Predictive reconstruction of the mitochondrial iron-sulfur cluster assembly metabolism: I. The role of the protein pair ferredoxin-ferredoxin reductase (Yah1-Arh1)

A kinetic model of iron trafficking in growing Saccharomyces cerevisiae cells; applying mathematical methods to minimize the problem of sparse data and generate viable autoregulatory mechanisms

Iron is an essential transition metal for all eukaryotic cells, and its trafficking throughout the cell is highly regulated. However, the overall cellular mechanism of regulation is poorly understood despite knowing many of the molecular players involved. Here, an ordinary-differential-equations (ODE) based kinetic model of iron trafficking within a growing yeast cell was developed that included autoregulation. The 9-reaction 8-component in-silico cell model was solved under both steady-state and time-dependent dynamical conditions. The ODE for each component included a dilution term due to cell growth. Conserved rate relationships were obtained from the null space of the stoichiometric matrix, and the reduced-row-echelon-form was used to distinguish independent from dependent rates. Independent rates were determined from experimentally estimated component concentrations, cell growth rates, and the literature. Simple rate-law expressions were assumed, allowing rate-constants for each reaction to be estimated. Continuous Heaviside logistical functions were used to regulate rate-constants. These functions acted like valves, opening or closing depending on component "sensor" concentrations. Two cellular regulatory mechanisms were selected from 134,217,728 possibilities using a novel approach involving 6 mathematically-defined filters. Three cellular states were analyzed including healthy wild-type cells, iron-deficient wild-type cells, and a frataxin-deficient strain of cells characterizing the disease Friedreich's Ataxia. The model was stable toward limited perturbations, as determined by the eigenvalues of Jacobian matrices. Autoregulation allowed healthy cells to transition to the diseased state when triggered by a mutation in frataxin, and to the iron-deficient state when cells are placed in iron-deficient growth medium. The in-silico phenotypes observed during these transitions were similar to those observed experimentally. The model also predicted the observed effects of hypoxia on the diseased condition. A similar approach could be used to solve ODE-based kinetic models associated with other biochemical processes operating within growing cells.

A mathematical model for strigolactone biosynthesis in plants

Strigolactones mediate plant development, trigger symbiosis with arbuscular mycorrhizal fungi, are abundant in 80% of the plant kingdom and help plants gain resistance to environmental stressors. They also induce germination of parasitic plant seeds that are endemic to various continents, such as Orobanche in Europe or Asia and Striga in Africa. The genes involved in the early stages of strigolactones biosynthesis are known in several plants. The regulatory structure and the latter parts of the pathway, where flux branching occurs to produce alternative strigolactones, are less well-understood. Here we present a computational study that collects the available experimental evidence and proposes alternative biosynthetic pathways that are consistent with that evidence. Then, we test the alternative pathways through in silico simulation experiments and compare those experiments to experimental information. Our results predict the differences in dynamic behavior between alternative pathway designs. Independent of design, the analysis suggests that feedback regulation is unlikely to exist in strigolactone biosynthesis. In addition, our experiments suggest that engineering the pathway to modulate the production of strigolactones could be most easily achieved by increasing the flux of β-carotenes going into the biosynthetic pathway. Finally, we find that changing the ratio of alternative strigolactones produced by the pathway can be done by changing the activity of the enzymes after the flux branching points.

Molecular modeling of the binding modes of the iron-sulfur protein to the Jac1 co-chaperone from Saccharomyces cerevisiae by all-atom and coarse-grained approaches

The iron-sulfur protein 1 (Isu1) and the J-type co-chaperone Jac1 from yeast are part of a huge ATP-dependent system, and both interact with Hsp70 chaperones. Interaction of Isu1 and Jac1 is a part of the iron-sulfur cluster biogenesis system in mitochondria. In this study, the structure and dynamics of the yeast Isu1-Jac1 complex has been modeled. First, the complete structure of Isu1 was obtained by homology modeling using the I-TASSER server and YASARA software and thereafter tested for stability in the all-atom force field AMBER. Then, the known experimental structure of Jac1 was adopted to obtain initial models of the Isu1-Jac1 complex by using the ZDOCK server for global and local docking and the AutoDock software for local docking. Three most probable models were subsequently subjected to the coarse-grained molecular dynamics simulations with the UNRES force field to obtain the final structures of the complex. In the most probable model, Isu1 binds to the left face of the Γ-shaped Jac1 molecule by the β-sheet section of Isu1. Residues L105 , L109 , and Y163 of Jac1 have been assessed by mutation studies to be essential for binding (Ciesielski et al., J Mol Biol 2012; 417:1-12). These residues were also found, by UNRES/molecular dynamics simulations, to be involved in strong interactions between Isu1 and Jac1 in the complex. Moreover, N(95), T(98), P(102), H(112), V(159), L(167), and A(170) of Jac1, not yet tested experimentally, were also found to be important in binding.

Two distinct and competitive pathways confer the cellcidal actions of artemisinins

The biological actions of artemisinin (ART), an antimalarial drug derived from Artemisia annua, remain poorly understood and controversial. Besides potent antimalarial activity, some of artemisinin derivatives (together with artemisinin, hereafter referred to as ARTs), in particular dihydroartemisinin (DHA), are also associated with anticancer and other antiparasitic activities. In this study, we used baker’s yeast Saccharomyces cerevisiae as cellular and genetic model to investigate the molecular and cellular properties of ARTs. Two clearly separable pathways exist. While all ARTs exhibit potent anti-mitochondrial actions as shown before, DHA exerts an additional strong heme-dependent, likely mitochondria-independent inhibitory action. More importantly, heme antagonizes the mitochondria-dependent cellcidal action. Indeed, when heme synthesis was inhibited, the mitochondria-dependent cellcidal action of ARTs could be dramatically strengthened, and significant yeast growth inhibition at as low as 100 nM ART, an increase of about 25 folds in sensitivity, was observed. We conclude that ARTs are endowed with two major and distinct types of properties: a potent and specific mitochondria-dependent reaction and a more general and less specific heme-mediated reaction. The competitive nature of these two actions could be explained by their shared source of the consumable ARTs, so that inhibition of the heme-mediated degradation pathway would enable more ARTs to be available for the mitochondrial action. These properties of ARTs can be used to interpret the divergent antimalarial and anticancer actions of ARTs.

Biochemical Systems Theory: A Review

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.

Glutathione regulates the transfer of iron-sulfur cluster from monothiol and dithiol glutaredoxins to apo ferredoxin

Holo glutaredoxin (Grx) is a homo-dimer that bridges a [2Fe-2S] cluster with two glutathione (GSH) ligands. In this study, both monothiol and dithiol holo Grxs are found capable of transferring their iron-sulfur (FeS) cluster to an apo ferredoxin (Fdx) through direct interaction, regardless of FeS cluster stability in holo Grxs. The ligand GSH molecules in holo Grxs are unstable and can be exchanged with free GSH, which inhibits the FeS cluster transfer from holo Grxs to apo Fdx. This phenomenon suggests a novel role of GSH in FeS cluster trafficking.

Cysteine desulfurase Nfs1 and Pim1 protease control levels of Isu, the Fe-S cluster biogenesis scaffold

Fe-S clusters are critical prosthetic groups for proteins involved in various critical biological processes. Before being transferred to recipient apo-proteins, Fe-S clusters are assembled on the highly conserved scaffold protein Isu, the abundance of which is regulated posttranslationally on disruption of the cluster biogenesis system. Here we report that Isu is degraded by the Lon-type AAA+ ATPase protease of the mitochondrial matrix, Pim1. Nfs1, the cysteine desulfurase responsible for providing sulfur for cluster formation, is required for the increased Isu stability occurring after disruption of cluster formation on or transfer from Isu. Physical interaction between the Isu and Nfs1 proteins, not the enzymatic activity of Nfs1, is the important factor in increased stability. Analysis of several conditions revealed that high Isu levels can be advantageous or disadvantageous, depending on the physiological condition. During the stationary phase, elevated Isu levels were advantageous, resulting in prolonged chronological lifespan. On the other hand, under iron-limiting conditions, high Isu levels were deleterious. Compared with cells expressing normal levels of Isu, such cells grew poorly and exhibited reduced activity of the heme-containing enzyme ferric reductase. Our results suggest that modulation of the degradation of Isu by the Pim1 protease is a regulatory mechanism serving to rapidly help balance the cell's need for critical iron-requiring processes under changing environmental conditions.

Investigation of in vivo diferric tyrosyl radical formation in Saccharomyces cerevisiae Rnr2 protein: requirement of Rnr4 and contribution of Grx3/4 AND Dre2 proteins

The β(2) subunit of class Ia ribonucleotide reductase (RNR) contains a diferric tyrosyl radical cofactor (Fe(2)(III)-Tyr(•)) that is essential for nucleotide reduction. The β(2) subunit of Saccharomyces cerevisiae is a heterodimer of Rnr2 (β) and Rnr4 (β'). Although only β is capable of iron binding and Tyr(•) formation, cells lacking β' are either dead or exhibit extremely low Tyr(•) levels and RNR activity depending on genetic backgrounds. Here, we present evidence supporting the model that β' is required for iron loading and Tyr(•) formation in β in vivo via a pathway that is likely dependent on the cytosolic monothiol glutaredoxins Grx3/Grx4 and the Fe-S cluster protein Dre2. rnr4 mutants are defective in iron loading into nascent β and are hypersensitive to iron depletion and the Tyr(•)-reducing agent hydroxyurea. Transient induction of β' in a GalRNR4 strain leads to a concomitant increase in iron loading and Tyr(•) levels in β. Tyr(•) can also be rapidly generated using endogenous iron when permeabilized Δrnr4 spheroplasts are supplemented with recombinant β' and is inhibited by adding an iron chelator prior to, but not after, β' supplementation. The growth defects of rnr4 mutants are enhanced by deficiencies in grx3/grx4 and dre2. Moreover, depletion of Dre2 in GalDRE2 cells leads to a decrease in both Tyr(•) levels and ββ' activity. This result, in combination with previous findings that a low level of Grx3/4 impairs RNR function, strongly suggests that Grx3/4 and Dre2 serve in the assembly of the deferric Tyr(•) cofactor in RNR.

Iron-sulfur clusters: biogenesis, molecular mechanisms, and their functional significance

Iron-sulfur clusters [Fe-S] are small, ubiquitous inorganic cofactors representing one of the earliest catalysts during biomolecule evolution and are involved in fundamental biological reactions, including regulation of enzyme activity, mitochondrial respiration, ribosome biogenesis, cofactor biogenesis, gene expression regulation, and nucleotide metabolism. Although simple in structure, [Fe-S] biogenesis requires complex protein machineries and pathways for assembly. [Fe-S] are assembled from cysteine-derived sulfur and iron onto scaffold proteins followed by transfer to recipient apoproteins. Several predominant iron-sulfur biogenesis systems have been identified, including nitrogen fixation (NIF), sulfur utilization factor (SUF), iron-sulfur cluster (ISC), and cytosolic iron-sulfur protein assembly (CIA), and many protein components have been identified and characterized. In eukaryotes ISC is mainly localized to mitochondria, cytosolic iron-sulfur protein assembly to the cytosol, whereas plant sulfur utilization factor is localized mainly to plastids. Because of this spatial separation, evidence suggests cross-talk mediated by organelle export machineries and dual targeting mechanisms. Although research efforts in understanding iron-sulfur biogenesis has been centered on bacteria, yeast, and plants, recent efforts have implicated inappropriate [Fe-S] biogenesis to underlie many human diseases. In this review we detail our current understanding of [Fe-S] biogenesis across species boundaries highlighting evolutionary conservation and divergence and assembling our knowledge into a cellular context.

A Boolean probabilistic model of metabolic adaptation to oxygen in relation to iron homeostasis and oxidative stress

Background

In aerobically grown cells, iron homeostasis and oxidative stress are tightly linked processes implicated in a growing number of diseases. The deregulation of iron homeostasis due to gene defects or environmental stresses leads to a wide range of diseases with consequences for cellular metabolism that remain poorly understood. The modelling of iron homeostasis in relation to the main features of metabolism, energy production and oxidative stress may provide new clues to the ways in which changes in biological processes in a normal cell lead to disease.

Results

Using a methodology based on probabilistic Boolean modelling, we constructed the first model of yeast iron homeostasis including oxygen-related reactions in the frame of central metabolism. The resulting model of 642 elements and 1007 reactions was validated by comparing simulations with a large body of experimental results (147 phenotypes and 11 metabolic flux experiments). We removed every gene, thus generating in silico mutants. The simulations of the different mutants gave rise to a remarkably accurate qualitative description of most of the experimental phenotype (overall consistency > 91.5%). A second validation involved analysing the anaerobiosis to aerobiosis transition. Therefore, we compared the simulations of our model with different levels of oxygen to experimental metabolic flux data. The simulations reproducted accurately ten out of the eleven metabolic fluxes. We show here that our probabilistic Boolean modelling strategy provides a useful description of the dynamics of a complex biological system. A clustering analysis of the simulations of all in silico mutations led to the identification of clear phenotypic profiles, thus providing new insights into some metabolic response to stress conditions. Finally, the model was also used to explore several new hypothesis in order to better understand some unexpected phenotypes in given mutants.

Conclusions

All these results show that this model, and the underlying modelling strategy, are powerful tools for improving our understanding of complex biological problems.

Mathematical modeling of monolignol biosynthesis in Populus xylem

Recalcitrance of lignocellulosic biomass to sugar release is a central issue in the production of biofuel as an economically viable energy source. Among all contributing factors, variations in lignin content and its syringyl-guaiacyl monomer composition have been directly linked with the yield of fermentable sugars. While recent advances in genomics and metabolite profiling have significantly broadened our understanding of lignin biosynthesis, its regulation at the pathway level is yet poorly understood. During the past decade, computational and mathematical methods of systems biology have become effective tools for deciphering the structure and regulation of complex metabolic networks. As increasing amounts of data from various organizational levels are being published, the application of these methods to studying lignin biosynthesis appears to be very beneficial for the future development of genetically engineered crops with reduced recalcitrance. Here, we use techniques from flux balance analysis and nonlinear dynamic modeling to construct a mathematical model of monolignol biosynthesis in Populus xylem. Various types of experimental data from the literature are used to identify the statistically most significant parameters and to estimate their values through an ensemble approach. The thus generated ensemble of models yields results that are quantitatively consistent with several transgenic experiments, including two experiments not used in the model construction. Additional model results not only reveal probable substrate saturation at steps leading to the synthesis of sinapyl alcohol, but also suggest that the ratio of syringyl to guaiacyl monomers might not be affected by genetic modulations prior to the reactions involving coniferaldehyde. This latter model prediction is directly supported by data from transgenic experiments. Finally, we demonstrate the applicability of the model in metabolic engineering, where the pathway is to be optimized toward a higher yield of xylose through modification of the relative amounts of the two major monolignols. The results generated by our preliminary model of in vivo lignin biosynthesis are encouraging and demonstrate that mathematical modeling is poised to become an effective and predictive complement to traditional biotechnological and transgenic approaches, not just in microorganisms but also in plants.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

BACKGROUND

Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements.

RESULTS

We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer-approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock

CONCLUSION

Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Recent developments in parameter estimation and structure identification of biochemical and genomic systems

The organization, regulation and dynamical responses of biological systems are in many cases too complex to allow intuitive predictions and require the support of mathematical modeling for quantitative assessments and a reliable understanding of system functioning. All steps of constructing mathematical models for biological systems are challenging, but arguably the most difficult task among them is the estimation of model parameters and the identification of the structure and regulation of the underlying biological networks. Recent advancements in modern high-throughput techniques have been allowing the generation of time series data that characterize the dynamics of genomic, proteomic, metabolic, and physiological responses and enable us, at least in principle, to tackle estimation and identification tasks using 'top-down' or 'inverse' approaches. While the rewards of a successful inverse estimation or identification are great, the process of extracting structural and regulatory information is technically difficult. The challenges can generally be categorized into four areas, namely, issues related to the data, the model, the mathematical structure of the system, and the optimization and support algorithms. Many recent articles have addressed inverse problems within the modeling framework of Biochemical Systems Theory (BST). BST was chosen for these tasks because of its unique structural flexibility and the fact that the structure and regulation of a biological system are mapped essentially one-to-one onto the parameters of the describing model. The proposed methods mainly focused on various optimization algorithms, but also on support techniques, including methods for circumventing the time consuming numerical integration of systems of differential equations, smoothing overly noisy data, estimating slopes of time series, reducing the complexity of the inference task, and constraining the parameter search space. Other methods targeted issues of data preprocessing, detection and amelioration of model redundancy, and model-free or model-based structure identification. The total number of proposed methods and their applications has by now exceeded one hundred, which makes it difficult for the newcomer, as well as the expert, to gain a comprehensive overview of available algorithmic options and limitations. To facilitate the entry into the field of inverse modeling within BST and related modeling areas, the article presented here reviews the field and proposes an operational 'work-flow' that guides the user through the estimation process, identifies possibly problematic steps, and suggests corresponding solutions based on the specific characteristics of the various available algorithms. The article concludes with a discussion of the present state of the art and with a description of open questions.

Computational systems analysis of dopamine metabolism

A prominent feature of Parkinson's disease (PD) is the loss of dopamine in the striatum, and many therapeutic interventions for the disease are aimed at restoring dopamine signaling. Dopamine signaling includes the synthesis, storage, release, and recycling of dopamine in the presynaptic terminal and activation of pre- and post-synaptic receptors and various downstream signaling cascades. As an aid that might facilitate our understanding of dopamine dynamics in the pathogenesis and treatment in PD, we have begun to merge currently available information and expert knowledge regarding presynaptic dopamine homeostasis into a computational model, following the guidelines of biochemical systems theory. After subjecting our model to mathematical diagnosis and analysis, we made direct comparisons between model predictions and experimental observations and found that the model exhibited a high degree of predictive capacity with respect to genetic and pharmacological changes in gene expression or function. Our results suggest potential approaches to restoring the dopamine imbalance and the associated generation of oxidative stress. While the proposed model of dopamine metabolism is preliminary, future extensions and refinements may eventually serve as an in silico platform for prescreening potential therapeutics, identifying immediate side effects, screening for biomarkers, and assessing the impact of risk factors of the disease.

Mitochondrial targeting of intact CYP2B1 and CYP2E1 and N-terminal truncated CYP1A1 proteins in Saccharomyces cerevisiae − role of protein kinase A in the mitochondrial targeting of CYP2E1

Previously we showed that intact rat cytochrome P450 2E1, cytochrome P450 2B1 and truncated cytochrome P450 1A1 are targeted to mitochondria in rat tissues and COS cells. However, some reports suggest that truncated cytochrome P450 2E1 is targeted to mitochondria. In this study, we used a heterologous yeast system to ascertain the conservation of targeting mechanisms and the nature of mitochondria-targeted proteins. Mitochondrial integrity and purity were established using electron microscopy, and treatment with digitonin and protease. Full-length cytochrome P450 2E1 and cytochrome P450 2B1 were targeted both to microsomes and mitochondria, whereas truncated cytochrome P450 1A1 (+ 5 and + 33/cytochrome P450 1A1) were targeted to mitochondria. Inability to target intact cytochrome P450 1A1 was probably due to lack of cytosolic endoprotease activity in yeast cells. Mitochondrial targeting of cytochrome P450 2E1 was severely impaired in protein kinase A-deficient cells. Similarly, a phosphorylation site mutant cytochrome P450 2E1 (Ser129A) was poorly targeted to the mitochondria, thus confirming the importance of protein kinase A-mediated protein phosphorylation in mitochondrial targeting. Mitochondria-targeted proteins were localized in the matrix compartment peripherally associated with the inner membrane and their ethoxyresorufin O-dealkylation, erythromycin N-demethylase, benzoxyresorufin O-dealkylation and nitrosodimethylamine N-demethylase activities were fully supported by yeast mitochondrial ferredoxin and ferredoxin reductase.

In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae

Background

Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC).

Results

Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure.

Conclusion

We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models.

Cooperativity and saturation in biochemical networks: A saturable formalism using Taylor series approximations

Cooperative and saturable systems are common in molecular biology. Nevertheless, common canonical formalisms for kinetic modeling that are theoretically well justified do not have a saturable form. Modeling and fitting data from saturable systems are widely done using Hill-like equations. In practice, there is no theoretical justification for the generalized use of these equations, other than their ability to fit experimental data. Thus it is important to find a canonical formalism that is (a) theoretically well supported, (b) has a saturable functional form, and (c) can be justifiably applicable to any biochemical network. Here we derive such a formalism using Taylor approximations in a special transformation space defined by power-inverses and logarithms of power-inverses. This formalism is generalized for processes with n-variables, leading to a useful mathematical representation for molecular biology: the Saturable and Cooperative Formalism (SC formalism). This formalism provides an appropriate representation that can be used for modeling processes with cooperativity and saturation. We also show that the Hill equation can be seen as a special case within this formalism. Parameter estimation for the SC formalism requires information that is also necessary to build Power-Law models, Metabolic Control Analysis descriptions or (log)linear and Lin-log models. In addition, the saturation fraction of the relevant processes at the operating point needs to be considered. The practical use of the SC formalism for modeling is illustrated with a few examples. Similar models are built using different formalisms and compared to emphasize advantages and limitations of the different approaches.

Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

Background

Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response.

Results

We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression.

Conclusion

Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.

How Escherichia coli and Saccharomyces cerevisiae build Fe/S proteins

Owing to the versatile electronic properties of iron and sulfur, iron sulfur (Fe/S) clusters are perfectly suited for sensing changes in environmental conditions and regulating protein properties accordingly. Fe/S proteins have been recruited in a wide array of diverse biological processes, including electron transfer chains, metabolic pathways and gene regulatory circuits. Chemistry has revealed the great diversity of Fe/S clusters occurring in proteins. The question now is to understand how iron and sulfur come together to form Fe/S clusters and how these clusters are subsequently inserted into apoproteins. Iron, sulfide and reducing conditions were found to be sufficient for successful maturation of many apoproteins in vitro, opening the possibility that insertion might be a spontaneous event. However, as in many other biological pathways such as protein folding, genetic analyses revealed that Fe/S cluster biogenesis and insertion depend in vivo upon auxiliary proteins. This was brought to light by studies on Azotobacter vinelandii nitrogenase, which, in particular, led to the concept of scaffold proteins, the role of which would be to allow transient assembly of Fe/S cluster. These studies paved the way toward the identification of the ISC and SUF systems, subjects of the present review that allow Fe/S cluster assembly into apoproteins of most organisms. Despite the recent discovery of the SUF and ISC systems, remarkable progress has been made in our understanding of their molecular composition and biochemical mechanisms. Such a rapid increase in our knowledge arose from a convergent interest from researchers engaged in unrelated fields and whose complementary expertise covered most experimental approaches used in biology. Also, the high conservation of ISC and SUF systems throughout a wide array of organisms helped cross-feeding between studies. The ISC system is conserved in eubacteria and most eukaryotes, while the SUF system arises in eubacteria, archaea, plants and parasites. ISC and SUF systems share a common core function made of a cysteine desulfurase, which acts as a sulfur donor, and scaffold proteins, which act as sulfur and iron acceptors. The ISC and SUF systems also exhibit important differences. In particular, the ISC system includes an Hsp70/Hsp40-like pair of chaperones, while the SUF system involves an unorthodox ATP-binding cassette (ABC)-like component. The role of these two sets of ATP-hydrolyzing proteins in Fe/S cluster biogenesis remains unclear. Both systems are likely to target overlapping sets of apoproteins. However, regulation and phenotypic studies in E. coli, which synthesizes both types of systems, leads us to envisage ISC as the house-keeping one that functions under normal laboratory conditions, while the SUF system appears to be required in harsh environmental conditions such as oxidative stress and iron starvation. In Saccharomyces cerevisiae, the ISC system is located in the mitochondria and its function is necessary for maturation of both mitochondrial and cytosolic Fe/S proteins. Here, we attempt to provide the first comprehensive review of the ISC and SUF systems since their discovery in the mid and late 1990s. Most emphasis is put on E. coli and S. cerevisiae models with reference to other organisms when their analysis provided us with information of particular significance. We aim at covering information made available on each Isc and Suf component by the different experimental approaches, including physiology, gene regulation, genetics, enzymology, biophysics and structural biology. It is our hope that this parallel coverage will facilitate the identification of both similarities and specificities of ISC and SUF systems.

α-Actinin 4 and BAT1 interaction with the Cytochrome c promoter upon skeletal muscle differentiation

To identify common regulatory features of nuclear genes encoding mitochondrial proteins we searched for regulatory elements in the Cytochrome c promoter during skeletal muscle differentiation in cell culture. A consensus element with the sequence GCTGCCGCAC-(N4-20)-GGSCGYGGG was found in both rat Cyt c and coxIV promoters. This new sequence element with yet undescribed function, but high abundance in promoters of nuclear genes encoding mitochondrial proteins available from the databases, showed a striking change in protein binding in electromobility shift assays when myoblasts were compared to myotubes. Proteins involved in the observed protein-DNA complexes were isolated from myotubes and identified by MALDI-TOF as BAT1, a DEAD-box protein of yet unknown function, heat shock protein HSP84, and alpha-actinin 4, a non-muscle isoform of the structural protein alpha-actinin. alpha-actinin 4 was found to be preferentially localized in the nucleus upon induction of myogenesis, suggesting a signaling function during muscle differentiation. In conclusion, the analyzed sequence motif may be a new candidate for common regulatory elements specific for nuclear encoded mitochondrial genes, and alpha-actinin 4 may be involved in their regulation.