Back

Taking extreme measures: A quantitative study of multiple stress interactions at the limits of life.

Cane, R.; Cockell, C.

2020-01-14 microbiology
10.1101/2020.01.13.905562 bioRxiv
Show abstract

Environments exposed to simultaneously occurring extremes are prevalent in the natural world, yet analysis of such settings tends to focus on the effect of single environmental stresses. In this study, quantitative multiplicative and minimising models previously used to study nutrient limitation were applied to the growth of the hydrothermal vent-dwelling organism Halomonas hydrothermalis when subjected to combined nutrient limitation and NaCl-salt stress. Results showed an interactive effect from both salt and nutrient stresses under optimal conditions. However, the fit became more non-interactive as salinity is increased; at which point NaCl-salt had a more dominating effect on growth than inorganic phosphate (Pi). We discuss biochemical hypotheses to explain these data. This work shows that models developed to understand nutrient limitation can be used to quantify and separate the contributions of stresses under other physical and chemical extremes, such as extreme salinity, and facilitate the development of biochemical hypotheses of how extremes may be influencing cell physiology. ImportanceVery few environments in the natural world are exposed to just one extreme or stress at a time. To understand lifes ability to survive in multiple-extreme environments, we must be able to quantify how different extremes interact. Using methods developed for the study of multiple nutrient limitation, this study uses kinetic growth models to investigate at the effect of extreme environments on bacterial growth. Results show that closer to the extremes of life, individual stresses dominate growth; whereas under optimal conditions there is a multiplicative effect from both salt and nutrient stresses. This approach offers a new way to quantify and potentially understand and develop hypotheses for how life operates under multiple extremes.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.