Analysis of protein homeostatic regulatory mechanisms in perturbed environments at steady state

Recovery of mrs3Δmrs4Δ Saccharomyces cerevisiae Cells under Iron-Sufficient Conditions and the Role of Fe580

Mrs3 and Mrs4 are mitochondrial inner membrane proteins that deliver an unidentified cytosolic iron species into the matrix for use in iron-sulfur cluster (ISC) and heme biosynthesis. The Mrs3/4 double-deletion strain (ΔΔ) grew slowly in iron-deficient glycerol/ethanol medium but recovered to wild-type (WT) rates in iron-sufficient medium. ΔΔ cells grown under both iron-deficient and iron-sufficient respiring conditions acquired large amounts of iron relative to WT cells, indicating iron homeostatic dysregulation regardless of nutrient iron status. Biophysical spectroscopy (including Mössbauer, electron paramagnetic resonance, and electronic absorption) and bioanalytical methods (liquid chromatography with online inductively coupled plasma mass spectrometry detection) were used to characterize these phenotypes. Anaerobically isolated mitochondria contained a labile iron pool composed of a nonheme high-spin FeII complex with primarily O and N donor ligands, called Fe580. Fe580 likely serves as feedstock for ISC and heme biosynthesis. Mitochondria from respiring ΔΔ cells grown under iron-deficient conditions were devoid of Fe580, ISCs, and hemes; most iron was present as FeIII nanoparticles. O2 likely penetrates the matrix of slow-growing poorly respiring iron-deficient ΔΔ cells and reacts with Fe580 to form nanoparticles, thereby inhibiting ISC and heme biosynthesis. Mitochondria from iron-sufficient ΔΔ cells contained ISCs, hemes, and Fe580 at concentrations comparable to those of WT mitochondria. The matrix of these mutant cells was probably sufficiently anaerobic to protect Fe580 from degradation by O2. An ∼1100 Da manganese complex, an ∼1200 Da zinc complex, and an ∼5000 Da copper species were also present in ΔΔ and WT mitochondrial flow-through solutions. No lower-mass copper complex was evident.

Biophysical investigation of the iron in Aft1-1(up) and Gal-YAH1 Saccharomyces cerevisiae

Aft1p is a major iron regulator in budding yeast Saccharomyces cerevisiae. It indirectly senses cytosolic Fe status and responds by activating or repressing iron regulon genes. Aft1p within the Aft1-1(up) strain has a single amino acid mutation which causes it to constitutively activate iron regulon genes regardless of cellular Fe status. This leads to elevated Fe uptake under both low and high Fe growth conditions. Ferredoxin Yah1p is involved in Fe/S cluster assembly, and Aft1p-targeted iron regulon genes are also upregulated in Yah1p-depleted cells. In this study Mössbauer, EPR, and UV-vis spectroscopies were used to characterize the Fe distribution in Aft1-1(up) and Yah1p-depleted cells. Aft1-1(up) cells grown in low Fe medium contained more Fe than did WT cells. A basal level of Fe in both WT and Aft1-1(up) cells was located in mitochondria, primarily in the form of Fe/S clusters and heme centers. The additional Fe in Aft1-1(up) cells was present as mononuclear HS Fe(III) species. These species are in a nonmitochondrial location, assumed here to be vacuolar. Aft1-1(up) cells grown in high Fe medium contained far more Fe than found in WT cells. The extra Fe was present as HS Fe(III) ions, probably stored in vacuoles, and as Fe(III) phosphate nanoparticles, located in mitochondria. Yah1p-deficent cells also accumulated nanoparticles in their mitochondria, but they did not contain HS Fe(III) species. Results are interpreted by a proposed model involving three homeostatic regulatory systems, including the Aft1 system, a vacuolar iron regulatory system, and a mitochondrial Fe regulatory system.

Dose response relationship in anti-stress gene regulatory networks

To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O₂, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on the level of local gains, presence of gain-changing events, and degree of feedforward gene activation, this region can appear as superlinear, sublinear, or even J-shaped. The general dose response transition proposed here was further examined in a complex anti-electrophilic stress pathway, which involves multiple genes, enzymes, and metabolic reactions. This work would help biologists and especially toxicologists to better assess and predict the cellular impact brought about by biological stressors.

To maintain a stable intracellular environment, cells are equipped with multiple specialized defense programs that are launched in response to various external chemical and physical stressors. These anti-stress mechanisms comprise primarily gene regulatory networks, and like many manmade control devices, such as thermostats and automobile cruise controls, they are often organized into negative feedback circuits. A quantitative understanding of how these control circuits operate in the cell can help us to assess and predict more accurately the cellular impacts brought about by perturbing stressors, such as environmental toxicants. Using control theory and computer simulations, we explored nature's design principle for anti-stress gene regulatory networks, and the manner in which cells respond and adapt to perturbations. We showed that cells can exploit multiple mechanisms, such as protein homodimerization, cooperative binding, and auto-regulation, to enhance the feedback loop gain, which, according to control theory, is a basic principle for effective perturbation resistance. We also illustrated that the steady-state dose response curve is likely to transition through multiple phases as stressor level increases, and that the low-dose region is inherently nonlinear. Our results challenge the common practice of linear extrapolation for evaluating the low-dose effect, and would lead to improved human health risk assessment for exposures to environmental toxicants.

Dynamic responses of protein homeostatic regulatory mechanisms to perturbations from steady state

Nineteen hypothetical protein homeostatic regulatory mechanisms were constructed and analysed in terms of the rate at which they recovered from a perturbation in the steady-state concentration of any component. Systems were constructed to symbolize transcription/translation processes of the average protein from Escherichia coli (1000 copies of protein P along with 1 gene G per cell). In some model systems, G catalysed the synthesis of P directly, while in others G catalysed the synthesis of mRNA (called M), and M catalysed the synthesis of P in a subsequent step. Recovery rates for each regulatory mechanism were obtained by generating the corresponding system of differential equations, linearizing the system about the steady state, and determining eigenvalues of the associated coefficient matrix. The optimal rate of recovery for a given mechanism, R(D), was determined by combining random and gradient search approaches to find rate constants for which the system recovered fastest. Regulatory elements that improved dynamic regulation were identified. These consisted of negative feedback relationships that involved P binding to either G (to shut off the synthesis of P) or M (to stimulate its degradation). Regulation improved as increasing numbers of P's bound to either G or M; however, the binding to M was more effective. In other mechanisms PP dimers bound G. Dimer-binding mechanisms were roughly twice as effective in terms of regulation as those that bound P monomers. The effect of linking two regulatory "modules" was also investigated. Linking had no effect on R(D), but optimal rate constants for the linked system were similar to those of the unlinked modules, suggesting that it may be feasible to construct regulatory networks by linking individual modules of this type.