112 Y. Li et al. / Virology 421 (2011) 105–113
integrity was confirmed by Bioanalyzer 2100 (Agilent
Technologies,CA).
MicroRNA microarray analysis
MicroRNA expression profiling was carried out using the
miRCURYLNA™ microRNA array, v.11.0-other species (Exiqon, MA). The
dualchannel miRCURY LNA™ microRNA array was designed based on
theSanger miRBase release v.14 and contains probes for 477
rhesusmacaque (Macaca mulatta) specific microRNAs. The sequence
formicroRNA of rhesus macaque was used as that of cynomolgus has
notbeen made available. We expected that the expression profiles of
afew microRNAs may be underrepresented on the array output due
toslight sequence changes between rhesus and cynomolgus macaquesand
therefore non-optimized hybridization. 500 ng of total RNA wasused
to make microRNA probes labeled with Hy3 (pooled mock RNAfrom 7
animals) or Hy5 (RNA from individual animals infected with
in-fluenza virus), according to the manufacturer's protocol
(miRCURYLNA™ microRNA array Power Labeling kit, Instruction manual
v2.0).Probes were hybridized at 56 °C for 16 h. The slides were
then washedaccording to themanufacturer's protocol. After
beingwashed, the slideswere scanned using the Agilent Microarray
scanner (Model#: G2505C;Agilent, CA).
The microRNA microarray results were extracted using Agilent
Fea-ture Extraction software v9.5. The totalmicroRNA signal from
theGene-View result files, which summarized the fluorescence
intensitymeasurements of two channels (Hy3 and Hy5) for all probes
for eachmicroRNA on an array, was used in the analyses. Expression
data werenormalized across arrays using a median-centered approach.
Theexpression difference of microRNA between HPAI-infected and
Tx-infected samples or between 2:6-infected and Tx-infected
sampleswas calculated using fluorescence intensities. Differential
expressionof microRNAs between two groups of samples was assessed
by one-way analysis of variance (ANOVA). The average expression
change(Fold change) of a microRNA in two HPAI-infected or two
2:6-infectedsamples from the same groups compared to that in the
time-matchedTx-infected sample was calculated. A cutoff ANOVA
(P≤0.01) and anabsolute fold change of ≥1.5 between infection
groups were used toselect the differentially expressed microRNAs. A
fold change of 1.5was chosen because a microRNA expression change
of 1.5 fold wasenough to induce a significant biological impact on
the cellular func-tions (Hu et al., 2008).
mRNA microarray analysis
The mRNA microarray experiments were conducted in a
previousstudy (Baskin et al., 2009). The data was reprocessed for a
direct com-parison of the cellular gene expression profiles between
HPAI- andTx-infected lungs and between 2:6- and Tx-infected lungs
using Resolv-er 7.2 (Rosetta Biosoftware, WA). The gene expression
profiles of Tx-infected lungs from two animals at each time
pointwere in silico pooledand used as a time-matched reference. The
cellular gene expressions inlungs from two HPAI- or 2:6-infected
animals at each time point werecompared to the time-matched
reference to assess relative expressionchanges by one-way analysis
of variance (ANOVA). The average foldchange was used to indicate
the gene expression change upon HPAI-or 2:6-infection relative to
the time-matched Tx-infection.
MicroRNA target database
The predicted targets of human microRNAs were used in this
studybecause the macaque microRNA target prediction was
unavailablewhen the analyses were performed. The identifiers of
predictedhuman microRNA targets were downloaded from the Sanger
Institute(http://microrna.sanger.ac.uk/targets/v5/). To make the
gene identi-fiers in the target database consistent with the gene
identifiers assigned
by the Agilent Feature Extraction Software to the Agilent
microarray,the ENSEMBL gene IDs in the Sanger human target
databasewere trans-lated into Entrez Gene ID by BioMart
(www.ensembl.org/biomart).
Statistical analysis
To assess the relationship between microRNAs and their
predictedtarget genes, the correlation coefficients for the mean
values of the dif-ferentially expressed microRNAs and their
potential target genes atdays 1, 2, 4 and 7 post-infection were
calculated in the R environment(http://www.r-project.org/). The
differentially expressed microRNAtarget genes between the HPAI- and
the 2:6-infected samples wereidentified via direct comparisons
using a single selection criterion of aP≤0.01. ThemicroRNA-target
pairs identifiedwith inversely correlatedexpression patterns were
then selected for further analyses. The proba-bility of enrichment
of an inversely correlated target by chance wasassessed by
hypergeometric (HG) tests that considered the followingfactors: the
number of genes on the arrays, the number of targets onthe arrays,
the number of differentially expressed genes on the arrays,and the
number of inversely correlated targets on the arrays. The
calcu-lation for HG tests was performed in the R environment. An HG
test,with P≤0.05, was used as the cutoff for statistically
significantenrichment.
Bioinformatics analysis
Functional analysis of statistically significant gene
expressionchangeswas performedwith Ingenuity Pathways Analysis
(IPA; Ingenu-ity Systems). This software analyzes RNA expression
data in the contextof known biological response, regulatory
networks, and higher-orderresponse pathways. For all analyses, a
Benjamini–Hochberg test correc-tion was applied to the
IPA-generated P-value to determine the proba-bility that each
biological function assigned to that data set was due tochance
alone. In the functional networks, genes are represented asnodes,
and the biological relationship between two nodes is representedas
an edge (line). All biological relationships used to determine
theedges are supported by at least one published reference stored
in theIngenuity Pathways Knowledge Base.
Supplementary materials related to this article can be found
on-line at doi:10.1016/j.virol.2011.09.011.
Conflict of interest
The authors declare no conflict of interest.
Acknowledgments
We thank Janine Bryan and Marcus Korth for critical reading of
themanuscript. We also thank Sean Proll, Lynn Law, and Glenn Zhang
fortheir helpful discussion. This work was supported by NIH Grant
P51RR00166 and U54 AI081680. The findings and conclusions in this
re-port are those of the author(s) and do not necessarily represent
theviews of the funding agency.
References
Aravin, A.A., Lagos-Quintana, M., Yalcin, A., Zavolan, M.,
Marks, D., Snyder, B., Gaasterland,T.,Meyer, J., Tuschl, T., 2003.
The small RNAprofile duringDrosophilamelanogasterde-velopment. Dev.
Cell 5, 337–350.
Bartels, C.L., Tsongalis, G.J., 2009. MicroRNAs: novel
biomarkers for human cancer. Clin.Chem. 55, 623–631.
Baskin, C.R., Bielefeldt-Ohmann, H., Tumpey, T.M., Sabourin,
P.J., Long, J.P., García-Sastre, A.,Tolnay, A.-E., Albrecht, R.,
Pyles, J.A., Olson, P.H., Aicher, L.D., Rosenzweig,
E.R.,Murali-Krishna, K., Clark, E.A., Kotur, M.S., Fornek, J.L.,
Proll, S., Palermo, R.E.,Sabourin, C.L., Katze, M.G., 2009. Early
and sustained innate immune response de-fines pathology and death
in nonhuman primates infected by highly pathogenicinfluenza virus.
Proc. Natl. Acad. Sci. 106, 3455–3460.
Davidson-Moncada, J., Papavasiliou, F.N., Tam, W., 2010.
MicroRNAs of the immunesystem. Ann. N. Y. Acad. Sci. 1183,
183–194.
http://microrna.sanger.ac.uk/targets/v5/http://www.ensembl.org/biomarthttp://www.r-project.org/
113Y. Li et al. / Virology 421 (2011) 105–113
de Jong, M.D., Simmons, C.P., Thanh, T.T., Hien, V.M., Smith,
G.J.D., Chau, T.N.B., Hoang,D.M., Van Vinh Chau, N., Khanh, T.H.,
Dong, V.C., Qui, P.T., Van Cam, B., Ha, D.Q.,Guan, Y., Peiris,
J.S.M., Chinh, N.T., Hien, T.T., Farrar, J., 2006. Fatal outcome
ofhuman influenza A (H5N1) is associated with high viral load and
hypercytokine-mia. Nat. Med. 12, 1203–1207.
Fang, Y., Shi, C., Manduchi, E., Civelek, M., Davies, P.F.,
2010. MicroRNA-10a regulationof proinflammatory phenotype in
athero-susceptible endothelium in vivo and invitro. Proc. Natl.
Acad. Sci. 107, 13450–13455.
Gavett, S.H., O'Hearn, D.J., Li, X., Huang, S.K., Finkelman,
F.D., Wills-Karp, M., 1995. In-terleukin 12 inhibits
antigen-induced airway hyperresponsiveness, inflammation,and Th2
cytokine expression in mice. J. Exp. Med. 182, 1527–1536.
Hien, T.T., Liem, N.T., Dung, N.T., San, L.T., Mai, P.P., Chau,
N.v.V., Suu, P.T., Dong, V.C.,Mai, L.T.Q., Thi, N.T., Khoa, D.B.,
Phat, L.P., Truong, N.T., Long, H.T., Tung, C.V.,Giang, L.T., Tho,
N.D., Nga, L.H., Tien, N.T.K., San, L.H., Tuan, L.V., Dolecek, C.,
Thanh,T.T., de Jong, M., Schultsz, C., Cheng, P., Lim, W., Horby,
P., Farrar, J., 2004. Avian influ-enza A (H5N1) in 10 patients in
Vietnam. N. Engl. J. Med. 350, 1179–1188.
Hu, S.-J., Ren, G., Liu, J.-L., Zhao, Z.-A., Yu, Y.-S., Su,
R.-W., Ma, X.-H., Ni, H., Lei, W., Yang,Z.-M., 2008. MicroRNA
expression and regulation in mouse uterus during
embryoimplantation. J. Biol. Chem. 283, 23473–23484.
Hu, G., Zhou, R., Liu, J., Gong, A.-Y., Eischeid, A.N., Dittman,
J.W., Chen, X.-M., 2009.MicroRNA-98 and let-7 confer cholangiocyte
expression of cytokine-inducible Srchomology 2-containing protein
in response to microbial challenge. J. Immunol.183, 1617–1624.
Iliopoulos, D., Hirsch, H.A., Struhl, K., 2009. An epigenetic
switch involving NF-[kappa]B, Lin28, Let-7 MicroRNA, and IL6 links
inflammation to cell transformation. Cell139, 693–706.
Johnnidis, J.B., Harris, M.H., Wheeler, R.T., Stehling-Sun, S.,
Lam, M.H., Kirak, O., Brum-melkamp, T.R., Fleming, M.D., Camargo,
F.D., 2008. Regulation of progenitor cellproliferation and
granulocyte function by microRNA-223. Nature 451, 1125–1129.
Karupiah,G., Chen, J.H.,Mahalingam, S., Nathan, C.F.,MacMicking,
J.D., 1998. Rapid interfer-on gamma-dependent clearance of
influenza A virus and protection from consolidat-ing pneumonitis
innitric oxide synthase 2-deficientmice. J. Exp.Med. 188,
1541–1546.
Kelliher, M.A., Grimm, S., Ishida, Y., Kuo, F., Stanger, B.Z.,
Leder, P., 1998. The death domainkinase RIP mediates the
TNF-induced NF-[kappa]B signal. Immunity 8, 297–303.
Koziczak-Holbro, M., Joyce, C., Glück, A., Kinzel, B., Müller,
M., Tschopp, C., Mathison, J.C.,Davis, C.N., Gram, H., 2007. IRAK-4
kinase activity is required for interleukin-1(IL-1) receptor- and
Toll-like receptor 7-mediated signaling and gene expression.J.
Biol. Chem. 282, 13552–13560.
Li, T.,Morgan,M.J., Choksi, S., Zhang, Y., Kim, Y.-S., Liu,
Z.-g., 2010a.MicroRNAsmodulate thenoncanonical transcription factor
NF-[kappa]B pathway by regulating expression of thekinase
IKK[alpha] during macrophage differentiation. Nat. Immunol. 11,
799–805.
Li, Y., Chan, E.Y., Li, J., Ni, C., Peng, X., Rosenzweig, E.,
Tumpey, T.M., Katze, M.G., 2010b.MicroRNA expression and virulence
in pandemic influenza virus-infected mice.J. Virol. 84,
3023–3032.
Lu, T.X., Munitz, A., Rothenberg, M.E., 2009. MicroRNA-21 is
up-regulated in allergic air-way inflammation and regulates
IL-12p35 expression. J. Immunol. 182, 4994–5002.
Maines, T.R., Lu, X.H., Erb, S.M., Edwards, L., Guarner, J.,
Greer, P.W., Nguyen, D.C., Szretter,K.J., Chen, L.-M., Thawatsupha,
P., Chittaganpitch, M., Waicharoen, S., Nguyen, D.T.,Nguyen, T.,
Nguyen, H.H.T., Kim, J.-H., Hoang, L.T., Kang, C., Phuong, L.S.,
Lim, W.,Zaki, S., Donis, R.O., Cox, N.J., Katz, J.M., Tumpey, T.M.,
2005. Avian influenza (H5N1)viruses isolated fromhumans inAsia in
2004 exhibit increased virulence inmammals.J. Virol. 79,
11788–11800.
Mao, J., Qiao, X., Luo, H., Wu, J., 2006. Transgenic drak2
overexpression in mice leads toincreased T cell apoptosis and
compromised memory T cell development. J. Biol.Chem. 281,
12587–12595.
O'Connell, R.M., Rao, D.S., Chaudhuri, A.A., Baltimore, D.,
2010. Physiological and patholog-ical roles for microRNAs in the
immune system. Nat. Rev. Immunol. 10, 111–122.
Olaru,A.V.,Ghiaur,G., Yamanaka, S., Luvsanjav,D., An, F.,
Popescu, I., Alexandrescu, S.,Allen, S., Pawlik, T.M.,
Torbenson,M.,Georgiades, C., Roberts, L.R.,Gores, G.J.,
Fergu-son-Smith, A., Almeida, M.I., Calin, G.A.,Mezey, E., Selaru,
F.M., in press. A microRNAdownregulated in human cholangiocarcinoma
controls cell cycle throughmultipletargets involved in the G1/S
checkpoint. Hepatology.
Park, S.-Y., Lee, J.H., Ha, M., Nam, J.-W., Kim, V.N., 2009.
miR-29 miRNAs activate p53 bytargeting p85[alpha] and CDC42. Nat.
Struct. Mol. Biol. 16, 23–29.
Ramachandran, S., Liu, P., Young, A.N., Yin-Goen, Q., Lim, S.D.,
Laycock, N., Amin, M.B.,Carney, J.K., Marshall, F.F., Petros, J.A.,
Moreno, C.S., 2005. Loss of HOXC6 expressioninduces apoptosis in
prostate cancer cells. Oncogene 24, 188–198.
Recchiuti, A., Krishnamoorthy, S., Fredman, G., Chiang, N.,
Serhan, C.N., 2011. Micro-RNAs in resolution of acute inflammation:
identification of novel resolvin D1-miRNA circuits. FASEB J. 25
(2), 544–560.
Szretter, K.J., Gangappa, S., Lu, X., Smith, C., Shieh, W.-J.,
Zaki, S.R., Sambhara, S.,Tumpey, T.M., Katz, J.M., 2007. Role of
host cytokine responses in the pathogen-esis of avian H5N1
influenza viruses in mice. J. Virol. 81, 2736–2744.
Tumpey, T.M., García-Sastre, A., Taubenberger, J.K., Palese, P.,
Swayne, D.E., Basler, C.F.,2004. Pathogenicity and immunogenicity
of influenza viruses with genes from the1918 pandemic virus. Proc.
Natl. Acad. Sci. U. S. A. 101, 3166–3171.
Tumpey, T.M., Garcia-Sastre, A., Taubenberger, J.K., Palese, P.,
Swayne, D.E., Pantin-Jackwood,M.J., Schultz-Cherry, S., Solorzano,
A., Van Rooijen, N., Katz, J.M., Basler, C.F., 2005. Path-ogenicity
of influenza viruses with genes from the 1918 pandemic virus:
functionalroles of alveolarmacrophages andneutrophils in limiting
virus replication andmortalityin mice. J. Virol. 79,
14933–14944.
Wang,H., Bloom,O., Zhang,M., Vishnubhakat, J.M., Ombrellino,M.,
Che, J., Frazier, A., Yang,H., Ivanova, S., Borovikova, L.,
Manogue, K.R., Faist, E., Abraham, E., Andersson, J.,Andersson, U.,
Molina, P.E., Abumrad, N.N., Sama, A., Tracey, K.J., 1999. HMG-1 as
alate mediator of endotoxin lethality in mice. Science 285,
248–251.
Yuen, K.Y., Chan, P.K.S., Peiris, M., Tsang, D.N.C., Que, T.L.,
Shortridge, K.F., Cheung, P.T.,To, W.K., Ho, E.T.F., Sung, R.,
Cheng, A.F.B., 1998. Clinical features and rapid viral di-agnosis
of human disease associated with avian influenza A H5N1 virus.
Lancet351, 467–471.
Zhou, R., Hu, G., Liu, J., Gong, A.Y., Drescher, K.M., Chen,
X.M., 2009. NF-kappaB p65-dependent transactivation of miRNA genes
following Cryptosporidium parvum in-fection stimulates epithelial
cell immune responses. PLoS Pathog. 5, e1000681.
Differential microRNA expression and virulence of avian, 1918
reassortant, and reconstructed 1918 influenza A
virusesIntroductionResults and discussionHPAI infections induced
unique cellular microRNA expression profiles in macaque lungsWe
identified a set of microRNAs that may be associated with high
virulence across species and influenza virusesPredicted targets of
microRNAs affected by infection with highlypathogenic influenza
viruses were associated with inflammatoryresponse pathways and cell
deathSynergistic regulation of inflammation and cell death by
cellular microRNAs during the HPAI infection in macaques
Material and methodsVirusesMacaque experimentsRNA
isolationMicroRNA microarray analysismRNA microarray
analysisMicroRNA target databaseStatistical analysisBioinformatics
analysis
Conflict of interestAcknowledgmentsReferences