**1. Introduction**

128 Understanding Tuberculosis – Deciphering the Secret Life of the Bacilli

Zhang, Y., Lathigra, R., Garbe, T., Catty, D. & Young, D. (1991). Genetic analysis of

Molecular Microbiology 5, 381-391.

superoxide dismutase, the 23 kilodalton antigen of *Mycobacterium tuberculosis.*

The infectious diseases caused by intracellular bacterial pathogens, such as *M. tuberculosis*, are among the most important problems in public health worldwide. The development of an infectious process depends on intricate interactions between the host defence systems and the specific systems regulating mycobacterial gene expression. Changes in expression in response to host defence are a necessary condition for the *M. tuberculosis* survival and functioning. Tracking these changes makes possible to analyze the biochemical cascades that are triggered in response to host defence mechanisms and to find the targets for designing new therapeutics and monitoring bacterial infections; in addition, these results are useful for both theoretical (for example, dynamics of the pathogen transcriptome changes during longterm persistence in the host) and applied (for example, the study of the bacterial response to various therapeutic interventions) research.

The completion of the *M. tuberculosis* genome sequence in 1998 (Cole et al., 1998) marked the beginning of the so called post genome era, the main characteristic of which are large scale studies of genome functional activity. The information on the bacterial genome organization allowed to construct macro- and microarrays containing fragments of a majority of ORFs, which enabled analysis of the pathogen transcription profile variations under different conditions. It's no wonder that the first study of the *M. tuberculosis* transcriptome using microarray technology was carried out in the first year after the publication of the genome sequence (Wilson et al., 1999). In as little as 5 years, there have been published many reports with the results of using microarrays for *in vitro* mycobacterial transcriptome analysis (for review, see (Butcher, 2004; Kendall et al., 2004)).

However, the *in vivo* analysis of mycobacterial gene expression during infection process, which is of special scientific interest, is rather complicated, and this can explain a relatively small number of such works. Experiments with analysis of a pathogen transcriptome *in vivo* are determined by the choice of: (1) an experimental model of infection; (2) a method of pathogen RNA isolation; (3) a method of analysis of RNA or cDNA enriched in bacterial transcripts. The brief features of these steps are given in the review.

*Mycobacterium tuberculosis* Transcriptome *In Vivo* Studies –

**3. Experimental models of infection** 

**3.1 Host phagocytes (mouse and human)** 

below.

(Rohde et al., 2007).

et al., 2010).

status of the host macrophage.

**3.2 Models of** *M. tuberculosis* **infection in laboratory animals** 

agreement with similar data of the Talaat's group (Talaat et al., 2007).

A Key to Understand the Pathogen Adaptation Mechanism 131

Experimental models of tuberculosis used for whole transcriptome studies *in vivo* are very diverse. The most frequently used models and examples of their applications are described

The first work with a whole genome description of *M. tuberculosis* gene expression is that of Schnappinger et al. (Schnappinger et al., 2003). Activated by INF-γ and non-activated mouse macrophages were used in this work as a model system. Rachman et al. characterized the *M. tuberculosis* genes with enhanced expression in activated and inactivated mouse macrophages both relative to each other and to mycobacteria *in vitro* (Rachman et al., 2006). Rohde et al. studied changes in the *M. tuberculosis* transcriptome at the initial stages of infection of mouse macrophages and demonstrated a dynamic enhancement in the expression level of some genes during the first 24 hours post infection

Cappelli et al. were the first to characterize the *M. tuberculosis* whole genome gene expression *in vivo* in human macrophages (Cappelli et al., 2006). Fontan et al. analyzed transcriptomes of *M. tuberculosis* from macrophages of the THP-1 cell line in 4 and 24 hours post infection (Fontan et al., 2008). In the work of Tailleux et al., the authors performed the first comparative analysis of gene expression in *M. tuberculosis* from infected macrophages and dendrite cells (Tailleux et al., 2008). An *in vivo* transcriptome comparison of two differently virulent *M. tuberculosis* strains (H37Rv and H37Ra) was first done by Li et al. (Li

By the present time, the most extensive study of mycobacterial gene expression *in vivo* is that by Homolka et al. (Homolka et al., 2010). The authors performed a comparative analysis of expression profiles for 3 clinical isolates of *M. africanum*, 12 clinical isolates of *M. tuberculosis*, and two reference laboratory strains (*M. tuberculosis* H37Rv and CDC1551) in activated and non-activated mouse macrophages. This work resulted in the isolation of gene groups whose expression changes irrespective of mycobacterial strain and/or the activation

In 2004, Talaat et al. first performed an analysis of whole genome *M. tuberculosis* gene expression under natural conditions in a living organism (mouse) (Talaat et al., 2004). They studied changes in the pathogen transcriptome composition at different time intervals post infection (7, 14, 21 or 28 days) and for different host genotypes (immunocompetent Balb/c mice and immunodeficient SCID mice). In 2007, Talaat et al. published a paper devoted to the analysis of *M. tuberculosis* gene expression in the lungs of Balb/c mice at later stages of the infection process (Talaat et al., 2007). In 2010, researchers of our group used a new approach to the enrichment of bacterial cDNA for analysis of *M. tuberculosis* gene expression in lung tissues of infected mice (Azhikina et al., 2010). The data obtained by us on quantitative and qualitative composition of the bacterial transcriptome were in good
