Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Haematococcus pluvialis Cell-Mass Sensing Using Ultraviolet Fluorescence Spectroscopy

  • Lababpour, Abdolmajid (Institute of Industrial Biotechnology, Department of Biotechnology, Inha University) ;
  • Hong, Seong-Joo (Institute of Industrial Biotechnology, Department of Biotechnology, Inha University) ;
  • Lee, Choul-Gyun (Institute of Industrial Biotechnology, Department of Biotechnology, Inha University)
  • Published : 2007.12.31
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Abstract

A simple whole-cell-based sensing system is proposed for determining the cell mass of H. pluvialis using ultraviolet fluorescence spectroscopy. An emission signal at 368 nm was used to detect the various kinds of green, green-brown, brown-red, and red H. pluvialis cells. The fluorescence emission intensities of the cells were highest at 368 nm with an excitation wavelength of 227 nm. An excitation wavelength of 227 nm was then selected for cell-mass sensing, as the emission fluorescence intensities of the cell suspensions were highest at this wavelength after subtracting the background interference. The emission fluorescence intensities of HPLC-grade water, filtered water, and HPLC-grade water containing a modified Bold's basal medium (MBBM) were measured and the difference was less than 1.6 for the selected wavelengths. Moreover, there was no difference in the emission intensity at 368 nm among suspensions of the various morphological states of the cells. A calibration curve of the fluorescence emission intensities. and cell mass was obtained with a high correlation ($R^2=0.9938$) for the various morphological forms of H. pluvialis. Accordingly, the proposed method showed no significant dependency on the various morphological cell forms, making it applicable for cell-mass measurement. A high correlation was found between the fluorescence emission intensities and the dry cell weight with a mixture of green, green-brown, brown-red, and red cells. In conclusion, the proposed model can be directly used for cell-mass sensing without any pretreatment and has potential use as a noninvasive method for the online determination of algal biomass.

Keywords

References

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