Detecting Phytoplankton Cell Viability Using NIR Raman Spectroscopy and PCA

Nina I Novikova; Hannah Matthews; Isabelle Williams; Mary A Sewell; Michel K Nieuwoudt; M Cather Simpson; Neil G R Broderick

doi:10.1021/acsomega.1c06262

Detecting Phytoplankton Cell Viability Using NIR Raman Spectroscopy and PCA

ACS Omega. 2022 Feb 10;7(7):5962-5971. doi: 10.1021/acsomega.1c06262. eCollection 2022 Feb 22.

Authors

Nina I Novikova^{1

2

3

4}, Hannah Matthews^{1

2

3

4}, Isabelle Williams^{1

2

3

4}, Mary A Sewell⁵, Michel K Nieuwoudt^{1

2

3

4}, M Cather Simpson^{1

2

3

4}, Neil G R Broderick^{6

2

3}

Affiliations

¹ School of Chemical Sciences, University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand.
² The Photon Factory, University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand.
³ The Dodd-Walls Centre for Photonic and Quantum Technologies, Science III Building, 730 Cumberland Street, Dunedin 9016, New Zealand.
⁴ MacDiarmid Institute for Advanced Materials and Nanotechnology, Wellington Central, Wellington 6011, New Zealand.
⁵ School of Biological Sciences, University of Auckland, 3A Symonds Street, Auckland 1010, New Zealand.
⁶ Department of Physics, University of Auckland, 38 Princes Street, Auckland 1010, New Zealand.

Abstract

Raman spectroscopy has long been suggested as a potentially fast and sensitive method to monitor phytoplankton abundance and composition in marine environments. However, the pitfalls of visible detection methods in pigment-rich biological material and the complexity of their spectra have hindered their application as reliable in situ detection methods. In this study we combine 1064 nm confocal Raman spectroscopy with multivariate statistical analysis techniques (principle component analysis and partial leas-squares discriminant analysis) to reliably measure differences in the cell viability of a diatom species (Chaetoceros muelleri) and two haptophyte species (Diacronema lutheri and Tisochrysis lutea) of phytoplankton. The low fluorescence background due to this combined approach of NIR Raman spectroscopy and multivariate data analysis allowed small changes in the overall spectral profiles to be reliably monitored, enabling the identification of the specific spectral features that could classify cells as viable or nonviable regardless of their species. The most significant differences upon cell death were shown by characteristic shifts in the carotenoid bands at 1527 and 1158 cm^-1. The contributions from other biomolecules were less pronounced but revealed changes that could be identified using this combination of techniques.