4.4 Article

Development of a Surface-Enhanced Raman Spectroscopic Methodology to Detect Immobilized Organic Materials in Biogeological Contexts

期刊

ASTROBIOLOGY
卷 21, 期 9, 页码 1089-1098

出版社

MARY ANN LIEBERT, INC
DOI: 10.1089/ast.2020.2278

关键词

Raman spectroscopy; Biomarkers; SERS

资金

  1. University of Bradford

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The likelihood of finding intact cellular structures on the surface or in the near subsurface of Mars is slim due to intense bombardment of the surface by ionizing radiation. Therefore, it is more logical to search for evidence of microbial life by looking for molecules produced by the breakdown of cellular matter, known as biomarkers. Raman spectroscopy, a method used for detecting organic biomarkers among inorganic geomaterials, has low signal intensity on the martian surface due to the low concentration of organics.
The likelihood of finding intact cellular structures on the surface or in the near subsurface of the martian regolith is slim, due in part to the intense bombardment of the surface by ionizing radiation from outer space. Given that this radiation is predicted to be so intense that it would render a living cell inactive within minutes, it is logical to search for evidence of microbial life by looking for molecules produced by the breakdown of cellular matter. This pool of molecules, known as biomarkers, consists of a range of species with various functionalities that make them likely to interact with minerals in the martian regolith. Raman spectroscopy, a molecularly specific analysis method utilized for detecting organic biomarkers among inorganic geomaterials, suffers from low signal intensity when the concentration of organics is as low as it appears to be on the martian surface. This article describes the utility of a surface-enhanced Raman spectroscopy (SERS) method used to detect extremely low levels of biomarkers that were passively adhered to mineral surfaces in a method that represents how this interaction would take place in a natural environment on Mars. The methodology showed promise for the detection of multiple classes of biomarkers.

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