gene expression in the medulla following oral infection of cattle with bovine spongiform...

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Gene Expression in the Medulla Following OralInfection of Cattle with Bovine SpongiformEncephalopathyLuciane M. Almeida a , Urmila Basu a , Bina Khaniya a , Masaaki Taniguchi a , John L. Williamsb , Stephen S. Moore a & Le Luo Guan aa Department of Agricultural, Food and Nutritional Science , University of Alberta ,Edmonton, Alberta, Canadab Parco Tecnologico Padano, Via Einstein , Polo Universitario, Lodi, ItalyPublished online: 06 Jan 2011.

To cite this article: Luciane M. Almeida , Urmila Basu , Bina Khaniya , Masaaki Taniguchi , John L. Williams , Stephen S.Moore & Le Luo Guan (2011) Gene Expression in the Medulla Following Oral Infection of Cattle with Bovine SpongiformEncephalopathy, Journal of Toxicology and Environmental Health, Part A: Current Issues, 74:2-4, 110-126, DOI:10.1080/15287394.2011.529061

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Journal of Toxicology and Environmental Health, Part A, 74:110–126, 2011Copyright © Taylor & Francis Group, LLCISSN: 1528-7394 print / 1087-2620 onlineDOI: 10.1080/15287394.2011.529061

GENE EXPRESSION IN THE MEDULLA FOLLOWING ORAL INFECTION OF CATTLEWITH BOVINE SPONGIFORM ENCEPHALOPATHY

Luciane M. Almeida1, Urmila Basu1, Bina Khaniya1, Masaaki Taniguchi1, John L. Williams2,Stephen S. Moore1, Le Luo Guan1

1Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton,Alberta, Canada2Parco Tecnologico Padano, Via Einstein, Polo Universitario, Lodi, Italy

The identification of variations in gene expression in response to bovine spongiformencephalopathy (BSE) may help to elucidate the mechanisms of neuropathology and prionreplication and discover biomarkers for disease. In this study, genes that are differentiallyexpressed in the caudal medulla tissues of animals infected with different doses of PrPBSE at12 and 45 mo post infection were compared using array containing 24,000 oligonucleotideprobes. Data analysis identified 966 differentially expressed (DE) genes between control andinfected animals. Genes identified in at least two of four experiments (control versus 1-ginfected animals at 12 and 45-mo; control versus 100-g infected animals at 12 and 45 mo)were considered to be the genes that may be associated with BSE disease. From the 176 DEgenes associated with BSE, 84 had functions described in the Gene Ontology (GO) database.Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of 14 genes revealedthat prion infection may cause dysfunction of several different networks, including extracel-lular matrix (ECM), cell adhesion, neuroactive ligand–receptor interaction, complement andcoagulation cascades, MAPK signaling, neurodegenerative disorder, SNARE interactions invesicular transport, and the transforming growth factor (TGF) beta signaling pathways. Theidentification of DE genes will contribute to a better understanding of the molecular mecha-nisms of neuropathology in bovine species. Additional studies on larger number of animalsare in progress in our laboratory to investigate the roles of these DE genes in pathogenesisof BSE.

Bovine spongiform encephalopathy (BSE),one of the transmissible spongiform encepha-lopathies (TSE) diseases, is a fatal cattle disor-der caused by progressive neurodegenerationof the central nervous system (CNS), leadingslowly but inexorably to death (Prusiner, 1998).BSE captured worldwide attention becauseof its impact on the farming industry andinternational trade and, more importantly,

This research was supported by PrionNet Canada, Alberta Prion Institute and Alberta Bovine Genomic Program. We thank theVeterinary Laboratories Agency (Weybridge, UK) for providing the tissue samples to prepare RNA used in this study (funded by Defraproject SE1736 and EU project FAIR CT98-778). JLW thanks the Cariplo Foundation for its support.

Current address for Masaaki Taniguchi is Animal Genome Research Unit, National Institute of Agrobiological Sciences, 2 Ikenodai,Tsukuba, Japan.

Address correspondence to Le Luo Guan, 310D Agr/For Centre, University of Alberta, Edmonton, Alberta, Canada, T6G2P5. E-mail:[email protected]

its transmission to humans, causing a fatal vari-ant form of Creutzfeldt–Jakob disease (Will,2003). The pathology of TSE is associatedwith posttranslational conformational conver-sion of host-encoded cellular prion (PrPC)to a misfolded disease isoform of the prionprotein (PrPTSE), which is highly enrichedin β-sheets and partially resistant to pro-tease digestion (Prusiner, 1998). Accumulation

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GENES ASSOCIATED WITH BSE PATHOGENESIS 111

of PrPTSE may be associated with neu-ronal death and the appearance of vacuolesin the brain, giving the typical spongiformappearance.

While changes in the morphology of theCNS associated with BSE disease are welldocumented, the underlying molecular eventsare poorly defined. The BSE neurodegener-ation process involves several cell types thatcould have diverse cellular interactions andaffect the function of multiple genes. Severalapproaches were used to investigate the molec-ular mechanisms involved in neurodegenera-tion in prion disease by the identification ofdifferentially expressed (DE) genes associatedwith TSE. These studies were based upon dif-ferential gene expression analysis using cDNAlibraries (Diedrich et al., 1991), mRNA dif-ferential display (Dandoy-Dron et al., 1998),suppression subtractive hybridization (Kopaceket al., 2000), and more recently microar-rays (Riemer et al., 2004; Xiang et al., 2004;Greenwood et al., 2005; Skinner et al., 2006;Sawiris et al., 2007; Martínez & Pascual,2007; Sorensen et al., 2008; Fasano et al.,2008). Large numbers of DE genes were iden-tified using the microarray approach fromseveral different animal models of TSE infec-tion, commonly using mice and hamsters.Rodent models have been useful in studyingsome aspects of disease pathogenesis; how-ever, it would be more appropriate to ana-lyze the process in the natural target speciesinfected by oral route, as biomarkers for priondisease discovered in murine models (Mieleet al., 2001) have not provided a discrim-inatory diagnostic test for BSE infection ofcattle or scrapie infection of sheep (Brownet al., 2007). Furthermore, different studiesshowed that TSE pathogenesis varies depend-ing on the route of infection (Sales, 2006;Sigurdson et al., 2008). To date, there has beenno report on global gene expression profilingof brain tissues of cattle orally infected withBSE.

In the present study, gene expression pro-files in medulla tissues of cattle orally infectedwith different amounts of PrPBSE-infected

material were analyzed. A group of 167genes differentially expressed (DE) betweencontrol and infected animals were identifiedthat may be associated with BSE disease.Quantitative reverse-transcription polymerasechain reaction (RT-PCR) analyses were per-formed for eight selected genes to validatethe microarray results. Gene Ontology andKyoto Encyclopedia of Genes and Genomes(KEGG) analysis of the DE genes was used toobtain more information on the specific bio-logical processes and pathways affected by BSEinfection. Comparing the global gene expres-sion between control and BSE-infected ani-mals, and identification of variations in geneexpression in response to BSE, may help elu-cidate the mechanisms of neuropathology andprion replication.

MATERIAL AND METHODS

BSE Animals and RNA ExtractionMedulla samples used in this study were

collected from male steers in VeterinaryLaboratories Agency (Weybridge, UK). Thesesteers were randomly allocated to 3 groupsof about 90 individuals. All three groups werehoused at the same location, but separately, inthe same barn, and managed under the sameconditions. The first group remained as unex-posed controls; the second and the third groupswere exposed orally at approximately 6 mo ofage in August and September 1998 to 1 and100 g of BSE brain homogenate with a titerof 103.1 mouse (intracerebral/intraperitoneal)units LD50/g. The challenged animals weretracked by IHC analysis of obex and medullatissues at the time point of slaughter. Forthe present study, infected and age-matchedcontrol steers slaughtered at 12 and 45mo (one for each group and each timepoint) following oral exposure of 1 or100 g BSE brain homogenate, respectively,were used.

Caudal medulla tissues were collectedrapidly after post mortem and snap frozen intoliquid nitrogen. Total RNA was extracted usingthe RNA-Easy Column method (Qiagen, UK)

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112 L. M. ALMEIDA ET AL.

according to the manufacturer’s instructions.The quality and quantity of RNA was measuredusing the Agilent Nano 6000 assay (Agilent,USA).

Microarray Hybridization and DataAnalysisGlobal gene expression variations between

control and BSE-infected (1 or 100 g) ani-mals at 12 and 45 mo post infection (PI) werecompared by the following combination ofhybridizations: (1) control 12 mo × 1 g infected12 m; (2) control 12 mo × 100 g infected12 mo; (3) control 45 mo × 1 g infected 45 mo;and (4) control 45 mo × 100mg infected45 mo. Duplicates of 24,000 bovine oligonu-cleotide probes (www.Bovineoligo.org) werespotted onto ultragap slides (Corning) using Q-array2 (Genetix, Hampshire, UK). One micro-gram of total RNA was reverse-transcribed,amino-allyl coupled (Applied Biosystems), andlabeled with Cy3 or Cy5 fluorescent dyes(GE Healthcare) according to the manufac-turer’s instructions. For each experiment fourslides were used, including dye swaps, andtwo technical replicates. Therefore, each genewas represented eight times in the statisti-cal analysis. Hybridizations were carried outin a hybridization chamber (Genetix, UK)at 42◦C overnight. Hybridized slides werewashed with low-stringency buffer (2 × SSCand 0.5% sodium dodecyl sulfate [SDS]),high-stringency buffer (0.5 × SSC and 0.2%SDS), and 0.05 × SSC. Hybridized slideswere scanned at 5 µm resolution and theirsignal intensities were detected by Q-Scan(Genetix, UK).

Data analysis was performed usingGeneSifter (VizX Labs). Differences in geneexpression levels at different times post infec-tion and at different infection concentrationswere analyzed using the t-test statisticalmethod. The criterion for the detection ofDE genes was twofold or greater changein expression level, with p < .01, whichwas adjusted by Bonferroni correction. Thequality filter of 95% was used to eliminate

data from probes in any group that hadan intensity variation larger than 5%. GeneOntology was used to determine the func-tion of DE genes, and the KEGG pathwaydatabase was used to pathway map of DEgenes to evaluate their roles in the biologicalprocesses.

Quantitative Real-Time PCR AnalysisThe quantitative real-time polymerase

chain reaction (qRT-PCR) analyses of selectedgenes were performed using amplified RNA.The aRNA was used in this study due tothe limited amount of RNA. Previous studyshowed no difference of expression levelswas detected when using either total RNAor aRNA (Taniguchi et al., 2008). The RNAabundance was measured using the TaqManUniversal PCR Master Mix with gene-specificMGB probes labeled with FAM and VIC flu-orescent dyes (Applied Biosystems). The tem-plates used were 500 ng of aRNA obtained byreverse-transcribed synthesis using an amino-allyl kit (Applied Biosystems). The targetedgenes and primer and probe sequences foreach targeted gene are described in Table 1.Each reaction was carried out in triplicateusing the StepOnePlus Real Time PCR System(Applied Biosystems). The thermal cycling con-ditions were as follows: 95◦C for 20 s fol-lowed by 40 cycles of 95◦C for 1 s and60◦C for 20 s. Three genes were tested asthe endogenous control: GPADH, 18S, andPSMB2. According to Bestkeeper software(Pfaffl et al., 2004), the PSMB2 showed moststable expression in medulla tissues; there-fore, this was selected to be the endogenouscontrol. Threshold cycle (CT) values for eachgene were calculated by subtracting the ref-erence gene CT from the targeted gene CT.Gene expression for infected samples wasquantitatively measured relative to RNA fromcontrol animals at the same time post infec-tion. Relative quantification values were deter-mined using the 2–��CT method and expressedas fold change in infected versus controlanimals.

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TABLE 1. Oligonucleotides and Probes Used in qRT-PCR Studies

Gene Nucleotide sequence (5’-3’) Probe Accession numbe

Prion gene (PRNP) F: TTTGTGGCCATGTGGAGTGAR: CATCCTCCTCCAGGTTTTGG

TGGGCCTCTGCAAGA NM_181015

Osteopontin (OPN) F: CTGACTGACCACAGCAAGGAAAR: GCCTTTGGCGTGAGTTCTTT

AGTAGCGAGCTTTC NM_174187

Cadherin 1 (DH1) F: GCCGTGTCTTCAAATGGACAAR: CGGTCACGGTGATCACAATC

CCATTGAAGAGCCTATG NM_001002763

Angiotensin IIreceptor-like 1(AGTRL1)

F: CTCATGAACGTCTTCCCCTACTGR: GGGTTGAGGCAGCTGTTGA

ACGTGCGTCAGCTAC NM_001102524

Tachykinin 1 (TAC1) F: CCGTGGCAGTGATTTTTTTCAR: CGTTGGCTCCGATTTCTTCT

CTCCACTCAACTGTCTG NM_174193

Synaptosomal-associatedprotein (SNAP25)

F: CCGTCATATGGCCCTGGATR: TGTCGATCTGGCGGTTCTG

TGGGCAATGAGATTGATA NM_001076246

Apoptosissignal-regulatingkinase 1 (ASK-1)

F: AACGGCCTTCAGATCAAACTGTR: GGCCACCGCGTCTTCA

AAGACCTCATGCCGTCC XM_617542

Amyloid beta precursorprotein (APB A1)

F: CACGCACACATGGTCATTCCR: CAAGGAGGGCATCACTCACA

TACCGCTGCCTGGTT NM_001076796

Proteasome subunit,beta type, 2 (PSMB2)

F: ATATATTCAGAAAAACGTGCAGCTCTATR: GCTGCCGTGGGAGACAGT

AGATGCGAAATGGTTATG NM_001015615

Note. F, forward primer; R, reverse primer.

RESULTS AND DISCUSSION

BSE Symptoms of PrPBSE-ChallengedAnimalsNo control animals displayed signs of

BSE, and immunohistochemistry (IHC) testsof medulla tissues were negative for PrPBSE.Animals at 12 mo post infection (with both1 and 100 g of PrPBSE) showed no apparentsigns of BSE, and medulla IHC tests were neg-ative. Possible pathological signs of BSE weredetected in animals 45 mo after infection with100 g for observed positive medulla IHC tests,while the medulla IHC test was negative for ani-mals 45 mo after infection and no BSE signswere observed for these animals.

Microarray Analysis of DE GenesBetween Control and BSE-InfectedAnimalsAfter analysis of the microarray data

obtained from 4 comparisons, 966 DE geneswere identified between control and infectedanimals. Some of these genes were identifiedin more than one comparison (Table 2). Toavoid overestimation of DE genes, the over-lapping genes between each comparison were

eliminated. Therefore, 805 and 337 of DEgenes were identified in BSE-infected medullatissues 12 and 45 mo post infection, respec-tively (Table 2). In total, 176 genes identified incommon between at least 2 of 4 experimentswere considered as probable candidate genesassociated with BSE disease (Table 2). As shownin Table 3, some of these genes have beenpreviously reported to be associated with TSEpathogenesis, suggesting that similar molecularmechanisms may be common in various TSE.However, our data differ from previous stud-ies in mice, which reported that fewer geneswere DE during the preclinical stage comparedto the late clinical period (Booth et al., 2004;Sorensen et al., 2008). This difference maybe due, first, to difference of the host andsource of infective material. Both the murinestudies used scrapie (strains ME7, 79a and22A) challenged mice. Second, other studiesof gene expression associated with prion dis-eases were performed using intracerebral infec-tion, whereas the present study investigated theeffects following oral infection. Third, variationsbetween individual animals may cause the dif-ferent responses to BSE development. In thepresent study, data were only available for a sin-gle animal for each time point, and therefore

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TABLE 2. Numbers of Differential Expressed Genes (DE) Identified Between Control and BSE-Infected Animals Under DifferentConditions

12 mo 45 mo

DE genes 1 g 100 gCommon DEgenes 1 g 100 g

Common DEgenes

12 and 45 mo,Common DE genes

Upregulated 317 127 64 174Downregulated 448 84 69 69In total 765 211 171 133 243 39 176

the variation between animals could not beaddressed. Further studies using additional ani-mals are necessary to identify the impact ofindividual variations in BSE development in cat-tle. Fourth, different microarray platforms andexperimental conditions may have contributedto the difference.

The higher number of DE genes detectedfrom 12-mo post infection medulla tissue isconsistent with the previous study by Tanget al. (2009), in which the largest numbers ofdifferentially regulated genes were identifiedfor 21 mo post infection brain as comparedto the number of DE detected in the brainat 45 month post infection, supporting theirspeculation that global changes of gene expres-sion activities are prior to the PrPBSE accu-mulation and the appearance of clinical signs.Findings of the large amount of DE gene at apreclinical stage suggest that these differencesreflect probably a more specific prion-inducedcellular response than those observed at theterminal stage of the disease when cells areseriously damaged. Among all the DE genes,only BoLA-DQ A gene was found to have thesame expression trend (upregulated) under fourconditions (Table 3), suggesting that differentcellular response may be associated with dif-ferent stages of the disease. In addition, the12-mo 1-g infected animals showed a highnumber of DE genes (765) different from the100-g infected animal at the same time point.Since only one animal was tested, the highnumber of DE genes may be the results ofthe high response from this particular individ-ual. Therefore, future studies to include morebiological replicates is essential to validate thegene expression differences in the early stageof the prion infection.

Expression of PrPC in Medulla ofBSE-Infected AnimalsIn this study, the expression of PRNP gene

was evaluated using qRT-PCR since this genewas not included in the microarray platform.Studies of PrP knockout mice demonstratedthat the cellular prion protein PrPC is essentialfor TSE infection and the development of priondiseases (Brandner et al., 1996). A quantita-tive rise in PrP RNA levels was observed in allexperimental conditions (Figure 1). Increasedexpression of PrP gene was reported in Peyer’spatch tissue after scrapie infection in sheep(Austbø et al., 2007). However, the overex-pression of PRNP gene may not be requiredfor pathogenesis in brain. Paquet and cowork-ers (2007) reported that PrPC did not mediateinternalization of PrPSc, although it is requiredfor De Novo prion infection of Rov cells at theearly stage.

Gene Function and Prediction UsingKEGG AnalysisFrom 176 DE genes, 84 have func-

tions described in the Gene Ontology (GO)database. The DE genes fell into more than oneGO functional category; however, for simplic-ity these genes are presented under a singlefunctional heading in Table 3. To understandmetabolic pathways implicated by these DEgenes, which may identify the cellular pro-cesses involved in, or affected by, BSE infection,the KEGG pathway database was used to linkthe DE genes to biological systems by path-way mapping. Studies focused on analyzingthe biological processes of the DE genes withthe KEGG pathways, instead of using Gene

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TABLE 3. Differentially Expressed Genes (DE) Associated With BSE Disease in Caudal Medulla Tissues Detected by MicroarrayMethodology

Fold change

GO function A B C D Previousand 12 mo 45 mo 12 mo 45 mo TSEGenBank ID Gene name (1 g) (1 g) (100 g) (100 g) studies

Cell adhesionBt.10536 Bone sialoprotein I/early T-lymphocyte

activation 16.35 2.73 Sorensen et al.,

2008Bt.49639 Epithelial V-like antigen 1 −2.12 −2.03Bt.53255 Hypothetical protein LOC614712 4.77 3.9 2.51Bt.64827 Cadherin 1, type 1, E-cadherin −2.15 −2.45 Khaniya et al.,

2009Bt.23316 Collagen, type I, alpha 1 (COL1A1) −13.15 2.27Bt.53485 Collagen, type I, alpha 2 −12.86 2.21Bt.41071 Predicted: Bos taurus similar to cadherin

12 (LOC540672)404.32 16.73

Protein binding and protein foldingBt.23178 Decorin −15.34 3.0 Greenwood

et al., 2005Bt.7955 Procollagen C-endopeptidase enhancer

(PCOLCE)−3.83 2.1

Bt.42529 Synaptosomal-associated protein, 25 kD(SNAP25)

17.59 2.17 Skinner et al.,2006

Bt.6630 Calponin 1, basic, smooth muscle (CNN1) −10.04 −2.12 Xiang et al., 2004Bt.72530 Hypothetical protein LOC511417 −5.86 2.4Bt.76948 12.6-kD FKBP/FK506-binding protein

1B/immunophilin4.33 2.01 Martínez and

Pascual, 2007Bt.21115 Sec23 homolog A −2.08 −2.94 Greenwood

et al., 2005Bt.48998 PDZ and LIM domain 4 (PDLIM4), −2.44 2.53 Sawiris et al.,

2007Bt.24896 Kinesin-associated protein 3 (KIFAP3) 2.05 −2.07 Skinner et al.,

2006Bt.3540 Hypothetical protein LOC518004 −7.99 −2.78 2.68

Calcium bindingBt.61440 Ca2+-binding protein 7.09 3.27 Voigtländer et al.,

2008Bt.49146 CDNA clone IMAGE:7963200 −2.29 2.01Bt.21097 Hypothetical protein LOC522276 −44.8 −2.3Bt.49702 Neurocalcin alpha (visinin-like) 19.91 16.4 −3.32 Skinner et al.,

2006Bt.48894 Protein S, alpha −2.03 2.37 Xiang et al., 2004Bt.357 S100 calcium-binding protein A12

(calgranulin C)−3.23 −2.7 Xiang et al., 2004

Bt.28966 Phospholipase A2 group IIA-like −8.98 −12.3Bt.3595 Matrix Gla protein −13.36 −2.85

Nucleotide bindingBt.56284 Predicted: Bos taurus similar to

BRUNO-like 6 RNA-binding protein,transcript variant 1 (LOC539205)

4.76 2.04

Bt.33930 Eukaryotic translation elongation factor 1alpha 2 (EEF1A2)

14.95 3.1 Greenwood et al2005

Bt.34807 Predicted: Bos taurus similar toneurofilament triplet H protein

19.64 5.0 2.05 −2.79

Bt.43053 Septin 11 (SEPT11) 2.58 −4.58 Sorensen et al2008

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TABLE 3. (Continued)

Fold change


Neurotransmiter, neuroactive ligand–receptor, and neurodegenerativedisordersBt.25073 Predicted: Bos taurus hypothetical

LOC616071 (LOC616071)10.22 2.23

Bt.65813 Synaptotagmin 1 3.86 −2.33Bt.88110 Angiotensin II receptor-like 1 (AGTRL1) −6.02 2.33Bt.12930 Neurokinin 1/neurokinin 2/neurokinin

alpha/neuromedin L2.98 −2.05

Bt.1978 Protease serine 2 (PRSS2) −2.43 −2.27Bt.35938 Hypothetical protein LOC531593 12.49 4.97 −2.07Bt.67878 Predicted: Bos taurus neuron-specific gene

family member 12.43 3.07

Bt.40062 Amyloid precursor protein proteasenexin-II

2.07 −2.56

Bt.5457 Growth-associated protein 43 8.83 2.81 3.45 Greenwoodet al., 2005

Bt.20015 Cocaine- and amphetamine-responsivetranscript

16.02 6.28 2.08 −4.11 Sorensen et al.,2008

Bt.33726 Neuropeptide Y 4.61 −5.6 Diez et al., 2007

Defense- and immune response-related genesBt.5356 BoLA-DRB3.2/DR beta-chain antigen

binding domain3.01 2.65

Bt.91543 BoLA-DQA/MHC class II antigen/majorhistocompatability class II

−3.56 −4.08 −3.23 −2.81

Bt.73288 Predicted: Bos taurus complementcomponent 4A (C4A)

−2.65 4.76 Xiang et al., 2004

Bt.77962 Major histocompatibility complex, class II,DQ alpha, type 3

2.58 6.61

Transport-related genesBt.31577 Potassium inwardly rectifying channel J8 2.62 2.04Bt.16310 Predicted: Bos taurus similar to glutamate

transporter GLT1 (LOC541119)10.16 4.96 −7.87

Bt.25241 Predicted: Bos taurus similar to mucolipin2 (LOC532671)

2.11 −2.91 −3.39

Bt.76429 Similar to ceruloplasmin precursor(ferroxidase), mRNA (cDNA cloneIMAGE:8040685)

−3.39 2.3 −3.19

Bt.66422 Solute carrier family 14 (urea transporter),member 1/urea transporter

−3.38 2.23 2.65

Bt.49611 Ras-related protein Rab-19 −2.7 −2.21Bt.207 Prealbumin −2.88 −2.59Bt.4516 Aquaporin −28.69 2.49 Riemer et al.,

2004Bt.396 Cellular retinoic acid-binding protein 1 4.26 −2.61 −7.11Bt.45049 Beta globin −2.14 −3.46Bt.10591 Hemoglobin alpha chain, mRNA (cDNA

clone MGC:157272)2.19 −2.34

Bt.88760 Serum amyloid A-like (LOC506412) −8.04 2.55

Signal transductionBt.24342 Angiopoietin-like 7 (ANGPTL7) 3.05 −2.76 2.41 3.68Bt.49586 Neuroepithelial cell-transforming gene 1

(NET1)−2.02 −2.05

Bt.37430 Predicted: Bos taurus similar to Ras-likefamily 11 member A (LOC505695)

2.18 2.28 Martínez andPascual, 2007

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Fold change


Bt.26628 RAP2C, member of RAS oncogene family(RAP2C)

−2.78 −2.08 Martínez andPascual, 2007

Bt.3704 Stathmin-like 2 (STMN2) 12.0 3.78 2.58 Greenwoodet al., 2005

Metabolic processBt.31710 Hypothetical protein LOC510845 −4.36 2.67Bt.55620 Predicted: Bos taurus similar to succinic

semialdehyde dehydrogenase(LOC532724)

−2.23 −2.52 −3.39

Bt.87840 Predicted: Bos taurus similar to TFIIA(LOC785612)

−2.23 −2.39

Bt.1286 Retinoic acid receptor responder(tazarotene induced) 2 (RARRES2)

−2.84 2.18

Hormone activityBt.35964 Predicted: Bos taurus similar to urotensin II

transcript (LOC506055)8.22 2.39 2.83

Bt.51437 Predicted: Bos taurus similar toMGC45438 protein (LOC618703)

−2.52 −3.14

Bt.98687 Insulin-like growth factor 2 −6.74 −2.38 Sorensen et al.,2008

Bt.4102 Natriuretic peptide precursor C 2.36 −2.11

Cellular activityBt.49630 Haptoglobin (HP) −5.3 2.33Bt.53829 Hypothetical protein LOC510102 −4.8 2.1Bt.15725 Hypothetical protein LOC514788 16.54 2.72Bt.43467 Hypothetical protein LOC618738 8.77 2.0Bt.63555 LanC lantibiotic synthetase component

C-like 12.93 −2.23

Bt.4057 Myosin heavy polypeptide 10,nonmuscle/nonmuscle myosin heavychain B

2.14 −2.03 Martínez andPascual, 2007

Integral membraneBt.9807 Glycoprotein (transmembrane) nmb

(GPNMB), mRNA−2.29 −3.04 Xiang et al., 2004

Bt.53818 Myelin oligodendrocyte glycoprotein 2.12 2.33Bt.20855 PDZK1 interacting protein 1 (PDZK1IP1) −3.55 −4.38

Regulation of cell growthBt.9958 Insulin-like growth factor-binding protein 6 −6.37 −2.27 2.17

Multiple organismal developmentBt.11341 Neuronatin 2.46 −5.41 −6.43

CytoskeletonBt.31841 Similar to talin 2 −2.79 −5.45

Cytoplasmic vesicleBt.5448 Chromogranin B (secretogranin 1) −9.56 −2.01

Peptide cross-linkingBt.19195 Coagulation factor XIII, A1 polypeptide

(F13A1)−2.92 −2.1 Xiang et al., 2004

OthersBt.45367 Abelson murine leukemia viral (v-abl)

oncogene homolog 1−2.39 −2.09

Bt.31917 Apoptosis signal-regulating kinase 1 −2.06 −3.28

(Continued)

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Fold change


Bt.91529 Bromodomain and WD repeat domaincontaining 1 (BRWD1)

−2.61 −3.3

Bt.21940 Coiled-coil domain containing −2.67 4.11Bt.26387 Glutamate receptor, ionotropic, kainite 1

(GRIK1)Bt.100362 IgG1 heavy chain constant region

(IgC-gamma)−5.54 5.19

Bt.12809 Immunoglobulin heavy constant mu −2.49 −2.27Bt.89014 Major neuronal intermediate filament

subunit/neurofilament M subunit8.25 4.79 −2.92

Bt.64746 Osteoblast specific factor 2 (fasciclin I-like) −3.51 −48.21Bt.91020 Transcribed locus, strongly similar to

NP_035040.1 neurofilament, lightpolypeptide

28.03 10.17 3.1 −2.38 Sorensen et al.,2008

Bt.30375 Peripherin (PRPH) Skinner 12.83 6.21 4.16Bt.24470 Tripartite motif-containing 37 protein 2.37 2.17

Note. Negative and positive numbers in fold change column indicate down- and upregulated genes.

FIGURE 1. Validation of microarray data by qRT-PCR. Gene expression between control and infected animals at 12 mo (A) and 45 mo(B) post infection for animals fed with different doses of BSE material (1 g and 100 g). Genes analyzed were prion protein (PRNP),osteopontin (OPN), cadherin 1 (CDH1), angiotensin II receptor-like 1 (AGTRL1), tachykinin 1 (TAC1), synaptosomal-associated protein(SNAP25), apoptosis signal-regulating kinase 1 (ASK-1), and amyloid beta precursor protein (APBA1).

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TABLE 4. KEGG Pathway Classification of DE Genes Detectedby Microarray Analysis

Gene identified usingmicroarray KEGG pathways

Osteopontin ECM receptorCollagen type 1, α2Cadherin 1 Cell adhesionBoLA-DQA2BoLA-DRB3Angiotensin II receptor-like 1 Neuroactive

ligand-receptorinteraction

Tachykinin 1Synaptosomal-associated

protein, 25 kDSNARE interactions in

vesicular transportApoptosis signal-regulating

kinase 1MAPK signaling pathway

Amyloid precursor protein,protease nexin-II

Neurodegenerativedisorder

Decorin TGF beta signalingProtein S alpha Complement and

coagulation cascadespathways

Predicted Bos tauruscomplement component 4A

cDNA clone IMAGE:7963200

Ontology to determine the candidate genes.This approach identified 14 genes related to8 biological pathways (Table 4), 5 of whichare considered in detail here: extracellularmatrix (ECM) receptor, cell adhesion, neuroac-tive ligand–receptor interaction, SNARE inter-actions in vesicular transport, and MAPK sig-naling pathway. In addition, the individual DEgenes associated with neurodegenerative disor-ders network were also investigated.

Extracellular Matrix (ECM) ReceptorPathways Associated With BSEThe ECM provides the principal means by

which information is communicated betweenthe extracellular environment and the cell. TheECM plays an important role in protein traf-ficking and protein turnover. Lima et al. (2007)suggested that the ECM may be involved instability and cellular localization of PrPC andneuronal differentiation, and hence this path-way may be associated with entry of PrPBSE

into the cell and subsequent replication andpathogenesis.

Three genes associated with the ECM net-work were found to be differentially expressedin BSE infected brain: osteopontin, collagentype 1-α2, and fibronectin. The osteopontin(OPN) was upregulated in microarray experi-ments (6.35- and 2.73-fold change at 12 and45 mo post infection, respectively; Table 3),which was confirmed by qRT-PCR analysis(6.06- and 1.50-fold, respectively; Figure 1).Osteopontin is involved in viability of neurons(Iczkiewicz et al., 2004) and the control of themigration of mononuclear cells (Denhardt &Guo, 1993) by maintaining cellular integrity,cytoskeletal organization, and inhibition ofapoptosis. To date, OPN has not been impli-cated in neurodegenerative diseases. Collagentype 1-α2 also showed significant changes inexpression following BSE infection; however,the level of expression differed between timepoints following infection: At 12 mo post infec-tion, it was significantly downregulated (experi-ment A, −12.86, Table 3), while at 45 mo it wasupregulated (experiment D, −2.21, Table 3).According to Hajj et al. (2007), the collagenproteins do not interact directly with PrPC, butthe differential gene expression may be a cellu-lar response to maintain cell integrity after TSEinfection. Fibronectin was also downregulated,but only at 12 mo post infection (−2.67-fold, 1-g infected animal; data not shown). The KEGGanalysis of OPN, collagen, and fibronectinindicates that they all interact with integrin inthe same ECM network (Figure 2).

In addition, laminin is an integral part ofECM network (Figure 2). Gene expression stud-ies in cell cultures infected with scrapie demon-strated that the laminin gene is downregulated(Fasano et al., 2008), while an important roleof laminin was suggested in prion replica-tion (Gauczynski et al., 2006; Hundt et al.,2001; Schmitt-Ulms et al., 2001). Molecularinteraction studies showed that PrPC binds tothe laminin receptor (Gauczynski et al., 2006;Hundt et al., 2001), promoting neuritogenesis(Schmitt-Ulms et al., 2001) and inducing neu-rite maintenance and neuronal differentiation(Graner et al., 2000). Further study of the rolesof the laminin genes needs to be investigatedto completely understand the functions of ECMpathways in BSE pathogenesis.

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FIGURE 2. ECM pathway and DE genes associated with BSE infection. This KEGG map represents all molecular interaction and reactionnetwork known for the ECM pathway. Gray region represents the extracellular matrix space and double bar represents cell surface. ThreeDE genes associated with BSE-infected brain were identified in our microarray experiments: osteopontin (OPN), collagen type 1-α2, andfibronectin. Microarray gene expression levels are shown by numbers in front of box name. Negative numbers represent underexpressionand positive numbers represent overexpression in relation to control animals.

Cell Adhesion Pathway and DE GenesAssociated With BSEFour major families of cell adhesion

molecules (CAM) are defined on the basisof their structure: integrins, selectins, CAM ofthe immunoglobulin gene (IgG-like) superfam-ily, and cadherin (Winter et al., 2003). In thepresent study, differences in the gene expres-sion for three CAM genes were observed: theBoLA class II genes DQA and DRB3, and cad-herin 1, which are part of the cell adhesion

network. The BoLA-DQA gene was downreg-ulated in microarray experiments at both 12and 45 mo post infection (fold change var-ied from −2.81 to −4.08, Table 3), while theBoLA-DRB3 gene was found to be upregu-lated in microarray analysis at 45 mo postinfection following infection with 1 and 100 g(3.01- and 2.65-fold change, Table 3). Previousstudies suggested the MHC class II antigensfacilitate the entry of the infectious agentinto macrophages, dendritic cells, and B cells,

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which facilitate the transport of infectious agentfrom peripheral entry sites to secondary lym-phoid organs, in which prions accumulate andreplicate prior to their transport to neural tis-sues (Maignien et al., 2005).

Cadherin 1 (CDH1) is a calcium-dependent cell–cell adhesion membraneglycoprotein that plays an essential role inmaintaining epithelial polarity by formingCa2+-dependent adherens junctions betweenepithelial cells and down regulating cell growth(Nelson, 2008). This protein was found tobe downregulated at both 12 and 45 mopost infection in the microarray experiments(−2.15- and −2.45-fold change, Table 3), andit was confirmed by qRT-PCR at both timesfollowing infection (fold change from 0.24to 0.58, Figure 1). KEGG pathway analysisshowed that CDH1 is an important cell surfacereceptor of Schwann cells, which plays apivotal role in the maintenance and regen-eration of axons in the peripheral nervoussystem (Bhatheja & Field, 2006). The down-regulation of CDH1 in our study suggests thatthe formation of adherens junctions betweenepithelial cells in the brain may be affectedby the BSE progression but needs furtherstudies.

Neuroactive Ligand–Receptor InteractionPathway and DE Genes Associated WithBSEIn this study, two genes involved in the neu-

roactive ligand–receptor network, angiotensinII receptor like 1 (AGTRL1) and tachykinin1 (TAC 1), were found to be upreg-ulated in BSE-infected animals (Figure 1and Table 3). Electron microscopic studiesdemonstrated that degeneration of synapsesprecedes neuronal degeneration in scrapie-infected murine hippocampus (Jeffrey et al.,2000). Therefore, synapses neuroactive ligandsmay be important in TSE disease develop-ment. Immunohistochemical studies showeddecreased expression of synaptic proteins inhuman and animal prion diseases, therebysuggesting abnormal presynaptic terminals andsynaptic loss (Clinton et al., 1993). AGTRL1 was

upregulated in all experiments except in ani-mals at 12 mo post infection with 1 g (Figure 1and Table 3). Angiotensin-converting enzyme(ACE) cleaves angiotensin I to angiotensin II(Coates, 2003). Variations in the ACE genehave been associated with Alzheimer’s disease(Lehmann et al., 2005), suggesting that ACEand ACE receptors may play a role in, or beaffected by, neurodegenerative disease.

Tachykinin 1 (TAC1) and its receptors areinvolved in cardiovascular, digestive, and res-piratory functions through brainstem neurons(Severini et al., 2002). The microarray andqRT-PCR data presented here for the TAC1neuromodulater gene were variable betweenthe experiments. High expression was observedat the preclinical time-point (12 mo post infec-tion), while expression was downregulated inanimals at 45 mo post infection (Table 3 andFigure 1A). To date, there have been no reportsassociating TAC1 with prion diseases.

SNARE Interactions in VesicularTransport Pathway and DE GenesAssociated With BSEThe 25-kD synaptosomal associated pro-

tein (SNAP-25) belongs to an important classof proteins involved with regulated neuro-transmitter vesicle trafficking (Sollner et al.,1993). This protein is widely distributed inthe brain and its levels were previously shownto be reduced in neurodegenerative diseases(Greber-Platzer et al., 2003). Reduced SNAP-25 expression was also reported in the brainof scrapie-infected mice, although SNAP-25was found to accumulate in the thalamus,midbrain, and pons (Sisó et al., 2002). Highexpression of SNAP-25 was detected in patientswith schizophrenic disorder and Down’s syn-drome (Thompson et al., 1999; Greber-Platzeret al., 2003), suggesting that SNAP-25 couldbe a potential clinical marker in schizophrenia(Thompson et al., 1999). In the present study,high expression of SNAP-25 was detected inall experiments (from 10.72- to 143.24-foldchange according to qRT-PCR analysis), withthe exception of animals at 45 mo post infec-tion with 100 g (Table 3 and Figure 1).

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MAPK Signaling Pathway and DE GenesAssociated With BSEThe MAPK pathway is a signal transduction

pathway that couples intracellular responses tothe binding of growth factors to cell surfacereceptors (Orton et al., 2005). The apopto-sis signal-regulating kinase 1 (ASK1) is a crit-ical component in cell apoptosis and is acti-vated by a variety of death stimuli, includingtumor necrosis factor (TNF) alpha and oxida-tive stress (Li et al., 2005). Several studiessuggested that TNF may be involved in theneurodegenerative processes associated withTSE disease (Williams et al., 1997). The presentstudy demonstrated the downregulation ofASK1 in 12-mo post infection animals andupregulation in 45-mo post infection animals(Table 3 and Figure 1), suggesting that genesassociated with the MAPK pathway may beassociated with BSE progression.

Other KEGG Pathways and DE GenesAssociated With BSENeurodegenerative disorders such as prion

diseases, Alzheimer’s disease, Parkinson’s dis-ease, and Huntington’s disease are charac-terized by the formation of amyloid plaquesin the CNS (Vicent et al., 2008). The maincomponent of these abnormal deposits isan aggregated form of amyloid beta-peptide,which is produced from a large transmem-brane type-1 protein, the beta-amyloid precur-sor protein (Vicent et al., 2008). The proteasenexin-II (APBA1), an amyloid precursor pro-tein, was found to be up regulated at 12mo post infection (2.07-fold change, Table 3)and downregulated at 45 mo post infec-tion (−2.56-fold change, Table 3); however,qRT-PCR data showed overexpression in allexperiments (from 1.13- to 2.39-fold change,Figure 1). Tamguney et al. (2008) noted thatmice deficient for amyloid beta precursor genewere found to have prolonged scrapie incu-bation times. Our observation of upregulationof APBA1 in BSE-infected animals supportsthe previous study and suggests an involve-ment of the amyloid beta precursor gene in

prion pathogenesis. In addition, our microar-ray analyses showed that the decorin genewas downregulated in 12-mo post infection 1-g infected animals (−15.34-fold change) butoverexpressed at 45 mo in the 100-g doseanimals (3.0-fold change). Decorin is a small,leucine-rich proteoglycan that binds to colla-gen and regulates fibrillogenesis (Reed & Iozzo,2002) and belongs to the transforming growthfactor beta (TGFβ) signaling pathway. Up tonow, there have been no reports of this path-way being involved in BSE pathogenesis.

CONCLUSIONS

The identification of genes that contributeto pathogenesis of TSE diseases is crucial forunderstanding the disease processes. Althoughhundreds of genes were reported to have differ-ential expression associated with TSE diseasesin the last decade, only a few were foundto contribute directly to prion pathogenesis(Tamgüney et al., 2008). In contrast to mostof the gene expression studies of TSE diseasepublished to date, the present study addressedTSE infection in the natural host, i.e., BSEinfection of cattle via the oral route. KEGGanalysis was performed on the gene expressionresults to identify gene networks and molec-ular interactions that may be associated withBSE disease. This approach identified 14 DEgenes involved in 8 KEGG pathways. DE genesfrom ECM receptor, cell adhesion, neuroac-tive ligand–receptor interaction, SNARE inter-actions in vesicular transport, and MAPK sig-naling pathways were analyzed, and some ofthe genes within these pathways were found tohave different expression levels early or late inthe disease (either at 12 or 45 mo post infec-tion), revealing results similar to those reportedby Tang et al. (2009). The findings of this studymay be limited in number of samples used—i.e., no biological replicates have been used.The gene expression profiling studies in themedulla tissue provided preliminary informa-tion regarding the molecular pathogenesis ofBSE; however, additional studies are neededto unravel the pathogenesis of TSE at the host

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level by conducting experiments at variousstage of infection to the stage where the animalshows the response to infection in different tis-sues during prion infection and to study morenumbers of animals in each group to revealthe individual variation in the response to theprion challenge. It is also known that many fac-tors, including genetic diversity, single-animalanalysis, and cell population changes as theanimals progress to clinical disease, may havean impact on gene expression analysis results.Future studies including confounding factorssuch as breed, age, and nutrition on BSE pro-gression are vital to identify the gene markersfor BSE progression. Although the DE genesidentified in this study represent the particularcase from one tested animal for each treat-ment, these candidate genes could be appliedfor screening other animals to confirm theirroles in TSE pathogenesis. Studies using addi-tional animals are in progress in our laboratoryto verify the roles of these genes in prion dis-eases, hopefully to be able to contribute to theknowledge for the development of TSE diag-nostic tests based on discriminatory surrogatebiomarkers for prion infection.

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