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  3. Chemical identification of microfossils from the 1.88‐Ga Gunflint chert: Towards empirical biosignatures using laser ablation ionization mass spectrometer
 

Chemical identification of microfossils from the 1.88‐Ga Gunflint chert: Towards empirical biosignatures using laser ablation ionization mass spectrometer

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BORIS DOI
10.48350/161272
Date of Publication
October 2021
Publication Type
Article
Division/Institute

Physikalisches Instit...

Author
Lukmanov, Rustam
Physikalisches Institut, Weltraumforschung und Planetologie (WP)
Tulej, Marekorcid-logo
Physikalisches Institut, Weltraumforschung und Planetologie (WP)
Ligterink, Niels Frank Willem
Physikalisches Institut, Weltraumforschung und Planetologie (WP)
de Koning, Coenraad Pieter
Physikalisches Institut, Weltraumforschung und Planetologie (WP)
Riedo, Andreasorcid-logo
Physikalisches Institut, Weltraumforschung und Planetologie (WP)
Riedo, Valentine
Physikalisches Institut, Weltraumforschung und Planetologie (WP)
Neubeck, Anna
Wacey, David
Wurz, Peterorcid-logo
Physikalisches Institut, Weltraumforschung und Planetologie (WP)
Subject(s)

500 - Science::520 - ...

500 - Science::530 - ...

600 - Technology::620...

Series
Journal of chemometrics
ISSN or ISBN (if monograph)
0886-9383
Publisher
Wiley
Language
English
Publisher DOI
10.1002/cem.3370
Description
In this contribution, we investigated the chemical composition of Precambrianmicrofossils from the Gunflint chert (1.88 Ga) using a miniature laser ablationionization mass spectrometer (LIMS) developed for in situ space applications.Spatially resolved mass spectrometric imaging (MSI) and depth profilingresulted in the acquisition of 68,500 mass spectra. Using single mass unit spec-tral decomposition and multivariate data analysis techniques, we identified thelocation of aggregations of microfossils and surrounding inorganic host min-eral. Our results show that microfossils have unique chemical compositionsthat can be distinguished from the inorganic chert with high fidelity. Chemicaldepth profiling results also show that with LIMS microprobe data, it is possibleto identify chemical differences between individual microfossils, thereby pro-viding new insights about nature of early life. Analysis of LIMS spectraacquired from the individual microfossils revea ls complex mineralization,which can reflect the metabolic diversity of the Gunflint microbiome. Anintensity-based machine learning model trained on LIMS Gunflint data mightbe applied for the future investigations of putative microfossils from silicifiedmatrices, where morphological integrity of investigated structures is lost, andpotentially in the investigation of rocks acquired from the Martian surface
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/57579
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File(s)
FileFile TypeFormatSizeLicensePublisher/Copright statementContent
cem.3370.pdftextAdobe PDF60.31 MBpublishedOpen
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