点击显示 收起
Division of Infectious Diseases, Department of Medicine
Center for Expression Arrays, University of Washington, Seattle
Department of Biomedical Sciences, Oregon State University, Corvallis
We compared growth rate and host-cell transcriptional responses of a Chlamydia trachomatis variant strain and a prototype strain. Growth dynamics were estimated by 16S rRNA level and by inclusion-forming units (IFUs) at different times after infection in HeLa cells. When inoculated at the same multiplicity of infection and observed 2448 h after infection, the variant 16S rRNA transcriptional level was 3%4% that of the prototype, and the IFUs of the variant strain were 0.1%1% those of the prototype. Specific host-cell transcriptional responses to the variant were identified in a global-expression microarray in which variant straininfected cells were compared with mock-infected and prototype straininfected cells. In variant straininfected cells, 47% (16/34) of specifically induced host genes were related to immunity and 32% (8/25) of specifically suppressed genes were related to lipid metabolism. The variant strain grew significantly more slowly and induced a modified host-cell transcriptional response, compared with the prototype strain.
As a sexually transmitted pathogen, Chlamydia trachomatis causes clinical manifestations that range from virtually asymptomatic to clinically severe [1]. To date, the mechanisms by which variations in the phenotype and genotype of the organism contribute to the diverse clinical outcomes are not understood.
Chlamydiae are characterized by an obligate intracellular life cycle and a unique biphasic developmental cycle. This cycle alternates between the infectious, extracellular, metabolically inert elementary body (EB) and the noninfectious, intracellular, metabolically active reticulate body and is accomplished within membrane-bound vacuoles termed "inclusions" [2, 3]. We have identified and studied a naturally occurring C. trachomatis variant strain that was selected from a group of isolates that exhibit unique morphological characteristics of inclusion during development [4]. This phenotype was initially discovered because multiple nonfusing inclusions were found to coexist in a single host cell, in contrast to infections with prototype strains, in which only a single inclusion eventually remains during development [5]. Almost all strains with the nonfusing phenotype carry mutations in the chlamydial incA gene, which encodes the inclusion membrane protein A (IncA), and these strains also lack IncA on the inclusion membrane, as has been demonstrated by immunofluorescence microscopy [4, 5].
This variant phenotype accounts for 2% of all clinical isolates recovered from patients in Seattle, and it is associated with infections characterized by a less-severe clinical course [5, 6]. Although an individual patient's immunogenetic background certainly affects the outcome of the infection, these data suggest that phenotypic variability and genotypic polymorphisms of the organism may also be important determinants of the consequences of infection. Variant strains that have a markedly altered growth rate may interact with host cells differently and contribute to the diverse outcomes of chlamydial infection. In the present study, we examined growth dynamics, mutations, and pathogenhost cell interactions of a naturally occurring variant of C. trachomatis with the nonfusing inclusion. We demonstrate that this variant strain grew dramatically more slowly than the prototype strain and that the host-cell transcriptional response was uniquely characterized by the induction of immune-related genes and the suppression of lipid biosynthesis genes.
MATERIALS AND METHODS
C. trachomatis strains and cell lines.
The experimental strain, D(s)5058, is a naturally occurring C. trachomatis variant that develops nonfusing inclusions and carries a mutation in incA [4, 5]. For the present study, we sequenced the complete incA open-reading frame in the variant strain and found a 1-bp deletion at position 45 that created frame shifting thereafter, in addition to 3 other point mutations (data not shown). The comparison strain is the sequenced prototype strain of the same serovar, D/uw-3/cx [7]. According to the results of immunofluorescence studies, D(s)5058 does not localize IncA to the inclusion membrane, whereas D/uw-3/cx does [5]. Both McCoy cells and HeLa 229 cells were used for testing the stability of the phenotype (nonfusing inclusions). Purified EBs from both strains were titered and aliquoted as described elsewhere [8, 9]. For host-cell response studies, HeLa cells were infected and cultured in 6-well plates as described elsewhere [8]. For mock infection, infectious EBs were inactivated by incubation for 20 min at 65°C. Inactivation was confirmed by the inability to detect inclusions from both 24 and 48 h after infection. The morphological characteristics of inclusions of both the experimental and comparison strains were verified by fluorescence microscopy, as described elsewhere [5].
RNA preparation.
After the aspiration of cell-culture medium, HeLa cells infected with either D(s)5058 or D/uw-3/cx were immediately lysed and homogenized at designated times after infection. RNAs were isolated by use of the RNeasy kit (Qiagen), in accordance with the manufacturer's instructions. The integrity of RNA preparations was assessed with the Bioanalyzer 2100 instrument (Agilent) before target preparation for microarray hybridization, as described elsewhere [8].
Real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR).
qRT-PCR was used to estimate relative copy numbers of C. trachomatis 16S rRNA. The human -glucuronidase transcript was used to control the number of host cells infected by C. trachomatis. The PCR primers for the 16S rRNA were adopted from a study by Mathews et al. [10]. RT was performed for 1 h at 42°C with 1 g of total RNAs and 1 g of random hexamer, 5 mmol/L dNTPs, 10 mmol/L dithiothreitol, 50 U of Rnasin (Promega), and 200 U of Superscript II in 20 L of 1× first-strand buffer (GIBCO). Five nanograms of the resulting cDNAs were used in the subsequent qRT-PCR in separate tubes that contained primers for either the chlamydial 16S rRNA with Sybr Green (Applied Biosystems) detection or for the human housekeeping gene -glucuronidase with a VIC TaqMan probe (Applied Biosystems). All samples and controls were run under the same conditions, except for the presence or absence of RT. All samples were run in triplicate on the ABI PRISM 7900HT Sequence Detection System (Applied Biosystems). Relative levels of C. trachomatis 16S rRNA transcription were determined on the basis of the Ct method and were calculated by 2-Ct ± SD. The predeveloped TaqMan Gene Expression Assays (Applied Biosystems) human gene primer/probe sets were used to verify the results of the microarray experiments. To increase specificity for the detection of single-stranded cDNA, each presynthesized human-gene primer set was paired with an oligonucleotide probe that had been labeled with 6FAM fluorescent dye (Applied Biosystems) at the 5 end as a reporter and minor groove-binding nonfluorescent molecules at the 3 end as a quencher. During amplification, the probe was cleaved by the 53 exonuclease activity of the Taq polymerase, which then allowed the measurement of fluorescence emission. The qRT-PCR assays were performed in triplicate.
Microarray, biotin-labeled cRNA target, and hybridization.
The GeneChip Human Genome U133A oligonucleotide microarray (Affymetrix), representing >22,000 well-characterized human genes, was used to measure host-gene transcriptional levels affected by C. trachomatis infection. To prepare biotinylated cRNA targets, 5 g of total RNA from HeLa cells infected with the variant, prototype, and inactivated strains were used in first-strand cDNA synthesis primed by a T7-linked oligo(dT) primer. After the second-strand synthesis was complete, an in vitro transcription (IVT) reaction was performed by use of biotinylated UTP and CTP and T7 RNA polymerase, in accordance with the manufacturer's protocol (Enzo Diagnostics). Biotinylated cRNAs (Affymetrix) were then processed further in accordance with the manufacturer's recommendations. RNA and cRNA quality was assessed by use of the Bioanalyzer 2100, as described elsewhere [8].
Assay quality assessment.
The amount and purity of total RNA and corresponding cRNA were determined by optical densities of 260 and 280 nm, respectively, by use of a UV spectrophotometer. The quality of each microarray experiment and overall chip performance were determined by visual inspection of the raw scanned data for artifacts, scratches, or bubbles, as well as of intensities of both internal and external controls. The internal controls used housekeeping genes that controlled the RT and IVT procedures in sample preparation. External controls used spiked external genes that were added before the hybridization procedure, which was indicative of whether the hybridization, washing and staining, scanning, and probe alignment had been performed properly.
Data analysis.
The raw data of probe cell intensity and set annotation were obtained by use of MAS (version 5.1) and GCOS (version 1.2) software (Affymetrix). Merging of data from biological repeats of microarray experiments into a single data set and further analysis were performed by use of the Resolver (Rosetta Inpharmatics) and Data Mining Tool (version 3.1; Affymetrix). The transcription level of a given gene was determined on the basis of hybridization signals from multiple probe pairs of perfect matches and mismatches, as detailed in the GeneChip Expression Analysis Technical Manual (Affymetrix). Gene-expression ratios between different experimental conditions that were 2-fold at the P < .001 significance level were initially selected as candidates for differentially transcribed genes. The P value was calculated under the assumption of a normal distribution of the logarithmically transformed expression ratios. Genes specifically induced or suppressed because of infection with the variant strain were finally determined by a dual-comparison algorithm that compared variant straininfected cells with both mock-infected and prototype straininfected cells.
RESULTS
To confirm that approximately equal numbers of host cells were initially infected with the prototype and variant strains, we measured quantities of the human GUS transcript (a constitutively expressed eukaryotic gene) present in total RNAs from either variant strain or prototype straininfected HeLa cells. GUS levels in both variant strain and prototype straininfected cells were virtually constant across all time points tested. In addition, dissociation curves demonstrated that the amplification of the target 16S rRNA was highly specific (data not shown).
Equalization of load of infection for the examination of host-cell responses.
Because the variant strain replicates at a significantly slower rate than the prototype strain, host-cell responses to the 2 infections would be biased by substantially different loads of infection if this were not equalized. We addressed this concern by matching relative chlamydial 16S rRNA levels at 24 h after infection with inoculations of differential MOIs. The prototype strain was inoculated onto 6 × 106 HeLa cells at MOIs of 0.125, 0.25, 0.5, 1, 2, and 4 in separate plates, whereas the variant strain was inoculated at an MOI of 10 onto the same number of cells. At 24 h after infection, the chlamydial 16S rRNA level of the prototype straininfected cells inoculated at an MOI of 0.25 closely matched that of the variant straininfected cells. RNAs extracted from these 2 cell sets were then further analyzed to compare host-cell responses to infections with the variant and prototype strains.
Host-cell transcriptional responses to the variant and prototype C. trachomatis strains.
Because the variant strain has both phenotypic and genotypic differences from the prototype strainincluding the morphological characteristics of inclusions, rate of multiplication, and mutations in incAwe hypothesized that there would be unique host-cell responses to infection by the variant strain. To perform a comprehensive survey of the host-cell responses, we used the microarray approach and investigated >22,000 human genes for transcriptional level after HeLa cells were infected with the variant strain. Host-cell transcriptional levels were assessed in 3 cell populations: variant straininfected cells, mock-infected cells, and prototype straininfected cells. To identify a unique group of host genes whose responses are both specific for C. trachomatis development and variant strain, we used a dual-comparison algorithm by which a specifically transcribed gene must be significantly (P < .001) differentially (expression ratio, 2) transcribed when variant straininfected cells are compared with both mock-infected cells and prototype straininfected cells. By this dual comparison, 59 cellular genes with unique National Center for Biotechnology Information nucleotide numbers were identified as differentially transcribed in the variant straininfected cells, including 34 induced and 25 suppressed genes (table 1). These differentially transcribed host-cell genes were then grouped on the basis of their biological functions as classified by the Gene Ontology Consortium [12].
Analysis demonstrated 2 prominent features in these 59 differentially transcribed cellular genes. First, 16 of 34 induced genes were host immune genes; most of these were related to host innate immunity. In contrast, there were no transcriptionally suppressed immune genes. Second, 8 of 25 suppressed genes were related to metabolism. In comparison, only 2 induced genes were related to metabolism. Importantly, 5 of 8 suppressed metabolic genes encoded enzymes for lipid metabolism, including components of fatty-acid synthase, squalene epoxidase, isopentenyl-diphosphate -isomerase, 3-hydroxy-3-methylglutarylcoenzyme A reductase, and lanosterol synthase. Both squalene epoxidase and lanosterol synthase are key enzymes in the last stage of cholesterol biosynthesis, in which squalene is converted to lanosterol (the immediate precursor of cholesterol). There were no induced genes involved in lipid metabolism. In addition, in the variant straininfected cells, more genes involved in cell growth and/or maintenance were suppressed than induced.
DISCUSSION
Genetic manipulation of the chlamydial genomes for the creation of isogenic mutants has been unsuccessful, despite many attempts [13]. Given this situation, the examination of well-characterized, naturally occurring variants may provide valuable insights into the pathogenesis of chlamydiae. The unique phenotype of the variant C. trachomatis strain used in the present study was identified in clinical isolates by the presence of multiple nonfusing inclusions within an infected host cell, in contrast to the single fused inclusion seen in prototype strains [5]. DNA sequencing has revealed multiple variations within the incA gene of the majority of C. trachomatis nonfusing strains that are generally associated with an absence of IncA in the inclusion membrane, as determined by immunostaining with antibody to IncA [4]. Epidemiologically, this phenotype has been associated with patients who manifest fewer clinical signs and symptoms, compared with patients infected with normal strains. Patients infected with nonfusing strains also had a significantly reduced bacterial load (as manifested by numbers of IFUs on culture), compared with patients infected with normal strains [6]. In light of these distinctive traits, we selected one variant strain to further examine its growth rate and its interaction with host cells in comparison with a prototype strain of the same serovar.
Our data on measurements of the relative chlamydial rRNA quantities in the multiplying organisms as a function of time have revealed that the variant strain grows dramatically more slowly than the prototype. From 24 through 48 h after infection, the bacterial 16S rRNA levels of the variant strain were only 3%4% of those of the prototype strain. This low level of rRNA indicates a reduced rate of bacterial protein synthesis and, thus, decreased multiplication efficiency. The slow growth may explain why nonfusing strains are more likely to cause infections with low bacterial loads, as well as with fewer signs and symptoms. The notion that a low level of chlamydial rRNA predicts a low number of bacteria was supported by experiments in which IFUs were measured. Yields of IFUs of the variant strain were 0.1%10% of those of the prototype when infections initiated at equal MOIs were compared. The sheer number of bacteria at the infection site is likely an important factor in determining the outcome of the infection. Host innate immune defenses may effectively keep a pathogen of low multiplicity in check, as opposed to a rapidly growing strain that overwhelms innate immunity before adaptive immune mechanisms can be activated. The nature and magnitude of these initial interactions between chlamydiae and epithelial cells may determine the direction of the subsequent adaptive immune responses as well [14].
We have demonstrated in the present study that the host-cell transcriptional response to the variant strain is marked by a specific subset of differentially transcribed genes. After equalizing bacterial load and the number of host cells infected, we compared cells infected with the variant strain to both heat-inactivated EB-infected cells and prototype straininfected cells. Remarkably, nearly one-half (16/34) of these up-regulated genes were related to immunity; many of them encode proteins related to the innate immune system, including several interferon-induced proteins, cytokines, cytokine receptors, and mediators of inflammation (table 1). These enhanced immune responses elicited by the variant strain may effectively impede the progress of the infection and result in immune-mediated resolution. Alternatively, such slow-growing strains associated with elevated local innate immune responses may result in increased pathogenicity [14].
Another prominent feature of the host-cell response to the nonfusing strain is the suppression of a group of lipid-metabolism genes. Host-cell lipid metabolism may effectively influence the accumulating chlamydial cell membranes and the inclusion membrane during chlamydial growth. Previous studies have demonstrated that eukaryotic glycerophospholipids, such as phosphatidylcholine and phosphatidylinositol, are transported to the chlamydiae and that the host-derived lipids are then modified by the organism. As a result of this modification, host-provided straight-chain fatty acids are substituted by chlamydia-synthesized branched-chain fatty acids [15, 16]. Host-provided sphingomyelin plays an essential role in the modification of the inclusion membrane to avoid the fusion of inclusions with lysosomes [3]. Furthermore, the down-regulation of 2 key enzymes (squalene epoxidase and lanosterol synthase) involved in the biosynthesis of cholesterol may contribute to the slow growth of the variant strain. A recent study has shown that C. trachomatis has cholesterol in both purified EB and inclusion membranes and that these cholesterols were synthesized by the host cell and transported to the bacteria through a Golgi-dependent pathway [17]. The interruption of host-cell cholesterol biosynthesis may retard the development of the inclusion membrane. The down-regulation of fatty-acid synthase and other lipid-metabolism genes may effectively limit the supply of eukaryotic lipids to the expanding inclusion membrane and cell membranes of chlamydia during development and may contribute to the slow growth of the variant strain.
In addition to genes in the above-mentioned functional groups, we also observed the induction of genes related to apoptosis (caspase 4) and to signal transduction (regulator of G-protein signaling 2 [RGS2] and P-GDP dissociation inhibitor ). Previous studies have shown that RGS2 is a multifunctional regulator of G proteinlinked signaling pathways that enhance cellular antiviral immunity [18] and that ARHGDIA mediates the negative regulation of cell adhesion through the suppression of signal transduction [19].
Although it is clear that there are major differences in growth dynamics and in the host-cell response to the nonfusing strain, compared with the prototype strain, many questions remain. First, whether these differences in host-cell responses are caused by mutations in incA or in other genes is uncertain, because the 2 comparison strains, although they belong to the same serovar, are not isogenic. Second, if slow growth often results in asymptomatic infections, whether the variant strains are more pathogenic in the long term in untreated chronic or persistent infections and subsequent sequelae is unknown. It is also not clear whether the slowly multiplying nonfuser strains respond to antimicrobials in the same manner as do fusing strains or whether they are more or less likely than fusing strains to be eradicated by the innate immune system.
Despite C. trachomatis biovars sharing a high degree of genomic nucleotide homology, different biovars have different tissue tropisms that may be determined by DNA polymorphisms in a number of chlamydial genes [2023]. These variations in gene polymorphism are likely reflected in altered host-cell responses. Our previous study showed that host cells respond to the lymphogranuloma venereum (LGV) biovar L2 strain by a transcriptional pattern different from that induced by the variant genital strain used in the present study [8]. In addition to differences in host-cell transcriptional responses, our preliminary data indicated that the LGV strain grows even faster than both the prototype D strain and the variant strain in the present study (data not shown). For the present, we are limited by available resources committed to examining only 2 isolates (the variant and the prototype); in future studies, we will examine a diverse group of chlamydial strains for growth and inclusion phenotypes.
Acknowledgments
We thank Dr. Kyle Serikawa, Aubree Hoover, and Mitsuhiro Tsuchiya (Center of Expression Array, School of Medicine, University of Washington) and Dr. Edward Kelly (Center for Sequencing and Gene Analysis, School of Pharmacy, University of Washington), for useful discussions and technical assistance.
References
1. Stamm WE. Chlamydia trachomatis infections: progress and problems. J Infect Dis 1999; 179(Suppl 2):S3803. First citation in article
2. Moulder JW. Interaction of chlamydiae and host cells in vitro. Microbiol Rev 1991; 55:14390. First citation in article
3. Hackstadt T, Fischer ER, Scidmore MA, Rockey DD, Heinzen RA. Origins and functions of the chlamydial inclusion. Trends Microbiol 1997; 5:28893. First citation in article
4. Rockey DD, Viratyosin W, Bannantine JP, Suchland RJ, Stamm WE. Diversity within inc genes of clinical Chlamydia trachomatis variant isolates that occupy non-fusogenic inclusions. Microbiology 2002; 148:2497505. First citation in article
5. Suchland RJ, Rockey DD, Bannantine JP, Stamm WE. Isolates of Chlamydia trachomatis that occupy nonfusogenic inclusions lack IncA, a protein localized to the inclusion membrane. Infect Immun 2000; 68:3607. First citation in article
6. Geisler WM, Suchland RJ, Rockey DD, Stamm WE. Epidemiology and clinical manifestations of unique Chlamydia trachomatis isolates that occupy nonfusogenic inclusions. J Infect Dis 2001; 184:87984. First citation in article
7. Stephens RS, Kalman S, Lammel C, et al. Genome sequence of an obligate intracellular pathogen of humans: Chlamydia trachomatis. Science 1998; 282:7549. First citation in article
8. Xia M, Bumgarner RE, Lampe MF, Stamm WE. Chlamydia trachomatis infection alters host cell transcription in diverse cellular pathways. J Infect Dis 2003; 187:42434. First citation in article
9. Caldwell HD, Kromhout J, Schachter J. Purification and partial characterization of the major outer membrane protein of Chlamydia trachomatis. Infect Immun 1981; 31:116176. First citation in article
10. Mathews SA, Volp KM, Timms P. Development of a quantitative gene expression assay for Chlamydia trachomatis identified temporal expression of factors. FEBS Lett 1999; 458:3548. First citation in article
11. Gourse RL, Gaal T, Bartlett MS, Appleman JA, Ross W. rRNA transcription and growth rate-dependent regulation of ribosome synthesis in Escherichia coli. Annu Rev Microbiol 1996; 50:64577. First citation in article
12. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 2000; 25:259. First citation in article
13. Stephens RS. Challenge of Chlamydia research. Infect Agents Dis 1992; 1:27993. First citation in article
14. Stephens RS. The cellular paradigm of chlamydial pathogenesis. Trends Microbiol 2003; 11:4451. First citation in article
15. Wylie JL, Hatch GM, McClarty G. Host cell phospholipids are trafficked to and then modified by Chlamydia trachomatis. J Bacteriol 1997; 179:723342. First citation in article
16. Hatch GM, McClarty G. Phospholipid composition of purified Chlamydia trachomatis mimics that of the eucaryotic host cell. Infect Immun 1998; 66:372735. First citation in article
17. Carabeo RA, Mead DJ, Hackstadt T. Golgi-dependent transport of cholesterol to the Chlamydia trachomatis inclusion. Proc Natl Acad Sci USA 2003; 100:67716. First citation in article
18. Kehrl JH, Sinnarajah S. RGS2: a multifunctional regulator of G-protein signaling. Int J Biochem Cell Biol 2002; 34:4328. First citation in article
19. Leffers H, Nielsen MS, Andersen AH, et al. Identification of two human Rho GDP dissociation inhibitor proteins whose overexpression leads to disruption of the actin cytoskeleton. Exp Cell Res 1993; 209:16574. First citation in article
20. Brunelle BW, Nicholson TL, Stephens RS. Microarray-based genomic surveying of gene polymorphisms in Chlamydia trachomatis. Genome Biol 2004; 5:R42. First citation in article
21. Carlson JH, Hughes S, Hogan D, et al. Polymorphisms in the Chlamydia trachomatis cytotoxin locus associated with ocular and genital isolates. Infect Immun 2004; 72:706372. First citation in article
22. Stothard DR, Toth GA, Batteiger BE. Polymorphic membrane protein H has evolved in parallel with the three disease-causing groups of Chlamydia trachomatis. Infect Immun 2003; 71:12008. First citation in article
23. Yuan Y, Zhang YX, Watkins NG, Caldwell HD. Nucleotide and deduced amino acid sequences for the four variable domains of the major outer membrane proteins of the 15 Chlamydia trachomatis serovars. Infect Immun 1989; 57:10409. First citation in article