Adaptation of Acidithiobacillus ferrooxidans to the extreme acid mine drainage environment

Acidithiobacillus ferrooxidans is an important species within the acid mine drainage environment and within biomining applications. To better understand its ability to adapt to the extreme physico-chemical stressors found in these systems, the cytoplasmic membrane characteristics of physiologically distinct strains were examined for evidence of active membrane adaptation. The simultaneous analysis of membrane fluidity, phase, and fatty acid composition provide a multivariate approach to facilitate the understanding of the effects of extreme stresses on a viable bacterial membrane and the means by which A. ferrooxidans compensates for stress-induced perturbations. These methods are used to assess the effects of cold temperatures, pH, copper, and nickel concentrations both individually and in binary combinations. Strain variation is illustrated through a range of adaptive mechanisms and reflects the ability of given strains to better tolerate particularly extreme levels of stress compared to strains that are sensitive. Additional investigation into the unique membrane features of psychrotrophic A. ferrooxidans strains finds that not only do they have abilities to tolerate sub-optimal membrane properties, but also induce a host of global stress-response and membrane related proteins as well as increase the transcription for fatty acid synthase and desaturase enzymes following cold shock and in cold-adapted cells. The ability to oxidize ferrous iron at 5°C is also related to a more efficient induction of rusticyanin synthesis compared to mesophilic strains exposed to 15°C. A general adaptive model is presented and indicates that control of the total unsaturated and cyclopropane 19:0 fatty acids is a primary mechanism for altering membrane properties under stress in A. ferrooxidans. Membrane properties can be used for identifying more stress tolerant A. ferrooxidans strains for optimization of biomining processes, in particular, to assess the synergistic or antagonistic effects of multiple variables.