Highly tissue substructure-specific effects of human papilloma virus in mucosa of HIV-infected patients revealed by laser-dissection microscopy-assisted gene expression profiling

Abstract

Human papilloma virus (HPV) causes focal infections of epithelial layers in skin and mucosa. HIV-infected patients on highly active antiretroviral therapy (HAART) appear to be at increased risk of developing HPV-induced oral warts. To identify the mechanisms that allow long-term infection of oral epithelial cells in these patients, we used a combination of laser-dissection microscopy (LDM) and highly sensitive and quantitative, non-biased, two-step multiplex real-time RT-PCR to study pathogen-induced alterations of specific tissue subcompartments. Expression of 166 genes was compared in three distinct epithelial and subepithelial compartments isolated from biopsies of normal mucosa from HIV-infected and non-infected patients and of HPV32-induced oral warts from HIV-infected patients. In contrast to the underlying HIV infection and/or HAART, which did not significantly elaborate tissue substructure-specific effects, changes in oral warts were strongly tissue substructure-specific. HPV 32 seems to establish infection by selectively enhancing epithelial cell growth and differentiation in the stratum spinosum and to evade the immune system by actively suppressing inflammatory responses in adjacent underlying tissues. With this highly sensitive and quantitative method tissue-specific expression of hundreds of genes can be studied simultaneously in a few cells. Because of its large dynamic measurement range it could also become a method of choice to confirm and better quantify results obtained by microarray analysis.

Figure 1

Schematic outline of LDM-assisted multiplex real-time RT-PCR. Shown are the steps involved in generating gene expression profiles of tissue subcompartments and small clusters of cells from frozen sections isolated by laser-dissection microscopy. For details, see Materials and Methods.

Figure 2

Multiplex pre-amplification yields linear amplification over a wide range of pre-amplification cycles. A–E: Results from real-time RT-PCR analysis of 88 genes (A, strongest expressers; E, weakest expressers) quantified in LDM-isolated tonsil material following multiplex RT-PCR pre-amplification when varying 15 to 30 pre-amplification cycles were used. Note the good correlation between Ct values obtained with real-time RT-PCR and the number of amplification cycles used during the first (multiplex) amplification step between 20 and <30 amplification cycles. Ct value of 40, 0 copies of RNA.

Figure 3

Strong correlation of gene copy number and cycle threshold in multiplex RT-PCR. Indicated numbers of RNA copies obtained from cloned PCR products (CD23 for top, CCR6 for bottom) were amplified by real-time RT-PCR in the absence (a, r² = 0.9862) or presence (b) of an excess of 10 different control RNA (100,000) copies) (diamonds, solid line; r² = 0.9957) and 10 (squares, dashed line; r² = 0.9987), or 90 (triangles, speckled line; r² = 0.9845) distinct primer sets. None of those conditions significantly affected the linearity or sensitivity of the assay.

Figure 4

Relationship between RNA input copy number and Ct value. Shown are the mean ± SD Ct values obtained by repeated amplification of 5000 copies of cloned PCR product (RNA) from the indicated genes. Although Ct values are similar for each gene, differences in Ct values exist between amplification of same amounts of RNA from different genes. Titration of control RNA for each gene showed a near perfect correlation between input RNA and cycle threshold value (Figure 3 and data not shown).

Figure 5

Strong correlation between gene expression levels and tissue of origin. The degree of variation for expression of individual genes within similar tissue structures from the same patient was studied. For this amplification of 88 genes was conducted for two different epithelial and follicular areas from the same human tonsil isolated by LDM. Shown are the Ct values for each of the two collections, plotted against each other. The tightest correlations were found for genes that resulted in Ct values below 25 (area between dotted lines marks Ct value differences of <2). Higher Ct values often resulted in one analysis not showing any gene expression (Ct, 40).

Figure 6

Amplification of GAPDH accurately reflects the size of captured tissue areas. B: Indicated areas marked 1 to 8 of normal oral mucosa from HIV⁺ patients were captured by laser-dissection microscopy, RNA was extracted and expression levels for GAPDH were determined as described in Materials and Methods and shown in Table 1, column 2. From this relative areas of tissue were calculated as “relative diameters” shown in Table 1, column 4 and are displayed graphically in (A) (see also Table 1).

Figure 7

Isolation of mucosal tissue substructures by LDM. Fresh-frozen normal buccal mucosa is shown before sectioning by LDM (A) and following removal of (e) stratum spinosum (B) and (b) basal layer, and suprabasal stratum spinosum (C). Box in (A) indicates area shown in (C). Isolation of superficial connective tissue was done from area marked (c). Isolated tissue samples were verified by microscopy as shown in (D) for stratum spinosum and processed for RNA isolation as outlined in Materials and Methods.

Figure 8

Significant differences in gene expression of stratum spinosum from oral warts and normal mucosa from HIV-infected patients. Shown is a graphic representation of the fold-differences in gene expression (listed in Table 2) between the stratum spinosum of normal oral mucosa and of oral warts both from HIV-infected patients on HAART.