Aug. 4, 2010 -- Researchers have identified nearly 100 gene variants linked to blood lipids, which they say could explain a quarter to a third of hereditary factors influencing cholesterol -- a major risk factor for heart disease.
In one of the largest gene mapping studies ever conducted, a global team of investigators scanned the genomes of more than 100,000 people from 17 countries in an effort to locate the genetic hotspots associated with high cholesterol and triglycerides.
Their efforts led to the identification of 59 new genetic variants, or mutations, which contribute to high LDL, or bad, cholesterol within families.
Focusing on one of these variants, a subgroup of researchers also identified a novel regulator of low-density lipoprotein (LDL), or bad, cholesterol, which could potentially lead to new treatments for high cholesterol and heart disease.
A researcher who led that study says the findings demonstrate the value of large-scale gene mapping studies.
Both studies appear in the Aug. 5 issue of the journal Nature.
“There has been some disappointment, especially in the lay press, that genome-wide association studies haven’t led to new therapies,” University of Pennsylvania School of Medicine professor of medicine Daniel J. Rader, MD, tells WebMD. “That is a little naive since we are really very early in the process.”
The first gene mapping studies were conducted just five years ago, and as recently as three years ago only a few gene variants associated with blood lipids had been identified, says Christopher O’Donnell, MD, of the NIH’s National Heart Lung and Blood Institute’s (NHLBI) Framingham Heart Study.
The NHLBI funded the larger cholesterol gene mapping study, along with other NIH agencies.
The goal of large, diverse genome-wide association studies (GWAS), as they are known in research circles, is to identify previously unknown common genetic factors that influence health and disease.
The more than 100,000 genomes scanned in the latest research included people of European, Eastern Asian, Southern Asian, and African-American descent participating in 46 separate heart studies across the globe.
In all, O’Connell and colleagues identified 95 gene variants associated with LDL and triglyceride levels, including 59 new ones. These variants were seen in men and women and in different ethnic groups.
Two of the identified regions are already targets of existing cholesterol drugs, but many others had not previously been associated with cholesterol.
O’Connell tells WebMD that as many as several hundred more gene variants that help regulate cholesterol and triglyceride levels may be identified in the near future.
“We are beginning to understand the biology of lipids in a way that we never did before,” he says. “And new approaches for sequencing genes should help us find less common, but potentially more powerful, hot spots.”
【关键词】 Genomic
Screening the Saccharomyces cerevisiae homozygous diploid deletion library against a sublethal concentration of cisplatin revealed 76 strains sensitive to the drug. As expected, the largest category of deletions, representing 40% of the sensitive strains, was composed of strains lacking genes involved in DNA replication and damage repair. Deletions lacking function of the highly conserved vacuolar H+ translocating ATPase (V-ATPase) composed the category representing the second largest number of sensitive strains. The effect on cell death exhibited by V-ATPase mutants was found to be a general response to various DNA damaging agents as opposed to being specific to cisplatin, as evidenced by sensitivity of the mutants to hydroxyurea (a DNA-alkylating agent) and UV irradiation. Loss of V-ATPase does not affect DNA repair, because double mutants defective for V-ATPase function and DNA repair pathways were more sensitive to cisplatin than the single mutants. V-ATPase mutants are more prone to DNA damage than wild-type cells, indicated by enhanced activation of the DNA damage checkpoint. Vacuole function per se is not cisplatin-sensitive, because vacuolar morphology and vacuolar acidification were unaffected by cisplatin in wild-type cells. V-ATPase also controls cytoplasmic pH, so the enhanced sensitivity to DNA damage may be associated with the drop in pHi associated with V-ATPase mutants. The increased loss in cell viability induced by cisplatin at lower pH in V-ATPase mutants supports this hypothesis. The loss in viability seen in wild-type cells under the same conditions was far less dramatic.
Cisplatin [cis-diamminedichloroplatinum(II)] is one of the most widely used anticancer drugs. Platinum-based chemotherapy cures most cases of advanced testicular cancer and has high efficacy in the treatment of other solid tumors, such as ovarian and small-cell lung cancers. The principal cytotoxic mechanism associated with cisplatin is the generation of platinum-DNA adducts, the most significant DNA lesions being 1,2-intrastrand cross-links that form across adjacent guanines (Wang and Lippard, 2005).
Unfortunately, acquired resistance to cisplatin can limit therapeutic potential (Perez, 1998). There are several resistance mechanisms, including decreased intracellular drug accumulation, enhanced cellular detoxification by glutathione and metallothionein, altered DNA repair, and inhibition of apoptosis (Perez, 1998; Huang et al., 2005). However, these mechanisms do not completely account for the observed in vivo unresponsiveness of certain tumors to cisplatin (Niedner et al., 2001; Schenk et al., 2003). Therefore, novel pathways mediating cisplatin resistance exist.
Use of model organisms, such as the yeast Saccharomyces cerevisiae, has been instrumental in revealing the molecular basis of cisplatin toxicity. Complex systems driving signal transduction, DNA repair, and the cell cycle are all highly conserved throughout the eukaryotic lineage. The range of mechanisms that can be probed using S. cerevisiae are those relating to maintenance of viability at the unicellular as opposed to the multicellular level. However, conclusions drawn from studies using these organisms are unambiguous because of the ability to disrupt expression of individual genes. Not surprisingly, these studies confirm the importance of DNA repair pathways including NER, RER, and PR (Grossmann et al., 2001; Beljanski et al., 2004; Wu et al., 2004). A significant advantage conferred by the use of S. cerevisiae genome-wide resources has been the identification of new genes not associated with DNA repair that mediate response to cisplatin. For example, elevated levels of phosphodiesterase 2 and the transcription factor Cin5 confer resistance to cisplatin (Burger et al., 2000; Furuchi et al., 2001). Cells lacking the serine/threonine kinase Sky1, the copper transporter Ctr1, and the nitrogen permease regulator Npr2, are also resistant to cisplatin (Ishida et al., 2002; Schenk et al., 2003, 2004). These strategies, exploiting gene overexpression from genomic libraries or transposon-mediated gene disruption, do not provide comprehensive coverage of the entire genome, because overexpression libraries rarely include all genes, and transposon insertion libraries do not disrupt genes in a random manner. Therefore, we screened the entire set of 4728 homozygous deletion strains, representing deletion of all nonessential open reading frames in S. cerevisiae, to identify genes that lead to sensitivity to cisplatin. A similar screen found 130 deletion strains that were sensitive to cisplatin (Wu et al., 2004). This screen, however, involved mixing all deletions followed by exposure to cisplatin and extraction of genomic DNA. Molecular barcodes identifying each deletion were amplified, and hybridized to an oligonucleotide array, enabling abundance of each deletion strain to be determined (Wu et al., 2004). Cisplatin itself is a potent DNA damaging agent. As a result, a DNA barcode associated with a strain that is sensitive to cisplatin might not be amplified, because it has sustained excessive damage. This would be the case in barcodes bearing consecutive guanines, given the nature of cisplatin-induced DNA damage. Lack of amplification is more likely in strains most sensitive to the drug. To avoid this problem, we individually assessed each deletion, as described previously in screens for strains sensitive to the DNA-alkylating agent methyl methanesulfonate and tirapazamine, a topoisomerase II inhibitor (Chang et al., 2002; Hellauer et al., 2005). Our approach was vindicated because we present identification of 49 cisplatin-sensitive deletions not identified by the screen involving amplification of molecular barcodes. Among the deletions novel to our screen were eight strains that each lacked a component of the highly conserved vacuolar H+ translocating ATPase (V-ATPase). Work in mammalian systems correlates V-ATPase activity with the response to cisplatin. Genes encoding subunits of the V-ATPase are induced when human cell lines are treated with cisplatin and are up-regulated in cisplatin-resistant cell lines (Murakami et al., 2001; Torigoe et al., 2002). Many genes are up-regulated in tumors, although not all of the corresponding proteins play a role in tumor progression. Our data suggest that correlation between V-ATPase function and cisplatin sensitivity underpins a key relationship between the enzyme and sensitivity to the drug. Furthermore, we showed that reduction in V-ATPase activity increased susceptibility to DNA damage per se, explaining why V-ATPase inhibitors render tumors more sensitive to DNA-damaging agents in general.
Yeast Strains and Media. The homozygous diploid deletion strains and individual haploid deletion strains were made by the Saccharomyces Gene Deletion Project (Winzeler et al., 1999). They were obtained from the European Saccharomyces cerevisiae Archive for Functional Analysis (Frankfurt, Germany). The parental diploid strain BY4743 was used as control in the screening of the deletion library for sensitivity to cisplatin. Strain BY4742 was used as the control for work using haploid strains. Genes encoding Vma6 or Vma8 subunits of V-ATPase were deleted in the BY4742 background using a Hygromycin B resistance gene as selectable marker, as described by Goldstein and McCusker (1999). Combinations of mutants in the same strain were constructed by standard procedures (Rose et al., 1990). The genotypes of strains used in this study are listed in Table 1. Yeast was grown in YPD (1% yeast extract, 2% peptone and 2% dextrose) prepared as described in Rose et al., 1990. Cisplatin, HU, and MMS were obtained from Sigma (St. Louis, Missouri). Cisplatin stock solutions were prepared in YPD or phosphate-buffered saline (PBS) and stored as aliquots at -20°C.
TABLE 1 S. cerevisiae strains used in this study.
Screen for Cisplatin-Sensitive Yeast Strains. We determined that the sublethal concentration of cisplatin required to result in visibly slower growth of the parental yeast diploid strain (BY4743) was 250 µg/ml. Deletion strains were maintained by growth as arrays of 384 colonies on solid YPD. All replications were automated and were carried out using a 384-pin replicator operated by a Biomek FX Laboratory Automation Workstation (Beckman Coulter, Fullerton, CA). Colonies were picked and resuspended in 50 µl of YPD in 384-well plates and incubated for 48 h at 30°C (to stationary phase). Each culture (5 µl) was transferred to fresh 50 µl of YPD in 384-well plates and grown to log-phase (14 h at 30°C with intermittent agitation). Replicas of these plates were made on solid YPD media with and without cisplatin (250 µg/ml), followed by incubation at 30°C. During incubation for 3 days, growth was scored by colony size compared with that of the wild-type strain BY4743 (as described in Hellauer et al., 2005). Mutants showing a significant growth defect or absence of growth after 1 day in the presence of 250 µg/ml cisplatin were scored as "x" or "xx." Mutants showing a significant growth defect or absence of growth after 3 days in the presence of 250 µg/ml cisplatin were scored as "xxx" or "xxxx."
Assessing Sensitivity or Viability of Individual Strains to Cisplatin. Cultures were grown in liquid YPD at 30°C to exponential phase and diluted to equal cell density. Six-fold serial dilutions were spotted across YPD, or YPD containing the concentration of cisplatin indicated in figure legends, followed by incubation at 30°C for 3 days. For viability assays, equal cell densities of exponential phase cultures were incubated in PBS, pH 7.4, containing the concentration of cisplatin indicated in figure legends; aliquots were removed after 1 h, diluted, and spread over YPD plates. Percentage viability was determined from the number of colonies that appeared after incubation for 3 days at 30°C, as a percentage of the number of colonies that appeared for each strain without cisplatin treatment.
Sensitivity to DNA Damaging Agents Other than Cisplatin. Cultures were grown at 30°C to exponential phase and diluted to equal cell density (1 x 107 cells/ml). Four successive 6-fold serial dilutions were spotted across YPD or YPD plus 20 mM hydroxyurea (HU) or 0.01% methyl methanesulfonate (MMS). For assessing sensitivity to UV irradiation, dilutions spotted across YPD were exposed to 40 J/m2 UV using a UV cross-linker (Syngene, Frederick, MD). All plates were subsequently incubated for 3 days at 30°C.
Vacuole Staining. FM4-64 was obtained from Invitrogen (Carlsbad, CA) and quinacrine from Sigma (St. Louis, MO). Staining with FM4-64 was performed as described by Conibear and Stevens (2002). FM4-64 was loaded into cells at 40 µM for 15 min followed with one wash to remove free dye and a chase period for 60 min at 30°C in YPD, or YPD with 100 µg/ml cisplatin. Cells were examined by confocal laser microscopy using Texas Red filters. Staining with 200 µM quinacrine (in the presence or absence of 100 µg/ml cisplatin) was performed as described by Roberts et al. (1991). Once stained, cells were visualized within 10 min by confocal laser microscopy using fluorescein filters.
Western Blot Analysis of Rad53. Exponential phase cultures grown at 30°C were incubated for 1 h in the presence of cisplatin at concentrations indicated in the figure legends. Yeast protein extracts were prepared from TCA-treated cells, and Rad53 was detected with a rabbit polyclonal antibody (Tercero et al., 2003).
Effect of pH on Cisplatin Sensitivity. Equal cell densities of exponential phase cells were incubated for 1 h at 30°C in PBS (pH 7.4 or 5.8) containing cisplatin, at the concentrations of drug indicated in figure legends, followed by dilution and inoculation over YPD plates. Percentage viability was determined from the number of colonies that appeared after incubation for 3 days at 30°C and expressed as a percentage of the number of colonies that appeared for each strain without cisplatin treatment.
Screen for Cisplatin-Sensitive Yeast Strains. Hypersensitive strains revealed by screening with a sublethal concentration of cisplatin would reveal the identities of genes that normally function in pathways sensitive to this drug. We performed a high-throughput robot-aided screen for sensitivity to 250 µg/ml cisplatin, using a collection of 4728 homozygous diploid yeast deletion mutants corresponding to nonessential yeast genes. Sensitive mutants were scored by comparison with colony size of the isogenic wild-type strain, after incubation for 1 day. The same colonies were scored again after a further 2-day incubation. Overall, 76 strains were sensitive to cisplatin (Table 2). The sensitivity of these mutants was confirmed by individually pinning serial dilutions of deletion strains on 250 µg/ml cisplatin and control plates.
TABLE 2 Cisplatin-sensitive deletion strains
Mutants showing a significant growth defect or absence of growth after 1 day in the presence of 250 µg/ml cisplatin scored as "x" or "x x." Mutants showing a significant growth defect or absence of growth after 3 days in the presence of 250 µg/ml cisplatin scored as "x x x" or "x x x x."
Four of the seventy-six strains, however, correspond to deleted open reading frames that overlap with other genes. These are the YLR235c, YGL167c, YOR331c, and YKL118w deletions, which overlap with TOP3, HUR1, VMA4, and VPH2, respectively. Two of the overlapped genes (TOP3 and HUR1) are involved in DNA repair. The other two are involved in V-ATPase structure and function. In each case, it is likely that the resistance is due to deletion of the overlapping gene (TOP3, HUR1, VMA4, and VPH2), given 1) the well established importance of DNA repair mechanisms in the processing of cisplatin-DNA adducts, and 2) the importance of V-ATPase activity in resistance to cisplatin, demonstrated in the work presented here and inferred through correlative studies by others (Murakami et al., 2001; Torigoe et al., 2002). The genes are presented in categories based on known or inferred function (Table 2).
Exposure to cisplatin leads to DNA damage, so it was not surprising to find that the largest category, representing 42% of the sensitive strains, was composed of 31 strains deleted for genes involved in DNA replication and damage repair. These fell mainly into the following categories of DNA repair: NER (six genes, including RAD1 and RAD2), RER (eight genes, including RAD51 and RAD52); replication-dependent repair (RR; eight genes, including MUS81 and POL32), and PR (three genes, including RAD18). Deletions of two DNA helicases (HPR5 and SGS1) and one topoisomerase (TOP3) were also sensitive. Twenty-three (of the 31 strains) were reported previously to be cisplatin-sensitive (Birrell et al., 2002; Wu et al., 2004); and seven were reported to be sensitive to tirapazamine, another anticancer drug that causes DNA damage (Hellauer et al., 2005). Deletion of genes in the following functional categories also gave rise to cisplatin sensitivity: cell cycle (10 genes: Table 2), cell stress, and signal transduction (YDJ1, PPH3, SOD1, ZUO1, SEP1, and HAL5), protein synthesis (EAP1, MRF1, RPL13B, RPL7A, and SRO9), transcription (RPB9 and HCM1), and two transporters (TPK1 and GUP1).
The category represented by the second largest number of cisplatin-sensitive deletions was composed of strains lacking function of the vacuolar H+ translocating ATPase (V-ATPase). The disruption of V-ATPase function is lethal in all eukaryotic organisms except S. cerevisiae (Graham et al., 2003). The lethality in higher systems is connected to aspects of V-ATPase function that are more significant in such organisms than they are in a unicellular organism like yeast, such as receptor-mediated endocytosis. Yeast has one hormone receptor, the action of which is nonessential; this is in contrast to various essential receptors in membranes of complex organisms (Graham et al., 2003). This made budding yeast an ideal system to further investigate the role of V-ATPase in cisplatin resistance. We present data to explain why such mutants show more sensitivity to cisplatin as well as other DNA-damaging agents.
V-ATPase Mutants Are Sensitive to Cisplatin. The V-ATPase is composed of thirteen subunits (Graham et al., 2003). Loss of any one of eight V-ATPase subunits led to cisplatin sensitivity (Table 2). Four strains lacked a component of the catalytic (V1) domain responsible for ATP hydrolysis, and the other four lacked a component of the proton translocating (Vo) domain. In addition, deletion of VPS33, a gene required for assembly of V-ATPase (though itself not a part of the enzyme) also led to cisplatin sensitivity. To confirm these results, we generated two strains, one lacking a component of the Vo domain (vma6, Table 1), the other lacking a component of the V1 domain (vma8, Table 1). As expected, both vma6 and vma8 strains exhibited severely impaired growth in the presence of cisplatin compared with growth on media without the drug (Fig. 1A). In a cell survival assay, rapid loss of viability was exhibited by these mutants in the presence of cisplatin (Fig. 1B).
Fig. 1. Sensitivity of the V-ATPase mutants to cisplatin. A, wild-type and V-ATPase mutants were grown at 30°C to exponential phase and diluted to equal cell density. Six-fold serial dilutions were spotted across YPD or YPD containing 150 µg/ml cisplatin; plates were incubated at 30°C for 3 days. B, exponential phase wild-type and V-ATPase mutants diluted to equal cell density were incubated in PBS, pH 7.4, containing cisplatin at the concentration indicated; aliquots were removed after 1 h, diluted, and spread over YPD plates. Viability was determined from the number of colonies that appeared after incubation at 30°C for 3 days-as a percentage of the number of colonies that appeared for each strain without cisplatin treatment.
Vacuolar Morphology and Acidity Are Not Disrupted by Cisplatin. The vacuole of budding yeast is required for protein turnover, nutrient recycling, osmoregulation, storage of amino acids and inorganic phosphate, and maintenance of cytoplasmic pH (Graham et al., 2003). The vacuole (or an aspect of vacuolar function) may be a target of cisplatin, in that loss of V-ATPase function rendered cells hypersensitive to the drug. To investigate this possibility, we assessed the effect of cisplatin on vacuole morphology and vacuole acidification. In general, one to five vacuoles can be visualized in wild-type cells when stained with the fluorescent dye FM4-64 (Conibear and Stevens, 2002). Many mutants defective for vacuole function exhibit aberrant morphology of the vacuole itself (Raymond et al., 1992). Cisplatin at 100 µg/ml had no effect on the viability of wild-type cells but clearly led to loss of viability in the vma6 strain (Fig. 1B). However, under these conditions, vacuole morphology was unaltered in either strain, appearing normal in size, shape, and number (Fig. 2A). Even though cisplatin does not affect vacuolar morphology, it could disrupt vacuole acidification. The lumen of the vacuole is more acidic than the surrounding cytoplasm, so the resulting luminal pH drives numerous vacuole-associated processes (Graham et al., 2003). Cells were stained with quinacrine, a fluorescent weak base that accumulates only in the vacuolar lumen upon acidification (Roberts et al., 1991). Intensity of fluorescence is directly proportional to the degree of vacuolar acidification. Wild-type cells treated with up to 200 µg/ml cisplatin accumulate the same amount of quinacrine as cells incubated without the drug (Fig. 2B). As expected, vma6 cells could not be stained with quinacrine because of the failure of V-ATPase-mediated vacuolar acidity (Fig. 2B). These data indicate that vacuoles in wild-type cells are acidified and morphologically normal in cells treated with cisplatin, suggesting that the vacuole per se is not the target of cisplatin.
Fig. 2. Vacuolar morphology and acidity are not disrupted by cisplatin. Wild-type and V-ATPase mutants were grown at 30°C to exponential phase and diluted to equal cell density, followed by incubation with cisplatin at the concentration indicated. Cells were stained with FM4-64 for visualization of vacuolar morphology (A) or quinacrine for assessing the acidity of the vacuole (B).
Fig. 3. Sensitivity of V-ATPase mutants to various DNA damaging agents. Wild-type and V-ATPase mutants were grown at 30°C to exponential phase and diluted to equal cell density. Six-fold serial dilutions were spotted across YPD, YPD containing 20 mM HU or 0.01% MMS, or YPD followed by exposure to 40 J/m2 UV; plates were incubated at 30°C for 3 days.
V-ATPase Mutants Are Hypersensitive to Other DNA-Damaging Agents. Cisplatin hypersensitivity in V-ATPase mutants could be due to increased levels of DNA damage, or may diminish the effectiveness of DNA repair mechanisms. We assessed the response of V-ATPase mutants to various DNA-damaging agents. MMS is a DNA-alkylating agent, and HU is a DNA replication inhibitor, giving rise to stalled replication forks that are sensed by the cell as abnormal DNA structures (Tercero et al., 2003). vma6 and vma8 strains are both hypersensitive to each agent (Fig. 3). The vacuole itself can act as a detoxification mechanism by accumulation of small molecules via the endocytic machinery. The vma6 and vma8 strains, however, are both also hypersensitive to UV irradiation compared with the wild type (Fig. 3). Therefore, it is likely that the increased sensitivity to cisplatin, HU, and MMS exhibited by V-ATPase mutants is not due to a defect in a mechanism that involves vacuolar sequestration of these cytotoxic agents. Instead, DNA could be more prone to damage in these cells or repair mechanisms may be less efficient.
Assessing Sensitivity of V-ATPase/DNA Repair Double Mutants to Cisplatin. The cisplatin-induced DNA cross-linked adducts in S. cerevisiae are repaired mainly by three DNA repair mechanisms: the NER, RER, and PR pathways. To determine the possibility that loss of V-ATPase would diminish the effectiveness of these repair pathways, we performed epistasis analysis using V-ATPase/DNA repair double mutants. RAD1, encoding a single-stranded DNA endonuclease, is a classic NER gene. REV3 encodes a subunit of DNA polymerase zeta, which is involved in PR. RAD52 encodes a protein that stimulates strand exchange during RER. Double mutants were constructed that were defective for V-ATPase function and one DNA repair pathway. All three double mutants (vma6rad1, vma6rev3, and vma6rad52) were more sensitive to cisplatin than the single mutants (Fig. 4). This suggests that involvement of V-ATPase with DNA damage sensitivity is independent of DNA repair pathways. Instead, V-ATPase mutants could be more sensitive to cisplatin simply because more damage is caused by a given concentration of drug.
Fig. 4. Sensitivity of [V-ATPase/DNA repair] double mutants to cisplatin. Exponential phase wild type and single and double mutants were diluted to equal cell density and incubated in PBS, pH 7.4, containing cisplatin at the concentration indicated; aliquots were removed after 1 h, diluted, and spread over YPD plates. Viability was determined from the number of colonies that appeared after incubation at 30°C for 3 days and expressed as a percentage of the number of colonies that appeared for each strain without cisplatin treatment.
Activation of the DNA Damage Checkpoint in V-ATPase Mutants. When yeast cells are treated with cisplatin, the DNA damage checkpoint is activated, leading to cell cycle arrest at G2/M. Mutants in components of the checkpoint display increased sensitivity to cisplatin (Grossmann et al., 1999). The sensitivity to cisplatin exhibited by strains lacking the S-phase checkpoint protein MRC1 is in agreement with this (Table 2). Rad53, the effector protein kinase in this pathway, is activated via hyperphosphorylation in response to DNA damage (Tercero et al., 2003). Phosphorylated Rad53 is detected as a smear of slowly migrating forms of the protein on Western blots immunoprobed with anti-Rad53 antisera. We incubated cells in the presence of various concentrations of cisplatin for 1 h. The incubation of both wild-type and vma6 cells with 200 µg/ml cisplatin led to the appearance of hyperphosphorylated forms of Rad53, suggesting that lack of V-ATPase activity did not impair the DNA damage checkpoint pathway (Fig. 5). A single band that indicated the nonphosphorylated form of Rad53 was detected in the absence of the drug, in both wild-type and vma6 cells (Fig. 5). In vma6 cells, however, hyperphosphorylated Rad53 was detected on incubation with 50 µg/ml cisplatin. In contrast, hyperphosphorylated Rad53 was barely detectable in wild-type cells treated in the same way, suggesting that V-ATPase mutants suffered more DNA damage than the wild-type cells.
Fig. 5. Phosphorylation of the Rad53 checkpoint effector kinase. Wild-type or V-ATPase mutant cells were grown to early log phase at 30°C and then incubated for 1 h with cisplatin at the concentration indicated. Rad53 was visualized by probing Western blots with anti-Rad53 antibody. The positions of unphosphorylated Rad53 and phosphorylated Rad53 (Rad53-p) are shown on the right.
Effect of pH on Cisplatin Sensitivity. One of the major functions of V-ATPase is maintenance of intracellular pH by translocating protons from the cytosol into the lumen of the vacuole (Graham et al., 2003). In both unicellular and multicellular organisms, cytoplasmic pH is reduced when function of the V-ATPase is compromised (Moreno et al., 1998; Murakami et al., 2001). The increased DNA damage sensitivity in the V-ATPase mutants could be due to the acidified cytoplasm. To investigate the effect of pH on cisplatin sensitivity, we followed viability of cells after incubation with cisplatin in neutral (pH 7.4) or acidic (pH 5.8) conditions. Wild-type yeast cells are efficient at maintaining a constant intracellular pH, even when they are incubated in media buffered to varying pH. This is due principally to the action of a plasma membrane H+-translocating ATPase. This enzyme pumps H+ out of the cell, consuming up to 40% of total cellular ATP. To remove the possibility that action of this enzyme would compensate for the effect of incubating cells at varying pH, we incubated cells in the absence of a carbon source so that cells could not make ATP to drive H+ extrusion by PM ATPase. Intracellular pH of S. cerevisiae incubated under these conditions closely approaches the pH of the extracellular medium, with intracellular pH changes being due to H+ leakage across the plasma membrane (Brett et al., 2005).
Both wild-type and vma6 cells were more sensitive to cisplatin when incubated at lower pH. The effect of low pH, however, was more dramatic in vma6 cells (Fig. 6). In the presence of 20 µg/ml cisplatin, the viability of vma6 cells at pH 5.8 was decreased by 76% (by 24.% at neutral pH), whereas the viability of the wild-type cells at pH 5.8 was decreased by 25% (by 10% at neutral pH). This implies that lower cytoplasmic pH increases sensitivity to DNA damage in V-ATPase mutants.
Fig. 6. Effect of pH on cisplatin sensitivity. Exponential phase cultures diluted to equal cell density were incubated in PBS, pH 7.4 or 5.8, with cisplatin at the concentration indicated; aliquots were removed after 1 h, diluted, and spread over YPD plates. Percentage viability was determined from the number of colonies that appeared after incubation at 25°C for 3 days, expressed as a percentage of the number of colonies that appeared for each strain without cisplatin treatment.
Pathways that modulate cisplatin sensitivity could be induced in tumor cells, and development of agents to inhibit these pathways can overcome the resistance that emerges frequently during treatment. Development of new platinum drugs by substitution of ligands or chloride, leaving groups of cisplatin has not been successful in terms of overcoming drug resistance. New approaches can be developed based on discovery of mechanisms that mediate toxicity of this drug.
The budding yeast S. cerevisiae has been used as a powerful tool to identify and investigate pathways targeted by drugs. In the present study, we have applied a systematic approach to search for the nonessential genes in yeast that play a role in the response to cisplatin, leading to the identification of 76 deletion strains sensitive to this drug.
More than 40% of the cisplatin-sensitive strains lacked various components involved in DNA damage repair. The deleted genes were mainly involved in three DNA repair pathways: RR and PR, RER, and NER. However, none of the components involved in base excision repair or mismatch repair were identified in this screen, suggesting that PR, RR, and NER are the main mechanisms by which cells repair cisplatin-induced DNA damage, whereas base excision repair and mismatch repair are not involved. This is in agreement with previous studies (Grossmann et al., 2001; Beljanski et al., 2004; Wu et al., 2004).
A novel insight from our screen is that sister chromatid cohesion plays a role in the response to cisplatin. Dcc1, Ctf8, and Ctf18 are components of a complex required for establishment of sister chromatid cohesion. Cells lacking the genes encoding any of these three proteins are sensitive to cisplatin. Cells lacking another gene involved in cohesion (Ctf4) are affected in the same way. Recruitment of the cohesin complex to sites of DNA damage is necessary for recombination-mediated repair of double-strand breaks (Strom et al., 2004). Therefore, it is likely that the Dcc1/Ctf8/Ctf18 complex and Ctf4 facilitate RER of cisplatin-induced DNA damage. In addition, two mutants (asf1 and mrc1), known to impair the Rad53-dependent DNA damage checkpoint pathway, were sensitive to cisplatin. This is in agreement with work showing that cisplatin causes a checkpoint-dependent G2/M arrest (Grossmann et al., 1999). To support this notion, we showed that cisplatin resulted in hyperphosphorylation of Rad53, indicating the activation of this checkpoint pathway (Fig. 5).
Several mutants that compromised cell stress tolerance and signal transduction were sensitive to cisplatin. In mammalian cells, the oxidative and osmolar stress responses protect cells from cisplatin-induced nephrotoxicity (Hanigan et al., 2005). In addition, genes involved with ribosomal function and protein synthesis were identified as cisplatin-resistant genes. In agreement with this are reports describing cisplatin-induced disruption of the translation initiation complex and overexpression of a ribosomal protein conferring resistance to cisplatin (Rosenberg and Sato, 1993; Shen et al., 2006).
It is noteworthy that a group of nine genes encoding V-ATPase subunits and an assembly factor for this enzyme were identified as cisplatin-hypersensitive strains. It is not surprising that so many genes involved in V-ATPase function were identified, given that loss of any V-ATPase subunit or assembly factor is known to result in loss of V-ATPase activity (Graham et al., 2003). In yeast, this enzyme is localized to the membrane of the vacuole, with a smaller population of V-ATPase complexes localized to the endosomal network. In mammalian cells, the enzyme is similarly localized to the lysosome (equivalent to the yeast vacuole) and endocytic compartments. In addition, the enzyme is localized to the membranes of specialized cells, notably the brush-border membranes of renal proximal tubules (Stevens and Forgac, 1997). In mammalian cells, one of the V-ATPase subunits is induced by cisplatin (Torigoe et al., 2002). Furthermore, several genes encoding V-ATPase subunits are up-regulated in drug-resistant tumor cell lines (Martinez-Zaguilan et al., 1999; Murakami et al., 2001). This increase in levels of V-ATPase in cisplatin-resistant cells is correlative, and could be a consequence of drug treatment rather than a cause of resistance. The data we present, however, points toward V-ATPase activity directly contributing to drug tolerance.
V-ATPase translocates H+ from the cytoplasm to the vacuole. Two consequences of this are regulation of cytoplasmic pH and acidification of the vacuole; the latter is crucial for maintenance of processes associated with the vacuole lumen. We showed that cisplatin did not affect the morphology of vacuoles in wild-type cells or a V-ATPase mutant. Furthermore, acidification of vacuoles in wild-type cells was also unaffected. This implied that sensitivity to cisplatin exhibited by V-ATPase mutants was associated with an effect on processes outside the vacuole, such as DNA repair, or the extent to which cisplatin damages DNA in the first place. V-ATPase mutants were also sensitive to the DNA-alkylating agent MMS, the DNA replication inhibitor HU, and UV irradiation. This suggested that the activity of the V-ATPase was required for limiting the effects of DNA damaging agents in general. This concept is supported by a recent report describing the sensitivity of yeast V-ATPase mutants to tirapazamine, an anticancer drug that targets topoisomerase II (Hellauer et al., 2005).
V-ATPase mutants may be defective in DNA damage repair mechanisms or may lead to enhanced DNA damage. PR, RR, and NER are the mechanisms that repair damage induced by cisplatin. Epistasis analysis ruled out the possibility that a defect in V-ATPase diminished the effect of repair pathways, because [V-ATPase/repair pathway] double mutants were far more sensitive to cisplatin than the single mutants (Fig. 4). Activation of the DNA damage checkpoint by low concentrations of cisplatin was enhanced in V-ATPase mutants. This suggested that loss of the V-ATPase function facilitates the DNA damage caused by cisplatin.
V-ATPase is a regulator of cytoplasmic pH. Consequently, loss of V-ATPase activity leads to intracellular acidification, which may lead to greater levels of cisplatin-mediated DNA damage. At lower pH, a greater proportion of hydrolyzed cisplatin has an aqua ligand, rather than a hydroxoligand. This enhances the reactivity of cisplatin because the aquated form is more labile. Chemical activity of cisplatin in vitro is greater at lower pH, promoting DNA platination (Murakami et al., 2001). The increased sensitivity to cisplatin in a V-ATPase mutant incubated at lower pH supports this hypothesis. At 50 µg/ml cisplatin, it is notable that cell viability of the wild type in pH 5.8 buffer, is similar to cell viability of vma6 at pH 7.4. This may well reflect a similar intracellular pH in these cells.
The role played by lower pH, however, must be more complex than straightforward increases in chemical reactivity of drugs, because V-ATPase mutants were also hypersensitive to UV irradiation. Low pH can change DNA conformation (Robinson et al., 1992). Therefore, sensitivity to DNA damaging drugs or UV irradiation in V-ATPase mutants may be associated with altered DNA conformation at low cytosolic pH, rendering DNA more prone to damage. This may explain why use of V-ATPase inhibitors in human cell lines renders them more sensitive to cisplatin (Laurencot et al., 1995; Murakami et al., 2001; Luciani et al., 2004).
In mammalian cells, cellular acidosis is an early event in apoptosis. Limiting the drop in cytoplasmic pH represses apoptosis, this being frequently associated with an up-regulation of V-ATPase subunits in tumors (Torigoe et al., 2002; Izumi et al., 2003). Accordingly, enhanced cell death in yeast V-ATPase mutants incubated with cisplatin could be due, in part, to activation of apoptosis caused by lowering of intracellular pH. Some controversy does surround the concept of yeast apoptosis. However, yeast demonstrates several markers typical of apoptosis including DNA fragmentation, phosphatidylserine externalization, chromatin condensation, and histone H2B phosphorylation (Madeo et al., 2004; Ahn et al., 2006). Furthermore, a growing list of genes that regulate apoptosis in mammalian cells have been identified in yeast, including the Yca1 caspase and the apoptosis-inducing factor Aif1 (Madeo et al., 2004).
We also demonstrated that loss of four genes associated with ribosome function and protein synthesis rendered cells sensitive to cisplatin. Accordingly, we predict that enhancing protein synthesis would confer drug resistance. This is in agreement with recent work involving use of a human epidermoid carcinoma cell line that showed cisplatin resistance is induced by overexpression of the ribosomal protein gene RPL36 (Shen et al., 2006). Another study revealed that inactivation of the Sky1 kinase in S. cerevisiae leads to cisplatin resistance. Monitoring levels of the orthologous protein in testicular tumors revealed that expression of the kinase in cisplatin resistant cells are lower than in tumors from patients who were responding to platinum drug-based therapy, so levels of the protein could predict the response to the drug (Schenk et al., 2004). Such work clearly demonstrates that conclusions drawn from use of the S. cerevisiae model system are of direct relevance to mammalian systems. This indicates that other genes identified in our screen are worthy of further investigation, because they may be important for predicting the responsiveness of tumors to cisplatin.
Acknowledgements
We thank Drs. Mehdi Mollapour and Nicholas L. Harris (University of Sheffield, Sheffield, UK) for assistance with rearraying the genomic library from 96 to 384 colony format, and we thank Professor Peter W. Piper (University of Sheffield) for allowing access to robotic facilities used for the re-arraying procedure. We are grateful to Dr. John F. X. Diffley (Cancer Research UK, Clare Hall, UK) for providing antisera against Rad53. We also thank Dr. Katherine E. Bowers (University College London, London, UK) for advice pertaining to work with V-ATPase mutants.
ABBREVIATIONS: NER, nucleotide excision repair; RER, recombination dependent repair; PR, postreplication repair; RR, replication-dependent repair; V-ATPase, vacuolar H+-transporting ATPase; YPD, yeast extract/peptone/dextrose; PBS, phosphate-buffered saline; HU, hydroxyurea; MMS, methyl methanesulfonate.
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作者单位：Pharmaceutical Science Research Division (C.L., B.H., B.P.) and Genomics Facility (M.J.A.), School of Biomedical and Health Sciences, King's College London, London, United Kingdom
1 From the Interdepartmental Nutrition Program and Department of Foods and Nutrition, Purdue University, West Lafayette, IN.
2 Presented at the conference "Vitamin D and Health in the 21st Century: Bone and Beyond," held in Bethesda, MD, October 9–10, 2003. 3 Supported by a grant from the NIH (grant DK54111). 4 Address correspondence to JC Fleet, 700 West State Street, Purdue University, West Lafayette, IN 47907-2059. E-mail: fleetj{at}cfs.purdue.edu.
ABSTRACT
Although we have learned a great deal about vitamin D metabolism and function since it first became apparent that this factor was required for bone health, there are still many gaps in our understanding, at both the basic science (eg, the molecular actions and targets of vitamin D) and applied (eg, what "adequate" vitamin D status means) levels. For example, although the identification of extrarenal 1-hydroxylase activity suggests that autocrine/paracrine actions of 1,25-dihydroxyvitamin D complement the classic endocrine actions of the hormone, the practical implications of this finding are only now being explored. In addition, studies showed that 1,25-dihydroxyvitamin D rapidly activates signal transduction pathways in addition to the classic transcriptional activation pathways that require the vitamin D receptor. These new modes of vitamin D action may be crucial to our understanding of both the traditional calcium-regulating actions of vitamin D and the anticancer actions of this essential mediator. Recent developments in genomics and proteomics have provided new opportunities for us to identify molecular targets of vitamin D action. Cancer researchers have demonstrated that these methods have utility for identifying useful biomarkers of disease states. Can these approaches be used to help clarify what constitutes optimal serum concentrations of 25-hydroxyvitamin D? I present an overview of how proteomic and genomic evaluations of cells, animals, and human subjects have been and can be used to improve our understanding of vitamin D biological processes and the role of vitamin D in health.
Key Words: Proteomics • genomics • biomarker
INTRODUCTION
Traditionally, vitamin D metabolism has been viewed as an endocrine system that responds to changes in serum calcium concentrations (1). Low dietary calcium intake is reflected by a decrease in serum calcium concentrations, which is in turn a signal for the increased production and release of parathyroid hormone (PTH). Among its functions, PTH stimulates renal 1-hydroxylase activity, leading to increased conversion of 25-hydroxyvitamin D3 [25(OH)D3] to 1,25-dihydroxyvitamin D3 [1,25(OH)2D3]. Elevated serum 1,25(OH)2D3 concentrations then stimulate the expression of vitamin D-responsive genes within the primary target tissues that control calcium homeostasis (ie, TRPV6 and calbindin D9k in intestine, osteocalcin and RANKL in bone, and TRPV5 and calbindin D28k in kidney) through activation of the vitamin D receptor (VDR). Although this system is clearly functional and biologically important during periods of calcium stress, it may not be sufficient to explain all of the biological actions of vitamin D.
As several recent reports and other reviews in this conference demonstrated, improved bone health and cancer chemoprevention may be more closely related to changes in serum 25(OH)D3 concentrations than to serum 1,25(OH)2D3 concentrations. For example, increases in serum 25(OH)D3 concentrations were associated with both maximal suppression of PTH (a proresorptive agent) (2–4) and increased efficiency of calcium absorption (5–8). There is also evidence that regular, high-dose, vitamin D supplementation decreased factures rates for common osteoporotic sites (9). This finding and other data suggest that local production of 1,25(OH)2D3, rather than endocrine signaling attributable to renal production, is critical for optimal bone health and cancer prevention (10–12). In addition, as we have come to understand more about the details of the molecular mechanisms controlling VDR function (13, 14), researchers have identified 1,25(OH)2D3 as an activator of various signal transduction pathways leading to the stimulation of protein kinases such as Src kinase, protein kinase C, protein kinase A, and the mitogen-activated protein kinases (15). These examples suggest that strict adherence to the accepted concepts of vitamin D biological mechanisms and actions are not likely to explain fully the health benefits of vitamin D.
In light of these and other recent findings, I contend that the field of vitamin D research would be well served by the use of several new technologies in an attempt to better describe the full range of vitamin D actions. The advances in technologies that permit whole-transcriptome analysis and large-scale proteomic analysis permit us to conduct unbiased evaluations of physiologic states and responses to treatments and interventions. In this review, I briefly demonstrate several instances in which genomic or proteomic analysis has expanded our understanding of vitamin D actions, I present a paradigm for future discovery-based research, and I demonstrate how these and other tools might be used to better define optimal vitamin D status.
GENOMIC AND PROTEOMIC APPROACHES: WHAT DO THEY OFFER TO THE FIELD OF VITAMIN D RESEARCH?
General approach
In the past decade, advances in the areas of genomics and proteomics created a revolution in science. These approaches are reviewed in detail elsewhere (16, 17) but are summarized briefly in Figure 1. Our traditional approach to understanding biological processes has been reductionist. We look for proteins that modulate functions of cells and tissues, and we study the regulation of their production and activity. There is no question that this approach has been very fruitful and will continue to be so. However, while this approach focuses our attention on testable hypotheses, it also provides virtual blinders, ie, we look only for the things we have already been studying. Moving beyond this approach can lead to dramatic advances in our understanding of scientific areas. For example, studies of the known proteins involved in iron metabolism failed to identify the cause of the iron-overload disease hemochromatosis. Only after the gene that is mutated in hemochromatosis was identified through a large-scale sequencing effort (genomics) did researchers find that the mutated gene encoded a protein with features similar to the major histocompatibility complex proteins, rather than a protein that was previously thought to be involved in iron metabolism (18). Similarly, studies have revealed that bone mass and metabolism can be regulated by genes that we would classically associate with obesity, such as leptin (19) and LDL receptor-related protein 5 (20). "Omic" approaches give us the opportunity to see beyond our expectations and discover new gene targets for vitamin D actions and functions.
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FIGURE 1.. Comparison of reductionist and genomic/globalist approaches to elucidating biological processes.
Studies identifying potential, new, vitamin D-regulated targets with genomics
Several transcript-profiling studies with microarrays have been conducted to elucidate the biological role of 1,25(OH)2D3. Because of the high cost of microarray-based gene expression profiling, most of the studies reported in the literature used very restricted conditions [eg, a single dose and time of treatment with 1,25(OH)2D3] and did not include replicates. This limits the utility of the approach and decreases our confidence in the results. However, more carefully controlled experiments were conducted and addressed some of the experimental design points noted in Figure 2. Figure 2A demonstrates that, depending on the time point examined after 1,25(OH)2D3 treatment and the time course of primary responses to the treatment, the changes in transcript levels could include both primary responses (eg, those resulting from direct, VDR-mediated interactions with gene promoters) and downstream responses that are indirect. Detection of a change in expression does not prove that a gene is a direct vitamin D target gene.
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FIGURE 2.. Experimental issues relevant to the use of genomic approaches to study vitamin D biological processes. A: Temporal relationship between vitamin D treatment and the molecular response at the level of the cell. B: Use of multiple independent perturbations to confirm the molecular actions of vitamin D. 1 OHase, 1-hydroxylase.
This phenomenon of differential patterns of responses to vitamin D is evident in the work of Lin et al (21). Those authors examined the time course of the response to 100 nmol/L 1,25(OH)2D3 or the vitamin D analog EB1089 in squamous cell carcinoma cells (SCC25) and identified 152 genes as being regulated by vitamin D (89 up and 63 down), with the use of the Affymetrix FL array (Affymetrix, Santa Clara, CA) and a 2.5-fold cutoff for determining a meaningful change in expression. Clustering was performed on the basis of the pattern of expression or the functional classification of the transcripts. Figure 3 shows the diversity of the vitamin D responses in these cells. Even within the genes with documented, functional, vitamin D response elements (VDREs) in their promoters, there was heterogeneity in responses. For example, the CYP24 transcript levels were rapidly increased by vitamin D treatment (significantly increased in 1 h), whereas osteopontin transcript levels increased more slowly in response to treatment (maximal expression at 12 h). This suggests that similar VDREs are differentially regulated, depending on the promoter context (22), but it also demonstrates the difficulty of discerning a direct transcriptional response solely on the basis of a time course, ie, even later responses can be attributable to direct effects. Another interesting finding from that study was that the vitamin D-induced responses in the transcript profile were much more diverse than might have been predicted previously. For example, several transcripts coding for proteins involved in protection from oxidative stress were gradually up-regulated by the vitamin D analog, including glucose-6-phosphate dehydrogenase (generating NADPH), glutathione peroxidase, and selenoprotein P. In addition, the thioredoxin reductase transcript was increased by 1 h after treatment, with peak induction by 6 h. Rapid suppression of transcripts for a variety of signaling peptides (eg, PTH-related protein and galanin) and induction of intracellular cell signaling proteins (eg, Cox-2, phosphoinositide-3-kinase, and p85 subunit) were also observed after treatment. It is not clear which of these responses is primary; none of these genes was previously shown to be regulated by vitamin D or to contain a functional VDRE. However, because 1,25(OH)2D3 promotes cellular differentiation, the up-regulation of some transcripts may represent a vitamin D-induced shift to a more differentiated phenotype. In any case, these data suggest that the traditional approach of examining only the expression of genes controlling cell cycle proteins in an attempt to explain the prodifferentiating action of vitamin D may provide limited information regarding the biological mechanisms of 1,25(OH)2D3 actions in proliferating or cancer cells.
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FIGURE 3.. Summary of patterns observed in response to treatment of squamous carcinoma cells with calcitriol or the vitamin D analog EB1089. The symbols represent the 10 distinct groups of up-regulated (5 groups) (black symbols) and down-regulated (5 groups) (white symbols) transcripts. These data demonstrate that there is considerable diversity in the temporal response of transcripts to vitamin D treatment. Adapted from Lin et al (21).
To identify direct vitamin D actions, scientists often conduct multiple complementary experiments and compare the results for consistency. In Figure 2B, 3 complementary mouse experiments are illustrated. Treatment of normal mice with 1,25(OH)2D3 would be expected to up-regulate or down-regulate specific genes in a target tissue, whereas the examination of target tissue transcript profiles in mice that lack essential components of the vitamin D signaling system (eg, VDR or 1-hydroxylase) would be expected to demonstrate opposite effects on vitamin D target genes [eg, a gene that is activated with 1,25(OH)2D3 injection would be down-regulated in VDR- or 1-hydroxylase-null mice]. A preliminary attempt at this approach with a small group of animals was recently reported by Li et al (23). By comparing the gene expression profile changes that occurred in kidney after 1,25(OH)2D3 injection with those that resulted from loss of the VDR (wild-type mice compared with VDR knockout mice), those authors identified 95 genes for which the response attributable to vitamin D injection was the opposite of the response attributable to loss of the VDR. Twenty-eight of those transcripts (including 1-hydroxylase mRNA) were up-regulated in VDR-null mice and down-regulated in vitamin D-treated mice, whereas 67 of the transcripts (including 24-hydroxylase mRNA) were down-regulated in VDR-null mice and up-regulated in vitamin D-treated mice. Like the study by Lin et al (21), this study identified many potential vitamin D target genes. Although neither of these studies definitively identified new targets, they narrowed the list of candidates considerably and provided clear guidance for investigators who wish to conduct careful reductionist experiments involving these genes.
Studies identifying new protein complexes necessary for vitamin D actions
Very few studies have taken a proteomics approach to the examination of vitamin D actions in cells. One notable study was recently conducted with keratinocytes by Oda et al (24). Previously, Rachez et al (25) developed an in vitro assay to assess the complex of proteins that associates with the VDR during vitamin D-mediated gene transcription. By using a VDR ligand-binding domain–glutathione S-transferase fusion protein, they were able to identify the VDR-interacting protein (DRIP) complex, a complex of 16 proteins that is essential for vitamin D-mediated gene transcription because of its ability to recruit RNA polymerase II to vitamin D-responsive genes (14, 25). Oda et al (24) used this approach to identify the proteins associated with the VDR in nuclear extracts from proliferating and differentiated keratinocytes. Although they identified a similar complex of proteins interacting with the VDR in proliferating keratinocytes (eg, DRIP complex members and RXR), they found that key members of the complex had changed in differentiated keratinocytes. Proteomic analysis of the proteins associated with the VDR in proliferating and differentiated nuclear extracts showed that at least 5 members of the DRIP complex were lost with differentiation but 2 new proteins, SRC-2 and SRC-3, became prominent members of the complex. That study suggested that the complex mediating VDR-mediated gene expression might not be uniform across vitamin D target tissues or even within the cells of a tissue at different stages of their life spans. This could account for the observed diversity of sensitivity of various cell types/tissues to 1,25(OH)2D3 treatment or the ability of a vitamin D analog to work in one tissue but not another.
At least one other line of vitamin D research might also be improved with a proteomics approach. Specifically, it is now clear that vitamin D stimulates rapid activation of signal transduction pathways, eg, it activates several protein kinases, leading to phosphorylation of various proteins (15). The final targets of the kinases activated by 1,25(OH)2D3 have not yet been identified but it is clear that these targets of phosphorylation are critical for understanding the biological importance of these rapid vitamin D actions. It is apparent that new technologies developed for assessment of the phosphoproteome (26) are likely to identify not only the signal transduction pathways used by 1,25(OH)2D3 but also the terminal proteins whose biological functions are either activated or inhibited through stimulation of these phosphorylation cascades.
Identification of functional biomarkers of vitamin D actions
A major issue in the area of vitamin D research is defining the amount of vitamin D needed for optimal health. Although there are some concerns about the reliability and cross-comparison of various assays for measuring 25(OH)D3 concentrations as an index of vitamin D status (27), the main issue is how 25(OH)D3 concentrations relate to function, ie, bone biological processes related to the risk of osteoporosis or epithelial cell biological processes related to cancer risk. The data from several studies suggest that the cutoff value for adequate serum 25(OH)D3 concentrations may be higher than simply the concentration that prevents rickets (2–4). This idea is based on the association of high vitamin D concentrations with suppression of serum PTH concentrations, a measurement that is being used as a surrogate marker of bone resorption (with the assumption that maximal suppression of PTH is necessary for maximal protection of bone). However, is the PTH concentration an appropriate marker for bone resorption? Or would linking serum 25(OH)D3 concentrations to a more relevant functional endpoint or using a biomarker that is correlated directly with a functional endpoint be better for defining optimal vitamin D status? And what about cancer risk? Should we assume that the serum 25(OH)D3 concentration that is optimal for the protection of bone is optimal for the prevention of cancer? In a perfect world, scientists would be able to directly relate vitamin D status to factors such as fracture incidence, changes in bone density with time, or the development of prostate, breast, or colon cancer. However, such studies would require very large populations and a long study period (as well as being ethically questionable). An alternative might be to correlate vitamin D status with an intermediate endpoint; for bone health, for example, active bone resorption could be measured for a smaller, more controlled, study population. Unfortunately, the means to study active bone resorption (and early functional indices of cancer risk) are currently inadequate for this task. Bone density changes require long periods for reliable observation, and current serum markers are highly variable and thus less reliable. This indicates that new biomarkers of relevant functional endpoints important for bone health and vitamin D biological processes are needed.
Cancer researchers are leading the way toward using the techniques of genomics and proteomics to provide diagnostic markers. For example, Sorlie et al (28) used gene expression profiling of breast tissue biopsies to define the discriminating diagnostic signatures for 6 distinct classes of breast cancer, which suggests that a molecular signature could be used instead of a more subjective histologic evaluation. Although that study and other cancer-profiling studies made great use of gene expression profiles for tumor biopsies as a classification system, the need for a tissue biopsy is a serious limitation to the use of gene expression profiling as a general screening tool for healthy people. Effective biomarkers for assessing healthy people are likely to come from readily available, minimally invasive sampling of blood, blood cells, serum, or urine. The use of serum proteomic profiles, such as that used for ovarian cancer diagnosis, as reported by Petricoin et al (29), may be a more fruitful approach for issues related to nutrient status and health.
In the "omic" approach to identifying and defining biomarkers of disease or of physiologic deficits, the basic idea is to compare the profiles of individuals in 2 well-defined groups (eg, vitamin D-replete and vitamin D-deficient subjects) and then define the changes in the profiles that are correlated best with changes in the condition of interest. For continuous variables such as vitamin D status, the markers may be continuous or they may exhibit breakpoints. Although this approach may provide us with assessment parameters that may be easier to measure than vitamin D metabolite concentrations, without functional correlates this would be no more informative than serum 25(OH)D3 concentrations. Functional assessment could be included to strengthen the relationship; this general scheme is presented in Figure 4. For example, bone resorption could be measured directly through assessment of the release of calcium from bone. Ongoing work in Dr. Connie Weaver's laboratory at Purdue University suggests that a new technique for labeling bones in vivo with small amounts of the natural isotope 41Ca may provide an objective accurate measure of bone resorption (30). 41Ca is a long-lived isotope of calcium that can be produced inexpensively through neutron activation. Because miniscule amounts of 41Ca can be measured with atomic mass spectroscopy, radiologically benign amounts of the isotope can be administered to human subjects to label their bones. After 41Ca has been cleared from soft tissues (100 d), the appearance of 41Ca in the serum or urine is a direct reflection of calcium lost from bone. Because of the long half-life of 41Ca and the relatively low turnover of bone, subjects can be examined repeatedly for >10 y (permitting assessment of multiple treatments or multiple levels of a treatment for the same subject). With the exception of the long study period, this is consistent with work that was previously conducted with animals and high concentrations of 45Ca or tetracycline (31).
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FIGURE 4.. Scheme for the identification and cross-validation of serum biomarkers related to vitamin D (VD) status and bone resorption.
A discordance in the relationship between the effects of vitamin D status on bone resorption and on the serum proteome could have important physiologic implications. For example, if serum proteins changed as vitamin D status was reduced but this was not accompanied by coordinate changes in bone resorption (41Ca release), then this could be an indication that the vitamin D biomarker is related more to cancer risk (or one of the other potential functions now being proposed for vitamin D, such as diabetes mellitus risk). This could prove to be the basis for future work on the vitamin D–non-bone disease connections.
CONCLUSIONS
The field of vitamin D biology has a long history. However, we are now being confronted with both basic questions related to vitamin D actions and applied issues regarding how to use our fundamental understanding of vitamin D biological processes. Advances in chromatographic techniques have permitted us to better understand vitamin D metabolism, and the revolution in molecular biology has helped us explain the mechanistic basis for vitamin D actions on cells. In this review, I have attempted to explain how the new approaches of genomics and proteomics have the potential to expand our understanding of vitamin D biological processes and the role of vitamin D in human health.
REFERENCES
【摘要】
Objective— Genomic changes were defined in cultures of regenerated porcine coronary endothelial cells to explain the alterations that underlie their dysfunction.
Methods and Results— Regeneration of the endothelium was triggered in vivo by endothelial balloon denudation. After 28 days, both left circumflex (native cells) and left anterior descending (regenerated cells) coronary arteries were dissected, their endothelial cells harvested, and primary cultures established. The basal cyclic GMP production was reduced in regenerated cells without significant reduction in the response to bradykinin and A23187. The mRNA expression levels in both native and regenerated cells were measured by microarray and RT-PCR. The comparison revealed genomic changes related to vasomotor control (cyclooxygenase-1, angiotensin II receptor), coagulation (F2 and TFPI), oxidative stress (Mn SOD, GPX3, and GSR), lipid metabolism (PLA2 and HPGD), and extracellular matrix (MMPs). A-FABP and MMP7 were induced by regeneration. RT-PCR revealed upregulation of A-FABP and downregulation of eNOS and TR. The differential gene expression profiles were confirmed at the protein level by Western blotting for eNOS, F2, Mn SOD, MMP7, and TR.
Conclusions— Cultures from regenerated coronary endothelial cells exhibit genomic changes explaining endothelial dysfunction and suggesting facilitation of coagulation, lipid peroxidation, and extracellular matrix remodeling.
Genomic changes were determined in cultured regenerated endothelial cells. cGMP production was reduced. Changes in mRNA expression related to vasomotor control, coagulation, oxidative stress, extracellular matrix, and lipid were confirmed by Western blotting for eNOS, F2, Mn SOD, matrix metalloproteinase 7, and TR. These findings reveal linkages between regeneration and endothelial dysfunction.
【关键词】 endothelial regeneration genomics nitric oxide ROS coagulation extracellular matrix lipids
Introduction
The endothelium produces nitric oxide (NO) and prostacyclin, 1–3 which contribute to the anticoagulant properties of the intima and the inhibition of the adhesion and transmigration of inflammatory cells into the arterial wall. 4,5 Endothelial dysfunction attributable to aging and prolonged exposure to turbulent shear stress, coupled with risk factors, accelerates apoptosis, senescence, and turnover of endothelial cells. 4,5 Denuded areas are relined by regenerated endothelium. However, the latter is dysfunctional and no longer produces sufficient NO in response to thrombin and platelet-derived serotonin, 5–7 losing part of its protective role. 4,8–10 Impairment of NO synthesis favors cell apoptosis, which contributes to endothelial dysfunction and the development of atherosclerosis. 9 Other phenotypic changes in regenerated endothelial cells suggest an accelerated senescence and an accumulation of oxidized forms of modified lipoproteins (LDL). 6,11–13
The cellular mechanisms underlying these phenotypic changes are unknown. The present experiments were designed to define the genomic changes in regenerated endothelial cells, which could explain their phenotypic alterations.
Materials and Methods
The Online Data Supplement gives a detailed description of Materials & Methods (please see http://atvb.ahajournals.org.).
Briefly, female pigs were subjected to endothelial denudation of the left anterior descending coronary artery (LAD) to induce endothelial regeneration. 6 Twenty-eight days later, the animals were euthanized and their hearts removed. Native (left circumflex artery) and regenerated cells were harvested for primary cell culture. Cultures derived from native and regenerated endothelial cells are termed native and regenerated cells, respectively. Confluent cultures at passage zero were studied, except when stated otherwise. Native and regenerated cells derived from the same 6 hearts were compared as regards:
Genomic expression by Microarray (GeneChips Porcine Genome Array, Affymetrix). Fold-changes greater than or equal to 0.8 were considered to indicate genomic differences. 14 Certain changed genes were subjected to computational simulation of biological interactions (PathwayAssist version 3).
Basal and stimulated (bradykinin, A23187 ) levels of cyclic GMP by radioimmunoassay. 11
mRNA expression by RT-PCR. 15
Protein presence by Western blotting. 16
Histochemical staining. 17
Student t test for paired observations was used for the statistical analysis of differences between native and regenerated cells.
Results
Microarray Gene Expression
The array used contained 23 937 probe sets that interrogate approximately 23 256 transcripts from 20 201 S. scrofa genes for target hybridization. The average presence of probe sets for native and regenerated endothelial cells of 6 animals was 61.15±0.0% and 60.3±0.01%, respectively, of the 24 123 probe sets present. The distribution profile (supplemental Figure I) of all differentially expressed genes in regenerated endothelial cells consisted of 7.7±1.2% (1860±278) upregulated and 9.4±1.8% (2266±443) downregulated genes.
Of the identified genes 125 were upregulated and 444 downregulated (supplemental Table I). The expression of the genes for adipocyte-fatty acid binding protein (A-FABP) and matrix-metalloproteinase 7 (MMP7) was observed only in regenerated cells ( Figure 1 ). Among the other genes known to be related to endothelial function and vasomotor control, 18 were upregulated ( Figure 1 ) and 25 downregulated ( Figure 2 ) significantly. The Microarray analysis revealed 425 unknown genes which were either up- or downregulated (supplemental Table II).
Figure 1. Upregulation of genes in regenerated cells. A-FABP indicates adipocyte-fatty acid binding protein; MMP7, matrix-metalloproteinase 7; HPGD, hydroxyprostaglandin dehydrogenase 15-(NAD); GADD45A&B, growth arrest and DNA-damage-inducible, alpha and beta; F2, coagulation factor II; CXCL12, stromal cell-derived factor-1; MMP23A&B, matrix-metalloproteinase 23A&B; COL1A1, collagen alpha 1; GM-CSF, granulocyte macrophage-colony stimulating factor; TGF-β1, TGF beta 1; PPAR gamma 1a, peroxisome proliferators-activated receptor gamma 1a; Gp VII PLA2, phospholipase A2. * P <0.05 (with GCOS normalization strategy). P <0.05 (with GeneSpring GX analysis).
Figure 2. Downregulation of genes in regenerated cells. LOX receptor 1 indicates lectin-like oxidized LDL receptor-1; VLCAD, acyl-coenzyme A dehydrogenase (very long chain); TGF-β1R-II, TGF-beta 1 receptor, type II; ACAT, acyl-coenzyme A:cholesterol acyltransferase; PAI-2, plasminogen activator inhibitor-2; GSR, glutathione reductase; Lrp 1&6, LDL receptor-related protein 1 and 6; COX-1/PGHS-1, cyclooxygenase 1; GPX3, glutathione peroxidase 3; TXNIP, thioredoxin interacting protein; MnSOD, superoxide dismutase (Mn type); GPIIIa, glycoprotein IIIa; Apo B, apolipoprotein B; TFPI (Lp-associated), tissue factor pathway inhibitor (lipoprotein-associated); I B, IkappaB; ABCA1, ATP-binding cassette transporter A1; CAV1, caveolin-1. * P <0.05 (with GCOS normalization strategy). P <0.05 (with GeneSpring GX analysis).
The expression of a number of genes known to be related to endothelial function, including eNOS (NOS3), was comparable in native and regenerated cells (supplemental Table III).
The Microarray analysis demonstrated absence or minimal expression, in both native and regenerated cells, of CD14, CD18, CD133, Flk 1 type VEGF receptor VEGFR2 (KDR/Flk), and comparable expression of CD31 and CD34 antigens (supplemental Table III).
Cyclic GMP
The basal level of cyclic GMP (measured as an index of the production of NO, and thus of the activity of eNOS) in regenerated cells at passage one was reduced significantly compared with native cells ( Figure 3 D). Bradykinin (1 µmol/L) and A23187 (1 µmol/L) increased the level of cyclic GMP significantly and to a comparable extent in native and regenerated cells ( Figure 3 E).
Figure 3. mRNA expression (A) and protein presence of eNOS (B) and Akt 1/2 (C) in native and regenerated cells. Cyclic GMP levels in native and regenerated cells at basal level (D) and on stimulation by bradykinin (BK) and A23187 (E). The asterisks indicate statistical significant differences ( P <0.05) from the corresponding control.
Real-Time PCR
Real-time PCR revealed a significant reduction in the expression of eNOS ( Figure 3 A) and thioredoxin reductase ( Figure 4 A) in regenerated cells. It also confirmed the upregulation of the expression of A-FABP gene ( Figure 5 A) in these cells.
Figure 4. mRNA expression of thioredoxin reductase (TR) as analyzed by RT-PCR (A). Protein presence of TR (B) and superoxide dismutase (Mn SOD; C). The asterisks indicate statistical significant differences ( P <0.05) from the corresponding control.
Figure 5. mRNA expression of A-FABP as analyzed by RT-PCR (A); protein presence of MMP7 (B) and coagulation factor II (F2; C). The asterisks indicate statistical significant differences ( P <0.05) from the corresponding control.
Western Blotting
The experiments were performed in cells at passage 1 to 4. The presence of eNOS protein was significantly reduced in regenerated compared with native cells ( Figure 3 B), as was that of Akt 1/2 ( Figure 3 C). The protein levels of thioredoxin reductase ( Figure 4 B) and superoxide dismutase (Mn SOD; Figure 4 C) also were reduced significantly in regenerated cells. The protein level of coagulation factor II (F2) was augmented significantly in regenerated cells ( Figure 5 C). The presence of MMP7 protein was demonstrated in regenerated cells only ( Figure 5 B).
Immunohistochemistry
Cultures of regenerated endothelium contained more multinucleated and enlarged cells (supplemental Figure II). More than 99% of native and regenerated cells stained for von Willebrand factor (vWF; supplemental Figure II). A more intense immunohistochemistry staining for senescence-associated galactosidase beta 1 (SA-β-Gal) was observed in regenerated cells at passage one ( Figure 6 ).
Figure 6. Histochemical staining of SA-β-Galactosidase activity in (A) native and (B) regenerated cells (in blue) in the cytoplasmic region of the cells.
Pathway Analysis
Changed genes for which we believe that they play a role in endothelial function were subjected to computational simulation of biological interactions (supplemental Figure III). This simulation suggested that the downregulation of Mn SOD, GPX3, and GSR should raise the level of oxidative stress, hamper DNA integrity, and reduce the level of nitric oxide, and thus that of cyclic GMP. At the same time, the formation of peroxynitrite should accelerate the lipid peroxidation and promote inflammatory responses. Similarly, the increased level of F2 as well as the elevated level of tissue factor caused by the reduction in TFPI should reduce the anticoagulatory properties of regenerated cells. The reduced expression of plasminogen activator inhibitor (PAI)-2 and the increased levels of MMP7, MMP23, and several subtypes of collagen should facilitate extracellular matrix remodeling leading to vascular thickening.
Discussion
The present study was initiated to identify the genomic changes in regenerated endothelial cells. The pig was selected as experimental animal because the development, morphology, and function of its cardiovascular system closely resemble that of humans. 18 In the present experiments, endothelial regeneration was induced in a minimal area along the LAD to maintain the well-being of the animals. This limits the amount of samples for the analysis both at genomic and proteomic levels. Hence, primary cultures of endothelial cells 11–13 were used to permit harvesting of sufficient RNA to perform the microarray analysis (cells at passage zero) and protein analysis (cells between passage 1 and 4 which provided sufficient proteins, at the risk of introducing changes due to the multiple passaging). To minimize genetic background noise, the comparison was performed systematically in parallel between native and regenerated cells of the same hearts. The microarray data revealed a large number of up- or downregulated genes. This manuscript focuses on the changes that we felt are the most important in terms of endothelial dysfunction and atherosclerosis.
The regeneration of injured endothelium occurs mainly by the proliferation and migration of the neighboring mature endothelial cells to cover the damaged area in order to uphold the homeostasis within the vascular system. 19 Bone marrow–derived stem cells, particularly the circulating endothelial progenitor cells (EPC; CD133 + KDR + CD34 + cells), 19 can differentiate into endothelial phenotype in response to injury. 19 This accelerates reendothelialization and influences the release of cytokines and growth factors (VEGF, M-colony stimulating factor , IGF). 19,20 After 28 days, 70% or more of the previously denuded surface is covered by regenerated endothelium. 20,21 In the present study, upregulation was observed of CXCL12 and GM-CSF, which may reflect the mobilization of progenitor cells by chemokines to site of injury for reendothelialization 22 although the expression of CD34 + was not changed in regenerated cells. The absent or insignificant expression in CD133, KDR, 19 CD14 and CD18 23 demonstrated the purity of endothelial mRNA with minimal contamination by progenitor or mononuclear cells. The endothelial origin of both native and regenerated cells was confirmed by genetic expression of eNOS and CD31, as well as by positive staining for vWF. 24
Vasomotor Control
eNOS and Akt
The basal production of cyclic GMP was reduced in regenerated cells by approximately 30% compared with native cells, which is indicative of endothelial dysfunction. 11 This interpretation is supported by the reduced genetic expression of eNOS, as detected by RT-PCR (but not by microarray), and by the reduced protein presence of the enzyme. The reduced expression of flow-sensitive caveolin-1, which in the caveolae along the cell membrane can activate resident eNOS to produce nitric oxide, may suggest a reduced response to physiological stimulations such as shear stress. 25 The reduced protein presence of Akt also is consistent with a diminished production of NO. 26 The observed downregulation of arginase (type II) implies that competition by this enzyme for substrate arginine is not likely to contribute to reduced production of NO. 27
The cyclic GMP response to endothelium-dependent vasodilators was not reduced. This is in line with earlier studies demonstrating normal endothelium-dependent relaxations to bradykinin and A23187 in arteries covered with regenerated endothelium. 6 By contrast, earlier work has shown that the endothelium-dependent relaxations to serotonin (and thrombin) are impaired by the regeneration process. 6,7,13,28
Other Enzymes and GPCRs
The present data did not reveal significant changes in expression level of the detected serotonin (5-HT1D and 5-HT2B receptors) and endothelin-1 receptors in regenerated cells, whereas that of angiotensin II and oxytocin receptors was augmented. The observed upregulated gene expression of the angiotensin II (Ang II) type 1 receptor may result in inactivation of the bradykinin-nitric oxide pathway and thus endothelial dysfunction on exposure to angiotensin II. 29 It also could facilitate inflammatory reactions attributable to oxidative stress resulting from inactivation of antioxidant enzymes such as superoxide dismutase which would favor lipid oxidation and damage proteins and nucleic acids in the endothelial cells. 29,30 The expression of the 5-HT1D subtype was minimal in cultures derived from both native and regenerated cells. The minimal expression of serotonin receptors observed in the present study helps to explain earlier work demonstrating a loss in ability to release endothelium-derived relaxing factor in cultured cells in response to monoamine. 28 The downregulation of endothelin-converting enzyme 1 (ECE 1) observed in the present studies in regenerated cells may imply that despite the unchanged expression of endothelin receptors, endothelin-1 does not contribute to the dysfunction of these cells, although obviously a reduced bioavailability of NO could favor the production and the action of the peptide. 31
G-Proteins
The selective loss of the response to serotonin and thrombin has been attributed to a reduced activity of pertussin-toxin sensitive Gi-proteins, whereas that of Gq proteins (which mediate the response to bradykinin) is maintained much longer. 6,7,13,28 The absence of differences in the expression of Gi-protein family genes in regenerated cells supports that interpretation and is in line with the earlier demonstration, by immunostaining, of a comparable presence of these proteins in native and regenerated cells. 13 Endothelium-dependent vasodilatation may also be dampened further by a reduced production of prostacyclin by the main producing enzyme, COX-1/PGHS-1, 32 the expression of which is reduced in regenerated cells.
Oxidative Stress
Endothelial reactive oxygen species (ROS) can originate from various sources (eg, the mitochondrial oxidative respiratory chain, xanthine oxidase, uncoupled NOS, cytochrome P-450 enzymes, cyclooxygenases and NADPH oxidases). 33 ROS alter gene transcription and enzyme activities, reduce the production of nitric oxide, and cause oxidative damage to lipids, proteins, and DNA. 34,35 The expression of the subunit complexes of oxidative phosphorylation were not changed in regenerated cells. The present experiments predict an elevated level of hydrogen peroxide, originating from the mitochondria in regenerated cells attributable to downregulation of several antioxidant enzymes (Mn SOD , GPX3, GSR, TR, 35 and thioredoxin-interacting protein). High levels of ROS, including hydrogen peroxide, as a result of the reduced activities of Mn SOD in the mitochondria diffuse and exert an oxidative effect in cytosol to catalyze the conversion of nitric oxide into peroxynitrite. 35 This could reduce eNOS level in regenerated cells, bioavailability of NO, 35 and augment the production of endothelium-derived vasoconstrictor substances. 36 The protective role of adenosine on oxidant injury 37 could also be diminished as a result of upregulation of adenosine deaminase, the major enzyme that catabolizes this nucleoside. Furthermore, an augmented production of ROS would also inhibit other mitochondrial enzymes including aconitase and pyruvate dehydrogenase kinase, 33 explaining the reduced expression of those enzymes revealed by the present microarray experiments.
Cholesterol/Fatty Acid Metabolism
Another aspect related to endothelial function is the metabolism of lipids. The gene expression of A-FABP was induced in regenerated cells, whereas the gene for this protein was not present in native cells. Activation of A-FABP is dependent on ox-LDL and PPAR gamma and essential for transformation of macrophages to foam cells in the subendothelial layer. 38 It is also involved in the development of atherosclerosis by promoting accumulation of cholesterol esters and production of inflammatory mediators. 39 The gene for Gp VII PLA2 (which releases proinflammatory eicosanoids as well as platelet-activating factor 40 ) and HPGD (which minimizes the availability of lipoxin 41 ) were also upregulated. This, together with elevated levels of ROS, would provide a genomic explanation for increased acetylated LDL uptake 11 and intracellular accumulation of ox-LDL 12 without changes in number of LOX receptors in regenerated cells. 12 An increase in acetylated and oxidized LDL as well as in oxidized ApoB-100 in cells decreases the production of nitric oxide, which contributes to vascular disease. 4,5 The observed downregulated expression of acyl-coA oxidase and VLCAD should reduce the β-oxidation of long chain fatty acids in mitochondria 42 and increase lipid accumulation in the cells, 43 whereas the reduced expression of ACAT and ApoB should diminish inflammation in vascular cells. 44 A reduced presence of HDL binding protein, ABCA1 in regenerated cells, would limit the efflux of lipids from endothelial cells 45 and pose further cardiovascular risk by facilitating the accumulation of cholesterol.
Coagulation
The endothelium becomes prothrombotic after the regeneration process. 8 Indeed, the reduced expression of endogenous lipoprotein-associated TFPI gene in regenerated cells could lead to augmented levels of tissue factor. 46 Similarly, lipid peroxidation can accelerate the oxidative degradation of TFPI in endothelial cells which becomes a marker for endothelial dysfunction. 47 Upregulation of genes like F2 in regenerated cells should facilitate thrombin formation. 48
Extracellular Matrix, Vascular Smooth Muscle Proliferation, and Neointimal Formation
The immediate vascular response after the injury leads to elastic recoil of the media and the adventitia 49 and initiates several subsequent events including recruitment and migration of inflammatory cells, proliferation of vascular smooth cells, and deposition of extracellular matrix at site of injury with the formation of neointima. 50 The reduced expression of PAI-2 in regenerated cells may increase the proteolytic power of proteinases and hence the upregulation of MMP genes in regenerated cells 51 including MMP7, MMP23A&B. MMP7 at both the genomic and proteomic levels was expressed only in regenerated cells. This proteinase may promote plaque rupture. 52 The altered gene expression of other extracellular matrix proteins in particular the collagens could also accelerate the susceptibility toward cardiovascular disease. 53 Although intima-media thickening was not observed significantly in the present experiments, the augmented transforming growth factor (TGF) beta 1 but downregulated expression of TGF beta 1 receptor II in association with altered expression in thrombospondins in regenerated cells may have pathophysiological consequences. 54
Inflammation and Apoptosis
The gene expression data indicate that inflammatory, tumor necrosis factor (TNF)-related and apoptotic events were downregulated. This probably reflects complete reendothelialization of denuded area to maintain vascular homeostasis after injury. These observations then imply that inflammatory reaction, which initiates atherosclerotic process 55 follows rather than precedes regeneration.
Growth Regulation and Senescence
The present genomic and histochemical data demonstrate that β-galactosidase, an established marker for cellular senescence during aging and after chronic oxidative stress, 17 is upregulated in regenerated cells. The exact mechanism causing increase of this enzyme during aging is unclear. However, its upregulation is in line with that of genes such as GADD45A and GADD45B as well as growth arrest specific 6. This could cause endoplasmic reticulum stress and prevent DNA synthesis. 56 That early senescence occurs in regenerated cells is suggested also by morphological changes (larger, multinucleated cells) observed, confirming earlier observations. 13
Angiogenesis
The expression of angiogenic factors for endothelial cell proliferation like VEGF and angiopoietin-2 57 was not changed, presumably reflecting the fact that completed reendothelialization has occurred after the injury.
In conclusion, the present study outlines genomic and proteomic changes that accompany endothelial regeneration and presumably vascular changes related to intima-media thickening (supplemental Figures III and IV). These findings provide new information on genomic changes which help to understand the phenotypic alterations of regenerated endothelial cells.
Acknowledgments
The authors thank Professor H. Shimokawa (Tohoku University, Japan) for the demonstration of angioplasty.
Sources of Funding
This work was supported in part by grant HKU7490/06M of the Research Grant Council of Hong Kong and by the Research Centre of Heart, Brain, Hormone and Healthy Aging of the University of Hong Kong.
Disclosures
None.
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作者单位：Department of Pharmacology (M.Y.K.L., R.Y.K.M., P.M.V.) and the Cardiology Division, Department of Medicine (H.F.T., C.W.S., S.G.Z.), Li Ka Shing Faculty of Medicine, The University of Hong Kong.
【摘要】
Bladder cancer transformation and immortalization require the inactivation of key regulatory genes, including TP53. Genotyping of a large cohort of bladder cancer patients (n = 256) using the TP53 GeneChip showed mutations in 103 cases (40.2%), the majority of them mapping to the DNA-binding core domain. TP53 mutation status was significantly associated with tumor stage (P = 0.0001) and overall survival for patients with advanced disease (P = 0.01). Transcript profiling using oligonucleotide arrays was performed on a subset of these cases (n = 46). Supervised analyses identified genes differentially expressed between invasive bladder tumors with wild-type (n = 24) and mutated TP53 (n = 22). Pathway analyses of top-ranked genes supported the central role of TP53 in the functional network of such gene patterns. A proteomic strategy using reverse phase arrays with protein extracts of bladder cancer cell lines validated the association of identified differentially expressed genes, such as gelsolin, to TP53 status. Immunohistochemistry on tissue microarrays (n = 294) revealed that gelsolin was associated with tumor stage and overall survival, correlating positively with TP53 status in a subset of these patients. This study further reveals that TP53 mutations are frequent events in bladder cancer progression and identified gelsolin related to TP53 status, tumor staging, and clinical outcome by independent high-throughput strategies.
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The nuclear protein Tp53 plays an essential role in the regulation of cell cycle and apoptosis, contributing to transformation and malignancy.1 Tp53 is a DNA-binding protein containing transcription, DNA binding, and oligomerization activation domains, functioning as a tumor suppressor.2,3 Mutants of TP53 that frequently occur in a number of different human cancers, including bladder cancer, fail to bind the consensus DNA-binding site and hence cause the loss of tumor suppressor activity.4 Alterations of the TP53 gene occurs both as germline mutations, such as in cancer-prone families with Li-Fraumeni syndrome, or somatic mutations in diverse human malignancies.5
TP53 is one of the proteins better characterized in cancer research with reported targets, regulators, and binding proteins. For example, targets regulated by TP53 include cell-cycle genes, such as p21, and anti-apoptotic genes, such as bax. Regulators of TP53 include ataxia telangiectasia mutated (ATM) and Chk2, whereas Abl1 and the adenomatous polyposis gene (APC) are among known binding TP53 proteins.6-8 However, little is known of the differential gene expression patterns of human tumors presenting wild-type TP53 compared with those with a mutant protein. With the advent of microarray technologies, characterization of TP53 sequences and gene expression profiles associated with TP53 status are available in a high-throughput manner. Bladder cancer is one of the tumors in which TP53 is altered with a high frequency, mutation rates being 40% in advanced stages of the disease.9-12 The present study was designed to identify targets that would differentiate patients presenting advanced disease with wild-type versus mutant TP53 (Figure 1 ). Gelsolin was selected as one on the genes located to chromosome 9q33, a frequently mutated locus in bladder cancer.9,13 Two proteomic approaches were used to evaluate the link of gelsolin with tumor progression and TP53 status. Immunohistochemical analyses on tissue arrays containing well-annotated bladder tumors and known TP53 status served to associate the expression of gelsolin with TP53, tumor stage, and survival. The differential expression of gelsolin among several bladder cancer cell lines of known TP53 alterations was evaluated by custom-made reverse phase arrays.
Figure 1. Experimental design. TP53 genotyping was performed on 256 bladder tumors using the TP53 sequencing arrays. Gene expression analyses using the U133A array were performed in a subset of 46 bladder tissues to identify targets differentially expressed in bladder cancer regarding their TP53 status (TP53 wild type, n = 24; and TP53 mutated, n = 22). Supervised methods identified 149 probes differentially expressed between those cases with either wild-type or mutated TP53. Two types of validation studies of the association of molecular profiles with TP53 status were performed. Immunohistochemical patterns were analyzed on tissue arrays containing 294 tumors, a subset of them of known TP53 and clinical outcome status. Proteomic reverse phase arrays were also performed on protein extracts of bladder cancer cell lines of known TP53 status.
【关键词】 proteomic profiles association gelsolin progression
Materials and Methods
TP53 Sequencing Analyses
DNA Extraction and Tissue Samples
Total DNA was extracted using a nonorganic method (Oncor, Gaithersburg, MD). Macrodissection of OCT-embedded tissue blocks was performed to ensure a minimum of 75% tumor cells.13 DNA quality was evaluated based on 260/280 ratios of absorbances. Specimens were collected under institutional review board approval. These tumors comprised 10 pTa, 32 pT1, 22 pT2, 175 pT3, and 15 pT4 specimens from patients with bladder cancer.
TP53 oligonucleotide array assay (GeneChip p53; Affymetrix, Santa Clara, CA). Purified DNA (100 ng) was subjected to multiplex-polymerase chain reactions (PCRs) amplifying exons 2 to11 simultaneously, using reagents supplied by the manufacturer (Affymetrix). Apart from the DNA, each PCR reaction contained 10 U of AmpliTaq Gold, PCR buffer II, 2.5 mmol/L MgCl2, 5 µl of the primer set, and 0.2 mmol/L each dNTP. The reaction was performed in a final volume of 100 µl. The PCR profile consisted of an initial heating at 95??C for 10 minutes, followed by 35 cycles of 95??C for 30 seconds, 60??C for 30 seconds, and 72??C for 45 seconds, with a final extension step at 72??C for 10 minutes. Forty-five µl of the PCR product was then fragmented by the addition of 0.25 U of fragmentation reagent (DNase I in 10 mmol/L Tris-HCl, pH 7.5, 10 mmol/L CaCl2, 10 mmol/L MgCl2, and 500 ml/L glycerol) along with 2.5 U of calf intestine alkaline phosphatase, 0.4 mmol/L ethylenediaminetetraacetic acid, and 0.5 mol/L Tris-acetate, and incubation at 25??C for 15 minutes, followed by heat inactivation at 95??C for 10 minutes. For labeling, 50 µl of the fragmented DNA was incubated at 37??C for 45 minutes with 10 µmol/L fluorescein-N6-dideoxy-ATP, 25 U of terminal transferase, and TdTase buffer in a total volume of 100 µl, followed by heat inactivation at 95??C for 10 minutes. The sample was hybridized to the chip in a volume of 0.5 ml containing 6x sodium chloride/sodium phosphate/EDTA (SSPE) buffer, 0.5 ml/L Triton X-100, 1 mg of acetylated bovine serum albumin, 2 nmol/L control oligonucleotide, and the labeled DNA sample. Hybridization was done in an oven with constant agitation at 45??C for 30 minutes. The chip was then washed on the wash station four times with 3x SSPE containing 0.05 ml/L Triton X-100. After washing, GeneChips were read using a confocal laser scanner, and data were aligned and analyzed. A reference from the control DNA supplied was also analyzed. This reference belonged to the same PCR round and was measured on the same batch of chips.14,15
Gene Profiling Using U133A GeneChips
Tissue Samples and RNA Extraction
Tumors belonging to patients with invasive bladder cancer (pT2+) were obtained by cystectomy or cystoprostatectomy at Memorial Sloan-Kettering Cancer Center. Specimens were collected under institutional review board approval of this institution. Macrodissection of OCT-embedded tissue blocks was performed to ensure a minimum of 75% tumor cells. Because of the high heterogeneity of muscle-invasive bladder tumors, this conservative cutoff of 75% would guarantee that tumor subpopulations would be representative enough to identify targets associated with TP53 status in cancer cells. Total RNA was extracted using TRIzol (Life Technologies, Rockville, MD) and purification with RNeasy columns (Qiagen, Valencia, CA). RNA quality was evaluated based on 260/280 ratios of absorbances and by gel analysis using an Agilent 2100 BioAnalyzer (Agilent Technologies, Palo Alto, CA).13 Selection of cases for oligonucleotide arrays focused on balancing numbers of cases with wild-type (n = 24) and mutant TP53 (n = 22), covering the most frequent TP53 mutations in the DNA-binding core domain in cases displaying all advanced disease (PT2+).
Labeling and Hybridization
Complementary DNA of the analyzed specimens was synthesized from 1.5 µg of total RNA using a T7-promoter- tagged oligo-dT primer. RNA target was synthesized by in vitro transcription and labeled with biotinylated nucleotides (Enzo Biochem, Farmingdale, NY). Labeled target was hybridized on GeneChip test 3 arrays (Affymetrix) to assess the quality of the sample before hybridizing onto the human genome U133A arrays including 22,283 probes representing known genes and expressed sequence tags (Affymetrix), as previously reported.13
GeneChip Analysis
Scanned image files were visually inspected for artifacts and analyzed using Affymetrix Microarray Suite 5.0 (MAS 5.0). Expression values of each array were multiplicatively scaled to have an average expression of 500 at least across the central 95% of all genes on the array. Signal was used as the primary measure of expression level, and detection was retained as a complementary measure.13
Immunohistochemical Analyses
Cell Lines, Tissue Arrays, and Immunohistochemistry
Cytospins of bladder cancer cell lines were obtained after centrifugation at low speed, 800 rpm, for 5 minutes.16 Four different bladder cancer microarrays were constructed in the Division of Molecular Pathology and used in this study. These arrays included a total of 294 primary transitional cell carcinomas (TCCs) of the bladder, belonging to patients recruited at Memorial Sloan-Kettering Cancer Center under institutional review board-approved protocols. A total of 93 non-muscle-invasive and 201 invasive TCC tumors were analyzed in these microarrays. These tumors corresponded to 34 grade 1, 69 grade 2, and 191 grade 3 lesions. One of these tissue microarrays comprised a cohort of four non-muscle-invasive lesions and 91 invasive tumors with annotated follow-up and known status of TP53. This array allowed clinical outcome assessment and evaluation of the associations of novel markers with TP53. Protein expression patterns of gelsolin were assessed at the microanatomical level on these tissue microarrays by immunohistochemistry using standard avidin-biotin immunoperoxidase procedures. Western blot assays were performed to address the specificity of the antibodies under study. We used a mouse monoclonal antibody against TP53 (1801) at 1:500 dilution (Calbiochem, San Diego, CA) and gelsolin at 1/1000 (Sigma, St. Louis, MO) on formalin-fixed/paraffin-embedded sections. The avidin-biotin immunoperoxidase technique was the immunohistochemical method applied. For specific epitopes on paraffin sections, we used antigen retrieval methods (0.01% citric acid for 15 minutes under microwave treatment) before incubation with primary antibodies or antiserum overnight at 4??C. Secondary antibodies were biotinylated horse anti-mouse or goat anti-rabbit antibodies (Vector Laboratories, Peterborough, UK), which were used at 1:500 or 1:1000 dilution, respectively. Diaminobenzidine was used as the final chromogen and hematoxylin as the nuclear counterstain. Two independent pathologists (C.C.-C. and N.B.), blinded to the TP53 or clinical status of the samples, reviewed immunohistochemical stainings.
Statistical Analysis
All TCCs (n = 294) were used for the analysis of association among gelsolin with clinicopathological variables and the expression patterns of TP53. The consensus value of the representative cores from each tumor sample arrayed was used for statistical analyses. The association of the expression of the selected targets with histopathological stage and tumor grade was evaluated using the nonparametric Wilcoxon-Mann-Whitney and Kruskall-Wallis tests. There is no consensus on the cutoffs of the immunohistochemical expression of the other markers, and thus they were analyzed as continuous variables.17 Survival analyses were performed taking the cutoffs of 20% for TP53 and 5% for gelsolin.
The associations of the markers identified in the DNA microarray analysis to outcome were also evaluated at the protein level using a subset of 95 TCCs of the bladder cases for which follow up was available. Overall-survival time was defined as the years elapsed between transurethral resection or cystectomy and death from disease (or the last follow-up date). Patients who were alive at the last follow-up or lost to follow-up were censored. For survival analysis, the association of marker expression levels with overall survival was analyzed using the Wald test, and the log-rank test was used to examine their relationship when different cutoffs were applied.17 Survival curves were plotted using the standard Kaplan-Meier methodology. Associations among gelsolin with TP53 were analyzed using Kendall??s b-test.17 Statistical analyses were performed using the SPSS statistical package (version 10.0).
Reverse-Phase Arrays
Bladder Cancer Cell Lines
Nine bladder cancer cell lines were obtained from the American Type Culture Collection (Rockville, MD), grown, and collected under standard tissue culture protocols as previously reported.16 These cell lines were derived from TCCs of the bladder of early stage (RT4), low grade (5637), invasive (T24, J82, UM-UC-3, HT-1376, and HT-1197), and metastatic bladder tumors (TCCSUP), as well as a squamous cell carcinoma cell line (ScaBER). Bladder cancer cell lines were wild type for TP53 (RT4) or presented mutations in TP53 at the following exons: 4 (UM-UC-3, ScaBER), 5 (T24), 7 (HT-1376), 8 (5637 and J82), 10 (TCCSUP), and 11 (HT-1197).16
Protein Lysate Preparation
The bladder cancer cell lines were cultured, and protein extracts were prepared from them as previously described.16 In brief, cells were collected by scraping and washed three times with ice-cold phosphate-buffered saline. The resulting pellets were lysed in buffer containing 9 mol/L urea (Sigma), 4% 3--1-propanesulfonate (CHAPS; Calbiochem), 2%, pH 8.0 to 10.5, Pharmalyte (Amersham Pharmacia Biotech, Piscataway, NJ), and 65 mmol/L dithiothreitol (Amersham Pharmacia Biotech). After lysis, the samples were centrifuged briefly, and the supernatants were stored at C80??C.
Protein Lysate Array Design and Production
Arrays were prepared on nitrocellulose-coated glass slides (FAST Slides; Schleicher & Schuell, Keene, NH) by using a pin-in-ring format GMS 417 arrayer (Affymetrix) with four 500-µm-diameter pins. Because the samples were viscous, the pin-in-ring format was used to avoid problems because of clogging of quills. Five twofold serial dilutions were made from each lysate. Four 384-well microtiter plates (Genetix, New Milton, UK) were used to array 180 spots (plus eight spatial registration marks for use in image processing) on a 21 x 35-mm area of nitrocellulose membrane. The first dilution (fourfold) was made with buffer containing 5 mol/L urea, 2% Pharmalyte, pH 8 to 10.5, and 65 mmol/L dithiothreitol. The remaining dilutions were then made with buffer containing 6 mol/L urea, 1% CHAPS, 2% Pharmalyte, pH 8 to 10.5, and 65 mmol/L dithiothreitol. Hence, only the lysate concentration changed along each dilution series. The urea concentration was thus kept at 6 mol/L and the CHAPS concentration at 2%, to keep proteins in their denatured forms. To avoid evaporation in the microtiter plate during spotting, humidity in the array chamber was kept at 70 to 90% with a Vicks ultrasonic humidifier (Kaz, Hudson, NY).18
Detection of Specific and Total Protein on Microarrays
Each array was incubated with a specific primary antibody, which was detected by using the catalyzed signal amplification system (DAKO, Carpinteria, CA). Briefly, each slide was washed manually with deionized water to remove urea. Then, in an Autostainer universal staining system (DAKO), it was blocked with I-block (Tropix, Bedford, MA) and incubated with primary and secondary antibodies. Also in the Autostainer, it was then incubated with streptavidin-biotin complex, biotinyl tyramide (for amplification) for 15 minutes, streptavidin-peroxidase for 15 minutes, and 3,3'-diaminobenzidine tetrahydrochloride chromogen for 5 minutes. Between steps, the slide was washed with catalyzed signal amplification buffer. The signal was scanned with a Perfection 1200S scanner (Epson America, Long Beach, CA) with 256-shade gray scale at 600 dots per inch. For detection of total protein, arrays were stained with SYPRO ruby protein blot stain (Molecular Probes, Eugene, OR) and scanned with a FluorImager SI (Amersham Pharmacia Biotech) at 100-µm resolution. Gelsolin expression was quantified at a 1/1000 dilution using a mouse monoclonal antibody (Sigma), whereas mutated TP53 was measured using a mouse monoclonal at 1/500 (Calbiochem, Darmstadt, Germany). Spot images were converted to raw pixel values by a modified version of the P-SCAN (Peak Quantification with Statistical Comparative Analysis) software.18,19
Western Blotting
Murine monoclonal antibodies were screened for specificity by Western blotting with 20 µg of lysate protein per lane. Western blotting of gelsolin was performed at a 1/500 dilution using a mouse monoclonal antibody (Sigma). The running buffer contained 62.5 mmol/L Tris-HCl, pH 6.8, 2% sodium dodecyl sulfate, 10% glycerol, and 2.5% 2-mercaptoethanol. We used a 4 to 15% sodium dodecyl sulfate-polyacrylamide linear gradient gel (Tris?
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作者单位：From the Tumor Markers Group,* Spanish National Cancer Center, the Division of Molecular Pathology, the Computational Biology Center, and the Department of Urology,¶ Memorial Sloan-Kettering Cancer Center, New York, New York; and the Center for Applied Proteomics and Molecular Medicine, George
Department of Microbiology, National Taiwan University College of Medicine, and Departments of Internal Medicine and Forensic Medicine, National Taiwan University Hospital, Taipei, Taiwan
Background.
Primary pyogenic liver abscess (PLA) with septic complication by Klebsiella pneumoniae is an emerging infectious disease.
Methods and results.
Using DNA microarray hybridization, we identified a 20-kb chromosomal region that contained 15 open-reading frames (ORFs), including an iron-uptake system (kfu), a phosphoenolpyruvate sugar phosphotransferase system (PTS), and 6 unknown ORFs. The region was more prevalent among tissue-invasive strains (35/46) than among noninvasive strains (19/98) (P < .0001, 2 test). To test the role played by this region in pathogenesis, 3 different deletion mutants (NTUH-K2044 [kfu], K2044 [ORF79], and K2044 [PTS]) were constructed. Only the kfuABC mutants showed decreased virulence in mice, compared with the wild-type strain. An in vitro assay confirmed the involvement of kfu in iron acquisition. There was a high correlation rate (85%) between the kfu/PTS region and 2 tissue invasionassociated chromosomal regions (allS and magA). Moreover, all 3 regions were present in strains that caused PLA plus endophthalmitis or meningitis.
Conclusion.
Our results suggest that chromosomal heterogeneity is present in tissue-invasive K. pneumoniae strains. A genotype containing all 3 regions is strongly associated with PLA and metastatic infection. These regions may serve as convenient markers for the rapid diagnosis of emergent tissue-invasive strains.
Klebsiella pneumoniae is an important hospital-acquired pathogen that is a frequent cause of urinary tract infection, septicemia, and pneumonia in immunocompromised individuals; it is also an important pathogen with respect to community-acquired infectious diseases, such as community-acquired pneumonia [1]. In Taiwan, K. pneumoniaeassociated primary pyogenic liver abscess (PLA) has recently become an important emerging infectious disease [28]. This disease is also a global concern, as is attested by reports from North America [9], Europe [10, 11], and Asia [1214].
Fulminant tissue-invasive K. pneumoniae infections can attack healthy persons who have no history of hepatobiliary disease, and only 50% of patients have a predisposing condition, such as diabetes mellitus [28]. PLA is manifest with other septic metastatic lesions, including pyogenic meningitis and endophthalmitis, in 10%12% of patients [35, 7]. Despite aggressive antibacterial strategies, significant morbidity and mortality still exists, especially in those with diabetes mellitus [28].
Using transposon mutagenesis and full genome expression analysis, we recently identified genomic segments of 33 kb (magA) and 22 kb (allS), which were absent in the genome of MGH 78578 and present in most tissue-invasive strains from patients with PLA, meningitis, or endophthalmitis [15, 16]. Therefore, it is probable that these tissue-invasive strains might represent a specific genotype that harbors specific regions involved in pathogenesis and prevalence.
DNA microarray technology provides a useful tool for assessment of the differences and changes in bacterial genomes [17, 18]. Therefore, we used this technology to compare genomic variations between tissue-invasive strains and noninvasive strains.
PATIENTS, MATERIALS, AND METHODS
K. pneumoniae strains and culture conditions.
K. pneumoniae isolates were obtained consecutively from cultures of blood samples obtained from patients between 1997 and 2003. A total of 46 tissue-invasive K. pneumoniae strains were obtained from patients with PLA or meningitis at National Taiwan University Hospital (NTUH). Of these, 22 were isolated from patients with diabetes mellitus, and 24 were isolated from patients who had previously been healthy.
For comparison, 98 noninvasive strains were obtained from patients with sepsis but without any tissue-invasive disease (such as PLA, meningitis, and endophthalmitis). Of these strains, 33 were obtained from patients at NTUH, 32 were obtained from patients at Far Eastern Memorial Hospital (FEMH; Banciao, Taiwan), and 11 were obtained from patients at En Chu Kong Hospital (ECKH; Sansia, Taiwan). Also, 22 strains from the United States, including MGH 78578, were purchased from the American Type Culture Collection. MGH 78578 was chosen for full genome sequencing at Washington University (St. Louis, MO; available at: http://www.genome.wustl.edu/projects/bacterial/). Information pertaining to the 144 strains is listed in table 1. All strains were identified and cultured according to standard clinical microbiology methods [19].
Microarray construction and hybridization.
The genomic library was constructed from a clinical isolate, NTUH-K2044, obtained from a patient with PLA plus meningitis in a phagemid [20]. DNA fragments in phagemids of K. pneumoniae were amplified by polymerase chain reaction (PCR) with primers in vectors and were spotted onto a nylon membrane (Roche) by a computer-controlled XYZ translation system (PM500; Newport) [21].
Probe preparation and hybridization.
Genomic DNA from 4 PLA strains (NTUH-K2044, A1208, A3021, and A5011) and 3 noninvasive strains (N3423, N3529, and N5322) were extracted and were labeled with biotin-16-dUTP (Perkin Elmer) by a randomly primed polymerization reaction. The microarray membrane was prehybridized in 2 mL of hybridization buffer for 4 h at 65°C and was hybridized for 16 h at 68°C. The membrane was washed twice with 2× standard saline citrate (SSC) containing 0.1% SDS for 5 min at room temperature and was then washed 3 times with 0.1× SSC containing 0.1% SDS for 15 min at 65°C each time. Colorimetry detection and image analysis were then performed as described elsewhere [22].
Recombinant DNA techniques and plasmids.
K. pneumoniae deletion mutants were constructed by replacing the deletion region with a kanamycin (Km) cassette in a double-crossover integration of chromosomal DNA. All primers used in the present study are listed in table 2. To generate the NTUH-K2044 (kfu) mutant, a PCR fragment amplified by primers PVAR KO-1 and PVAR KO-2 was cloned into a pGEM-T Easy vector (Promega). PVAR KO-1(iPCR) and PVAR KO-2(iPCR) primers were used for inverse PCR with plaque-forming-unit polymerase (MBI Fermentas). A blunt-end Km gene was phosphorylated by use of a polynucleotide kinase (New England Biolabs) and was ligated to the inverse PCR product to generate the kfu disruption fragment. We cloned the fragment into a pUT suicide vector [23] containing an EcoRI site and added a second marker (spectionmycin; Spe) to the ApaLI site. pUT-(kfu) was transformed into wild-type NTUH-K2044 to generate a kfu deletion mutant by conjugation. Deletion clones were selected by Kmr and Spes. The same procedures were used for open-reading frames (ORFs) 79 and phosphoenolpyruvate sugar phosphotransferase system (PTS) deletion constructs. All of the deletion mutants were confirmed by PCR with multiple primer pairs and sequence determination.
Transcomplementation of Escherichia coli H1443.
An aroB- E. coli H1443 strain is deficient of siderophore for growth when cultured in medium containing iron chelator 2,2-dipyridyl (Sigma) [24, 25]. Transformed E. coli H1443 with plasmid pBR322::kfuABC, plasmid pSZ1 [25], or pBR322 were grown overnight at 37°C in Luria-Bertani (LB) broth. Each culture was diluted in fresh LB broth supplemented with 0.1, 0.2, or 0.5 mmol/L 2,2-dipyridyl. The growth rate was monitored spectrophotometrically at 620 nm.
RNA isolation and reverse-transcription (RT) PCR.
Total RNA was isolated from K. pneumoniae cultured at the exponential phase of growth, as described elsewhere [15]. For each RT, 5 g of RNA was used with 2 pmol of RT-PCR primer and 200 U of M-MLV reverse transcriptase (Invitrogen). Reaction mixtures without reverse transcriptase were included as negative controls. PCR was performed with 10% of each RT reaction volume under 30 cycles of amplification.
Murine experiments.
Initially, we infected BALB/cByl mice intraperitoneally (ip). However, later experiments showed that intragastric (ig) inoculation had a higher sensitivity to differential virulence [15, 16]. Mice were administered ig [26] either wild-type NTUH-K2044, MGH 78578, NTUH-K2044 (kfu), K2044 (ORF79), or K2044 (PTS) (103106 cfu; 4 mice for each dose). For ig inoculation, we carefully slipped a 1-mm polyethylene flexible tube (Becton Dickinson) past the pharynx into the stomach (5 cm of intubation) of each mouse and delivered 0.2 mL (103106 cfu) of bacterial suspension. Anesthesia was not used for this procedure. Mice were monitored for 4 weeks; upon death, the liver and brain were removed, and histopathological examination was conducted. Surviving mice were killed at the end of the 4 weeks. The LD50 was calculated as described elsewhere [27]. Survival was analyzed by Kaplan-Meier analysis with a log-rank test; P < .05 was considered to be statistically significant.
Slot-blot hybridization.
Ten micrograms of genomic DNA from K. pneumoniae strains were vacuum blotted onto nylon membranes. Hybridization was performed for 16 h at 68°C with each biotin-labeled probe generated by PCR. The gene encoding 23S rRNA was used as a positive control. Detection was performed by use of the Southern-Light Chemiluminescent detection system (Tropix), in accordance with the manufacturer's instructions.
RESULTS
DNA microarray hybridization.
A total of 3146 PCR clones were randomly selected for the microarray. The coverage rate was 88%, according to the formula N = ln(1 - P)/ ln(1 - f) [28]. To test the redundancy of the library, 798 of the 3146 clones were randomly selected for sequencing. These clones contained 678 distinct sequences, representing a redundancy rate of 15%.
Comparison of 4 tissue-invasive strains (A1208, A3021, A5011, and NTUH-K2044) and 3 noninvasive strains (N3423, N3529, and N5322) revealed 12 clones with significantly decreased hybridization signals (defined as 3 SDs of the mean ratio) in the noninvasive strains (figure 1 and table 3). These 12 clones were sequenced and then compared with the 10× shotgun sequences of K. pneumoniae MGH 78578 (available at: http://www.genome.wustl.edu/projects/bacterial/kpneumoniae/). Of them, there were 10 clones (clones 312) that bore no similarity in sequence to MGH 78578. Of these 10 clones, 8 overlapped and extended to encompass an 9-kb fragment, whereas the other 2 matched to a 200-kb plasmid (pLVPK) of K. pneumoniae CG43 [29] (hereafter, "the large plasmid").
Sequencing of the flanking regions of the 8 clones in NTUH-K2044.
The flanking regions of the 9-kb fragment were sequenced from the genomic library until both ends matched in MGH 78578. A 19,640-bp fragment (GenBank accession number AB115591) that was obtained replaced a 5292-bp fragment in the genome of MGH 78578 (figure 2). BLAST searches revealed that this fragment contained 15 ORFs (figure 2 and table 4). The common flanking regions of NTUH-K2044 and MGH 78578 respectively contained oppA and an ORF encoding a putative diogenase subunit. The overall GC content of this region was 56.9%, similar to the 57.7% GC content of the remainder of the genome.
Annotation of this fragment revealed a modular structure with 4 regions (figure 2 and table 4). Region 1 (2934704) carried ORF13. These ORFs showed homology to proteins involved in glycogen phosphorylase (ORF1), an antianti- factor (ORF2), and a putative protease (ORF3). Region 2 (51048743) harbored ORF46. These ORFs exhibited high homology to the bacterial ferric ironuptake system, which is a bacterial ABC iron transport system [30]. They include Sfu of Serratia marcescens [25, 31], Hit of Haemophilus influenzae [32], Yfu of Yersinia pestis [33], Afu of Actinobacillus pleuropneumoniae [34], and Fbp of Neisseria gonorrhoeae [35]. Therefore, these ORFs were putatively designated kfuA, kfuB, and kfuC, respectively ("kfu" stands for Klebsiella ferric iron uptake). Region 3 (899011,786) contained ORF79. ORF7 displayed no significant homology to any sequences in the database. However, ORF8 revealed similarity to the gene yijO, which encodes a putative ARAC-type regulatory protein in E. coli. ORF9 showed homology to a protein involved in the biosynthesis of mitomycin [36]. Region 4 (11,78619,553) extended from ORF10 to ORF15. These 6 ORFs showed high homology to the PTS. PTS catalyzes translocation with concomitant phosphorylation of sugars and hexitols and regulates metabolism in response to the availability of carbohydrates [37]. Some PTS proteins have been tentatively linked with bacterial virulence [3840]. This 20-kb region was designated "the kfu/PTS region."
Prevalences of the kfu/PTS region and the large plasmid among K. pneumoniae strains.
Because sequences of clones 1 and 2 were present in the noninvasive strain MGH 78578 (table 3), we studied the prevalences of the kfu/PTS region and the large plasmid among the clinical isolates to find regions that are specific to tissue-invasive strains. Genomic DNA extracted from 46 tissue-invasive and 98 noninvasive strains was used for PCR analysis. We used the inside and outside primers to detect the presence of the kfu/PTS region (figure 3), on the following basis: If a clinical strain contained the region being tested, then the primer pairs for the flanking regions (outside primers) should fail to amplify the fragments; however, the inside primers should amplify products with a predicted length. Conversely, if the clinical strain did not contain the region, then PCR with the outside primer pairs would be positive, whereas PCR with the inside primers would be negative. We also used the inside sequences of clones 11 and 12 to detect the existence of the large plasmid.
The prevalence of the kfu/PTS region was significantly higher in tissue-invasive strains than in noninvasive strains (35/46 vs. 19/98; P = .0001, 2 test) (table 1). However, no significant correlation was observed between the large plasmid and clinically invasive disease (42/46 vs. 76/98; P = .077, 2 test).
Analysis of deletion mutants.
Three deletion mutants (NTUH-K2044 [kfu], K2044 [ORF79], and K2044 [PTS]) were constructed by use of a suicide vector (figure 4A). The growth of the mutants was compared with that of the wild-type strain in nutrient-rich, undefined LB medium. However, no significant differences were found.
The effect on virulence of each mutation was investigated in a mouse model (figure 4B and 4C). All of the mice inoculated with 103 cfu survived. Half of the mice died when inoculated with 104 cfu of the wild-type strain, K2044 (ORF79), or K2044 (PTS); there were no significant differences in survival among these 3 groups (K2044 [ORF79] vs. wild-type strain, P = .76; K2044 [PTS] vs. wild-type strain, P = .67; log-rank test) (figure 4C). In contrast, all of the mice inoculated with K2044 (kfu) at the doses of 104106 cfu survived and appeared to be healthy after 4 weeks. The survival of the mice inoculated with K2044 (kfu) differed significantly from that of the mice inoculated the wild-type strain (P = .0067, log-rank test) (figure 4C).
When inoculated with the wild-type strain, K2044 (ORF79), or K2044 (PTS) at the highest dose (106 cfu), most of the mice had died by 7 days after infection, with no obvious signs before death and with no pathological changes detected on histological examination; they were considered to have died of septic shock. At lower inoculation doses (104105 cfu), most mice died between day 12 and 21 after infection, with signs of lethargy, labored breathing, or trembling 12 days before death. Large liver and/or brain abscesses were observed in this group, and septic shock with possible organ failure was considered to be the cause of death. However, there was no histological change in the livers and brains obtained from the mice inoculated with K2044 (kfu) at doses of 104106 cfu (figure 5). Because the manifestations of K. pneumoniae infection observed in BALB/cByl mice were very similar to those observed in patients, we did not try other murine strains.
Functional analysis of the kfu system in K. pneumoniae.
K. pneumoniae kfuABC was found to be preceded by a putative 19-bp Fur box consensus sequence (figure 6A). The 3 genes of kfu were transcribed in the same direction and had short intergenic sequences (maximum 21 bp between kfuA and kfuB), suggesting that they were in a single transcriptional unit. RT-PCR analysis confirmed that the 3 genes were transcribed as a single operon (figure 6B).
Comparison of the growth rates of the wild-type strain, K2044 (kfu), MGH 78578, and a noninvasive strain, N3423, in an iron-chelated medium revealed slightly lower growth for K2044 (kfu) and MGH 78578 (figure 6C). The E. coli aroB mutant carrying kfuABC or sfuABC grew well under conditions of iron limitation. However, the growth of H1443 with vector only (pBR322) was significantly inhibited (figure 6D).
The distribution of the 3 chromosomal regions was further analyzed according to the clinical disease of the patients (table 5). Strains from the patients with PLA plus endophthalmitis or meningitis were positive for all 3 regions. However, when strains from the 4 patients with meningitis but without PLA were examined, 2 of the strains were found to be negative for all 3 regions, and 2 of the strains were found to be positive for the kfu/PTS and magA regions but not for the allS region.
DISCUSSION
In the present study, microarray comparison of the genomic DNA of 4 tissue-invasive K. pneumoniae strains and 3 noninvasive strains identified 12 clones with significantly different hybridization signals. Two clones that matched the sequence in MGH 78578 were probably the result of experimental variations, because both were present in the 2 groups of strains. Another 2 clones were located in a large plasmid. However, the prevalences of the large plasmid were invariant in the 2 groups of strains. The remaining 8 clones connected together and further extended to encompass a 20-kb fragment (table 3). Only the deletion mutant NTUH-K2044 (kfu) showed decreased virulence in vivo. Functional studies confirmed the operon's involvement in iron uptake. Because our array was estimated to cover only 88% of the entire K. pneumoniae genome, we could miss some regions specific to tissue-invasive strains; hence, the allS and magA regions were not identified by this method.
The 20-kb kfu/PTS region was markedly more prevalent among tissue-invasive strains. The kfu/PTS region encoded an iron-uptake system involved in virulence and fit the size range (10200 kb) of a pathogenicity island. However, the GC content of this region was similar to the remainder of the whole genome, and no mobile elements or insertion sequences were noted [42]. Thus, the fundamental nature of the heterogeneity of this specific region in K. pneumoniae awaits further study [43].
Acquisition of nutrients such as iron to sustain growth in the host environment is essential for bacterial pathogens to establish an infection. Iron uptake is also critical to pathogenesis as a vital cofactor for many components of microbial antioxidative stress defense, including such components as superoxide dismutase, catalase, and peroxidase [44]. We have shown here that the kfu operon was present in most of the genomes of the tissue-invasive K. pneumoniae strains we examined and was absent from most of the genomes of the noninvasive strains. It is possible that the presence of a functional kfu operon might principally or secondarily modulate virulence in vivo and so provide a strong competitive advantage to those strains that harbor it.
There was a significant difference in the prevalence of the kfu/PTS region between noninvasive control strains from NTUH and FEMH. Strains from FEMH were all isolated from patients with nosocomial infection, whereas strains from NTUH were all isolated from patients with community-acquired infection. This could be the reason for the genetic difference. In addition, there would be an epidemiological difference between strains from a medical center (NTUH) and a those from a community hospital (FEMH).
How K. pneumoniae enter into the bloodstream and liver has not yet been documented. However, bacterial cells would enter the bloodstream through M cells [45] or as a result of minor mucosal injuries of the gastrointestinal tract. Larger abscesses were found in the mice infected via ig inoculation, whereas, in the mice infected via ip inoculation, microabscesses were found. This finding supports the hypothesis that K. pneumoniae gains entry into the bloodstream via the gastrointestinal tract, because all venous returns in the gastrointestinal tract were collected via a portal vein into liver. Many bacteria were likely trapped in the liver by Kupffer cells; however, the tissue-invasive strains were resistant to phagocytosis and serum killing. This may result in the subsequent formation of liver abscesses.
The present study reinforces our awareness of the vital role that bacterial virulence factors play in the pathogenesis of PLA and metastatic infection. According to the prevalences of the 3 specific chromosomal regions in tissue-invasive strains, we were able to classify the 54 invasive strains into 3 groups: group 1 strains contained all 3 regions, group 2 strains contained 12 regions, and group 3 strains contained none of the regions. When all 3 regions were absent, the strains were only occasionally capable of causing PLA. The most interesting finding was that all of the strains from patients with PLA plus metastatic infection contained all 3 regions. Most of the group 3 strains were noninvasive (table 1), suggesting that they might be less virulent than the group 1 strains. That the group 1 strains had an increased ability to invade tissue may well relate to their enhanced survival and ability to compete for nutrients. The kfu/PTS region could enrich the ability of bacteria to secure iron, even in the relatively iron-deficient conditions of the human host. The allS region could help bacteria to compete for nitrogen sources via the allantoin-utilizing ability [15]. Moreover, the magA region could render bacteria resistant to phagocytosis by polymorphonuclear leukocytes and serum killing [16]. Therefore, the group 1 strains might be classified as a specific genotype that is associated with PLA and metastatic infection. Two strains from 4 patients with meningitis but without PLA were negative for all 3 regions, and the remaining 2 strains were negative for the allS region. These results suggest that different pathogenic mechanisms could be at work in patients with meningitis plus PLA and in those with meningitis only.
In conclusion, we have identified a 20-kb chromosomal kfu/PTS region in K. pneumoniae that is associated with iron acquisition and virulence. This region is more prevalent in tissue-invasive strains. Strains containing the kfu/PTS, allS, and magA regions are strongly associated with PLA and metastatic infection and may be classified as a specific genotype. However, a different virulence mechanism seems to be at work in patients with meningitis but without PLA. Therefore, the kfu/PTS region, as well as the allS and magA regions, can be exploited as a genetic marker for rapid molecular diagnosis and for tracing the source of these emergent tissue-invasive strains.
Acknowledgment
We thank Dr. Volkmar Braun, Universitat Tubingen (Tubingen, Germany), for providing Escherichia coli strain H1443 and pSZ1 plasmid.
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Divisions of Communicable Disease and Immunology and Retrovirology, Walter Reed Army Institute of Research, Washington, DC
Henry M. Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland
Background.
An assessment of biomarkers from an analysis of human peripheral blood mononuclear cell gene-expression profiles was made, to acquire an understanding of transcriptional changes associated with human immunodeficiency virus type 1 (HIV-1) infection in vivo.
Methods.
Supervised learning algorithms were used to create signature gene sets that could be used to distinguish seropositive from seronegative samples and delineate changes in disease status during the early stages of infection. Bioinformatic tools were used to classify persons and to functionally characterize groups of differentially expressed genes, to elucidate the impact of viral infection on host cell gene-expression patterns.
Results.
A 10-gene signature set that could be used to accurately determine the HIV-1 serostatus was identified. A 6-gene signature set was used to distinguish seropositive persons exhibiting differential changes in CD4+ T cell counts, with 93% accuracy. Functional classification of differentially expressed genes in HIV-1 indicated a preponderance of down-regulated genes with functions related to the immune response and apoptosis. Hierarchical cluster analysis in persons whose CD4+ T cell counts increased, compared with that in persons whose CD4+ T cell counts decreased, was characterized by the down-regulation of genes associated with apoptosis, mitochondrial function, protein biosynthesis, and RNA binding.
Conclusions.
Gene-expression profile analysis of a complex infectious virus, such as HIV-1, may be useful to elucidate the functional genomic relationships associated with viral infection.
The wide range of clinical manifestations of HIV-1 infection is the result of a complex set of host-virus interactions [1, 2]. Classically, clinical markers used to assess the state of infection involve static assessment of CD4+ T cell counts and plasma viral loads. Particularly useful to efforts to elucidate the mechanisms of HIV-1 viral pathogenesis is the study of groups of seropositive persons exhibiting divergent rates of disease progression during the 510 years after seroconversion [36]. Results of such studies indicate that long-term survival involves maintenance of a low viral load by a strong virus-specific immune response [79]. Importantly, rates of disease progression can be modified, at least temporarily, by the diligent use of antiretroviral drugs to lengthen survival and reduce morbidity [10, 11]. Lacking, however, are biomarkers that might be used to prognosticate the rate of HIV-1 disease progression and, by extension, the success of drug or vaccine intervention administered earlier during disease and treatment.
Precedent for the use of cell-associated biomarkers to prognosticate disease progression and response to treatment exists in the implementation of gene-expression profile analysis to classify certain cancers and tumor types [1218]. Extending the successful use, in oncology, of cellular expressionbased molecular classification systems to an infectious disease, we used gene-expression profile analysis to examine primary peripheral blood mononuclear cells (PBMCs) from HIV-1seropositive and seronegative persons, to (1) determine the fundamental gene-expression signature that can be used to classify a sample according to its serostatus, (2) classify samples as being from persons with divergent degrees of change in disease status, and (3) examine functional classes of genes impacted by HIV-1 infection in the context of what is known about the disease.
SUBJECTS, MATERIALS, AND METHODS
Clinical specimens.
PBMCs were obtained from seropositive persons who provided informed consent and who were enrolled in studies approved by local institutional review boards. Confirmed-seronegative samples were clinical discards from the mandatory US Military Force Screening Program that evaluates the serostatus of active personnel on a regular basis. Peripheral blood was collected, by venipuncture, in acid citrate dextrose, and PBMCs were separated by Ficoll-gradient (Sigma) centrifugation and were cryopreserved. Plasma aliquots were stored at -80°C.
Preparation of samples for GeneChip analysis.
Preparation of cellular RNA for GeneChip analysis, cDNA preparation and in vitro transcription, and staining and scanning of Affymetrix Human Focus GeneChips (Affymetrix) were performed essentially as described elsewhere [19].
Plasma viral load assessment.
The Roche AMPLICOR HIV Monitor test (version 1.5; Roche Diagnostics) was used to quantify the amount of HIV-1 RNA in plasma. All persons had a viral load above the cutoff value (>50 copies/mL) of the ultrasensitive test.
Repository information.
The Affymetrix data sets can be accessed at http://www.ncbi.nlm.nih.gov/geo/, under the accession number GSE2171.
GeneChip quality control.
Two criteria were used to determine GeneChip quality: (1) the scaling factor, determined by use of the Affymetrix Microarray Suite 5.0, with target signal intensity set to its default (500), and (2) the array outlier percentage, determined by use of dChip (version 1.3) [20]. CEL files were normalized at the probe level by use of the robust multichip average method [21]. Genes (probe sets) that had >50% "absent" calls were filtered out.
Classification and prediction.
Twenty-two seropositive and 7 seronegative samples were used as a training set to generate a set of genes that could be used to determine the serostatus of an unclassified sample, as described by Ramaswamy et al. [22]. To determine the optimal number of genes to be included in a predictor set, a weighted-voting classification algorithm was applied. The leave-one-out cross-validation method was used to simulate classification accuracy for the top 100 genes on the basis of a signal-to-noise statistic. Simulation results indicated the top 10 genes that achieved 100% classification accuracy in a training set and that were subsequently evaluated in a test set. These 10 genes composed the serostatus predictor set. The same approach was used to generate a 6-gene signature set to be used to distinguish samples from seropositive persons with differential changes in CD4+ T cell counts during the study period.
Differential regulation.
Differentially regulated genes were identified by use of the statistical program Significance Analysis of Microarrays (SAM) [23], and cluster analysis of microarray data sets was performed by use of Cluster and Treeview software (available at: http://rana.lbl.gov/EisenSoftware.htm).
Derivation of gene ontology and functional associations.
The functions and biological classifications of differentially regulated gene sets were further analyzed by use of the Web-based tools Onto-Express (available at: http://vortex.cs.wayne.edu:8080/index.jsp) [24] and Gene Ontology Tree Machine (available at: http://genereg.ornl.gov/gotm/) [25]. PathwayAssist (version 2.5; Ariadne Genomics) software was used for analysis of the biological pathway.
RESULTS
Characteristics of the study groups.
A total of 87 primary clinical samples consisting of human PBMCs were used in the present study, including 12 seronegative samples from healthy control subjects, 22 seropositive samples from drug-naive persons, 21 seropositive samples from persons who had received at least 1 antiretroviral drug regimen, and 32 seropositive samples from persons whose CD4+ T cell counts either decreased or increased during the study period. Seropositive persons with differential changes in CD4+ T cell counts may have received nucleoside reverse-transcriptase inhibitors (NRTIs) but not highly active antiretroviral therapy (HAART). These study groups were defined ad hoc, and samples were drawn from a specimen repository.
Table 1 shows descriptive statistics for the 22 seropositive samples from drug-naive persons. This group is a cross-sectional cohort of seropositive persons distinguished by having high, medium, or low plasma viral loads.
Table 2 shows descriptive statistics for the seropositive persons with differential changes in CD4+ T cell counts. In the present study, these 2 groups of persons with changes in CD4+ T cell counts were defined by the magnitude and direction of the change in CD4+ T cell counts. Emphasis was placed on the transcriptional profiling of the early stages of infection in persons whose CD4+ T cell counts either increased or decreased between 2 consecutive time points during a 27-month period. There was no clinically relevant difference between the 2 groups during the interval between seroconversion and time point 1 (TP1), either for those persons whose CD4+ T cell counts decreased (mean ± SE, 1.0 ± .07 years) or for those persons whose CD4+ T cell counts increased (mean ± SE, 1.3 ± .03 years). There was no statistically significant difference between the 2 groups in terms of CD4+ T cell counts at TP1. Persons whose CD4+ T cell counts decreased were defined by a decrease of 8.29 CD4+ T cells/mL/month, whereas persons whose CD4+ T cell counts increased were defined by an increase of 4.80 CD4+ T cells/mL/month. Plasma viral loads at time point 2 (TP2) were significantly different between the 2 groups (mean ± SE, 89,075 ± 13,920 copies/mL in the group with decreasing CD4+ T cell counts vs. 10,461 ± 1961 copies/mL in the group with increasing CD4+ T cell counts; P = .01). The antiretroviral drug treatment regimens for persons in both groups are presented in table 3.
By use of supervised learning algorithms and a leave-one-out cross-validation method, the 10-gene signature set derived from the training set was applied to an independent test set of samples that were blinded with regard to HIV-1 serostatus, to assess the accuracy of classification. The results of the classification analysis for both the training set and the test set are shown as 3-dimensional principal-component plots (figure 1C). An accuracy of 93% was demonstrated for the 58 samples included in the test set. Four of the samples that were classified as seronegative were misclassified and, when unblinded, were determined to be seropositive. Although the training set was composed entirely of samples from persons who were completely drug naive, the test set was composed of samples from persons who could have been receiving any antiretroviral treatment. As this set was the most clinically relevant set, we felt that this conservative analysis was the most appropriate method to classify HIV-1positive samples.
Longitudinal analysis revealed striking differences in gene expression between the 2 groups. The majority of differentially expressed genes that changed over time were found exclusively in samples from persons whose CD4+ T cell counts increased (420 genes), compared with those whose CD4+ T cell counts decreased (15 genes). Gene-expression values for the 420 genes in the longitudinal data set and the 531 genes in the cross-sectional data set were expressed as log2 fold changes relative to the mean expression values from 12 seronegative persons and are shown as the average gene-expression ratio, in a centroid plot (figure 3D). The changes in expression that distinguished the 2 groups from each other were characterized by a switch in the pattern of gene expression from one of similar early induction in both groups to transcriptional repression in those persons whose CD4+ T cell counts increased.
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DISCUSSION
We determined whether a set of biomarkers that separate persons on the basis of their HIV-1 serostatus, independent of the amount of viremia present, could be identified. We found that host transcriptional profiling by use of unsupervised and supervised clustering methodologies could be used to classify persons according to serostatus, with a high degree of accuracy. The observations made in the present study are derived from an assessment of the PBMC compartment, which represents a highly heterogeneous mixture of cell types. Although sampling from this compartment facilitates access to clinical specimens, it may not reflect gene-expression patterns that are associated with specific cell types or processes confined to tissue-associated germinal centers known to be important in HIV-1 disease. Furthermore, gene-expression patterns that we identified by use of the Affymetrix GeneChip platform, a highly redundant oligomer array system, may differ from those identified by use of cDNA arrays or other array platforms [26].
Analysis of samples from drug-naive persons showed that >97% of all differentially expressed genes were down-regulated or underexpressed, compared with those from seronegative persons. Assessment of the functions of genes whose expression is impacted by HIV-1 revealed clusters of genes involved in cell proliferation and the nucleosome. Changes in chromatin structure and nucleosome remodeling include processes that are linked to transcriptional regulation by altering DNA replication and gene expression through accessibility to transcription factors, activators, and repressors involved both in host cell activity and regulation of HIV-1 gene expression [27, 28].
Immune-response genes that are usually transcriptionally repressed in HIV-1seropositive patients were overrepresented in the present study. Several of the genes that were significantly repressed have previously been shown to play central immunomodulatory roles in HIV-1 infection. Examples include HLA-DRB3, HLA-DRA, HLA-DMB, HLA-DQA1, and HLA-DOB genes, in which impaired class II expression contributes to the global immunosuppression observed in HIV-1 infection [29, 30]. CD14, which was down-regulated in persons in the present study, has previously been shown to be involved in lipopolysaccharide-induced stimulation of HIV-1 replication [31]. Interleukin (IL)15 and IL-16 were likewise repressed during HIV-1 infection. Studies in nonhuman primates have demonstrated that transcription of these cytokines in macaques infected with pathogenic isolates of simian immunodeficiency virus plays a role in containing viral replication [32, 33]. IL-16 has been shown to repress HIV infection in lymphocytes and monocytes by inhibiting viral transcription.
Viruses have evolved strategies to evade immune responses by enhancing viral replication and decreasing host cell survival, by modulation of genes of the NF- transcription-factor pathway [34]. A set of genes involved in the positive regulation of the I- kinase/NF- cascade was found to be repressed during HIV infection. NF- activation is induced by I- kinases, which are involved in orchestrating the host immune response against infection while, at the same time, promoting HIV-1 replication. In drug-naive seropositive persons, modulation of the NF- pathways during infection can also profoundly affect the pathways that influence the host cell cycle and regulation of cellular proliferation.
Transcriptional repression of signal transductionpathway genes involved in the regulation of NF- by HIV-1 can have dual, opposing effects, such as accelerating apoptosis or protecting cells from programmed cell death. Thus, it is not surprising to find that, in the present study, transcriptional activation or repression of functional clusters of differentially expressed genes involved in programmed cell death were identified as prominent features of HIV-1 infection. Our observations extend many of those made in gene-expression profile analyses of lymph node samples from seropositive persons receiving aggressive HAART regimens, in that productive viral infection is associated with the modulation of genes associated with the immune function, activation, and apoptosis [35].
We next explored the potential of using host biomarkers derived from gene-expression profile analysis to distinguish persons with differential changes in CD4+ T cell counts during the early stages of infection. PBMCs from these persons were successfully classified by use of a set of 6 predictor genes. It is necessary to consider that, although the selection of a small number of genes may yield a high degree of accuracy when used for classification purposes, such a limited set of genes is probably not reflective of the complex gene functions and interactions that distinguish persons with different disease states.
Analysis of gene-expression profiles in these 2 groups revealed several features that were not observed in investigation of differentially expressed genes from the drug-naive group. We found that the persons whose CD4+ T cell counts increased exhibited the most change in gene expression during the study period. By contrast, between TP1 and TP2, very few genes from persons whose CD4+ T cell counts decreased showed changes in expression. Differential gene expression between the 2 groups was greater at TP2 than at TP1, logically reflecting the study design, which closely matched persons at TP1. By TP2, the persons in the 2 progression groups differed significantly with respect to CD4+ T cell counts, plasma viral loads, and associated cellular gene-expression profiles. This observation was surprising, since it exposed a seemingly contradictory divergence in gene expression that occurred in persons whose viral infection progressed or remained inactive during >2 years of surveillance. We had speculated that groups of functionally expressed genes involved in programmed cell death would be incrementally activated or induced in persons whose CD4+ T cell counts decreased over time, compared with those in persons whose CD4+ T cell counts increased. Conversely, we discovered that persons whose CD4+ T cell counts increased had the most-acute changes in gene expression. These changes were reflected in clusters of statistically significant down-regulated genes belonging to functionally overrepresented groups involved in processes related to cell death. These genes are associated with mitochondrial functions, including electron transport, conversion of NADH to ubiquinone, and cytochrome c oxidase activity. The observations that genes associated with the mitochondria were differentially expressed must be qualified in the context that NRTIs are known to induce mitochondrial toxicity [36]. However, since the use of NRTIs in the 2 study groups was equivalent, the identification of differentially expressed mitochondrial genes associated with apoptosis remains significant.
The finding that biological processes, such as programmed cell death, distinguished persons with differential changes in CD4+ T cell counts was further supported by construction of a gene-interaction network by use of PathwayAssist. A gene that formed a central node in this biological-interaction network was TNFRSF6 (CD95 or FADD) [37]. That productive infection with HIV-1 resulted in down-regulation of the immune response and modulation of apoptosis may reflect mechanisms in the host cell that either foster viral production in a stable, otherwise healthy cellular host or control infection by down-regulating genes required for disease progression.
The present study has demonstrated that a complex infectious virus, such as HIV-1, can be effectively characterized by the use of gene-expression profile analysis and is a significant step toward the derivation of a set of biomarkers based on differential levels of transcription that may become powerful tools in the assessment of interventions that foster a slower rate of disease progression, especially when used with classic markers, such as CD4+ T cell count and viral load. Finally, identification of specific gene pathways impacted by viral infection may lead to the use of less-toxic targeted therapies. Further evaluation of the prognostic power of gene-expression analysis in HIV-1 disease awaits studies of greater numbers of persons.
Acknowledgments
We thank Dr. Deborah L. Birx (Director of the Military HIV-1 Research Program), for support of this effort, and Drs. Nelson Michael and Mark Lewis, for helpful discussions. Expert research of clinical data records and technical laboratory work in support of this study were executed by Eva Calero (Walter Reed Army Institute of Research) and Martin Nau, Alma Arnold, and Caroline Liebig (Henry M. Jackson Foundation).
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