Molecular analysis of bovine spongiform encephalopathy infection by cDNA arrays

Recently, DNA array analysis has been applied to obtain global gene-expression data for two diseases in the transmissible spongiform encephalopathy (TSE) family: Creutzfeldt–Jakob disease (CJD; Baker et al., 2004) and scrapie, a TSE disease of sheep that has been transmitted to laboratory rodents (Booth et al., 2004a, b; Brown et al., 2004; Riemer et al., 2004; Xiang et al., 2004; Greenwood et al., 2005). We now report the first DNA array analysis of differential gene expression in bovine spongiform encephalopathy (BSE), using a 17 000 mouse gene cDNA array (Tanaka et al., 2000) and brain tissue from VM mice infected with the 301V strain of BSE. Many of the genes identified as being expressed differentially in these experiments are members of some of the same functional groups that have been identified in the global gene-expression studies on scrapie and CJD, as well as studies on other neurodegenerative diseases such as Alzheimer’s disease. The gene-expression profiles for BSE-infected mice showed a subset of striking differences compared with normal, same-age mice, with no overlap between the two by cluster analysis.

VM mice were obtained initially from the Institute for Animal Health (IAH), Edinburgh, UK, and then bred and supplied to our laboratory by Harlan Sprague Dawley (Bruce et al., 1997). The 301V strain of BSE infectivity was obtained from Dr Moira Bruce of the Neuropathogenesis Unit of the IAH (Bruce et al., 1997). All work with BSE was done in a USDA-certified Biosafety Level 3 (BSL3) laboratory. All protocols for the use of animals were approved by the Institutional Animal Care and Use Committee of the University of Maryland, Baltimore, MD, USA, following NIH guidelines. Male mice (157–164 days old) were inoculated intraperitoneally (i.p.) with 60 μl brain homogenate [10 % (w/v) in PBS, pH 7.2] prepared from 301V BSE-infected mouse brain. The inoculated mice were monitored for symptoms of disease during the 203 day incubation period and were euthanized by CO₂ inhalation when they displayed the full panel of BSE symptoms (rough coat, hunched posture and weight loss). Uninfected mice were also euthanized at the same time by using identical protocols. Brains were dissected quickly, snap-frozen in liquid nitrogen and stored at −80 °C.

Separate RNA preparations were obtained from each of three individual BSE-infected brains (n_infected=3) and three individual normal brains (n_normal=3). Each RNA preparation was tested in triplicate for a total of 18 arrays. Each frozen brain was converted separately to a frozen tissue powder by using a cryogenic mill (model JFC-300; DyChrom) located within the BSL3 facility. The frozen, powdered brain tissue was transferred to a pre-weighed 50 ml Falcon tube pre-cooled to −80 °C. Total RNA was prepared from the powdered brain-tissue samples by using TRIzol reagent (Life Technologies), chloroform and 2-propanol, according to the manufacturer’s instructions. The resulting pellet from the extraction was washed with ethanol, air-dried and dissolved in DEPC-treated H₂O to a final concentration of 1.0 μg ml⁻¹. RNA concentration, visual inspection of RNA and the RNA integrity number (8–10) as calculated by the rin algorithm (Schroeder et al., 2006) were determined by using an Agilent 2100 Bioanalyzer running Bioanalyzer Expert software vB.01.03 and an Agilent RNA LabChip. Poly(A) RNA was isolated from total RNA by using an oligo-dT column [MicroPoly(A) Purist kit; Ambion]. cDNA probes were prepared from poly(A) RNA by using SuperScript reverse transcriptase (Invitrogen) in the presence of [α-³³P]dCTP (ICN Pharmaceuticals Inc.) as described previously (Tanaka et al., 2000).

The entire list of genes present on the m17k array is available online at . Array methods and hybridizations were performed as described previously (Tanaka et al., 2000). Differences in gene expression between normal and BSE-infected mice were calculated by using the ‘Z score’ normalization method of Cheadle et al. (2003). This is a conservative method of analysis that utilizes a logarithmic transformation of the raw data, de-emphasizes the contributions of outliers and noise and facilitates comparisons across experiments. Three criteria were applied to identifying genes that were scored as being expressed differentially: a Z ratio with an absolute value of ≥1.5, a P value of <0.05 by t-test and a raw signal intensity (as measured by pixel density) above 300 with a maximum coefficient of variance (cv.) of 0.30. Software used for expression profiling and data visualization was KyPlot v2.0 (Kyence Inc.) and Mathematica v4.4 (Wolfram Research Inc.).

Real-time PCR confirmation was performed on 31 genes indicated as being expressed differentially by the arrays, as well as on one gene, β-actin (actb), found to be expressed non-differentially by the array data, and three other genes of interest: cathepsin D (ctsd), amyloid β precursor protein (app) and glial fibrillary acidic protein (gfap). These genes were selected because of their abnormal expression level compared with normal samples or because of their relevance to BSE. Total RNA (2 μg) from normal and BSE-infected mouse brain was used to generate cDNA using SuperScript II reverse transcription reagents (Invitrogen). Real-time PCR was performed by using the Roche LightCycler system with a LightCycler FastStart DNA Master^PLUS SYBR green I kit (Roche Diagnostics) according to the manufacturer’s instructions. Reactions were incubated for 10 min at 95 °C (denaturation) before 50 cycles of 95 °C for 10 s, 55 °C for 5 s and 72 °C for 10 s (amplification), followed by a 40 °C incubation for 30 s (cooling). Fluorescence was detected in channel F2/F1 and measured at the end of each amplification cycle and continuously during the melting-curve cycle. LightCycler Software v3.5.3 was used to measure the crossing point for each reaction using the second derivative maximum method (Wittwer et al., 1997). Amplicon specificity was documented by gel electrophoresis, melting-curve analysis and, in some cases, direct PCR product sequencing. Pre-synthesized, commercially available PCR primers (see Supplementary Table S1, available in JGV Online) designed for SYBR green real-time PCR applications were used in the validation studies (Superarray Bioscience Corporation). The comparative threshold cycle (ΔC_T) method (Livak & Schmittgen, 2001) was used to determine relative quantification of gene expression for each gene compared with multiple control genes for more accurate and reliable normalization of gene-expression data (Vandesompele et al., 2002). Both glyceraldehyde-3-phosphate dehydrogenase (gapdh; indicated by array analysis as not being expressed differentially) and neurotrophin 3 (nt-3; found by real-time PCR analysis as not being expressed differentially) were used as control genes and calibrated against gfap, a protein well documented to be upregulated in TSE disease (Duguid et al., 1988, 1989; Lazarini et al., 1994). gfap was shown to be overexpressed in BSE-infected mice compared with normal mice when measured relative to both gapdh and nt-3.

Pairwise MA plots (Dudoit et al., 2002) and scatter plots of the raw intensity replicate hybridization values (three hybridizations per sample, 18 hybridizations in total) are shown in Supplementary Fig. S1 (available in JGV Online). Analysis of the array data indicated that 116 genes were upregulated and 180 genes downregulated in BSE-infected mouse brain tissue compared with normal controls. Eight of the genes identified as being expressed differentially were represented on the array by two different cDNA sequences with different accession numbers. The Z ratio values for six of these pairs were very similar, but for two of the genes, mitogen-activated protein kinase kinase kinase kinase 5 (map4k5) and nascent polypeptide-associated complex alpha polypeptide (naca), the Z ratios differed significantly (an array expression value of 3.30 and −2.14 for map4k5 and an array expression value of 1.61 and −2.21 for naca). In these two cases, real-time PCR validation was used to determine the Z ratio reported, −2.7 for map4k5 and −3.3 for naca (Fig. 1⇓).

Because BSE-infected animals were inoculated i.p. rather than intracranially (i.c.), we used brain tissue from normal, uninoculated animals as controls rather than tissue from sham-inoculated animals. Array studies on scrapie-infected mice have shown that, even when inoculation is done i.c., the expression profile of sham-inoculated animals is not significantly different from that of uninoculated animals (Booth et al., 2004a, b; Brown et al., 2004; Xiang et al., 2004).

Sequences initially identified by microarray as being expressed differentially for which the gene has been named (from Unigene; , as of 3 October 2005) and/or assigned a function (from search of databases using source; ) are shown in Supplementary Table S2, available in JGV Online. Semiquantitative real-time PCR analysis (Fig. 1⇑) shows that 26 of 35 genes analysed were expressed differentially. Agreement between real-time PCR and microarray data has been shown to be variable and gene-dependent (Etienne et al., 2004).

gfap, which has long been known to be upregulated strongly in scrapie (Diedrich et al., 1987; Duguid et al., 1988) and CJD (Manuelidis et al., 1987; Kordek et al., 1997), was not represented on the m17k array, but was included in the real-time PCR studies and was found to be overexpressed by 9.98-fold in the BSE-infected samples relative to normal controls. Eighteen genes identified by array as being expressed differentially in BSE brain are involved in ubiquitin-mediated protein degradation (Table 1⇓). The ubiquitin system plays a major role in the regulation of protein turnover (Finley et al., 2004). Proteins destined for degradation are tagged with mono- or polyubiquitin tails, and are then directed to either the proteasome or the lysosome for degradation. Aberrations in the ubiquitin proteolytic system have been implicated in a number of neurodegenerative diseases, sometimes in a causal role and sometimes as a pathological result (Ciechanover & Brundin, 2003). In scrapie, ubiquitin conjugates have been shown to accumulate in lysosome-related bodies very early in disease and to increase along with PrP accumulation and neuropathology (Laszlo et al., 1992; Lowe et al., 1992). Ubiquitin itself has been reported to be upregulated in scrapie (Kenward et al., 1994), in contrast with our array results, which show ubiquitin C to be slightly downregulated. It is not clear at this point whether the differences are due to technical factors, such as the array platform, or biological differences, such as the TSE strain.

With respect to lysosomal functions, array analysis indicated cathepsin D, a lysosomal aspartic protease, to be upregulated (Z ratio, 1.9), but because the signal intensity for this gene was below our chosen, stringent coefficient of variance limit, it does not appear in the initial list of differentially expressed genes (see Supplementary Table S1, available in JGV Online). Cystatin C, a potent inhibitor of lysosomal cysteine proteases, was indicated strongly as being upregulated in our array data. It, along with other cystatins, has also been reported to be upregulated in scrapie (Duguid et al., 1988, 1989; Duguid & Dinauer, 1990; Riemer et al., 2000; Booth et al., 2004a, b; Brown et al., 2004; Xiang et al., 2004) and CJD (Baker & Manuelidis, 2003).

Eight of the sequences identified by our array results are involved in protein folding, including a member of the heat-shock 90 family and alpha crystalline B (Table 1⇑). Heat-shock proteins and stress proteins, which function as molecular chaperones and aid in the correct folding of proteins, have been found repeatedly to be upregulated in scrapie (Duguid et al., 1988; Diedrich et al., 1993; Kenward et al., 1994; Doh-ura et al., 1995; Tatzelt et al., 1995, 1998). Molecular chaperones and the ubitquitin/proteasome system have been described as complementary systems that work to protect the cell from damage by abnormal proteins (Finley et al., 2004). Involvement of both of these systems in TSE disease indicates a host response to stress and is consistent with the major role that PrP^res, a misfolded version of the normal host protein, plays in these diseases. PrP has been found to be associated with the chaperone BiP (Jin et al., 2000).

Eight of the sequences identified by our array analysis as being expressed differentially in BSE are involved in apoptosis (Table 1⇑). This is not surprising, given that the clinical stage of all TSE diseases is marked by widespread neuronal death and that apoptosis has been shown, in the case of scrapie, to be a mode of this neuronal death (Giese et al., 1995). Some evidence from scrapie has suggested that one of the normal functions of PrP is to inhibit apoptotic pathways and that disruption of this function may be one of the pathogenic mechanisms of TSE disease (Kim et al., 2004). Another functional theme among the differentially expressed genes is zinc binding (Table 1⇑). In particular, the strong upregulation of the metallothionein gene mt2 agrees with earlier reports of mt1 and 2 upregulation in BSE-infected cattle (Hanlon et al., 2002) and in scrapie-infected rodents (Duguid et al., 1988; Dandoy-Dron et al., 1998; Riemer et al., 2000).

Seven identified gene candidates are also involved in calcium ion binding, transport or homeostasis (Table 1⇑). This is consistent with array studies on scrapie-infected neuronal cell lines, which have also identified genes involved in calcium binding, transport and homeostasis (Greenwood et al., 2005). Calcium homeostasis is involved intimately in many of the other functions identified by our array results as being affected in BSE, including metal toxicity (Valko et al., 2005) and the regulation of both apoptosis and necrosis (Rao et al., 2001; Brini, 2003; Artal-Sanz & Tavernarakis, 2005). Calcium-binding proteins have been implicated in neurodegenerative disease (Braunewell, 2005). Sixteen of the differentially expressed genes are involved with regulation of transcription. A number of other genes identified by the array analysis may be involved in one or more of the functional categories discussed above, as the gene ontology data are continuously evolving and genes are often involved in multiple biological processes.

Principal-component analysis (Fig. 2⇓) shows the clustering of the three BSE-infected and three normal mice. In this depiction of the data, the correlation coefficients are represented in a three-dimensional space, with samples exhibiting similar patterns of gene expression clustering closer together than samples with dissimilar patterns. Principal-component analysis readily differentiated the infected samples from normal samples.

In these experiments, the m17k microarray platform was utilized to screen expression changes in over 16 896 annotated genes in BSE-infected mouse brain relative to normal mouse brain. The global gene-expression profiles of BSE-infected samples were markedly different from, and completely non-overlapping with, those of normal samples. Extending these studies to earlier times in the incubation of BSE, when neurodegeneration is less pronounced, may reveal genes associated more closely with the infection event.