2003 Annual Science Report

Arizona State University Reporting  |  JUL 2002 – JUN 2003

Nanoscale Minerals as Biomarkers

4 Institutions
3 Teams
0 Publications
0 Field Sites
Field Sites

Project Progress

Using electron tomography, we showed that there is too much uncertainty in any transmission-electron-microscopy (TEM) results to date to confirm a biogenic origin for the magnetite in meteorite ALH84001. The magnetite crystals in bacterial strain MV-1, the standard for comparison for meteoritic magnetite, show variations within a chain and rounding of faces, which are neither as well developed nor as crisp as in published interpretations.

We implemented the acquisition and processing of digital three-dimensional (3-D) tomograms using several distinct methods of TEM imaging, which has involved the development of automated acquisition systems for two TEMs. One of these systems is fully implemented, and the other is in the process of testing and debugging. These modifications will allow computer control of the sample stage, electron beam, and focussing current so that the acquisition of a tilt-series of images (140 images) can be accomplished far more rapidly and with higher fidelity than if done “by hand.” The several acquisition modes will allow us to extract complementary signals to fully characterize the crystallites.

We made modifications to accommodate differences in images arising from different acquisition modes. Visualization and extraction of quantitative data from the reconstructed 3-D data cube is an essential aspect of this research. Algorithms are being tested to define the boundaries of interior objects of different densities so that volume and bounding surface data can be obtained reliably.

We studied whether the characteristics of crystal size distributions (CSDs) and shape factor distributions (SFDs) of magnetite from magnetotactic bacteria can be used as biomarkers. CSDs of magnetite from 16 uncultured strains revealed both similarities and differences among crystals from bacteria from distinct localities and environments. Using a numerical method, we sorted magnetite crystal populations based on features of the SFD of all particles. We found that the numerical methods are useful for identifying bacterial magnetite in rocks.