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The highly infectious bacterium Francisella tularensis is a facultative intracellular pathogen, whose virulence requires proliferation inside host cells, including macrophages. Here we have performed a global transcriptional profiling of the highly virulent F. tularensis subsp. tularensis Schu S4 strain during its intracellular cycle within primary murine macrophages, to characterize its intracellular biology and identify pathogenic determinants based on their intracellular expression profiles. Phagocytosed bacteria rapidly responded to their intracellular environment and subsequently altered their transcriptional profile. Differential gene expression profiles were revealed that correlated with specific intracellular locale of the bacteria. Upregulation of general and oxidative stress response genes was a hallmark of the early phagosomal and late endosomal stages, while induction of transport and metabolic genes characterized the cytosolic replication stage. Expression of the Francisella Pathogenicity Island (FPI) genes, which are required for intracellular proliferation, increased during the intracellular cycle. Similarly, 27 chromosomal loci encoding putative hypothetical, secreted, outer membrane proteins or transcriptional regulators were identified as upregulated. Among these, deletion of FTT0383, FTT0369c or FTT1676 abolished the ability of Schu S4 to survive or proliferate intracellularly and cause lethality in mice, therefore identifying novel determinants of Francisella virulence from their intracellular expression profile.
Through long-standing co-evolution with their hosts, intracellular bacterial pathogens have evolved strategies to successfully invade, survive and proliferate within mammalian host cells. Regardless of the specific pathogenic mechanisms used, the intracellular fate of these bacteria depends on a successful overriding of the host cell bactericidal mechanisms. This is achieved via the timely expression and/or activation of dedicated virulence factors, a result of the remarkable ability of bacteria to sense their intracellular environment and respond accordingly through the induction of appropriate genes. Examples in intracellular pathogens include genes encoding the Type III secretion system-2 (T3SS-2) of Salmonella enterica serovar Typhimurium or the VirB Type IV secretion system of Brucella species, which are both induced intracellularly upon acidification of the pathogen-containing vacuole (Boschiroli et al., 2002, Sieira et al., 2004, Starr et al., 2008, Valdivia et al., 1996) and required for intracellular survival and replication (Hensel et al., 1998, O'Callaghan et al., 1999, Sieira et al., 2000). Recent advances in RNA isolation techniques and DNA microarray technologies have allowed global transcriptional profiling of intracellular bacteria, such as S. Typhimurium (Eriksson et al., 2003, Hautefort et al., 2008), S. Typhi (Faucher et al., 2006), Shigella flexneri (Lucchini et al., 2005), Mycobacterium tuberculosis (Fontan et al., 2008, Schnappinger et al., 2003), Chlamydia trachomatis (Belland et al., 2003) Listeria monocytogenes (Chatterjee et al., 2006) and Bacillus anthracis (Bergman et al., 2007), bringing insight into the global responses of these pathogens to their respective intracellular environments. Additionally, some of these studies combined with mutagenesis approaches have identified novel genes involved in intracellular growth (Bergman et al., 2007, Chatterjee et al., 2006), indicating that the intracellular induction of specific bacterial genes can serve as a clue to identify genetic determinants of pathogenesis.
Francisella tularensis is a highly infectious, Gram-negative, facultative intracellular bacterium that causes tularemia, a widespread zoonosis that affects humans. Human tularemia is a fulminating disease that can be caused by exposure to as few as 10 bacteria, the pneumonic form of which can lead to up to 25% mortality if untreated (Oyston et al., 2004). Four subspecies of F. tularensis, F. tularensis subsp. tularensis (Type A), F. tularensis subsp. holarctica (Type B), F. tularensis subsp. novicida, and F. tularensis subsp. mediasiatica are recognized, among which strains from subspecies tularensis and holarctica can cause tularemia in humans (Ellis et al., 2002). Type A strains, which are geographically distributed in North America, are highly virulent and account for the most severe cases of the disease. As a facultative intracellular pathogen, F. tularensis is capable of infecting and proliferating in a variety of host cell types, including hepatocytes, endothelial cells, fibroblasts, and mononuclear phagocytes (Ellis et al., 2002). Macrophages are believed to be an important target for infection in vivo, and the pathogenesis of F. tularensis depends on the bacterium's ability to survive and replicate within these host cells (Ellis et al., 2002). Various models of Francisella-macrophage interactions using either virulent, attenuated or non-human pathogenic strains, and murine or human macrophages or macrophage-like cell lines, have been developed to characterize the intracellular cycle of this bacterium (Checroun et al., 2006, Clemens et al., 2004, Golovliov et al., 2003, Santic et al., 2005a, Schulert et al., 2006). Although the disparity of these models may have generated controversial findings about the timing of intracellular events (Checroun et al., 2006, Clemens et al., 2004, Santic et al., 2005a), a consensual model is that F. tularensis survival and replication inside macrophages relies upon its ability to escape from its initial phagosome and reach the cytosol where it extensively replicates. Following replication, the Live Vaccine Strain (LVS), an attenuated Type B derivative, and virulent Type A and Type B strains can reenter the endocytic compartment of murine primary macrophages to reside within large fusogenic vacuoles that display autophagic features (Checroun et al., 2006). Altogether, our current understanding of the Francisella intracellular cycle indicates that this pathogen trafficks through various intracellular compartments where it is likely subjected to different environmental cues.
Some genetic determinants of Francisella intracellular growth have been identified using random transposon mutagenesis and loss of function screens in various host cells (Gray et al., 2002, Maier et al., 2007, Qin et al., 2006, Tempel et al., 2006), or through differential expression analysis of genes regulated in vitro by the Francisella virulence regulator MglA (Baron et al., 1998, Lauriano et al., 2004, Brotcke et al., 2008, Brotcke et al., 2006). Additionally, in vivo screens for transposon insertional mutants defective for virulence have also identified genes involved in intracellular growth (Su et al., 2007, Weiss et al., 2007), illustrating how essential intracellular proliferation is to Francisella global virulence. A prominent locus required for intracellular growth is the Francisella Pathogenicity Island (FPI, Fig. 4A), a ~ 30-kb region that potentially encodes a secretion system (Nano et al., 2004, de Bruin et al., 2007) similar to the recently identified Type 6 secretion systems (T6SS) (Mougous et al., 2006, Pukatzki et al., 2006). This suggests that Francisella expresses specialized machineries to secrete proteins either to the bacterial surface or into the host cell, but such effectors of intracellular pathogenesis have not yet been identified. Nevertheless, functions encoded by the FPI have been associated with phagosomal escape and intracellular growth, since insertional or deletion mutants in iglA and iglB (Gray et al., 2002), iglC (Golovliov et al., 2003, Lauriano et al., 2003, Santic et al., 2005b), and pdpA (Nano et al., 2004), are defective for intramacrophage growth, and iglC mutants in novicida and holarctica LVS strains are defective in phagosomal escape (Lindgren et al., 2004, Santic et al., 2005b, Chong et al., 2008). This indicates that IglC-dependent FPI-encoded functions are involved in the early stages of Francisella intracellular trafficking.
Although genetic screens have proven valuable to identify the FPI (Gray et al., 2002, Nano et al., 2004), novel virulence genes (Brotcke et al., 2006) or specific F. novicida genes that modulate the host ASC/Caspase 1 cell death pathway (Weiss et al., 2007), much remains to be understood about the bacterial determinants of Francisella pathogenesis. Specifically, little is known about the intracellular biology of this bacterium and the specific genes it requires to ensure its intracellular survival and proliferation. Because Francisella likely responds to its intracellular environment by temporally expressing virulence factors during its intracellular cycle, we have postulated that genes required for intracellular pathogenesis and global virulence can be identified based on their increased expression inside macrophages. We have therefore performed the transcriptional profiling of intracellular virulent Type A Francisella during its infection cycle within murine bone marrow derived macrophages to globally identify genes that are upregulated intracellularly. Here we report a combination of genomics, cell biological and genetic approaches that have identified novel virulence factors of Francisella based on their intracellular expression, and characterized the intramacrophage biology of this highly infectious bacterium.
In order to perform relevant and meaningful transcriptional profiling of intracellular F. tularensis, it was necessary to first characterize the Francisella-macrophage interaction model we selected. In particular, detailing the timing of the bacterium's intracellular cycle was important to the experimental design of the transcriptional analysis. In this study, we used a model of primary murine bone marrow-derived macrophage (BMMs) infection with F. tularensis subsp. tularensis strain Schu S4, a prototypical highly virulent Type A strain whose genome has been sequenced (Larsson et al., 2005). In synchronized infections of BMMs, we examined the kinetics of phagosomal disruption using a phagosomal integrity assay (Checroun et al., 2006), quantified intracellular growth, and analyzed the overall intracellular cycle by confocal and transmission electron microscopy. As previously observed with the F. tularensis subsp. holarctica strain LVS in BMMs (Checroun et al., 2006), internalized Schu S4 were rapidly accessible to cytoplasmically delivered anti-Francisella LPS antibodies (Fig. 1A), demonstrating a rapid disruption of the Francisella-containing phagosome (FCP). While half of the bacteria remained enclosed within phagosomes at 30 min post infection (p.i., Fig. 1A and B), the majority of them had disrupted their phagosomal membrane at 1 h p.i. (73 ± 6.3%; Fig. 1A and C). By 4 h p.i., all bacteria were cytosolic and displayed patterns of initial replication (Fig. 1A and D). From 4 to 16 h p.i., Schu S4 underwent extensive cytosolic replication (Fig. 1A and E-F), with a maximal growth rate between 8 and 12 h p.i.. At that time, Schu S4 intracellular doubling time (53 ± 1.0 min, data not shown) significantly exceeded those of the virulent Type B strain FSC200 (109 ± 24 min, data not shown) or LVS (114 ± 4 min, data not shown), suggesting that highly virulent Type A strains exhibit higher intracellular fitness than less virulent or attenuated Type B strains. After 16 h p.i., intracellular growth stalled (Fig. 1A) and bacteria were found within late endosomal vacuoles characterized by LAMP-1-positive membranes and ultrastructural features of autophagic vacuoles (Fig. 1G), known as Francisella-containing vacuoles (FCVs) (Checroun et al., 2006). Hence, the intracellular cycle of Schu S4 in BMMs includes an early phagosomal stage up to 1h p.i., a lag phase in the cytosol, between 1 and 4 h p.i., a stage of extensive cytosolic proliferation between 4 and 16 h pi, and a late vacuolar stage between 16 and 24 h p.i.
Because of the variety of the intracellular stages in the cycle of Francisella inside macrophages, we postulated that the bacterium expresses various subsets of genes at specific stages. In an attempt to comprehend gene expression changes along the entire Francisella intracellular cycle, our experimental design included time points encompassing all intracellular stages, namely 1, 2, 4, 8, 12, 16 and 24 h p.i. Additionally, a time zero sample corresponding to the immediate processing of bacteria added directly to BMMs was generated to obtain initial bacterial expression profiles as a baseline for identification of genes upregulated within macrophages. BMMs were infected as described in the Materials and Methods section and samples were collected for total RNA isolation according to a predesigned randomization scheme. RNA isolation yielded high quality RNA, with detectable bacterial ribosomal RNAs in samples containing high numbers of bacteria (0, 12, 16 and 24 h p.i.; Fig. 2A). Because the amount of bacterial RNA in samples containing limited numbers of bacteria (1, 2, 4 and 8 h p.i.; Fig. 2A) was not sufficient (< 1 μg) to generate exploitable microarray data, all total RNA samples were subjected to an RNA amplification step, as described in the Materials and Methods section, which generated sufficient amounts of complementary RNA (cRNA) targets to proceed with hybridization on Affymetrix DNA custom GeneChip arrays. Analyses of the microarray data (GEO series number GSE12663) using either a Pearson correlation similarity measure (not shown) or quantile normalization without background correction (PCA plot, Fig. 2B) showed that whole genome expression profiles from biological replicates clustered according to time points (Fig. 2A), therefore validating our experimental design. Interestingly, distances between sample clusters within the PCA plot revealed important changes in gene expression between time zero and 1 h p.i., indicating a significant response of Francisella during the early phagosomal stage. Despite clustering separately, global gene expression profiles at 1 h and 2 h p.i. and at 8 and 12 h p.i., respectively, were similar (Fig. 2A), consistent with the specific intracellular stages of entry into the cytosol and extensive cytosolic replication, respectively (Fig. 1). Global expression profiles at 4, 16 and 24 h p.i. all appeared unique and likely represented the onset of intracellular growth (4 h p.i.), the transition towards FCV formation (16 h p.i.), and the late vacuolar stage (24 h p.i.), respectively. Overall, there was a temporal correlation between global gene expression profiles and specific intracellular stages, strongly suggesting that Francisella alters its transcriptional profile according to its intracellular location.
To further analyze Francisella expression profiles and identify genes upregulated during the intracellular cycle, signals from each gene probe set at each time point were normalized to those at time zero to generate heat maps of mRNA fold changes and reveal intracellular expression profiles of individual genes (Supplementary Material, Fig. S1). A two-fold change cut-off was used to define significant up- or down-regulation of a gene compared to its level at time zero. While a relatively constant number of genes were downregulated, ranging from 121 at 1 h p.i. to 183 at 12 h p.i. (Fig. 2C), the number of genes showing a significant upregulation increased over time, ranging from 78 at 2 h p.i. to 257 at 24h p.i., indicating an increasing response of Francisella to its intracellular environment. Over the whole time course, 658 genes showed significant changes in their expression, among which 298 were upregulated and 360 were downregulated (Fig. 2D). We defined an index of change in mRNA level (Fig. 2D) as the number of time points where significant changes in the expression of a particular gene were detected (Fig. 2D). Since most intracellular stages were represented in our experimental design through several time points, with the exception of the early phagosomal stage, we reasoned that genes exhibiting significant intracellular expression changes have an mRNA change index > 2. Additionally, genes showing unidirectional changes in expression over two consecutive time points (mRNA change index = 2) encompassing a particular intracellular stage were also retained for further consideration. Using these criteria, 111 genes with a mRNA change index ≥ 3 were upregulated, while 156 genes were downregulated (Fig. 2D). Further screening of the microarray data for genes showing either consistent increased expression over several consecutive time points and/or an expression profile coherent with the timing of specific intracellular stages identified a total of 152 genes that displayed expression profiles of significant upregulation within BMMs and 99 genes that were significantly downregulated (Supplementary Material, Table S1). Interestingly, various expression profiles were identified, showing significant upregulation either at all time points, during phagosomal and late vacuolar stages, or during the cytosolic replication stages. In order to examine the biological relevance of these findings, gene functions associated with these particular expression patterns were further analyzed.
Francisella genes that were most upregulated inside BMMs belonged to the general stress response pathway (Fig. 3A and Supplementary Material, Table S1). Genes encoding molecular chaperones and general stress proteins such as HtpG (FTT0356), ClpP (FTT0624), ClpX (FTT0625), the Lon protease (FTT0626), HslU (FTT0687c), HslV (FTT0688c), HtpX (FTT0862c), DnaJ (FTT1268c), DnaK (FTT1269c), GrpE (FTT1270c), a DnaJ-like chaperone (FTT1512c), GroEL/ES (FTT1696/1695), ClpB (FTT1769c) and Hsp (FTT1794) exhibited increased expression inside BMMs compared to their mRNA levels at time zero. Interestingly, most of these genes displayed a similar expression profile, with an early induction by 1 h p.i., followed by a second upregulation at 16 and 24 h p.i. (Fig. 3A). Such a remarkable expression profile was independently confirmed by quantitative PCR on clpB mRNA (Fig. 3D), therefore validating the microarray results. Because the highest mRNA levels of these genes corresponded to both the early phagosomal and late vacuolar stages of the Francisella intracellular cycle, this indicates that the early FCP and the late FCV subject Francisella to physiological stress, which the bacterium efficiently responds to in a coordinated manner. This genetic response is consistent with the rapid acidification of early phagosomes observed in F. novicida-infected human macrophages (Santic et al., 2008) and Schu S4-infected BMMs (Chong et al., 2008) and the fusogenic characteristics of late vacuoles (Checroun et al., 2006).
Not only general stress response genes were upregulated inside BMMs, but genes associated with oxidative stress response were significantly induced within 1 h p.i. and thereafter (Fig. 3B). These included genes encoding a Dyp-type peroxidase (FTT0086), HemC (FTT0259), glutaredoxins (FTT0533c and FTT0555), a peroxiredoxin (FTT0557), a short chain dehydrogenase (FTT0558), the methionine sulfoxide reductases MsrB (FTT0878c) and MsrA (FTT1105c, FTT1797c) and the superoxide dismutase SodC (FTT0879). While most of these genes were upregulated at 1 and 2 h p.i., only msrA1, msrB and sodC were also strongly upregulated at late stages (Fig. 3B), indicating that the temporal response to oxidative stress slightly differs from the general stress response. The early induction of these genes suggests the presence of oxidative stress in the early phagosome, possibly via the generation of reactive oxygen species (ROS). This is however inconsistent with the finding that LVS inhibits NADPH oxidase assembly and ROS production in human neutrophils (McCaffrey et al., 2006). Provided that the same phenomenon occurs in Schu S4-infected BMMs, it remains possible that oxidative stress response genes are either upregulated through the sensing of very low levels of ROS or of other intraphagosomal cues, such as cationic antimicrobial peptides that can induce oxidative stress response genes in S. Typhimurium (Bader et al., 2003). This would allow bacteria to consequently express redundant protective functions in addition to mechanisms of inhibition of ROS production. With such attributes, one would expect that intracellular survival of virulent Francisella is not affected by ROS. This hypothesis is in agreement with studies suggesting that Francisella killing by IFNγ-activated peritoneal exudate cells depends upon reactive nitrogen species (RNS) rather than ROS production (Lindgren et al., 2007, Lindgren et al., 2005). Lindgren et al. also examined the role of the catalase/peroxidase KatG in Schu S4 resistance to reactive species and concluded that it does not play a role in this particular strain (Lindgren et al., 2007). Compared to other oxidative stress response genes, katG (FTT0721c) did not show any upregulation and instead was downregulated from 4 h pi. and onwards (Supplementary Material, Table S1). In spite of its secretion by intracellular bacteria in monocytes (Lee et al., 2006), this enzyme does not seem to play a major role in counteracting any intracellular oxidative stress. Instead, the remarkable upregulation of other oxidative stress response genes we have identified points towards an intracellular role for these enzymes. Overall, our results demonstrate that Schu S4 efficiently responds to intracellular stress by coordinately expressing stress response genes during both the early and late endosomal stages of its intracellular cycle.
In addition to the expression profiles of stress-related genes, a significant number of genes exhibited expression profiles of upregulation at consecutive time points between 4 and 16 h p.i., that is during the cytosolic replication stage (Supplementary Material, Table S1). Expectedly, these included genes that belong to functional categories consistent with bacterial growth, such as de novo nucleotide synthesis (FTT0113, FTT0114, FTT0117, FTT1229), metabolism of vitamins and cofactors (FTT1389-1391), amino acids (Fig. 4), translation and protein biosynthesis (FTT0226, FTT0228, FTT0333, FTT0334, FTT0344, FTT0403), polyamine biosynthesis (FTT0431-0435) and cell division (FTT0697, FTT1635c). Upregulated genes encoding functions related to carbohydrate metabolism (FTT0080, FTT0414, FTT0417, FTT1295c, FTT1365c, FTT1367c and FTT1483c) pointed towards the use of both glycolysis and the pentose phosphate pathway for energy metabolism. Genes encoding various transporters, such as ABC transporters (FTT0209, FTT1124, FTT1125), MFS superfamily transporters (FTT708), oligopeptide transporters (FTT0572, FTT0688c, FTT0953, FTT1233c, FTT1253) and others (FTT0175c, FTT0598c, FTT0668), were also upregulated (Supplementary Material, Table S1), suggesting that replicating bacteria are characterized by enhanced nutrient acquisition capacities. In particular, the fslABCDE genes (FTT0025c-FTT0029c) (Ramakrishnan et al., 2008, Sullivan et al., 2006), or figABCDE genes in F. novicida (Kiss et al., 2008), were highly upregulated between 4 and 12 h p.i. (Fig. 3C). These genes encode a siderophore biosynthesis and transport system that is essential for in vitro growth in iron-depleted conditions (Ramakrishnan et al., 2008, Sullivan et al., 2006) and for LVS and F. novicida virulence (Su et al., 2007, Weiss et al., 2007), but no data is available on an intracellular role. The significant upregulation of this operon during the cytosolic replication phase (from 4 to 12 h p.i., Fig. 3C) of Schu S4 strongly suggests Francisella enhances iron acquisition during intracellular proliferation. Because the fsl genes are induced under iron-limiting conditions through their regulation by Fur (Ramakrishnan et al., 2008), their expression profile is consistent with restricted iron availability inside the mammalian cytosol (Shi et al., 2008, Lucchini et al., 2005) and illustrates Francisella adaptation to the cytosolic environment.
The majority of the metabolic genes upregulated intracellularly encoded functions associated with amino acid catabolism (Fig. 4A), including polyamine biosynthesis from L-arginine through spermidine (Fig. 4A), indicating that amino acids constitute a major source of nitrogen for intracellular Francisella. Amino acids availability likely results not only from the cytosolic pool of amino acids but also from uptake of oligopeptides, as Schu S4 remarkably encodes 8 di-/tripeptide transporters, 5 of which (FTT0572, FTT0686c, FTT0953c, FTT1233c and FTT1353) were upregulated intracellularly (Fig. 4B). Consistently, both a Xaa-Pro aminopeptidase (FTT0609) and the oligopeptidase A PrlC (FTT0899c) were upregulated inside BMMs. Taken together this indicates that Schu S4 has the capacity to transport and degrade oligopeptides during its infection cycle. Another oligopeptide transport system, the Opp ABC transporter, which is regulated in F. novicida by MglA but appears to downmodulate intracellular growth (Brotcke et al., 2006), is likely non functional in Schu S4, since the subunits OppB and OppC-encoding genes FTT0123 and FTT0124 are truncated. Consistently, the OppD and OppF subunits-encoding genes FTT0125 and FTT0126 did not generate any detectable transcripts at any time point analyzed (data not shown).
Although our study mostly focused on genes upregulated intracellularly, we also identified 99 genes with expression profiles of significant downregulation inside BMMs (Supplementary Material, Table S1). They encoded functions associated with DNA replication, transcription and translation (Supplementary Material, Table S1), indicating some alteration of Francisella nucleic acid metabolism and information processing in macrophages compared to in vitro growth conditions (time zero). Consistently, the RNA polymerase sigma-32 factor RpoH (FTT1112) was strongly downregulated while the RNA polymerase sigma-70 factor RpoD (FTT1035c) showed an early intracellular upregulation (Supplementary Material, Table S1), indicating a significant switch in gene expression following uptake by BMMs. Additionally, genes involved in either LPS (FTT0231c, FTT0232c, FTT1046c, FTT1305c) or polyglutamate capsule biosynthesis (FTT0805 and FTT0806) were downregulated within BMMs, suggesting alterations of major bacterial surface components following the transition from an extracellular to an intracellular stage. Genes encoding various transport systems, such as MFS superfamily permeases (FTT0442, FTT0446, FTT487, FTT488c), ion transporters (FTT0676, FTT1145, FTT1277c), multidrug resistance proteins (FTT1256, FTT1399, FTT1654, FTT1727c) and others (FTT0804, FTT0446) were downregulated (Supplementary Material, Table S1). Together with the intracellular upregulation of genes encoding other transporters (Supplementary Material, Table S1), these results clearly indicate significant changes in the physiology of Francisella following uptake and further illustrate its adaptability to the macrophage environment. Concluding that these downregulated genes are not required for intracellular growth needs to be cautiously assessed, since one has to consider that the observed decrease in mRNA levels of these genes is relative to their expression levels in in vitro-grown bacteria, where they may have been upregulated on CHAB above levels required to achieve any potential intracellular functions. Indeed, 10 genes that we found to be downregulated in our analysis have been identified independently using transposon mutagenesis approaches in either LVS or F. novicida as being required for intracellular growth and/or virulence (Table 1). For example, the capB and capC genes (FTT0805 and FTT0806) encode functions associated with polyglutamate capsule biosynthesis and are required for intracellular growth of LVS in J774 cells (Maier et al., 2007) and virulence of LVS (Su et al., 2007) and F. novicida (Weiss et al., 2007) in mice, yet these genes were downregulated inside BMMs (Supplementary Material, Table S1 and Table 1). Future studies on the roles of this putative Francisella capsule will clarify whether it plays a role in intracellular proliferation.
A major goal of our transcriptional analysis of intracellular Francisella was to identify genes required for pathogenesis based on their expression profiles. A more detailed analysis of the microarray data showed that 39 of the 152 genes (26%) significantly upregulated inside BMMs have been previously characterized as required for intracellular proliferation and/or virulence, through transposon mutagenesis-based approaches (Table 1). They included the iron acquisition genes fslABC, the stress response genes clpP, clpX, lon, dnaK, groEL and clpB, genes involved in amino acid metabolism (gcvTHP1, aspC1, metNIQ) and several FPI genes (Table 1). This demonstrates that Francisella virulence determinants are induced intracellularly. We further examined the transcriptional patterns of the FPI genes (Fig. 5A), which have been identified as required for intracellular growth and virulence (de Bruin et al., 2007, Gray et al., 2002, Lai et al., 2004, Maier et al., 2007, Nano et al., 2004, Santic et al., 2005b, Su et al., 2007, Tempel et al., 2006, Weiss et al., 2007). PdpA, pdpB, dotU, iglI, pdpD and iglABCD displayed significant upregulation inside BMMs (Fig. 5B), while most other FPI genes exhibited a similar expression profile, albeit below the 2-fold cut-off value for statistical significance (Fig. 5B). Although several of the FPI genes showed a rapid upregulation within the first hour p.i., maximal mRNA levels were reached by the end of the cytosolic replication stage, i.e. between 12 and 16 h p.i. (Fig. 5B). To independently validate these expression profiles, the mRNA levels of pdpD, iglA, iglC, pdpA and pdpC were measured using quantitative PCR and normalized to gyrA (FTT1575c) mRNA levels, which we found to be constitutively expressed at all time points (data not shown). The expression profiles of these 5 genes correlated with those obtained through microarray analysis (Fig. 5B and and6A).6A). While pdpC was globally down regulated compared to time zero, pdpD, iglA, iglC, pdpA were upregulated and displayed a comparable expression profile, with a rapid upregulation followed by a strong increase in mRNA levels between 12 and 16 h p.i. (Fig. 6A). This indicates a coordinated regulation of all FPI transcriptional units within the FPI. IglC mRNA levels were much higher than those of the other FPI genes tested, suggesting a higher transcription of this gene, or increased stability of its mRNA. Although further transcriptional analysis is required to understand the expression differences in this region of the FPI, these results are consistent with IglC being prominently expressed by LVS in macrophages (Golovliov et al., 1997) and by virulent Type A bacteria recovered from infected mouse spleens (Twine et al., 2006). To further validate our data, we examined the intrabacterial levels of the IglC and PdpC proteins during Schu S4 intracellular cycle. While PdpC levels did not dramatically change over the whole time course, IglC intrabacterial levels increased from 0 to 4 h p.i. (Fig. 6B), further demonstrating intracellular induction of this protein (Chong et al., 2008). This initial increase was later followed by a secondary accumulation visible at 24 h p.i. (Fig. 6B), consistent with the expression profiles of iglC (Fig. 5B and and6A).6A). Altogether, these results demonstrate the intracellular induction of FPI genes and validate our original assumption that genes involved in intracellular pathogenesis can be identified based on their intracellular expression profile. Through mutational analyses, functions associated with the FPI-encoded type VI secretion system have been assigned to early intracellular events, such as phagosomal escape (Lindgren et al., 2004, Santic et al., 2005b), implying that FPI genes must be induced rapidly upon entry. Our results corroborate these previous data by showing a rapid increase in FPI mRNA and protein levels. However, the finding that maximal expression of FPI genes takes place at the end of the cytosolic replication stage strongly argues for an additional requirement of FPI functions at later stages of the intracellular cycle.
Among genes displaying significant upregulation inside BMMs, 27 encoded hypothetical proteins (Supplementary Material, Table S1), most of which do not share any significant homology with any proteins and therefore appear to be rather specific to the Francisella genus. These include FTT0254c, FTT0297, FTT0383, FTT1536c, FTT1541c, FTT1586c, FTT1676 and FTT1771 (Supplementary Material, Table S1 and Fig. 7A). Upregulated genes encoding proteins with putative functions were also identified, such as a Sel1 family tetratricopeptide repeat-containing protein (FTT0369c), a putative secreted transglutaminase (FTT0989), a putative outer membrane protein Omp 26 (FTT1542c), and a homolog of the Bordetella pertussis Bvg Accessory Factor (FTT1392) (Supplementary Material, Table S1 and Fig. 7A). Hence, putative secreted proteins, outer membrane components and transcriptional regulators were induced during the intracellular cycle, a set of bacterial factors consistent with changes in gene regulation and molecular interactions with the host cell. Although all upregulated inside BMMs, these genes exhibited differential expression profiles, suggesting that their functions are required at various stages of Schu S4 intracellular cycle. Expression of FTT0989 was maximal during the cytosolic replication stages (Fig. 7A and B), while that of FTT1542c and FTT1392 peaked at both early and late stages of the cycle (Fig. 7A and B). Interestingly, one third of these genes have been shown to be regulated by the global virulence regulator MglA in F. novicida (Brotcke et al., 2006), a high percentage given that only 27 among the 152 genes (18%) we found to be significantly upregulated inside BMMs (Supplementary Material, Table S1) are MglA-regulated in F. novicida (Brotcke et al., 2006). Given the prominent role of MglA in regulating virulence-associated functions in Francisella, this suggests that these hypothetical proteins encode pathogenesis-related functions, which is supported by the evidence that disruption of the FTT0989 locus in F. novicida results in decreased intracellular growth, cytotoxicity and a slight attenuation in vivo (Brotcke et al., 2006).
To examine whether we could identify novel virulence determinants of Francisella through transcriptional profiling, we generated deletions of 10 upregulated loci encoding hypothetical functions (FTT0254c, FTT0297, FTT0369c, FTT0383, FTT0989, FTT1333c, FTT1392, FTT1542c, FTT1586c and FTT1676) and tested the resulting mutants for intracellular defects. We first designed and constructed a suicide vector, pJC84 (Fig. 8A) that allows for generation of untagged, in-frame deletions in the chromosome of virulent Type A strains through SacB-assisted allelic replacement. Along the allelic replacement process, PCR analysis of the targeted locus in the wild type, intermediate cointegrant and deletion mutant strains demonstrated deletion of each locus in the proper chromosomal region and loss of pJC84 sequences following the sucrose selection step (Fig. 8BCD, Supplementary Material and data not shown). To test for any intracellular growth defect of the Schu S4 mutants, BMMs were infected with either wild type or mutant strains and intracellular CFUs were enumerated. Deletion mutants in FTT0254c, FTT0297, FTT0989, FTT1333c, FTT1392, FTT1542c and FTT1586c did not show any defect in intracellular growth in BMMs (Fig. 9A and data not shown), but the Schu S4ΔFTT0383, Schu S4ΔFTT0369c and Schu S4ΔFTT1676 mutants exhibited obvious intracellular survival or growth defects (Fig. 9A-C). While the wild type strain displayed an expected intracellular growth profile over 24 h, the number of intracellular ΔFTT0383 bacteria rapidly decreased to barely detectable levels by 16 h p.i. (Fig. 9A), indicating intracellular killing of the mutant. Comparatively, growth of the ΔFTT0383 mutant in vitro in modified Mueller-Hinton broth was not affected (data not shown), ruling out a global physiological defect of this strain. During the course of this study, the FTT0383 ortholog in F. novicida was shown to encode a transcriptional regulator, FevR, which controls virulence gene expression and is essential for intracellular growth and pathogenesis (Brotcke et al., 2008). Numbers of viable intracellular ΔFTT0369c bacteria slightly increased up to 10 h p.i., then dramatically decreased by 2 Logs (Fig. 9B and F), indicating limited replication followed by intracellular killing. Compared to the parental strain that grew by 3 Logs over 16 h (Fig. 9A), ΔFTT1676 bacteria displayed an intracellular growth defect, since viable numbers remained steady during the same period before decreasing, although to a less dramatic extent than that observed with the ΔFTT0383 or the ΔFTT0369c mutants (Fig. 9C and F). Hence, deletion of either FTT0369c or FTT1676 affects intracellular proliferation and long-term survival. To confirm that the observed intracellular defects of these mutants were due to the respective single deletions of either FTT0383, FTT0369c or FTT1676, in trans complementation of the mutants with the respective full-length copies of the deleted gene were performed. While expression of either FTT0383 or FTT1676 under the control of the omp26 (FTT1542c) promoter fully restored their ability to survive and grow intracellularly (Fig. 9A, C and F), the omp26 promoter-mediated expression of FTT0369c only partially complemented the effect of the FTT0369c deletion (data not shown). Nonetheless, expression of ΔFTT0369c under its native promoter in the mutant strain (see Supplementary Material) fully restored both survival and intracellular growth (Fig. 9B and F). Altogether, these complementation studies demonstrate that the phenotypic defects of these mutants are due to their respective single gene deletion.
To further characterize these mutants, we examined their intracellular trafficking by confocal immunofluorescence microscopy using colocalization with LAMP-1-positive membranes as a readout of vacuolar versus cytosolic location (Checroun et al., 2006). Unlike the wild type strain that escaped from its original phagosome by 1 h p.i. (24.4 ± 1.0% of LAMP-1-positive bacteria; Fig. 9D and F) and extensively replicated in the cytosol by 10 h p.i. (Fig. 9D and F), the ΔFTT0383 mutant remained enclosed within a LAMP-1-positive compartment (≥ 85% of bacteria) at 1 and 10 h pi (Fig. 9D and F), consistent with intracellular killing within phagolysosomes. Complementation of the FTT0383 deletion restored phagosomal escape (Fig. 9E) and cytosolic replication (Fig. 9F). Hence, deletion of the FTT0383 locus abolishes Schu S4 ability to escape from its original phagosome, survive and replicate intracellularly, consistent with results obtained with F. novicida (Brotcke et al., 2008). By contrast, ΔFTT0369c bacteria showed phagosomal escape kinetics similar to wild type organisms, although a small fraction of bacteria (< 20%) localized to LAMP-1-positive vacuoles after 4 h p.i. (Fig. 9D). At 10 h pi., ΔFTT0369c bacteria showed limited intracellular growth by microscopy (Fig. 9F), consistent with viable numbers of intracellular bacteria (Fig. 9B). Complementation of the mutant with a full-length copy of FTT0369c restored intracellular growth (Fig. 9F) and did not affect the kinetics of phagosomal escape (Fig. 9E), demonstrating that deletion of the FTT0369c locus mostly affects cytosolic proliferation. Deletion of the FTT1676 locus decreased the ability of bacteria to rapidly escape from their original phagosome, since 60.5 ± 1.1% and 21 + 3.5% of bacteria colocalized with LAMP-1 at 1 and 4 h pi, respectively, yet the majority reached the cytosol afterwards (Fig. 9D and F). Although mostly cytosolic from 4 h pi, ΔFTT1676 bacteria did not undergo significant replication (Fig. 9C), despite some patterns of limited growth at 10 h pi (Fig. 9C and F). Complementation of the mutant with full-length FTT1676 restored phagosomal escape and intracellular growth to wild type levels (Fig. 9E and F), indicating that the product of the FTT1676 locus is required for optimal phagosomal escape and mostly for cytosolic replication. Taken together, these results identify FTT0383 (fevR), FTT0369c and FTT1676 as novel bacterial determinants of Schu S4 intracellular pathogenesis.
To extend these findings, we tested whether deletion of either FTT0383, FTT0369c or FTT1676 affects in vivo virulence of Schu S4. Compared to intranasal or intradermal infections of BALB/cJ mice with Schu S4, which caused 100% lethality by day 5 p.i., infections with either the ΔFTT0383 or the ΔFTT0369c mutants led to 100% survival up to 30 days p.i., regardless of the route of inoculation (Fig. 10A and B), and no viable mutants could be recovered from any organ at this time (data not shown). Similarly, intradermal and intranasal infections with the ΔFTT1676 mutant led to 100 and 80% survival, respectively (Fig. 10A and B), and morbidity in mice infected intranasally was protracted. Hence, deletion of either FTT0383, FTT0369c or FTT1676 abolishes Schu S4 virulence in mice, demonstrating that these loci encode virulence factors of this pathogen. Interestingly, the intracellular defects of the FTT0369c and FTT1676 mutants - impaired cytosolic replication - correlated with the expression profiles of the deleted genes, since both FTT0369c and FTT1676 were maximally expressed during the cytosolic phase (Fig. 7A). Such a correlation was less obvious for FTT0383, probably due to its pleiotropic role as a transcriptional regulator (Brotcke et al., 2008). Nonetheless, our results associate a gene function with its timed intracellular expression, endorsing transcriptional profiling to identify genes required at specific stages of the Francisella intracellular cycle.
In this study, we have established the intracellular transcriptome of a highly virulent strain of F. tularensis during its infection cycle within murine primary macrophages. The kinetic nature of our analysis has revealed key aspects of the intracellular biology of this pathogen, which effectively adapts its genetic response to its particular intracellular location. Although regulators of Francisella virulence gene expression have been characterized, such as MglA (Baron et al., 1998, Brotcke et al., 2006, Charity et al., 2007), SspA (Charity et al., 2007) and FevR (Brotcke et al., 2008), further studies are required to better understand the regulatory networks that respond to intracellular cues and control expression of Francisella genes required for intracellular pathogenesis. Nonetheless, our findings illustrate the high degree of adaptation of Francisella to the macrophage environment, a feature that undoubtedly contributes to its high infectivity and virulence. Importantly, we have used the Francisella intracellular transcriptome data to confirm previously identified and discover novel virulence determinants of this pathogen. Expression profiles of the FPI genes, which encode for a major virulence determinant of Francisella, revealed early and late induction events, a finding consistent with induction of FPI proteins during the early phagosomal stage (Chong et al., 2008), implying additional intracellular roles for the FPI. Furthermore, we have deleted a series of upregulated hypothetical functions and found that 3 out of 10 deletions caused intracellular defects in our BMM infection model. Surprisingly, we could not reproduce the intracellular growth defect observed upon deletion of the FTT0989 locus in F. novicida (Brotcke et al., 2006). This limited number of intracellular defect-causing mutations suggests that either not all genes upregulated during the intramacrophagic cycle are essential, or that such genes may be required under conditions that were not reproduced in our infection model. For example, it remains possible that the initial infectious cycle within macrophages induces genes required at a subsequent stage of the infectious process that cannot be mimicked in vitro. Mouse infections with these mutants are underway to address this hypothesis, which is supported by the recent identification of the F. novicida ortholog of FTT1392 (FTN_1355) as required for proliferation in the liver of infected mice (Kraemer et al., 2009). Nonetheless, deletion of the Schu S4 ortholog of the F. novicida FevR transcriptional regulator (Brotcke et al., 2008) showed that this upregulated gene is essential for intracellular survival and in vivo virulence of Schu S4. Given the strong defects caused by this mutation, Schu S4 FevR likely fulfills the same function as its F. novicida ortholog (Brotcke et al., 2008), making it a key regulator of virulence in highly virulent strains. Furthermore, we have identified two novel factors required for intracellular proliferation and in vivo virulence that are encoded by the FTT0369c and FTT1676 loci. These genes are specific to the Francisella genus and their sequence is highly conserved between subspecies. While FTT0369c encodes a Sel1 family tetratricopeptide repeat-containing protein and has not previously been identified as a virulence gene, FTT1676 possibly encodes an outer membrane protein that has been shown to be required in LVS for mouse lung infection (Su et al., 2007), consistent with an important role in the pathogenesis of Francisella. Future studies will address how the products of both genes contribute to intracellular proliferation and virulence.
The prototypic Type A virulent strain, F. tularensis subsp. tularensis Schu S4 was obtained from Rick Lyons (University of New Mexico, Albuquerque, USA). Schu S4 was grown on cysteine heart agar supplemented with 9% heated sheep blood (CHAB) plates or modified Mueller-Hinton (MMH) agar plates [Mueller-Hinton medium supplemented with 0.1% glucose, 0.025% ferric pyrophosphate and 2% IsoVitaleX (Becton Dickinson, Cockeysville, MD)] for 3 days at 37°C under 7% CO2. Immediately prior to infection of BMMs, a few colonies from a freshly streaked CHAB plate were resuspended in Tryptic-Soy broth supplemented with 0.1% L-cysteine and OD600nm was measured to estimate bacterial numbers. Schu S4 liquid cultures were performed in MMH broth. For animal infections, bacteria were cultured in MMH broth at 37°C with constant shaking overnight, aliquoted into 1 ml samples, frozen at -80°C and thawed just prior to use. Frozen stocks were titered by enumerating viable bacteria from serial dilutions plated on MMH agar plates. All manipulations of F. tularensis strain Schu S4 were performed in a Biosafety Level 3 facility according to standard operating procedures approved by the Rocky Mountain Laboratories Institutional Biosafety Committee.
To generate in-frame deletions of specific genes in F. tularensis subsp. tularensis Schu S4, we constructed a suicide vector allowing for SacB-assisted allelic replacement in Francisella, named pJC84. To engineer pJC84, the ampicillin resistance gene bla from pJC80 (Celli et al., 2005) was removed by inverse PCR using primers JC427 and JC428 (Supplementary Material, Table S2), digestion with AatII and religation. A 920 bp region upstream of the Bacillus subtilis sacB gene in pJC80 was subsequently removed from the ligation product by a second inverse PCR using primers JC418 and JC420 (Supplementary Material, Table S2), to remove the sacB promoter region. The resulting PCR fragment was digested with NheI and SalI. Independently, a ~ 350 bp fragment carrying the Francisella groEL promoter region was PCR amplified from pFNLTP gro-gfp (Maier et al., 2004) using primers JC414 and JC415 (Supplementary Material, Table S2) and the kanamycin resistance encoding gene aph was PCR amplified from pBBR1-MCS2 (Kovach et al., 1994) using primers JC416 and JC417 (Supplementary Material, Table S2) and fused together by overlap extension PCR (Horton et al., 1989) using primers JC414 and JC417. The resulting 1150 bp fragment was digested with NheI and SalI and ligated into the similarly digested pJC80 derivative to create pJC84. pJC84 (3775 bp, Fig. 8A) was fully sequenced and carries a bi-cistronic aph-sacB region under the control of the Francisella groEL promoter region, a feature essential to the proper expression of genes in Francisella (Gallagher et al., 2007), a multiple cloning site with 6 unique restriction sites (Fig. 8A), and the origin of replication ori from pSP72 (Promega) for cloning and propagation in Escherichia coli. The pJC84 sequence data has been submitted to the GenBank database under the accession number FJ155667.
Deletion constructs of the FTT0369c, FTT0383, FTT1542c and FTT1676 loci were generated as described in the Supplementary Material, and cloned into pJC84. To perform allelic replacement in the chromosome of Schu S4, electrocompetent bacteria were prepared as follows: Schu S4 was grown for 3 days on modified Mueller-Hinton agar plates at 37°C and 7% CO2 and fresh colonies were suspended in modified Mueller-Hinton broth and grown at 37°C under agitation until the culture reached an OD600nm between 0.4 and 0.5. Bacteria were collected by centrifugation at 4000 × g for 10 min at 20°C, washed twice with 0.5 M sucrose and concentrated 100 times in 0.5 M sucrose. Approximately 1×1010 bacteria were mixed with 1 μg of recombinant pJC84 plasmid DNA, pulsed (2.5 kV, 25 μF, 600W) using a BioRad GenePulser Xcell (BioRad, Hercules, CA) and immediately added to 1 ml of pre-warmed MMH broth and incubated at 37°C under agitation for 3 h, which was followed by plating on MMH plates supplemented with 10 μg/ml of kanamycin. Kanamycin-resistant colonies were tested for integration of the allelic replacement plasmid, using colony PCR with primers JC420 and JC427 (to amplify a 1.5 kb internal fragment of sacB) or JC589 and JC428 (to amplify a 900 bp fragment of pJC84 backbone). Independent clones were then subjected to sucrose counter selection: clones were inoculated in MMH broth and grown at 37°C under agitation up to an OD600nm of 0.6. Sucrose at a final concentration of 5% was then added and cultures were incubated for an additional hour before plating serial dilutions on MMH supplemented with 8% sucrose and incubation at 37°C, 7% CO2 for 2 days. Sucrose-resistant clones were patched on kanamycin-containing MMH plates to verify loss of the kanamycin-resistance marker, and colony PCR was performed to detect clones with allelic replacement within the correct chromosomal locus, using primers JC534 and JC535 and primers JC654 and JC655, respectively, for the FTT0383 deletion, using primers JC678 and JC679 and primers JC689 and JC690, respectively, for the FTT0369c deletion, using primers JC546 and JC625 and primers JC628 and JC629, respectively, for the FTT1542c deletion, using primers JC614 and JC615 and primers JC610 and JC613, respectively, for the FTT1676 deletion, and loss of the sacB gene using primers JC420 and JC427 (Supplementary Material, Table S2). Independent clones carrying the correct in-frame deletion in either FTT0383, FTT0369c, FTT1542c or FTT1676, were isolated and used for further studies. For genetic complementation of the mutants, plasmids pJC901, pJC903 and pJC904, which respectively express FTT0383 under the control of the omp26 (FTT1542c) promoter region, FTT0369c under the control of its own promoter region, or FTT1676 under the control of the omp26 (FTT1542c) promoter region, were constructed from pFNLTP6 (Maier et al., 2004) as described in the Supplementary Material and introduced into the respective mutant strains by electroporation.
Bone marrow cells were isolated from femurs of 6-10 week-old, C57BL/6J female mice (Jackson Laboratories, Bar Harbor, ME, USA) and differentiated into macrophages as described (Chong et al., 2008), and replated in either 6-, 12- or 24-well cell culture-treated plates at a density of 1×106, 5×105 or 1×105 macrophages/well, respectively. BMM infections were performed as described (Chong et al., 2008) at an appropriate multiplicity of infection (MOI) of 50, unless stated otherwise.
The number of viable intracellular bacteria per well was determined in triplicate for each time point, as described previously (Chong et al., 2008), with the exception that serial dilutions were plated on CHAB agar plates. To estimate intracellular growth rate of bacteria within a particular time interval, CFU doubling times were established were established as described previously (Chong et al., 2008) and were calculated from three independent experiments and expressed as mean ± SD.
BMMs grown on 12 mm glass coverslips in 24-well plates were infected and processed for immunofluorescence labeling as described previously (Chong et al., 2008). Primary antibodies used were mouse anti-F. tularensis LPS (US Biological, Swampscott, MA), and rat anti-mouse LAMP-1 (clone 1D4B, developed by J. T. August and obtained from the Developmental Studies Hybridoma Bank developed under the auspices of the NICHD and maintained by The University of Iowa, Department of Biological Sciences, Iowa City, IA 52242). Secondary antibodies were Alexa Fluor™ 488-donkey anti-mouse and Alexa Fluor™ 568-donkey anti-rat antibodies (Invitrogen). To quantify Francisella escape from its initial phagosome, phagosomal integrity assays were performed as described previously (Checroun et al., 2006) with minor modifications (Chong et al., 2008). Samples were observed on a Nikon Eclipse E800 epi-fluorescence microscope equipped with a Plan Apo 60×/1.4 objective for quantitative analysis, or Carl Zeiss LSM 510 or LSM 710 confocal laser scanning microscopes for image acquisition. Confocal images of 1024×1024 pixels were acquired and assembled using Adobe Photoshop CS.
Infected BMMs on 12 mm Aclar coverslips were infected and processed as described (Chong et al., 2008). Sections were viewed in a Hitachi H7500 transmission electron microscope at 80 kV. Images were acquired with a Hamamatsu 2K × 2K bottom mount AMT digital camera (Advanced Microscpy Techniques, Danvers, MA) and assembled in Adobe Photoshop CS3.
BMMs seeded in 12-well plates were infected with Schu S4 at a MOI of either 200 (0, 1, 2 and 4 h time points), 50 (8, 12 h time points) or 25 (16 and 24 h time points) as described above. The use of different MOIs in this experimental design was required to recover sufficient amount of bacterial RNA at all time points analyzed. Empirical monitoring of the infection demonstrated little changes in the timing of events in the Francisella intracellular cycle, suggesting that, although different MOIs were used, comparable biological samples were obtained. Time zero samples were generated by adding bacteria (MOI 200; 108/well) directly to BMMs that had been washed with PBS, followed by the immediate addition of lysis buffer, as described below. Uninfected controls were generated at both 0 and 24h post infection. To improve the accuracy and precision of the final measurements, 4 biological replicates at each time point were generated. Due to the number of samples that could be concurrently processed, infections were performed in separate batches. To ensure that differences between batches did not affect the final measurements, the samples were randomly assigned to batches, with the limitation that samples within one plate were grouped per time point and processed simultaneously.
At each time point, samples were washed 3 times with sterile PBS to remove residual extracellular bacteria, and both BMMs and bacteria were lysed directly in the wells by the addition of 1 ml TRIzol (Invitrogen, Carlsbad, CA) and pipetting 10 times. Samples were transferred to microtubes, 200 μl chloroform were added, vials were vortexed, and centrifuged at 16,000 × g for 15 min. The RNA-containing aqueous phase was collected from each sample and passed through a Qiashredder column (Qiagen, Valencia, CA) at 21,000 × g for 2 min to homogenize any remaining genomic DNA (gDNA) in the aqueous phase. RNA was purified using the RNeasy 96 kit (Qiagen, Valencia, CA) as described previously (Virtaneva et al., 2005). RNA quality was verified on Agilent 2100 Bioanalyzer using the Pico analysis kit (Agilent Technologies, Palo Alto, CA). Contaminating gDNA was removed by DNase I treatment (DNA-free™, Applied Biosystems, CA) as described previously (Virtaneva et al., 2005). During processing, all the 40 samples were randomized in 96-well plates in order to avoid any confounding due to well location, time-point, or biological replicate batch and minimize error due to plate edge effects and fluid transfers.
Because not all samples contained sufficient amounts of bacterial RNA to warrant direct hybridization on Affymetrix DNA GeneChips, an RNA amplification step was introduced as follows: all RNA samples that were generated from F. tularensis SchuS4-infected and non-infected BMMs were randomized on a single 96-well plate and the MessageAmp™ II-Bacteria kit (Ambion, Foster City, CA) was used to amplify 0.5 to 1 μg of mixture of F. tularensis and BMM RNAs according to manufacturer's instructions. Briefly, RNAs were concentrated to 5 μl, denatured for 10 min at 70°C, polyadenylated using E.coli polyA polymerase for 15 min at 37°C, and reverse transcribed for 2 h at 42°C using ArrayScript and polydT primer with a T7 tail. Second strand synthesis was performed immediately after first strand cDNA synthesis for 2 h at 16°C. Purified cDNA was mixed with 75 nmol of biotin-16-UTP (Roche Applied Science, Mannheim, Germany) and concentrated to 18 μl. Biotin-labeled complementary pathogen-host RNA was amplified at 37°C in an overnight 40 μl in vitro transcription reaction. The amount of target consisting of macrophage and F. tularensis cRNAs was determined by Absorbance measurements at 260 nm. The quality and the size of the amplified targets were determined on a Agilent 2100 Bioanalyzer using the Pico analysis kit (Agilent Technologies, Palo Alto, CA). The amount of F. tularensis cRNA was estimated by quantitative RT-PCR of the FTT0243 locus, as described below, using a standard curve method (Applied Biosystems, Foster City, CA). F. tularensis RNA extracted from a bacterial suspension in TSB-C was used for the RNA standard curve.
An estimated 1 μg of F. tularensis cRNA was fragmented to 20-100 bp in size. cRNA targets were biotinylated according to the manufacturer's instructions and hybridized to a custom Affymetrix GeneChip (RMLchip2a520312F) containing 1,933 probe-sets, among which 1,581 probe-sets were derived from the annotation of the F. tularensis subsp. tularensis SchuS4 genome (NC_006570) and 352 additional probe-sets from the F. tularensis subsp. holarctica LVS strain were derived from an annotation of the LVS genome sequence (NC_007880) by Integrated Genomics. Each sample was added to standard Affymetrix hybridization master mix (2× Hybridization Buffer, B2 Control Oligo, Herring Sperm DNA, BSA, and 1× Hybridization spike with BioB, BioC, BioC, and Cre DNAs) and applied to the chip for an overnight hybridization at 40°C. Upon completion of the fluidic process, the Affymetrix 7Gplus GeneChip scanner (Affymetrix, Santa Clare, CA) was used to scan each chip and create the image files (dat). Affymetrix GeneChip Operating Software (GCOS v1.4, http://www.affymetrix.com) was used to perform the preliminary analysis of the custom chips. All *.cel files, representing individual replicates, were scaled to a trimmed mean of 500 using a scale mask consisting of the F. tularensis probe sets to produce the *.chp files. A pivot table with all samples was created including calls, call p-value and signal intensity for each gene. Signals from the non-infected control samples indicated that 17 Schu S4 probe-sets out of 1,581 potentially cross-hybridized with host RNA (with at least 4 present calls out of 8) and were therefore not considered as biologically significant. The pivot table was then imported into GeneSpring GX 7.3 (http://www.chem.agilent.com), where hierarchical clustering (condition tree) using a Pearson correlation similarity measure with average linkage was used to verify that biological replicates grouped together. A separate analysis was performed from the *.cel files by directly importing the files into Partek Genomics Suite software (v6.3, 6.07.0730, Partek Inc. Saint Louis, Mo.) and running the quantile normalization without background correction to produce a PCA plot. Two samples were declared outliers based upon the quality of signal produced from the total present calls and the scale factor not grouping with the same time points. In order to create a balanced comparison, only three replicates were used for each time point. An ANOVA was formulated from this normalization process to generate p-values from the False Discovery Rate (FDR) report, and SAM (Significance Analysis of Microarrays, (Tusher et al., 2001)) was also performed.
In order to validate DNA microarray data, mRNAs from 15 selected Francisella genes were quantified using TaqMan® Real Time PCR analysis (Q-PCR). Remaining RNAs from either uninfected or Schu S4-infected BMMs were randomly distributed in a 96-well plate and subjected to cDNA synthesis and purification as previously described (Virtaneva et al., 2005). Briefly, 4.5 μg of random primers (Invitrogen) were annealed (10 min at 70°C, 10 min at 25°C) to remaining RNA. First-strand cDNA was synthesized with 25 U/ml SuperScript™ III (Invitrogen) in the presence of 0.5 mM dNTPs, 0.5 U/ml SUPERaseIn™ RNase inhibitor (Ambion) and 10 mM dithiothreitol (DTT) for 10 min at 25°C, 60 min at 37°C, 60 min at 42°C, 10 min at 70°C. RNA was removed by alkaline hydrolysis in 1 N NaOH (30 min at 65°C), neutralized with 1 N HCl, prior to cDNA purification using QiaQuick-96 (Qiagen, Valencia, CA) according to the manufacturer's recommendations, except that an additional 10 min centrifugation was performed to remove traces of ethanol. Quantitative PCR was performed as previously described (Virtaneva et al., 2005). All Q-PCR reactions were prepared using Biomek Nx (Beckman-Coulter, Fullerton, CA) robotics to minimize pipetting differences, and run in multiplex format on a 7900HT ABI TaqMan instrument (Applied Biosystems, Foster City, CA). Briefly, Platinum Q-PCR SuperMix-UDG RT-PCR reactions (Invitrogen) were carried out in a 20 μl reaction volume containing 1× Platinum Q-PCR SuperMix-UDG mix, 6 mM MgCl2, 1 × ROX reference dye (1.25 mM 5-carboxy-X-rhodamine, succinimidyl ester), 300nM VIC® dye and the quencher carboxytetramethylrhodamine (TAMRA; Applied Biosystems, Foster City, CA) labeled FTT1575c (gyrA) probe, 200 nM target forward and reverse primers, and 300 nM of the target TaqMan® oligo at 50 °C for 2 min, 95 °C for 2 min, 55 cycles of 95 °C for 15 sec and 60 °C for 1 min. All TaqMan® probes were labeled with 6-carboxy-fluorescein (6-FAM) at the 5′ end and the quencher TAMRA at the 3′ end. All the TaqMan® Q- PCR primers and probes were designed using Primer Express v. 2.0 (Applied Biosystems). Each primer and probe was tested for cross hybridization to other F. tularensis and mouse genes using BLASTN. The gyrA gene (FTT1575c) was used in multiplex Q-PCR reactions for normalization, due to its constitutive expression both extra- and intracellularly (data not shown). ΔCT values for each multiplex TaqMan® reaction were calculated by subtracting the CT value of the reference gene (gyrA) from the CT value of the tested gene. The median ΔCT values for 2-3 technical replicates for each of the 3-4 biological replicates was calculated followed by transformation using the formula 2-ΔCT to obtain normalized expression levels. The normalized values were plotted for each time point and were fit to a curve using the cubic spline algorithm in GraphPad Prism 5.0 (GraphPad, San Diego, CA). The Affymetrix GCOS software was used to interpret Affymetrix GeneChip results, and the MAS5 algorithm was used in construction of gene expression levels for the genes of interest in Q-PCR correlation. GraphPad Prism 5.0 software (GraphPad, San Diego, CA) was used to calculate the correlation of MAS5 and TaqMan® results. The correlation of log 2(MAS5) values and Q-PCR ΔCT values was significant with P<0.0001.
To examine the expression of FPI proteins by intracellular bacteria, BMMs were infected with Francisella strains at a MOI of either 200 (0, 1, 2 and 4h time points) or 50 (8, 12, 16 and 24h time points). At each time-point, cells were washed three times with PBS and lysed in sterile distilled water to release intracellular bacteria. An aliquot was used to enumerate bacteria by CFU analysis, and the remaining volume was spun down at 16,100 × g for 5 min, 4°C to pellet bacteria. Bacterial pellets were further processed for Western blotting as described previously (Chong et al., 2008). Samples were normalised to CFU equivalents.
Groups of ten 6-8 week-old BALB/cJ mice (Jackson Laboratories) were infected with the indicated wild type or mutant strains of F. tularensis Schu S4 via intranasal and intradermal routes for survival studies. Immediately prior to infection, a stock vial of bacteria was thawed and serially diluted in PBS to the appropriate bacterial density. Mice were anesthetized intraperitoneally (i.p.) with 100 μl of a 12.5 mg/ml ketamine + 3.8 mg/ml xylazine solution. For intranasal infections, approximately 10 CFU in 25 μl of PBS was administered to the nares of each mouse. This dose routinely results in 100% lethality with 5 days of infection with wild type Schu S4. For intradermal infections, mice were injected between the dermal sheets of the ear pinna with approximately 50 CFU of Schu S4 in 10 μl PBS. This dose routinely results in 100% lethality within 5 days of infection with wild type Schu S4. Actual doses were confirmed by plating the inoculum on modified Mueller Hinton (MMH) agar plates. Animals were monitored twice daily for signs of morbidity and euthanised when moribund. All animal infections were performed at Biosafety Level-3 and approved by the Rocky Mountain Laboratories Animal Care and Use Committee.
We are grateful to Rick Lyons and Francis Nano for the gift of strains and antibodies, to Leigh Knodler for critical reading of the manuscript and helpful suggestions, and to Tregei Starr for her help with generating the ΔFTT0369c mutant of Schu S4. This work was supported by the Intramural Research Program of the NIH, National Institute of Allergy and Infectious Diseases.