No description available.

Thesis (Ph.D.). / Written for the Dept. of Medicine, Division of Experimental Medicine. Title from title page of PDF (viewed 2008/05/08). Includes bibliographical references.

Iron is essential in nearly all organisms. It is a cofactor in many proteins and enzymes. This transition metal can also be toxic because it participates in reactions which produce reactive oxygen species. To avoid these toxic effects while still being used for essential processes, the cell must regulate tightly iron import, metabolism, trafficking, and homeostasis. These processes were studied using biophysical methods centered on Mossbauer spectroscopy supplemented by electron paramagnetic resonance, electronic absorption spectroscopy, and inductively coupled plasma mass spectrometry. This integrated biophysical approach was applied to yeast cells, isolated yeast mitochondria, and mouse brains. We determined the concentration of Fe, and the proportion of that Fe present as iron-sulfur clusters, heme centers, mononuclear nonheme centers, and as Fe3+ oxyhydroxide (phosphate) nanoparticles for each system. In yeast, the dependence of metabolic mode of growth and iron in the growth medium on this distribution was studied. Approximately three-quarters of the iron in fermenting cells was located in vacuoles, where it was present as high-spin mononuclear Fe3+ species with rhombic symmetry. The remaining quarter was present in the mitochondria. In fermenting mitochondria 4 distinct species of iron were observed, including [Fe4S4]2+ clusters and low-spin Fe2+ hemes arising from respiratory complexes, non-heme high spin (NHHS) Fe2+ species, high spin nonheme Fe3+ species, and nanoparticles. These distributions (in both the cells and mitochondria) change when the cells are grown on iron deficient medium but remained relatively unaltered as iron in the growth medium was increased. Respiring cells had less Fe associated with vacuoles, and more Fe present as HS Fe2+. Respiring mitochondria contain more [Fe4S4]2+ clusters and low-spin Fe2+ hemes, more S = 1/2 [Fe2S2]1+ clusters, and less NHHS Fe2+, HS Fe3+ species and Fe3+ nanoparticles. These changes were rationalized by assuming that the NHHS Fe2+ and Fe3+ species, and the nanoparticles were in equilibrium within the matrix of the mitochondria, and that the Fe2+ species served as feedstock for the synthesis of iron-sulfur clusters and heme centers. The iron in the mouse brain consisted mostly of [Fe4S4]2+ clusters and Fe2+ hemes from mitochondria respiratory complexes, and of ferritin, an Fe storage protein complex. NHHS Fe2+ and Fe3+ species were also observed. The ratio of stored Fe to mitochondrial Fe was sensitive to age. The brains of prenatal animals were dominated by ferritin. Following birth up to the first 4 weeks of life, there was an increase in mitochondrial Fe and a decline of ferritin Fe. Beyond 4 weeks up to 58 weeks, levels of ferritin increased and mitochondrial Fe remained constant. The brains of mice fed an Fe-deficient diet were also studied; most of the Fe in these brains was present as mitochondrial Fe, with little stored as ferritin. A model was developed to explain these changes.

Les travaux de cette thèse portent principalement sur le développement d'une méthodologie pour la modélisation de systèmes biologiques. Cette méthodologie, basée sur une modélisation en équations différentielles, intègre aussi bien des méthodes formelles (solveur sur intervalles, solveur de formules STL), qu'analytiques (calcul de stabilité d'état stationnaire) ou numériques (algorithme d'optimisation, analyses statistiques). Elle permet l'intégration de différents types de données, telles la réponse comportementale à une perturbation ou des données quantitatives (demie-vie, concentrations). En collaboration avec une équipe de biologistes, cette méthodologie est appliquée, avec succès, au système de l'homéostasie du fer : nous étudions la réponse intracellulaire du système, via des protéines régulatrices spécifiques (protéines IRP), face à une situation de carence en fer. Un résultat majeur de cette étude est l'amélioration des connaissances sur la concentration de fer intracellulaire nécessaire à la prolifération des cellules : cette concentration est mise en avant par l'étude du modèle, puis est confirmée expérimentalement.Le deuxième volet de ces travaux portent sur le développement d'un outil pour la modélisation de réseaux de gènes avec le formalisme des réseaux de Thomas. Cet outil, développé en ASP (Answer Set Programming), permet l'intégration de différents types de données telles des données sur des mutants ou l'existence de différents états stationnaires. Cet outil permet d'éviter automatiquement l'incohérence en cas de contradiction entre différentes hypothèses sur le système. Il permet également l'inférence de propriétés biologiques telles que l'ordre entre paramètres cinétiques. / The major part of this PhD consists in the creation of a methodology to model biological systems. This methodology considers models based on differential equations, and uses formal methods (interval solver, verification of STL formula), analytical methods (study of stability) and numerical methods (optimization algorithm, statistical analysis). Moreover, many kind of data, like behavioral response to perturbation, or quantitative data (metabolite half-life and concentration) can be incorporated. In collaboration with a biologist team, this methodology is successfully applied to the iron homeostasis network : we study the response of the system to an iron depletion, at the intracellular level, based on specific regulatory proteins (IRP proteins). A major output of this study is insight into the level of iron cells need to proliferate : this concentration is pointed out by the study of the model, and is experimentally validated.The second part of the PhD is the creation of a tool to model genetic regulatory networks, using Thomas' formalism. This tool, developed using ASP (Answer Set Programming) programming language, can integrate many kind of data, like mutation data, or the existence of many steady states. It automatically avoids inconsistency in case of contradiction between different hypotheses. It also infers biological properties such as relationships between kinetic parameters.

Les travaux de cette thèse portent principalement sur le développement d'une méthodologie pour la modélisation de systèmes biologiques. Cette méthodologie, basée sur une modélisation en équations différentielles, intègre aussi bien des méthodes formelles (solveur sur intervalles, solveur de formules STL), qu'analytiques (calcul de stabilité d'état stationnaire) ou numériques (algorithme d'optimisation, analyses statistiques). Elle permet l'intégration de différents types de données, telles la réponse comportementale à une perturbation ou des données quantitatives (demie-vie, concentrations). En collaboration avec une équipe de biologistes, cette méthodologie est appliquée, avec succès, au système de l'homéostasie du fer : nous étudions la réponse intracellulaire du système, via des protéines régulatrices spécifiques (protéines IRP), face à une situation de carence en fer. Un résultat majeur de cette étude est l'amélioration des connaissances sur la concentration de fer intracellulaire nécessaire à la prolifération des cellules : cette concentration est mise en avant par l'étude du modèle, puis est confirmée expérimentalement.Le deuxième volet de ces travaux portent sur le développement d'un outil pour la modélisation de réseaux de gènes avec le formalisme des réseaux de Thomas. Cet outil, développé en ASP (Answer Set Programming), permet l'intégration de différents types de données telles des données sur des mutants ou l'existence de différents états stationnaires. Cet outil permet d'éviter automatiquement l'incohérence en cas de contradiction entre différentes hypothèses sur le système. Il permet également l'inférence de propriétés biologiques telles que l'ordre entre paramètres cinétiques. / The major part of this PhD consists in the creation of a methodology to model biological systems. This methodology considers models based on differential equations, and uses formal methods (interval solver, verification of STL formula), analytical methods (study of stability) and numerical methods (optimization algorithm, statistical analysis). Moreover, many kind of data, like behavioral response to perturbation, or quantitative data (metabolite half-life and concentration) can be incorporated. In collaboration with a biologist team, this methodology is successfully applied to the iron homeostasis network : we study the response of the system to an iron depletion, at the intracellular level, based on specific regulatory proteins (IRP proteins). A major output of this study is insight into the level of iron cells need to proliferate : this concentration is pointed out by the study of the model, and is experimentally validated.The second part of the PhD is the creation of a tool to model genetic regulatory networks, using Thomas' formalism. This tool, developed using ASP (Answer Set Programming) programming language, can integrate many kind of data, like mutation data, or the existence of many steady states. It automatically avoids inconsistency in case of contradiction between different hypotheses. It also infers biological properties such as relationships between kinetic parameters.

Php4 is a subunit of the CCAAT-binding protein complex that has a negative regulatory function during iron deprivation in the fission yeast Schizosaccharomyces pombe. Under low iron conditions, Php4 fosters the repression of genes encoding iron using proteins. In contrast, under iron-replete conditions, Php4 is inactivated at both transcriptional and post-transcriptional levels. Our group has already described that Php4 is a nucleo-cytoplasmic shuttling protein, which accumulates into the nucleus during iron deficiency. On the contrary, Php4 is exported from the nucleus to the cytoplasm in response to iron abundance. Php4 possesses a leucine-rich NES (93LLEQLEML100) that is necessary for its nuclear export by the exportin Crm1. Our current study aims at understanding the mechanism by which Php4 is imported in the nucleus during iron starvation. Through microscopic analyses using different mutant strains, we showed that the nuclear localization of Php4 is independent of the other subunits of the CCAAT-binding core complex namely Php2, Php3 and Php5. Deletion mapping analysis of Php4 identifies two putative nuclear localization sequences (NLSs) in Php4 (171KRIR174 and 234KSVKRVR240). Using chimeric proteins that consist of GFP fused to Php4, we engineered substitutions of the basic amino acid residues 171AAIA174 and 234ASVAAAA240 and analyzed the functionality of both NLSs. We observed that both monopartite NLSs play critical role for Php4 nuclear localization. We also observed that mutant strains of cut15+, imp1+ or sal3+ exhibited defects in nuclear targeting of Php4, revealing that nuclear accumulation of Php4 is dependent on two karyopherin α (Imp1 and Cut15) and one karyopherin β (Sal3) receptors. Consistently, the Php4-mediated repression activity is abolished in the absence of two functional NLSs. Moreover, loss of Imp1, Cut15 or Sal3 resulted in increased expression of isa1+, which is a target gene of Php4. Co-immunoprecipitation assay (Co-IP) reveals physical interaction of Php4 with Imp1, Cut15 and Sal3 in vitro. Collectively, our results demonstrate that Php4 has two distinct NLS regions responsible for its nuclear localization. Furthermore, karyopherin α and β receptors play a role in the nuclear import of Php4. Because Php4 is essential for growth under low iron conditions, the presence of two NLSs would ensure the protein to reach its nuclear destination when cells undergo a transition from iron-sufficient to iron-limiting conditions.

Widespread antibiotic resistance is a major public health concern, and plants represent an emerging antibiotic exposure route. Recent studies indicate that crop plants fertilized with antibiotic-laden animal manure accumulate antibiotics, however, the molecular mechanisms of antibiotic entry and subcellular partitioning within plant cells remain unknown. Here we report that mutations in the Arabidopsis locus Multiple Antibiotic Resistance (MAR1) confer resistance, while MAR1 overexpression causes hypersensitivity to multiple aminoglycoside antibiotics. Resistance is highly specific for aminoglycosides and does not extend to antibiotics of other classes, including the aminocyclitol, spectinomycin. Yeast expressing MAR1 are hypersensitive to the aminoglycoside, G418, but not to chloramphenicol or cycloheximide. MAR1 encodes a protein with 11 putative transmembrane domains with low similarity to ferroportin1 from Danio rerio. A MAR1:YFP fusion protein localizes to the chloroplast, and chloroplasts from plants overexpressing MAR1 accumulate more of the aminoglycoside, gentamicin, while mar1-1 mutant chloroplasts accumulate less than wild type. MAR1 overexpression lines are slightly chlorotic, and this chlorosis is rescued by application of exogenous iron. MAR1 expression is also downregulated by low iron. Taken together, these data suggest that MAR1 is a plastid transporter that is likely to be involved in cellular iron homeostasis, and allows opportunistic entry of multiple antibiotics into the chloroplast. mar1 mutants represent an interesting example of plant antibiotic resistance that is based on the restriction of antibiotic entry into a subcellular compartment. Knowledge about this process – and other processes of antibiotic entry – could enable the production of crop plants that are incapable of antibiotic accumulation, aid in development of phytoremediation strategies for decontamination of water and soils polluted with antibiotics, and further the development of new plant-based molecular markers. The work described here also contributes to our understanding of how plants interact with the antibiotics they encounter, both in the laboratory (where aminoglycosides such as kanamycin are used heavily to select for transgenics) and in the natural environment. / text

Thesis (MSc (Genetics))--University of Stellenbosch, 2007. / Multiple sclerosis (MS) is a disease that causes neurological dysfunction. Studies attempting to elucidate the role of genes in MS development may aid efforts to control the damage caused by the disease that affects two million people worldwide, e.g. improved diagnosis and treatment. Although the association of MS and genes has not been fully characterized the proposed genetic etiology has been supported by the observed association of MS with the Major Histocompatibility Complex (MHC), haplotype HLA-DRB1*1501, DRB5*0101, DQA1*0102, DQB1*0602. Iron, or rather the dysregulation thereof, has also been implicated as a precipitating factor in MS development. Considering the factors of iron dysregulation and the genes involved in iron regulation, this study aims to identify variation within genes involved in iron metabolism namely the high iron gene (HFE), solute-carrier family 40 (iron regulated transporter) member 1 gene (SLC40A1), hepcidin anti-microbial peptide (HAMP), cytochrome b reductase 1 (CYBRD1) and hemojuvelin (HJV). Screening of 40 patients (33 female, seven male; 33 Caucasian, seven Coloured) for each of the five genes was achieved by the Heteroduplex Single-Stranded Conformation Polymorphism (HEX-SSCP) technique. Semi-automated DNA sequencing allowed for verification and characterization of the variants detected. Results included identification of four novel variants present in only the Caucasian patient group, characterized as IVS4-53G→A (HFE) (one of 33 patients; 3%), IVS2-65delA (CYBRD1) (two of 32 patients; 6.3%), 3’UTR+26delACGTCACGTTTCAAAACTA (CYBRD1) (one of 31 patients; 3.2%) and 219delG (HJV) (two of 33 patients; 6%). In addition, a total of 15 previously described variants were identified (seven intronic and eight exonic) of which three were also prevalent in only the Caucasian patient group. This study aimed to investigate the differences ...

The cause for childhood acute lymphoblastic leukemia (ALL) remains unknown, but male gender is a risk factor, and among ethnicities, Hispanics have the highest risk. In this dissertation, we explored correlations among genetic polymorphisms, birth characteristics, and the risk of childhood ALL in a multi-ethnic sample in 161 cases and 231 controls recruited contemporaneously (2007-2012) in Houston, TX. We first examined three lymphoma risk markers, since lymphoma and ALL both stem from lymphoid cells. Of these, rs2395185 showed a risk association in non-Hispanic White males (OR=2.8, P=0.02; Pinteraction=0.03 for gender), but not in Hispanics. We verified previously known risk associations to validate the case-control sample. Mutations of HFE (C282Y, H63D) were genotyped to test whether iron-regulatory gene (IRG) variants known to elevate iron levels increase childhood ALL risk. Being positive for either polymorphism yielded only a modestly elevated OR in males, which increased to 2.96 (P=0.01) in the presence of a particular transferrin receptor (TFRC) genotype for rs3817672 (Pinteraction=0.04). SNP rs3817672 itself showed an ethnicity-specific association (Pinteraction=0.02 for ethnicity). We then examined additional IRG SNPs (rs422982, rs855791, rs733655), which showed risk associations in males (ORs=1.52 to 2.60). A polygenic model based on the number of polymorphic alleles in five IRG SNPs revealed a linear increase in risk (OR=2.00 per incremental change; P=0.002). Having three or more alleles compared with none was associated with increased risk in males (OR=4.12; P=0.004). Significant risk associations with childhood ALL was found with birth length (OR=1.18 per inch, P=0.04), high birth weight (>4,000g) (OR=1.93, P=0.01), and with gestational age (OR=1.10 per week, P=0.04). We observed a negative correlation between HFE SNP rs9366637 and gestational age (P=0.005), again, stronger in males (P=0.001) and interacting with TFRC (PPinteraction=0.05). Our results showed that (i) ALL risk markers do not show universal associations across ethnicities or between genders, (ii) IRG SNPs modify ALL risk presumably by their effects on iron levels, (iii) a negative correlation between an HFE SNP and gestational age exists, which implicates an iron-related mechanism. The results suggest that currently unregulated supplemental iron intake may have implications on childhood ALL development.

Mycobacterium tuberculosis (M.tb), the causative agent of tuberculosis (TB), has remained the largest killer among infectious diseases for over a century. The increasing emergence of drug resistant varieties such as the multidrug resistant (MDR) and extremely drug resistant (XDR) strains are only increasing the global burden of the disease. Available statistics indicate that nearly one-third of the world’s population is infected, where the bacteria remains in the latent state but can reactivate into an actively growing stage to cause disease when the individual is immunocompromised. It is thus immensely important to rethink newer strategies for containing and combating the spread of this disease. Extraction of iron from the host cell is one of the many factors that enable the bacterium to survive in the harsh environments of the host macrophages and promote tuberculosis. Host–pathogen interactions can be interpreted as the battle of two systems, each aiming to overcome the other. From the host’s perspective, iron is essential for diverse processes such as oxygen transport, repression, detoxification and DNA synthesis. Infact, during infection, both the host and the pathogen are known to fight for the available iron, thereby influencing the outcome of the infection. It is of no surprise therefore, that many studies have investigated several components of the iron regulatory machinery of M.tb and the host. However, very few attempts have been made to study the interactions between these components and how such interactions lead to a better adapted phenotype. Such studies require exploration at multiple levels of structural and functional complexity, thereby necessitating the use of a multiscale approach. Systems biology adopts an integrated approach to study and understand the function of biological systems. It involves building large scale models based on individual biochemical interactions, followed by model validation and predictions of the system’s response to perturbations, such as a gene knock-out or exposure to drug. In multiscale modeling, an approach employed in this thesis, a particular biological phenomenon is studied at different spatiotemporal levels. Studying responses at multiple scales provides a broader picture of the communications that occur between a host and pathogen. Moreover, such an analysis also provides valuable insights into how perturbation at a particular level can elicit responses at another level and help in the identification of crucial inter-level communications that can possibly be hindered or activated for a desired physiological outcome. The broad objectives of this thesis was to obtain a comprehensive in silico understanding of mycobacterial iron homeostasis and metabolism, the influence of iron on host-pathogen interactions, identification of key players that mediate such interactions, determination of the molecular consequences of inhibiting the key players and finally the global response of M.tb to altered iron concentration. Perturbation of iron homeostasis holds a strong therapeutic potential, given its essentiality in both the host and the pathogen. Understanding the workings of iron metabolism and regulation in M.tb has been a main objective, so as to ultimately obtain insights about specific therapeutic strategies that capitalize on the criticality of iron concentration. An in-depth study of iron metabolism and regulation is performed at different levels of temporal and spatial scales using diverse methods, each appropriate to investigate biological events associated with the different scales. The specific investigations carried out in the thesis are as follows, a) Reconstruction of a host-pathogen interaction (HPI) model, with focus on iron homeostasis. This study represented the inter-cellular level analysis and was crucial for the identification of key players that mediate communication between the host and pathogen. Additionally, the model also provided a mathematical framework to study the effect of perturbations and gene knock-outs. b) Understanding the influence of iron on IdeR, an iron-responsive transcription factor, also identified as a key player in the HPI model. The study was carried out at the molecular level to identify atomistic details of how IdeR senses iron and the resulting structural modifications, which finally enables IdeR-DNA interaction. The study enabled identification of residues for the functioning of IdeR. c) Genome scale identification of genes that are regulated by IdeR to obtain an overview of the various biological processes affected by changing iron concentrations and IdeR mutation in M.tb. d) To understand the direct and indirect influences of iron and IdeR on the M.tb proteome using large scale protein-protein interaction network. The study enabled identification of highest differentially regulated genes and altered activity of the different biological processes under differing iron concentrations and regulation. e) Systems level analysis of the M.tb metabolome to investigate the metabolic re-adjustments undertaken by M.tb to adapt to altered iron concentration and regulation. The conceptual details and the background of each of the methods used to study the specific aims are provided in the Methodology chapter (Chapter 2). Construction of the host-pathogen interaction (HPI) model and the insights obtained from this study are presented in Chapter 3. A rule based HPI model was built with a focus on the iron regulatory mechanisms in both the host and pathogen. The model consisted of 194 rules, of which 4 rules represented interactions between the host and pathogen. The model not only represented an overview of iron metabolism but also allowed prediction of critical interaction that had the potential to form bottleneck in the system so as to control bacterial proliferation. Infact, model simulation led to the identification of 5 bottlenecks or chokepoints in the system, which if perturbed, could successfully interfere with the host-pathogen dynamics in favour of the host. The model also provided a framework to test perturbation strategies based on the bottlenecks. The study also established the importance of an iron responsive transcription factor, IdeR for regulating iron concentration in the pathogen and mediating host-pathogen interactions. Additionally, the importance of mycobactin and transferrin as key molecular players, involved in host-pathogen dynamics was also determined. The model provided a mathematical framework to test TB pathogenesis and provided significant insights about key molecular players and perturbation strategies that can be used to enhance therapeutic strategies. Given the importance of IdeR in HPI, its molecular mechanism of activation and dimerization was explored in Chapter 4. The main objective of the study was to explore the structural details of IdeR and its iron sensing capacity at the molecular level. A combination of molecular dynamics and protein structure network (PSN) were used to analyse IdeR monomers and dimers in the presence and absence of iron. PSNs used in this thesis are based on non-covalent interactions between sidechain atoms and are quite efficient in identifying iron induced subtle conformational variations. The study distinctly indicated the role of iron in IdeR stability. Further, it was observed that IdeR monomers can take up two major conformations, the ‘open’ and ‘close’ conformation with the iron bound structure preferring the ‘close’ conformation. Major structural changes, such as the N-terminal folding and increased propensity for dimerization were observed upon iron binding. Interestingly, careful analysis of structure suggests a role of these structural modifications towards DNA binding and has been tested in the next chapter. Overall, the results clearly highlight the influence of iron on IdeR activation and dimerization. The predisposition of IdeR to bind to DNA in the presence of metal is clearly visible even when the simulations are performed solely on protein molecules. However, to confirm the conjectures proposed in this chapter and to obtain the atomistic details of IdeR-DNA interactions, the IdeR-DNA complex was investigated. Chapter 5 focuses on the mechanistic details of IdeR-DNA interactions and the influence of iron on the same. IdeR is known to bind to a specific stretch of DNA, known as the ‘iron-box’ motif to form a dimer-of-dimer complex. Molecular dynamics followed by protein-DNA bipartite network analysis was performed on a set of four IdeR-DNA complexes to obtain a molecular level understanding of IdeR-DNA interactions. A striking observation was the dissociation of IdeR-DNA complex in the absence of iron, undoubtedly establishing the importance of iron for IdeR-DNA binding. At the residue level, hydrogen bond and non-covalent interactions clearly established the importance of N-terminal residues for DNA binding, thereby confirming the conjecture put forth in the previous chapter. An important aspect studied in this chapter is the allosteric nature of IdeR-DNA binding. Recent years have witnessed a paradigm shift in the understanding of allostery. Unlike the classical definition of allostery that was based on static structures, the newer definition is based on the conformational ensemble as represented by the shift in the energy landscape of the protein. The allosteric nature of IdeR-DNA complex was probed using simulated trajectories and indeed they suggest iron to be an allosteric regulator of the protein. Finally, based on the known experimental data and observations presented in Chapters 4 and 5, a multi-step model of IdeR activation and DNA binding has been proposed. In chapter 6, a global perspective of IdeR regulation in M.tb was obtained. This was important to gain insights about the influences of iron and its regulation at the M.tb cellular level. A genome scale identification of all possible IdeR targets based on the presence of ‘iron-box’ motif in the promoter region of the genes was carried out. An interesting aspect of this study was the use of energetic information from previous molecular dynamics study as an input for generation of the motif. A total of 255 such IdeR targets were identified and converted into an IdeR target network (IdeRnet). Along with IdeRnet, an unbiased systems level protein-protein interaction network was also generated. To study the response of the pathogen to external perturbations, iron-specific gene expression data was integrated into the network as node weights and edge weights. Analysis of IdeRnet provides interesting associations between fatty acid metabolism and IdeR regulations. Specific genes such as fadD32, DesA3 or lppW have been found to be affected by IdeR mutation. While IdeRnet discusses the direct associations, the global level responses are monitored by analysing pathways for the flow of information in the protein-protein interaction network (PPInet). Comparisons of the PPInets under conditions such as altering iron concentrations and lack of iron homeostasis led to the identification of the ‘top-most’ active paths under the different conditions. The study clearly suggests a halt in the protein synthesis machinery and decreased energy consumption under iron scarcity and an uninhibited consumption of energy when iron homeostasis is perturbed. In the final chapter (Chapter 7), flux balance analyses has been used to investigate the influence of iron on M.tb metabolism. The importance of iron for metabolic enzymes has already been established in the previous chapter. Additionally, M.tb is known to produce siderophores, an important metabolite that requires amino acids as its precursors, for iron extraction. All this, together highlighted the importance of iron and its regulation of M.tb metabolism. Flux balance analysis has been used previously to study the metabolic alterations that occur in an organism under different conditions. For this study, iron specific gene expression data was also incorporated into the model as reaction bounds and the flux values so obtained were compared in different environmental conditions. The study provided valuable insights into the metabolic adjustments taken up by M.tb under iron stress conditions and correlates well with the responses observed from the interactome as well as experimental observations. Most significantly, changes were observed in the energy preferences of the cell. For instance, it was noted that while the wild type strain of M.tb prefers synthesis of ATP via glycolysis, the IdeR mutant strain preferred oxidative phosphorylation. The picture becomes clearer when one accounts for the uncontrolled utilization of energy and rapid activation of protein synthesis machinery in the IdeR mutant strain. Biological systems are inherently multiscale in nature and therefore for a successful drug target regime, analysis of the genome to the phenome, which captures interactions at multiple levels, is essential. In this thesis, a detailed understanding of iron homeostasis and regulation in M.tb at multiple levels has been attempted. More importantly, insights obtained from one level, formed questions in the next level. The study was initiated at the inter-cellular level, where the influence of iron on HPI was modeled and analysed. From this study, IdeR, an iron-responsive transcription factor was identified as a key player that had the potential to alter host-pathogen interactions in the favour of the host. For a complete understanding of how IdeR regulates iron homeostasis, it was imperative to obtain a molecular level insight of its mechanism of action. Finally, the various aspects of IdeR regulation were investigated at the cellular level by analysing direct and indirect influences of IdeR on M.tb proteome and metabolome. The study suggests certain therapeutic interventions, such as 1) reduction in the concentration of free transferrin various, 2) mutations at the N-terminal sites of IdeR, 3) regulation of proteins involved in production of mycolic acids by iron and 4) perturbation of altering energy sources, which capitalize on iron and should be investigated in detail. In summary, the consequences of iron on TB infection were studied by threading different levels. This is based on the belief that most biological functions involve multiple spatio-temporal levels with frequent cross talks between the different levels, thereby making such multiscale approaches very useful.