Silicates Eroded under Simulated Martian Conditions Effectively Kill Bacteria-A Challenge for Life on Mars.

The habitability of Mars is determined by the physical and chemical environment. The effect of low water availability, temperature, low atmospheric pressure and strong UV radiation has been extensively studied in relation to the survival of microorganisms. In addition to these stress factors, it was recently found that silicates exposed to simulated saltation in a Mars-like atmosphere can lead to a production of reactive oxygen species. Here, we have investigated the stress effect induced by quartz and basalt abraded in Mars-like atmospheres by examining the survivability of the three microbial model organisms Pseudomonas putida, Bacillus subtilis, and Deinococcus radiodurans upon exposure to the abraded silicates. We found that abraded basalt that had not been in contact with oxygen after abrasion killed more than 99% of the vegetative cells while endospores were largely unaffected. Exposure of the basalt samples to oxygen after abrasion led to a significant reduction in the stress effect. Abraded quartz was generally less toxic than abraded basalt. We suggest that the stress effect of abraded silicates may be caused by a production of reactive oxygen species and enhanced by transition metal ions in the basalt leading to hydroxyl radicals through Fenton-like reactions. The low survivability of the usually highly resistant D. radiodurans indicates that the effect of abraded silicates, as is ubiquitous on the Martian surface, would limit the habitability of Mars as well as the risk of forward contamination. Furthermore, the reactivity of abraded silicates could have implications for future manned missions, although the lower effect of abraded silicates exposed to oxygen suggests that the effects would be reduced in human habitats.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution.