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1 Mycobacteria Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO 80523, USA
2 Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO 80523, USA
Correspondence
Richard A. Slayden
richard.slayden{at}colostate.edu
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Supplementary tables of data are available with the online version of this paper at http://mic.sgmjournals.org
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). In general, inhibition of bacterial division at the point of septum formation is characterized by normal chromosome replication and segregation that is not followed by cellular division leading to a filamentous phenotype (Goehring & Beckwith, 2005). Septum formation is dependent on the assembly of FtsZ into the contractile Z-ring at the site of division (Den Blaauwen et al., 1999; Romberg & Levin, 2003) and additional proteins recruited to the septum site in a sequential fashion, resulting in constriction and cell division. In spite of this biochemical information, the current understanding of regulatory elements and the precise nature of the signals driving the coordination of cell division with other cell cycle processes is largely unknown, especially in Mycobacterium tuberculosis.
Many of the proteins involved in cell division, such as FtsZ, are conserved across taxa, while others appear limited to one or a few bacterial groups (Goehring & Beckwith, 2005; Margolin, 2000). These include proteins known to interact with FtsZ and that modulate Z-ring assembly (Goehring & Beckwith, 2005; Romberg & Levin, 2003). The Z-ring is highly dynamic, and proper assembly of this structure and cell division are strongly influenced by direct interactions of FtsZ with ZipA, ZapA, FtsA, MinD, EzrA and SulA (Harry et al., 1999; Harry, 2001; Migocki et al., 2004; Romberg & Levin, 2003). These factors together with transcriptional regulators form a regulatory network that orchestrates the spatial and temporal control of cell division with other cell cycle processes. However, the underlying molecular mechanisms are only partially understood in model organisms and remain largely unknown for many unrelated organisms.
Analysis of the M. tuberculosis genome sequence revealed that homologues of the FtsZ-interacting proteins are not present (Table 1). It is likely that M. tuberculosis encodes orthologues of the FtsZ-binding proteins that fulfil these functions, but they are not evident. An alternative global approach is needed to identify putative regulators and potential FtsZ-interacting proteins such that networks controlling cell division in M. tuberculosis can be elucidated. In this current work we report inhibition of septum formation, morphological changes consistent with prevention of septum formation and the transcriptional responses associated with this process. This allowed the assignment of potential regulatory elements and FtsZ-interacting proteins in M. tuberculosis.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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0.5 and diluted 1 : 10. Drugs were prepared in DMSO (500–0.5 µM in a twofold serial dilution in 100 µl total volume of <0.05 % DMSO), tested in triplicate and MIC values were determined as the lowest concentration of drug that prevented bacterial outgrowth after 7 days incubation. Untreated paired control bacteria were grown under identical conditions to treated bacteria with the exception that no drug was added. For viability testing, drugs were added to 30 ml cultures and incubated for 7 days, and on each day an aliquot was plated on Middlebrook 7H11 agar medium. After continued incubation for 3 weeks, viability of the treated bacteria was determined by enumeration of c.f.u.
Ultrastructural analysis of M. tuberculosis.
For electron microscopy a 50 µl aliquot of bacteria was mixed with an equal volume of 2.5 % glutaraldehyde in 0.1 M sodium cacodylate (pH 7.2), 5 mM CaCl2 and 5 mM MgCl2, and incubated at room temperature (RT) for 1 h. The fixed bacterial cells were collected by centrifugation, washed twice and fixed overnight at 4 °C with 2.5 % glutaraldehyde. Final preparation for SEM was achieved by post-fixing with 1 % OsO4 in sodium cacodylate buffer for 1 h and dehydrating in a graded series of acetone (25–100 %). Ultrastructural examination was performed using a JOEL JEM-100CX electron microscope.
Microarray processing.
The M. tuberculosis microarrays were obtained through the TB Research Materials and Vaccine Testing Contract (N01 AI-75320) at Colorado State University. These arrays contained probes representing the ORFs of M. tuberculosis strains H37Rv (http://genolist.pasteur.fr/TubercuList) and CDC1551 (www.tigr.org). Oligonucleotides were printed at 40 µM with SMP-3 pins producing 100 µm spots. Slides were post-processed using succinic anhydride as described by Brown and colleagues (http://cmgm.stanford.edu/pbrown/protocols/index.html). M. tuberculosis cultures (30 ml) were grown to an OD600 of 0.3 with shaking at 150 r.p.m., each drug was added at its respective MIC (60 µM albendazole, 80 µM thiabendazole), or 0.01 % DMSO for the untreated control, and the cultures were grown for 5 h (0.25 of a generation). Bacterial cells were harvested by centrifugation and suspended in 1 ml TRIzol. Following physical disruption with 0.1 mm zirconium beads, RNA was purified using an RNeasy kit (Qiagen). Approximately 8 µg total RNA was converted to cDNA in the presence of either Cy5- or Cy3-labelled nucleotides as described by Brown and colleagues (http://cmgm.stanford.edu/pbrown/protocols/index.html). Hybridization was performed at 42 °C for 12 h. Slides were scanned using a Bio-Rad Chipreader Pro.
Data reduction and analysis.
The final microarray dataset resulted from combining two independent replicates of albendazole and thiabendazole treatments, thus four biological replicates of septum formation inhibition. Data reduction and global normalization were performed on the raw fluorescent intensities. Low intensity spots were eliminated based on a 15 % mean channel intensity cut-off. The normalized intensity values of treated and control cultures were used to generate ratio and log2 expression values for each gene. Self-organizing map (SOM) analysis (Xiao et al., 2003) was performed on the entire dataset. SOM is an unsupervised neural network model that effectively categorizes and clusters genes based on similarities in the gene expression profiles among treatment groups.
Quantitative real-time PCR verification.
Quantitative RT-PCR was performed on selected genes to verify the differential gene expression observed through microarray data analysis. Quantitative RT-PCR primers were designed and analyses were performed according to Manganelli et al. (2001a). PCR amplification was performed with a thermocycling program of 55 °C for 5 min, then 95 °C for 2 min and 45 cycles of 95 °C for 15 s, 60 °C for 30 s and 72 °C for 45 s. The relative number of transcripts for each gene was determined based on linear regression analysis of 100, 10 and 1 ng M. tuberculosis genomic DNA (see Table S1 for primer sequences, and the intercept and slope constants for each primer pair; available with the online version of this paper at http://mic.sgmjournals.org). All reactions were performed in triplicate on two independent RNA preparations from M. tuberculosis treated for 5 h with albendazole or thiabendazole.
Bioinformatic analysis.
To identify putative orthologues for genes that influence Z-ring formation, a reciprocal best hits (RBH) dataset was generated comparing the M. tuberculosis ORFs using FASTA (Pearson & Lipman, 1988) against ORFs from 20 actinobacterial genomes and from the genomes of Ralstonia solanacearum, Erwinia carotovora subsp. atroseptica, Escherichia coli and Xanthomonas campestris. Any gene selected for the RBH database aligned with the query over at least 80 % of its length to >30 % identity as described elsewhere (Bell et al., 2004). The resulting RBH dataset was mined to find putative orthologues of genes that influence Z-ring formation (FtsA, ZapA, ZipA, EzrA, MinD and SulA). BLASTX, BLASTP, TBLASTN analysis against searchable databases prepared from prototype protein datasets of each FtsZ assembly gene were also used. The resulting datasets of encoded FtsZ assembly proteins were analysed using POLYDOT (EMBOSS package; Rice et al., 2000) to confirm the similarity. In all BLAST searches, the percentage identity and bit-score were optimized to yield putative M. tuberculosis FtsZ-related proteins. Candidate proteins were further analysed using InterPro release 11 for motifs or domains and compared with those seen in the prototype FtsZ assembly protein datasets (Mulder et al., 2005).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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; Downing, 2000). Moreover, the three-dimensional structures of bacterial FtsZ orthologues show striking similarity to the structure of 
- and 
-tubulin and both FtsZ and tubulin possess GTPase activity (Lowe & Amos, 1998; Nogales et al., 1998). FtsZ of M. tuberculosis is similar to other prokaryotic FtsZ genes in sequence and structure, and possesses GTPase activity (White et al., 2000).
Based on the ability of benzimidazole and structurally related compounds to inhibit the GTPase activity of the M. tuberculosis FtsZ we hypothesized that albendazole and thiabendazole inhibit septum formation (Huang et al., 2006; Margalit et al., 2004). The MICs for albendazole and thiabendazole as determined by the microbroth dilution assay (Slayden et al., 2000) were found to be 60–120 µM and 80–160 µM, respectively. Treatment of M. tuberculosis with 60 µM albendazole or 80 µM thiabendazole for 3 days led to 4 and 3 logs reduction in bacterial viability, respectively (Fig. 1). These treatments also significantly altered bacterial cell length, as observed and measured by scanning electron microscopy. Maximum filamentation was achieved by the third day of drug exposure. Albendazole- and thiabendazole-treated cells displayed mean lengths of 6.2±1.4 µm and 9.6±1.9 µm, respectively. These observed lengths are in sharp contrast to the length of untreated cells 2.3±0.97 µm (Fig. 2).
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) and this was consistent with the inhibition of Z-ring formation (Goehring & Beckwith, 2005; Huang et al., 2006). As a control, M. tuberculosis cultures were also treated with 20 µM cephalexin and 40 µM piperacillin, two known inhibitors of FtsI (Pogliano et al., 1997). FtsI is a penicillin-binding protein required in the completion of cell division and acts post-septum formation. As expected the FtsI-treated cells were filamentous but, in contrast to FtsZ-inhibited cells, possessed clearly visible concentric rings indicative of septa (Fig. 3E, F) (Romberg & Levin, 2003).
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). This represents an altered expression of 6 % of the M. tuberculosis ORFs, a value consistent with global effects on regulatory cascades and compensatory responses of gene expression involved in multiple cell processes. It was noted that when the expression profiles of albendazole- and thiabendazole-treated cells were compared, there was a >70 % (n=1722) concordance in the transcriptional response between these treatments, indicating a similar mode of action for both these Z-ring inhibitors. Furthermore, when compared to previously reported expression profiles obtained during inhibition of basic metabolic processes such as transcription and protein synthesis (Boshoff et al., 2004), there was no overlap with the expression profiles induced by albendazole and thiabendazole treatment, thus adding confidence that the observed transcriptional response is due to inhibition of septum formation.
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). This assessment revealed a strong concordance in gene expression trends as measured by RT-PCR and microarray analyses. Specifically, inhibition of FtsZ polymerization led to an average induction of genes associated with DNA replication and septum formation, and an average repression of genes involved in resolution of the septum and cell wall synthesis.
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; Wang et al., 2002; Xiao et al., 2003) was performed on the complete dataset of 3182 transcriptionally active genes to construct a transcriptional map. SOM analysis organized the 3182 genes into 62 groups (0–61), with the number of genes in each group ranging from 23 to 337. Sets of discriminant genes representing the major cell cycle processes of DNA initiation and replication, chromosome segregation, cell division, peptidoglycan synthesis, LAM synthesis, arabinogalactan (AG) synthesis, and mycolic acid and related lipoglycan synthesis were selected to provide a more concise picture of how genes involved in cell division grouped relative to other cell cycle processes (Table S3, available with the online version of this paper at http://mic.sgmjournals.org). The discriminant gene sets were identified based on experimental work in M. tuberculosis and other bacteria (Crick et al., 2001, 2004; Laub et al., 2000, 2002; Mahapatra et al., 2005; Ryan & Shapiro, 2003; Slayden et al., 2003). The relative SOM grouping of genes discriminant for each cell process is displayed as the mean SOM group for all discriminant genes of a single cellular process (Fig. 5).
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, discriminant genes of DNA initiation and replication (dnaA and dnaE1, dnaN and dnaZX) fell within the SOM range of 9±5 (Greendyke et al., 2002; Salazar et al., 2003), and discriminant genes of DNA segregation (parA, parB and ftsK) were also distributed across a relatively narrow set of SOM groups (SOM mean 15±2) (Goehring & Beckwith, 2005). This SOM clustering is consistent with many of these genes being organized in a regulon structure. Moreover, the SOM assignments reflect transcriptional induction in response to albendazole and thiabendazole treatment, consistent with inhibition of septum formation.
In contrast to the SOM clustering of DNA replication and segregation genes, the genes encoding cell division components were distributed in a bimodal fashion (SOM 15±5 and 53±2) (Fig. 5). This major separation of genes was associated with the up-regulation of one set of genes (SOM 15±5) and down-regulation of another (SOM 53±2) in response to septum inhibition. Notably, the up-regulated genes (ftsZ, ftsW, ftsQ, ftsH and ftsE) are those involved in septum formation, whereas repressed expression occurred with genes involved in septum resolution (divIC and ftsI). This is consistent with the observed inhibition of septum formation and reports in other bacteria of temporal regulation of genes encoding septum formation and genes encoding septum resolution (Goehring et al., 2005; Katis et al., 1997).
Interestingly, regardless of genome location the genes encoding peptidoglycan synthesis demonstrated a transcriptional profile that overlapped with the genes for septum formation (Fig. 5). Correlated transcriptional activity of genes involved in septum formation and peptidoglycan synthesis with DNA replication and segregation is observed in other bacteria (Romberg & Levin, 2003). Thus, the transcriptional profiles for these cellular events support our hypothesis that inhibition of septum formation and subsequent interrogation of gene expression patterns will enable the identification of unknown gene products that participate in or regulate cell division.
It is important to note that genes encoding the synthesis of other mycobacterial cell envelope products (LAM, AG and mycolic acids) do not yield tight clusters based on expression profile analysis (Fig. 5). Together, the transcriptional response and organization of genes involved in cell wall biosynthesis suggest that these cell cycle processes are not linked to septum formation.
Regulatory elements and putative FtsZ-interacting proteins
The transcriptional profile that emerged in response to inhibition of septum formation was coupled with bioinformatic analyses to identify other genes that potentially participated in septum formation and cell division. Specifically, we targeted the identification of transcriptional regulators and proteins that would substitute for septum-associated products (ZipA, ZapA, FtsA, MinD, ErzA and SulA) that were not previously annotated in the M. tuberculosis genome. This process led to the identification of 14 genes encoding regulatory proteins. These could be grouped as regulators induced by inhibition of septum formation (Group I in Fig. 5 and Table 3) and those that were repressed by inhibition of septum formation (Group II in Fig. 5 and Table 3).
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; Moker et al., 2004; Zahrt & Deretic, 2000), TetR-family transcriptional regulator, a Lpr-family transcriptional regulator and three putative transcriptional regulators. The regulators with repressed expression (Group II) included GntR family regulators, two TetR like regulators, an alternative sigma factor and two putative transcriptional regulators. The differential expression of a large number of transcriptional regulators was consistent with the significant change in gene expression profiles and the wide number of metabolic processes that were altered as a result of cell division inhibition. As discussed below several of these regulators have already been associated with the control of bacterial growth and cell division. The genes that encode proteins associated with septum formation were narrowly spread between SOM groups 7–18. Thus, to identify genes encoding products that potentially interact with FtsZ and influence Z ring formation we applied detailed bioinformatics focusing on genes in SOM groups within this range. This limitation reduced the number of gene products to be analysed to 553, and when analysed for orthologues of ZipA, ZapA, FtsA, MinD, ErzA and SulA, four ORFs were identified. Two of these ORFs encode putative ZipA orthologues and two encode putative MinD orthologues as determined by bioinformatic analysis. The ZipA-like proteins, Rv2345 and Rv3835, are annotated as conserved hypothetical proteins. The MinD-like proteins are encoded by Rv1708 and Rv3660c, and are annotated as a putative initiation inhibition protein and a putative septum-site-determining protein, respectively. These genes have BLASTP bit scores of 30–100 to their respective orthologue. Thus, the use of gene expression profiling not only provided further confirmation of the involvement of already annotated gene products, such as FtsZ and FtsI, in cell division, but when coupled with bioinformatic approaches allowed for the identification of putative FtsZ-interacting gene products.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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, 2003; Boshoff et al., 2004; Manganelli et al., 2001b, 2002; Sherman et al., 2001; Wilson et al., 1999). Thus, we employed microarray analyses to evaluate our hypothesis that inhibition of septum formation would increase the expression of cell division genes and genes involved in upstream processes such as DNA replication and segregation, and would repress expression of genes involved in cell division events downstream of septum formation. It was also anticipated that this approach would allow for the identification of unassigned mycobacterial gene products involved in septum formation and regulation of cell division.
Albendazole and thiabendazole are known inhibitors of tubulin polymerization and, recently, additional benzimidazole and structurally related compounds were shown to inhibit the GTPase activity of M. tuberculosis FtsZ (Margalit et al., 2004). Albendazole and thiabendazole are relatively insoluble and have proven difficult to use with in vitro assays (White et al., 2000). Nevertheless, as we demonstrated in this work, concentrations within the soluble range of these drugs inhibited the growth of M. tuberculosis. It is well established in other organisms and in M. tuberculosis that inhibition of FtsZ leads to smooth filamentous cells while, in contrast, inhibition of FtsI produces filamentous cells with distinct septi (Goehring & Beckwith, 2005; Huang et al., 2006; Pogliano et al., 1997; Romberg & Levin, 2003). Analysis of M. tuberculosis treated with the benzimidazole compounds (FtsZ inhibitors) or known FtsI inhibitors (cephalexin and piperacillin) revealed cellular morphologies fully consistent with observations in other bacteria (Romberg & Levin, 2003). Moreover, when gene expression profiles were evaluated it was found that genes encoding septum formation in M. tuberculosis and events that proceed this process were up-regulated upon inhibition of Z-ring formation, and those genes associated with the resolution of septi were down-regulated. Thus, both the morphological characteristics and transcription profiles of M. tuberculosis treated with albendazole or thiabendazole demonstrate that septum formation was inhibited through the inhibition of FtsZ polymerization.
Bioinformatic analyses have led to the identification of several M. tuberculosis gene products that are involved in septum assembly and cell division. However, this same analysis failed to identify homologues to other cell-division-associated proteins (Table 1). The wealth of transcriptional profiling data obtained in our current studies when coupled with bioinformatic analysis led to the identification of potential orthologues of these otherwise unassigned proteins. With this two-pronged approach, multiple annotated regulatory proteins were defined. Of particular interest was the two-component system encoded by mtrA and mtrB. In Caulobacter crescentus the homologue of this regulatory module is also expressed at the transition of DNA replication and Z-ring formation (Ausmees & Jacobs-Wagner, 2003). Although attempts to knockout mtrA in M. tuberculosis have failed, similar studies performed in C. glutamicum revealed that MtrA-MtrB directly regulates cell morphology and cell wall macrostructure (Moker et al., 2004; Zahrt & Deretic, 2000). It is also of interest to note that the TetR-like transcriptional regulator (Rv3249c) located adjacent to mtrA/B is also upregulated. However, it is unknown whether this transcriptional regulator participates in cell division. Other regulatory elements that are of interest include an Lpr-like transcriptional regulator (rv3291c) and SigG. In M. tuberculosis, rv3291 expression is inversely related to bacterial growth rate and has been linked to a decrease in cell division, suggesting that Lpr may regulate multiple cellular processes (Betts et al., 2002; Landgraf et al., 1996). SigG is one of 13 sigma factors encoded in this bacterium and elucidating the role of these gene products has been a major focus (Manganelli et al., 2004). Previous expression profiling studies have reported that sigG is expressed under exponential growth in aerated conditions (Voskuil et al., 2004). The biological function of this sigma factor and the significance of its repression due to inhibition of Z-ring formation are not known. However, SOM analysis grouped SigG with genes involved with completion of cell division, suggesting that this sigma factor may be a regulatory ‘checkpoint’ in the M. tuberculosis cell cycle. Moreover, it is intriguing that this was the only sigma factor with consistently altered expression in these studies.
Beyond transcriptional control, regulation can be fine-tuned through post-translational mechanisms, including protein interactions. Bioinformatic and transcriptional mapping identified ORFs that encode putative ZipA and MinD orthologues. ZipA and MinD act as FtsZ assembly factors; specifically influencing the assembly or disassembly of FtsZ, respectively (Goehring & Beckwith, 2005). The transcriptional activity and resulting SOM assignments of the putative zipA and minD ORFs were consistent with a role in cell division.
Clearly, further experimentation is required to elucidate the precise role of the identified regulators and validate the involvement of the ZipA/MinD orthologues in mycobacterial cell division. Nevertheless, these studies now provide a foundation and rationale to target these gene products for further studies. Association of regulatory elements and identification of ORFs that encode proteins with previously undefined roles in Z-ring assembly will help unravel the regulatory circuitry controlling growth. Continued research in this area will help define regulatory cascades used by M. tuberculosis to emerge from a long-term persistent infection.
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ACKNOWLEDGEMENTS |
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Received 12 December 2005;
revised 1 February 2006;
accepted 6 February 2006.
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