: 151–159. https://doi.org/10.2216/06-27.1
  5. Dean A.P., Sigee D.C., Estrada B., Pittman J.K. Using FT-IR spectroscopy for rapid determination of lipid accumulation in response to nitrogen limitation in freshwater microalgae. Biores. Technol. 2010. 101: 4499–4507. https://doi.org/10.1016/j.biortech.2010.01.065 https://www.ncbi.nlm.nih.gov/pubmed/20153176
  6. Driver T., Bajhaiya A., Pittman, J.K. Potential of bioenergy production from microalgae. Curr. Syst. Renew. Energy Rep. 2014. 1: 94–103. https://doi.org/10.1007/s40518-014-0011-8
  7. Giordano M., Kansiz M., Heraud P., Beardall J., Wood B., McNaughton D. Fourier transform infrared spectroscopy as a novel tool to investigate changes in intracellular macromolecular pools in the marine microalga Chaetocerosmuellerii (Bacillariophyceae). J. Phycol. 2001. 37: 271–279. https://doi.org/10.1046/j.1529-8817.2001.037002271.x
  8. Giordano M., Ratti S., Domenighini A., Vogt F. Spectroscopic classification of 14 different microalga species: first steps towards spectroscopic measurement of phytoplankton biodiversity. Plant. Ecol. Divers. 2009. 2: 155–164. https://doi.org/10.1080/17550870903353088
  9. Mayers J.J., Flynn K.J., Shields R.J. Rapid determination of bulk microalgal biochemical composition by Fourier-Transform Infrared spectroscopy. Biores. Technol. 2013. 148: 215–220. https://doi.org/10.1016/j.biortech.2013.08.133 https://www.ncbi.nlm.nih.gov/pubmed/24050924
  10. Movasaghi Z., Rehman S., Rehmen I.U. Fourier Transform Infrared (FT-IR) spectroscopy of biological tissues. Appl. Spectroscop. Rev. 2008. 43: 134–179. https://doi.org/10.1080/05704920701829043
  11. Murdock J.H., Wetzel D.L. FT-IR microspectroscopy enhances biological and ecological analysis of algae. Appl. Spectrosc. Rev. 2009. 44: 335–361. https://doi.org/10.1080/05704920902907440
  12. Naumann D., Labischinski H., Giesbrecht P. The characterization of microorganisms by Fourier Transform Infrared Spectroscopy. In: Modern techniques for Rapid Microbiological Analysis. Weinheim; New York: VCH Verlag Chemie, 1991. P. 43–96.
  13. Pistorius M., DeGrip W.J., Egorova-Zachernyuk T.A. Monitoring of biomass composition from microbiological sources by means of FT-IR spectroscopy. Biotechnol. Bioeng. 2009. 103(1): 123–129. https://doi.org/10.1002/bit.22220 https://www.ncbi.nlm.nih.gov/pubmed/19132745
  14. Sivakumar S., Sivasubramanian J., Chandra Prasad Khatiwada, Manivannan J., Raja B. Aluminium induced metabolic changes in kidney and heart tissue of mice: a Fourier transform infrared spectroscopy study. RSC Advanc. 2013. 3: 20896–20904. https://doi.org/10.1039/c3ra42714e
  15. Wagner H., Liu Z., Langner U., Stehfest K., Wilhelm C. The use of FT-IR spectroscopy to assess quantitative changes in the biochemical composition of microalgae. J. Biophoton. 2010. 3: 557–566. https://doi.org/10.1002/jbio.201000019 https://www.ncbi.nlm.nih.gov/pubmed/20503222
  16. Ward J.H. Hierarchial grouping to optimize an objective function. J. Amer. Stat. Assoc. 1963. 58: 236–244. https://doi.org/10.1080/01621459.1963.10500845