Newly found 'Rosetta Stone' fossil site sheds light on early life forms

Researchers examined fossils from collections housed by National Museums Scotland and the Universities of Aberdeen and Oxford using the most recent non-destructive imaging techniques in conjunction with data analysis and machine learning.

Researchers from the University of Edinburgh were able to delve deeper than was previously feasible, which they claim may provide new information about samples that could be more well-preserved.

FTIR spectroscopy technique was used

Researchers discovered remarkable molecular information preservation within the rock's cells, tissues, and animals using FTIR spectroscopy, which uses infrared light to capture high-resolution data.

The researchers found molecular fingerprints that reliably distinguish between fungi, bacteria, and other groupings since they already knew which creatures most of the fossils represented.

Using these fingerprints, some of the more intriguing Rhynie ecosystem's inhabitants, such as two examples of a mystery tubular "nematophyte," were identified. These peculiar, previously difficult-to-classify creatures, found in Devonian and later Silurian strata, exhibit algal and fungal traits. According to the latest research, lichens or fungi were not likely to exist.

"We have shown how a quick, non-invasive method can be used to discriminate between different lifeforms, and this opens a unique window on the diversity of early life on Earth.” The team fed their data into a machine learning algorithm that could classify the different organisms, providing the potential for sorting other datasets from other fossil-bearing rocks," said Dr. Sean McMahonLead author, School of Physics and Astronomy and School of GeoSciences, University of Edinburgh.

The study was published in Nature Communications on March 13.

Study abstract:

The affinities of extinct organisms are often difficult to resolve using morphological data alone. Chemical analysis of carbonaceous specimens can complement traditional approaches, but the search for taxon-specific signals in ancient, thermally altered organic matter is challenging and controversial, partly because suitable positive controls are lacking. Here, we show that non-destructive Fourier Transform Infrared Spectroscopy (FTIR) resolves in-situ molecular fingerprints in the famous 407 Ma Rhynie chert fossil assemblage of Aberdeenshire, Scotland, an important early terrestrial Lagerstätte. Remarkably, unsupervised clustering methods (principal components analysis and K-mean) separate the fossil spectra naturally into eukaryotes and prokaryotes (cyanobacteria). Additional multivariate statistics and machine-learning approaches also differentiate prokaryotes from eukaryotes, and discriminate eukaryotic tissue types, despite the overwhelming influence of silica. We find that these methods can clarify the affinities of morphologically ambiguous taxa; in the Rhynie chert for example, we show that the problematic “nematophytes” have a plant-like composition. Overall, we demonstrate that the famously exquisite preservation of cells, tissues and organisms in the Rhynie chert accompanies similarly impressive preservation of molecular information. These results provide a compelling positive control that validates the use of infrared spectroscopy to investigate the affinity of organic fossils in chert.