System-wide coordinates of higher order functions in host-pathogen environment upon Mycobacterium tuberculosis infection

Molecular signatures and their interactions behind the successful establishment of infection of Mycobacterium tuberculosis (Mtb) inside macrophage are largely unknown. In this work, we present an inter-system scale atlas of the gene expression signatures, their interactions and higher order gene functions of macrophage-Mtb environment at the time of infection. We have carried out large-scale meta-analysis of previously published gene expression microarray studies andhave identified a ranked list of differentially expressed genes and their higher order functions in intracellular Mtb as well as the infected macrophage. Comparative analysis of gene expression signatures of intracellular Mtb with the in vitro dormant Mtb at different hypoxic and oxidative stress conditions led to the identification of the large number of Mtb functional groups, namely operons, regulons and pathways that were common and unique to the intracellular environment and dormancy state. Some of the functions that are specific to intracellular Mtb are cholesterol degradation and biosynthesis of immunomodulatory phenolic compounds. The molecular signatures we have identified to be involved in adaptation to different stress conditions in macrophage environment may be critical for designing therapeutic interventions against tuberculosis. And, our approach may be broadly applicable for investigating other host-pathogen interactions.


Differential expression analysis.
In order to identify differentially expressed genes during infection, we considered the samples during the final stage of the infection. Differential expression analysis of gene expression microarray data was carried out using an R package called 'RankProd' 29 . The package uses a modified 'rank product' method 29,30 to identify up or down-regulated genes in one condition against another. We have used RankProd because, it uses Rank Product method which is a non-parametric statistical method that detects genes which are consistently found among the most strongly up-regulated genes in with replicate or without replicate experiments. It is based on the assumption that under the null hypothesis the order of all items is random. Probability of finding a specific item among the top of items in a list is k/n, where k is the rank of the item and n is the total number of items. Multiplying these probabilities gives the rank product. Smaller the rank product value, smaller the probability that the observed placement of the item at the top of the lists is due to chance.
Meta-analysis of differential expression. Meta-analysis of gene expression microarrays was carried out using our previously described method 31 . We transformed the initial p-values of each gene obtained from the differential expression analysis of gene expression microarray datasets into the Z-scores, using the inverse cumulative distribution function (CDF) 32 . Then we took the weighted sum of the Z-scores and divided by the square root of sum of the weights to generate the average Z-score. Here the weights are equivalent to number of replicates in the gene expression microarray experiments. Finally the average Z-score was converted to p-value by using CDF 33 .

Inference of interactions of between Mtb and Human. Experimentally verified Host-Pathogen inter-
action data from different bacterial species were retrieved from PHISTO and HPIDB databases 34,35 . PHISTO is a Pathogen Host Interaction Search Tool which contains a total of 23,633 pathogen host PPI data including 9318 interactions between bacteria and human. HPIDB is a Host Pathogen Interaction Database that currently contains 23.485 interactions between 66 host and 541 pathogen species. In addition, we curated a total of 53 experimentally verified host-pathogen protein-protein interaction information from 12 pathogens including Mtb from literature. The genome sequences of Mtb and other bacteria, which have experimentally verified interactions, were downloaded from NCBI ftp site (ftp://ftp.ncbi.nlm.nih.gov/genomes/). Then, we identified orthologs of Mtb in ~1500 sequenced genomes of bacterial species, which have experimentally verified host-pathogen interactions. Finally, the experimentally verified interactions were transferred to Mtb on the basis of orthology relationship. Totally we identified 2808 host-pathogen interactions between two sets of proteins 564 from Human and 1725 from Mtb.
Preparation of functional gene groups. Annotated functions of human, i.e., pathways, motifs, gene ontology (GO) and immunological signatures were collected from Molecular Signature Database (MSigDB) 36,37 . Since the MSigDB does not maintain any functional gene groups for Mtb, we have curated the various functional gene groups such as complexes, pathways and operons etc., for Mtb from the published literature 38 . Functional over representation analysis of gene groups. Functional over-representation analysis (FOA) was carried out using our previously described method 39 . For each gene in a gene group, we have converted p-value of differential expression into Z-score using, inverse normal Cumulative Distribution Function (CDF). The FOA score of each gene group is the sum of the Z-scores divided by square root of number of genes. In order to identify the overrepresented target genes of various transcription regulators (regulon), we have taken sum of the absolute value of target genes Z-scores, then the total was divided by square root of number of genes. Finally the q-value was converted to P-value by using CDF. To calibrate the gene group (containing n genes) FOA score against the background distribution, we randomly sampled the n number of Z-scores and calculated the random FOA score. We repeated this process over 100,000 times and mean and standard deviation of the sampling distribution was used for correction of original score.

Results and Discussion
Since both the host and the pathogen reciprocally influence the gene expression profiles of each other, it is pertinent to study the gene expression profiling of the pathogen as well as the host. This would provide insight into the strategies employed by the pathogen to survive in host environment and the host response to contest against the virulence of the pathogen 16 . Therefore, we performed the meta-analysis of gene expression changes in both Mtb and human macrophages during stable infection. In addition, we carried out Functional over-representation analysis (FOA) to identify higher order functions of induced or suppressed gene expression signatures both in Mtb as well as in the infected macrophages by considering functional groups of genes such as operons, regulons, pathways, complexes and biological process. Inclusion of diverse functional gene groups for the analysis ensured functional annotation for most of the genes. We extensively discuss the relevance of higher order functions of the genes in relation to the mechanisms adopted by the pathogen for its adaptation as well as the host defence.

Meta-analysis of differentially expressed gene signatures during infection.
We have developed a systematic frame work to identify the genes induced in host-pathogen environment (Fig. 1). Initially, we have identified two sets of differentially expressed genes, one from the Mtb and the other from the macrophages during the course of infection. Differentially expressed genes of Mtb were identified by comparing the gene expression data of Mtb which resides inside macrophage after infection (call it intracellular Mtb) with the Mtb before infection (in vitro Mtb cultures) using RankProd 29 . Similarly, we have also identified differentially expressed genes of macrophages by comparing gene expression data of the infected macrophages with the uninfected macrophages (Supplementary data S1). The differential gene expression scores were given ranks and then combined to generate a single consensus ranked list, using a meta-analytical method described previously 31 . The genes ranked atop the consensus ranked list are more severely and consistently up-regulated during infection across experiments, and those that are ranked at the bottom were down-regulated during infection.
Host-pathogen interactions and essentiality of top ranked genes. We identified orthologs of Mtb in ~1500 sequenced genomes of bacterial species, which have experimentally verified host-pathogen interactions in HPIDB and PHISTO databases as well as curated from literature 34,35 . The known interactions were then transferred to Mtb on the basis of orthology relationships. Totally, we identified 2808 host-pathogen interactions between two sets of proteins 564 from human and 1725 from Mtb (Supplementary data S2). Meta-analytic Z-score distribution analysis of meta-analytic ranked list from macrophage and Mtb shows that the most of the genes from both sets have above average Z-scores indicating that most of the top ranked genes encode for proteins involved in host-pathogen interactions ( Fig. 2A,B). In addition, the studies conducted using genome wide siRNA screen also have large number of genes involved in the regulation of pathogen load and found to have above average Z-scores in meta-analytic ranked list of macrophage genes. (Fig. 2C) 18 . Moreover as the quality of RNAi hits (3 sets of genes) also have above average Z-score in the meta-analytic ranked list, indicating that top ranked genes in the meta-analytic list are highly important for defence against Mtb. Similarly, some of the genes reported to be important for survival of Mtb in different physiological environments were also have above average Z-scores ( Fig. 2D) 32,33,40 . Overlapping statistics using hyper geometric distribution also shows that the top ranked genes from both macrophages as well as Mtb were significantly overlap with their respective set of genes that encode for proteins involved in predicted host-pathogen interactions (Fig. 2E,F). There is a significant overlap between a large number of Mtb genes that are reported to be essential and the genes, whose products are predicted to interact with the host. The common candidates between the three set Mtb genes i.e., essential, host interacting and expressed with in macrophages could be potential targets for therapeutics.

Higher order functions of Mtb genes induced in host-pathogen environment. Previously there
were many gene expression microarray experiments conducted to identify the adaptive mechanisms of Mtb towards the in-vitro models of nutrient starvation, hypoxia, and oxidative stress in macrophage environment. There were two types of in-vitro models studied under hypoxic conditions, one is constant oxygen (0.2%) supply model and another one is Wayne growth (WG) model, in which the oxygen supply is gradually depleted 41 . In order to identify the nature of environment created by macrophage towards Mtb infection, we compared the meta-analytic ranked list of gene expression signatures induced inside macrophages with a large number of previously published gene expression signatures generated using in-vitro models of diverse environmental conditions at various time points (GSE16146, GSE8786, and GSE9331) 20  Z-scores of total macrophage genes that are differentially expressed upon infection and macrophage genes that were reported to be essential to regulate pathogen load using different levels of siRNA screen i.e., secondary, tertiary and universal. (C) Z-scores of total Mtb genes that are differentially expressed in infected macrophages and Mtb genes predicted to be host interacting (HI). (D) Z-scores of total Mtb genes that are differentially expressed in infected macrophages and Mtb genes reported to be essential for survival in different physiological environments. P-value calculated using Wilcoxon rank sum test shows that the distributions of each pair of comparisons are significantly different. (E) Venn-diagram with P-value of overlapping statistics between the genes that are expressed with in the macrophages, pathogen interacting and essential (tertiary screen) and (F) Venn-diagram with P-value of overlapping statistics between the Mtb genes that are expressed with in the macrophages, host interacting and essential.
SCIenTIfIC REPORtS | (2018) 8:5079 | DOI:10.1038/s41598-018-22884-8 (Diethylenetriamine) NO for 24hrs best correlates with the meta-analytic ranked list (intracellular), indicating the likely environmental conditions Mtb exposed in macrophage environment (Fig. 3A). Gene expression signatures related to hypoxia model of WG shows stronger correlation than constant O2 (0.2%) supply, model. 5 mM H2O2 shows the strongest correlation. In addition, gene expression signatures induced in all the five different conditions show significant correlation with each other (P-value > 1.5e-08). Particularly, the conditions of hypoxia, H 2 O 2 and NO show very strong correlation (Fig. 3B).
In order to identify the higher order functions of Mtb genes expressed across different conditions and in intracellular environment, we carried out FOA and functional interpretation of regulons, operons and pathways as following 39 . Regulons. We curated Mtb regulons by collecting known target genes of all transcription factors of Mtb from previously published literature 43,44 . We have performed FOA of target genes of various transcription regulators (regulons) in the ranked list of differentially expressed genes across the different conditions to get the list of the transcription regulators, which are critical for adaptation of Mtb to macrophage environment. Our analysis shows that the target genes of the persistence regulator, Rv0348 (MosR) were consistently differentially regulated across the different conditions ( Fig. 3C) (Supplementary data S3). In addition, the target genes of Rv0081, PhoP, Rv0678, TrcR, SigE, RegX3, Crp, DevR, Rv1353c, Lsr2, CsoR, Rv0324, WhiB3, SigG, Rv2034, Rv1985c, Rv0023, Rv0047c, kstR were also differentially regulated in intracellular environment (Fig. 3D). Although target genes of the RegX3 and WhiB3 were significantly altered in intracellular conditions (Fig. 3E), the respective transcription regulators were not significantly differentially expressed (Fig. 3F). In contrast to the MosR expression, most of its target genes were up-regulated, indicating that it represses the majority of the genes involved in adaptation to the macrophage environment. MosR and its associated genes in an operon Rv0347-Rv0348-Rv0349 were induced during the late stage of chronic tuberculosis in mice 45 . PhoP is a global regulator of Mtb and it plays an important role in pathogenesis and synthesis of cell wall lipids 46 . Operons. In most of the bacterial species such as Mtb, pathways, complexes and gene ontology terms were not well annotated, which hinders the functional annotation of gene expression signatures. Here, we circumvent the functional annotation problem by inclusion of predicted operons, because genes within the most of operons were known to encode proteins involved in a same pathway or potentially forming a functional protein complex. Over-representation analysis shows that the entire operon encoding for the components of NADH dehydrogenase complex-I were significantly down-regulated across the different conditions of intracellular, hypoxic and oxidative stress (Fig. 4A) (Supplementary data S4), indicating the complete shutdown of oxidative phosphorylation pathway. On the other hand, the operons such as Rv1465-csd-Rv1463-Rv1462-pps1-Rv1460, hspX-Rv2030c-pfkB-Rv2028, ceccCa1-eccB1-eccA1-espH-espG1-espF, hsaABCD, rplNXEN1, dnaK-grpE-dnaJ1-hspR, pks1-pks15-fad22-fad29, fadD26-ppsABCDE-drrABC, ltp2-fadE29-fadE28-cyp125 were highly expressed in intracellular conditions (Fig. 4B). The pps1 locus constitutes an operon with seven genes (Rv1465-Rv1460), which code for Suf-like proteins, which are part of SUF machinery, an exclusive Fe-S cluster assembly existing in Mtb 47 . The Pps1 protein is orthologous to SufB which is essential and conserved component of iron sulphur cluster assembly (Fe-S cluster) complex of prokaryotes. It was reported that as Fe-S clusters serve as cofactors of proteins which are involved in multiple cellular mechanisms 48 .
The operon hspX-Rv2030c-pfkB-Rv2028 was reported to be essential for the Mtb during persistent infection in the host and also for its survival during low iron, low pH and hypoxic condition [49][50][51] . The protein encoded by hspX gene of the operon is known to be highly up-regulated during the latent infection and reported to play an important role in anaerobic respiration of Mtb during stress conditions. The other genes of the operon are found to be involved in carbohydrate metabolism (pfkB) and nucleotide metabolism (Rv2030c) [49][50][51] . The two operons hsaABCD and cyp125-fadE28-fadE29-Rv3542c-Rv3541c-ltp2 were highly conserved across the members of Mtb complex 52,53 . They participate in cholesterol degradation pathway and play an important role in intracellular survival of Mtb by providing cholesterol as an alternative carbon source [54][55][56][57][58][59] . Another two operons pks1-pks15-fad22-fad29 and fadD26-ppsABCDE-drrABC were involved in synthesis of phthiodiolone dimycocerosates (DIMs) and immuno-modulatory phenolic glycolipids, which have a role in immuno-modulation [60][61][62] . Some of the genes (drrA, drrB and drrC) in aforementioned operon were known to encode for a drug efflux pump, which confers resistance to many antibiotics 63 . The genes with in the operon (alkB-rubA-rubB-Rv3249c) encode for alpha-ketoglutarate-dependent dioxygenase (alkB), which catalyses oxygenation of hydrocarbons 64 , could be having role in cholesterol degradation. The genes involved in cholesterol utilization and other genes (Rv0792c, Rv0791c, Rv0790c, Rv0789c) with unknown function were highly expressed in intracellular environment in comparison to the other conditions.
Comparative analysis of operons with the genes induced across different conditions has identified several functions that are common and unique to each of the environment. Pathways involved in biosynthesis of iron-sulfur cluster, mycobactins (mbtB-mbtC-mbtD) and meromycolic acids (accD6-kasB-kasA-acpB-fabD) were highly expressed in presence of NO and H 2 O 2 indicating their role in oxidative stress defence . On the other hand the genes with in the operons (devR-devS-Rv3134c and hspX-Rv2030c-pfkB-Rv2028c) were highly expressed during hypoxic conditions. Furthermore the genes with in the operons (furA-katG-Rv1907c and ahpC-ahpD) were expressed across intracellular, hypoxic, H 2 O 2 induced oxidative stress conditions. In contrast to the previous reports, co-expression of katG and furA indicates that furA may not be a repressor of katG under these conditions 65 . Pathways. Over-representation analysis of various Mtb pathways among the genes induced during infection shows that the glyoxylate pathway which is known to play an important role in persistence of Mtb in macrophages 66 is only active in Wane growth model of hypoxia and intracellular conditions (Fig. 4C) (Supplementary data S4). In addition, pathways involved in the biosynthesis of chorismate and branched chain amino acids such as L-leucine, L-isoleucine (from threonine) and assimilation of sulfate and cysteine biosynthesis were highly expressed during hypoxia and intracellular conditions, but not during oxidative stress. Furthermore, various catabolic pathways such as fatty acid & beta-oxidation I, glycolysis I (from glucose 6-phosphate), and glyoxylate cycles are highly expressed during intracellular conditions (Fig. 4D). The chorismate pathway, also called as shikimate pathway is found in Mtb but absent in humans and other mammals 67,68 . This pathway produces chorismate, which is a key intermediate compound for the biosynthesis of amino acids, ubiquinones, siderophores and other important metabolites essential for Mtb growth and survival in the host [69][70][71][72][73] . Overall, the pathways involved in the biosynthesis of L-Leucine, chorismate, cysteine, and assimilation of sulfate are linked to the long-time survival of Mtb during the pathogenesis.

Higher order functions of differentially expressed macrophages genes upon Mtb infection.
Pathways. In order to identify the macrophage pathways that were induced during infection, we have carried out over-representation analysis of pathway genes from various databases such as BioCarta, KEGG, and Reactome [74][75][76] (Fig. 5) (Supplementary data S5). The BioCarta pathways namely, IL-10 anti-inflammatory signalling, induction of apoptosis through DR3 and DR4/5 Death Receptors, IL22 soluble receptor signalling, NF-kB, TNFR2 signalling and Acetylation/deacetlyation of RelA were found to be highly expressed (Fig. 5A).
IL-10 family of cytokines has a total of 6 IL's. In contrast to the rest of the IL-10 family of cytokines, IL-10 acts as an anti-inflammatory cytokine and is also capable of inhibiting the synthesis of pro-inflammatory cytokines such as IL-2, TNF-α, IL-3, IFN-α which indirectly leads to the survival of Mtb inside the infected macrophage. Supporting this fact, there are reported evidence from the infection studies of Mycobacterium avium sub species paratuberclosis (MAP). It was documented that MAP adopts a different strategy to escape from the host defence. MAP activates the mitogen activated protein kinase pathway, which finally results in up-regulation of IL-10 and repression of other inflammatory cytokines. Further the up-regulated IL-10 also inhibits the apoptosis in macrophages 6,77,78 . According to our findings and the supporting evidence, it may be assumed that the up-regulation of IL-10, an anti-inflammatory pathway of macrophage may aid in the growth and virulence of Mtb and may also be considered as one of the immune-modulatory strategies adopted my Mtb to escape from host defence mechanisms for its survival.
The pathway 'induction of apoptosis through the engagement of death receptors' has a role in apoptosis of infected macrophages via engagement of variety of death receptors such as Fas, TNFR, DR3, DR4 and DR5 79 . Apoptosis of this kind, where there is engagement of death receptors is the sign of innate immune response of macrophages against Mtb 79 . IL22 soluble receptor signalling pathway was reported to inhibit the growth of Mtb by enhancing the expression of intracellular signalling molecule, calgranulin A. In addition, it was reported to be involved in tissue modulation, induction of proliferative and anti-apoptotic pathways and production of anti-microbial substances 80 .
NF-kB pathway, inflammatory cytokine and TNF-α are responsible for inflammatory response towards Mtb infection 81 . TNF-α shows its immune response in variety of ways such as macrophage activation, induction of cytokines, chemokines and induction of apoptosis and also restriction of bacterial growth in infected macrophage [81][82][83][84][85] . TNFR2 signalling pathway is mainly responsible for apoptosis, acetylation/deacetlyation of RelA and is responsible for innate immune response against Mtb. Overall the over-representation analysis in Biocarta pathway shows that all the pathways related to recognition of molecular patterns of Mtb are responsible for triggering inflammation and apoptosis, are up-regulated.
Over-representation of analysis of KEGG pathways show that the genes involved in cytokine-cytokine receptor interaction, toll-like receptor signalling, NOD-like receptor signalling, RIG-I like signalling, chemokine SCIenTIfIC REPORtS | (2018) 8:5079 | DOI:10.1038/s41598-018-22884-8 signalling and apoptosis signalling were highly up-regulated in the macrophages during Mtb infection (Fig. 5B). After infection of Mtb in pulmonary alveoli, macrophages express pattern recognition receptors (PRR) which in turn recognize the pathogen associated molecular patterns (PAMPS). The recognition of PAMPS by PRRs leads to the activation of transcription factors, which are involved in providing innate immunity 86 . In the case of mycobacterial infections, mycobacterial cell wall-associated components such as lipoarabinomannan are recognized by TLR1 and TLR2. Similarly there are several cell wall associated components which may be recognized during the time of mycobacterial infection as reported earlier [87][88][89] . In NOD-like receptor signalling pathway, the NOD like receptors belonging to NLR family and they may play key roles in innate immunity and inflammation 90 . They recognize the peptidoglycan fragments of the pathogens escaped from endosomal compartments leading to the activation of cytokine production and ultimately resulting in programmed cell death 91,92 .
Apart from the NOD like receptors, there are also few other proteins called as cytosolic RNA helicases (RIG-I like signalling pathway) that were also highly up-regulated. These cytosolic RNA helicases (RIG-I-like receptors) are reported to recognize the antigens from viral pathogens and induce the innate immune response against them by triggering the signalling pathways which produce the type I interferon and inflammatory cytokines 93,94 . These have been reported to be involved in the intracellular detection of all pathogens including Mtb 95 . Chemokine signalling pathway plays an important role in migration of leukocytes to the site of infection and orchestrates the host defence mechanism 96 .
The genes involved in apoptotic pathways were highly up-regulated (Fig. 5A,B). The cells follow two different kinds of pathways for undergoing apoptosis: the death receptor or extrinsic pathway and the mitochondrial or intrinsic pathway, where the final dead cells are cleared through phagocytosis by the macrophages [97][98][99] . In addition, the pathways in involved in branched chain amino-acid degradation were down-regulated, unlike in intracellular Mtb, in which the biosynthetic pathways of branched chain amino-acids were up-regulated as mentioned previously.
Analysis of Reactome pathways show that there are two kinds of the pathways that were up-regulated during infection: pathways pertaining to immune system activation and pathways responsible for cell survival and growth. The former category consists of cytokine signalling related genes, interferon signalling, interleukins signalling and adaptive immunity. The second category consisting of the pathways related to cell cycle, DNA replication and G1/S transition pathways were also observed to be highly up-regulated (Fig. 5C). In the first category, most of the pathways which were highly regulated were found to be cytokines with diverse functions. As previously described, cytokines have immune response triggering properties against the infections in the host. Interferon's are also cytokines (pleiotropic cytokines) which have immune-regulatory properties 103. In our analysis, we also have found the pathways pertaining to interferon α/β/γ signalling as highly up-regulated which are also actively involved in triggering immune response. These results confirm that the pathways in the first category are involved in providing innate and adaptive immunity against infection. The pathways which are involved in cell cycle, DNA replication, G1/S transition are well documented to be linked with cell growth and survival.
Cellular components. Over-representation analysis of genes encoding various cellular components shows that the genes that encode for proteins localized to Endoplasmic Reticulum (ER) were observed to be up-regulated during infection. In macrophages, the mycobacterial antigen ESAT-6 evokes the ER stress, which in turn mediates the process of apoptosis 100 . This induction of apoptosis further leads to the killing of Mtb. The other highly overrepresented proteins in the cellular localization data set are mainly related to the intracellular proteins associated with kinetochore ( Fig. 5D) (Supplementary data S5). In contrast to the ER, most of the mitochondrial components were down-regulated, indicating the shutdown of most of the mitochondrial functions in infected macrophages. Mtb virulence is known to correlate with mitochondrial cytochrome c release in infected macrophages 101 . Mitochondria could be an important target for mycobacteria, because of its involvement in the regulation of immune response and cell survival/programmed cell death [102][103][104] . Furthermore, the Mtb could also be exploiting some of the mitochondrial functions considering that mitochondria derived from endosymbiosis of an ancestral bacteria 105 . It has been shown that mycobacterial proteins carry mitochondrial localization signals, which may help its virulence proteins to be transported to the mitochondria and further hijack it's functions 106 .

Conclusions
In this report by performing the meta-analysis of publicly available gene expression datasets and analysis of higher order functions and interactions, we have derived comprehensive view about cross talk between Mtb and macrophages during the stable infection. We observed a strong correlation of gene expression signatures between the intracellular bacteria with in-vitro models of dormancy conditions, which reflects the likely environmental conditions in existing in macrophages at the time of infection. Moreover from this analysis, it is clear that Mtb effectively fights against the oxidative, starvation and hypoxic conditions presented by the host as defence against infection. Analysis of different functional signatures associated with different stress conditions provides the valuable information related to the strategies adapted by Mtb inside the macrophage for its survival and persistence. For instance such as, the mechanisms adapted by Mtb to encounter the oxidative stress induced by intracellular H 2 O 2 , through catalase-peroxidase and alkyl hydro peroxide reductase, similarly, recruitment of iron-sulfur clusters, mycobactins and meromycolic acids to encounter the oxidative stress induced by NO shows the strategies adapted by Mtb to survive in infected macrophage. Further, from our analysis it is observed that, Mtb effectively tackles the harsh environmental conditions of macrophage by intracellular environment by up-regulation of cholesterol utilization pathways and bio-synthesis of immuno-modulatory phenolic glycolipids. Further study of these pathways and other genes with unknown function would establish their role and mechanisms of action to counter each of the stress conditions posed by macrophage environment. In addition possible pathways of Mtb that target and exploit mitochondria should be identified. This study clearly inferred that, when therapeutic strategies to combat dormant Mtb should be designed, the multiple pathways involved in adaptation to different stress conditions and pathways that target mitochondrial functions should be taken into consideration.