Discrimination of natural gas-related bacteria by means of micro-Raman spectroscopy |
| |
| Institution: | 1. Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), College of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430072, China;2. Regional Institutes for Food and Drug Control, Yingbin Road 299, Kashgar 844099, China;3. China Center for Type Culture Collection, Wuhan University, Wuhan 430072, China;1. College of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, Baoji 721016, PR China;2. Baoji Key Laboratory of Ultrafast Spectroscopy, Baoji 721016, PR China;3. College of Physics and Information Technology, Shaanxi Normal University, Xi?an 710062, PR China;1. Department of Earth and Environmental Sciences, Rutgers University, Newark, NJ 07102, USA;2. Key Laboratory of Global Change and Marine-Atmospheric Chemistry, Third Institute of Oceanography, State Oceanic Administration, Xiamen, Fujian 361005, China;3. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China |
| |
| Abstract: | Methane-oxidizing bacteria (MOB) are a unique group of gram-negative bacteria that are proved to be biological indicator for gas prospecting since they utilize methane as a sole source of carbon and energy. Herein the feasibility of a novel and efficient gas prospecting method using Raman spectroscopy is studied. Confocal Raman spectroscopy is utilized to establish a Raman database of 11 species of methanotrophs and other closely related bacteria with similar morphology that generally coexist in the upper soil of natural gas. After strict and consistent spectral preprocessing, Raman spectra from the whole cell area are analyzed using the combination of principal component analysis (PCA) and Mahalanobis distance (MD) that allow unambiguous classification of the different cell types with an accuracy of 95.91%. The discrimination model based on multivariate analysis is further evaluated by classifying Raman spectra from independently cultivated bacteria, and achieves an overall accuracy of 94.04% on species level. Our approach using Raman spectroscopy in combination with statistical analysis of various gas reservoirs related bacteria provides rapid distinction that can potentially play a vital role in gas exploration. |
| |
| Keywords: | Raman spectroscopy Cellular distinction Methane-oxidizing bacteria Multivariate analysis Natural gas prospection |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
