Mol Biol Rep (2016) 43:175–181 DOI 10.1007/s11033-016-3952-8

ORIGINAL ARTICLE

Possible involvement of miRNAs in tropism of Parvovirus B19 Azadeh Anbarlou1 • Mahshid AkhavanRahnama2 • Amir Atashi1 • Masoud Soleimani1 Ehsan Arefian3 • Giorgio Gallinella4

•

Received: 9 December 2015 / Accepted: 9 February 2016 / Published online: 15 February 2016 Ó Springer Science+Business Media Dordrecht 2016

Abstract Human Parvovirus B19 (PVB19) is one of the most important pathogens that targets erythroid lineage. Many factors were mentioned for restriction to erythroid progenitor cells (EPCs). Previous studies showed that in non-permissive cells VP1 and VP2 (structural proteins) mRNAs were detected but could not translate to proteins. A bioinformatics study showed that this inhibition might be due to specific microRNAs (miRNAs) present in non-permissive cells but not in permissive EPCs. To confirm the hypothesis, we evaluated the effect of miRNAs on VP expression. CD34? HSCs were separated from cord blood. Then, CD34? cells were treated with differentiation medium to obtain CD36? EPCs. To evaluate the effect of miRNAs on VP expression in MCF7 and HEK-293 cell lines (non-permissive cells) and CD36? EPCs, dual luciferase assay was performed in presence of shRNAs against Dicer and Drosha to disrupt miRNA biogenesis. QRTPCR was performed to check down-regulation of Dicer and Drosha after transfection. All measurements were done in triplicate. Data means were compared using one-way

Azadeh Anbarlou and Mahshid AkhavanRahnama have contributed equally as first author to this work. & Amir Atashi [email protected]; [email protected] 1

Department of Hematology, Faculty of Medical Sciences, Tarbiat Modares University, P.O. Box 14115-331, Tehran, Iran

2

Department of Hematology, Tabriz University of Medical Sciences, Tabriz, Iran

3

Department of Microbiology, School of Biology, College of Science, University of Tehran, Tehran, Iran

4

Department of Pharmacy and Biotechnology, S.OrsolaMalpighi Hospital - Microbiology, University of Bologna, Bologna, Italy

ANOVAs. MicroRNA prediction was done by the online microRNA prediction tools. No significant difference was shown in luciferase activity of CD36? EPCs after co-transfection with shRNAs, while it was significant in non-permissive cells. Our study revealed that miRNAs may be involved in inhibition of VP expression in non-permissive cells, although further studies are required to demonstrate which miRNAs exactly are involved in regulation of PVB19 replication. Keywords Parvovirus B19  Erythroid Progenitors  microRNAs  MCF7  HEK-293

Introduction Human Parvovirus B19 (PVB19) is associated with a wide variety of diseases such as acute or chronic erythroid aplasia, erythema infectiosum (fifth disease), post-infection arthropathies, myocarditis, and possibly autoimmune diseases. The virus can be transmitted to the fetus, with possible consequences such as fetal death and/or hydrops fetalis [1]. The virus shows a marked tropism for erythroid progenitors (EPCs) that can support a productive viral replication. In vitro, myeloblastoid cell lines such as UT7/ EpoS1 or KU812Ep6 are partially permissive to B19V infection and can be used for study of PVB19/cell interactions, although the levels of infectivity are low [2, 3]. At first, researchers thought this restriction to EPCs could be related to specific receptors like red cell antigens P (globoside) which are expressed on EPCs, but some of non-permissive cells to PVB19 are expressed this receptor. The presence of other receptors, such as a5b1 integrins, or an uncharacterized receptor moiety, may be required to allow internalization of virus into cells, but also these coreceptors can be present in non-permissive cells. Hence,

123

176

other mechanisms may be involved in resistance of nonpermissive cells against PVB19 infection [4–6]. In productively infected cells, replication of viral DNA, transcription of the full set of viral mRNAs and production of viral proteins are coordinated events that lead to the release of progeny virus. PVB19 genome encodes a major nonstructural protein (NS), that plays a key role in replication and transcription of the viral genome [7], and two structural proteins (VP1 and VP2) that form the viral capsid. In some non-permissive cell systems, VP1 and VP2 mRNAs are not efficiently translated into proteins [8, 9]. Discovery of microRNAs (miRNAs) led to a massive revolution in our understanding of regulation of gene expression, due to their involvment in post-transcriptional regulation of gene expression. First transcription of miRNAs, are classified as noncoding RNA, known as primiRNA, then process by Drosha and Pasha and convert to pre-miRNA. Pre-miRNAs are metabolized to mature form of miRNAs by Dicer [10, 11]. Cellular miRNAs can be involved in restriction of viral infection [12]. For instance, replication of human immunodeficiency virus (HIV) and mink enteritis virus (MEV) is inhibited by hsa-miR-29a and miR-181b, respectively. Cellular miR-29a targets viral Nef mRNA and miR-181b targets the NS1 coding region which result in repression of mRNA translation directly [13]. On the basis of previous reports [8], to confirm the hypothesis expressed in [4] that in cells nonpermissive to PVB19, miRNAs exist that can target the 30 UTR region of VP mRNAs, preventing translation of capsid proteins, we evaluated the effect of miRNAs on VP expression, using dual luciferase assay in presence of shRNAs against Dicer and Drosha to disrupt miRNA biogenesis. Theses miRNAs should be down-regulated in erythroid progenitors and make them permissive to PVB19 infection.

Mol Biol Rep (2016) 43:175–181

Cell culture MCF7 (human breast adenocarcinoma cell line) and HEK293 (Human Embryonic Kidney 293 cells) cell lines were obtained from Iran Pasteur Institute (cell bank of Iranian Pasteur Institute) and cultured in DMEM (Dulbecco’s Modified Eagle’s Medium) medium supplemented with 10 % fetal bovine serum [FBS (Gibco; Carlsbad, CA)], 2 mmol/l L-glutamin, and 1 9 antibiotics. Differentiation of CD341 cells into Erythroid lineages Expanded HSCs were transferred to Alpha minimum essential medium (Sigma) supplemented with 1 % BSA (Sigma, USA), 10 lg/ml of insulin (Sigma), 200 g/ml of iron-saturated human transferrin (Sigma), 900 ng/ml of ferrous sulfate (Sigma), 90 ng/ml of ferric nitrate (Sigma), 1 M hydrocortisone (Sigma), 25 ng/ml of SCF (Peprotech, USA), 5 ng/ml of interleukin-3 (IL-3; Peprotech, USA), and 4 IU per milliliter of Erythropoietin (EPO; Peprotech, USA) for 10 days. Flow cytometry Flow cytometry was performed to evaluate purity of CD34? cells after cell separation. Purified CD34? cells were incubated with phycoerythrin (PE)-conjugated antiCD34 antibodies (Stem Cell Technology) for 45 min at 4 °C. Mouse IgG1was used as isotype control. To ensure differentiation of HSCs to erythroid lineages after 10 days, CD36 marker (FITC-conjugated Anti-CD36 antibodies (Abcam Technology, USA)) was evaluated. Plasmid preparation

Materials and methods Isolation of mononuclear cells from cord blood and immunomagnetic cell separation Immediately after delivery, UCB was obtained from cord vein and was collected in bags with CPDA 1 (Citrate– Phosphate–Dextrose–Adenine). Mononuclear cells were isolated from UCB by Ficoll-Paque PLUS (Amersham Biosciences, Inc. USA) density gradient centrifugation. The MACS indirect CD34 MicroBead Kit (Miltenyi Biotec) was used to separate CD34? HSCs according to the manufacturer’s instructions. Afterwards, CD34? HSCs were collected and transferred into serum-free Stemline II expansion medium (Sigma-Aldrich) supplemented with 10 ng/ml TPO, 25 ng/dl stem cell factor (SCF; Peprotech,USA), 25 ng/dl Flt-3L, 2 mmol/l L-glutamine and 1 9 antibiotics.

123

Dicer KO vector (Addgene plasmid # 16656), psicoR human Drosha (Addgene plasmid # 14767) and scramble shRNA (Addgene plasmid # 1864) were purchased from Addgene (MA, USA) and psiCHECKTM-2 from Promega (USA). Bacterial colonies were grown in LB-ampicillin broth by incubation with shaking at 37 °C overnight. Then plasmids were extracted using plasmid purification kit (Macherey–Nagel, Germany). Dual luciferase reporter assay We first cloned 30 UTR of VP mRNAs according to previous report (18) in the 30 of Renilla luciferase in psiCHECKTM-2 vector (Promega, USA) using VP 30 UTR-F CGTGTGCACCCATTGTAAAC; VP 30 UTR-R GCCATC TTGTACCGGAAGTC.

Mol Biol Rep (2016) 43:175–181

Luciferase assay was performed with dual luciferase assay kit (Promega, USA) according to the manufacturer’s instructions. Apparent luminescence was measured by Tube Luminometer (Berthold, USA) and normalized by dividing to luminescence from firefly luciferase. Transfection and nucleofection Transfection of MCF7 and HEK-293 cell lines with Dicer KO vector (Addgene plasmid # 16656), psicoR human Drosha (Addgene plasmid # 14767) and VP 30 UTR Luciferase vector was performed by Express-In transfection reagent (GE Dharmacon, USA) according to the manufacturer’s instructions. Nucleofection of CD36? EPCs was performed according to the manufacturer’s instructions with the Amaxa Nucleofector system (Lonza). The Cells (1 9 106) were resuspended in 100 ll of Nucleofector reagent V (Lonza), 2.5 lg of VP 30 UTR Luciferase vector was added. Sample was transferred into confirmed cuvette (Lonza) and transfected by nucleofection with program T-19. Fresh medium (500 ll) was added immediately after transfection to each cuvette, and the cells were plated and incubated at 37 °C. After nucleofection, viability of nucleofected cells was evaluated with 0.4 % Trypan Blue (Sigma-Aldrich). RT-PCR and qRT-PCR Total RNA was extracted with RNeasy Plus Mini Kit (QIAGEN, USA). Reverse transcription was performed using cDNA Synthesis Kit (Thermo Scientific, USA). Expression of EKLF (Erythroid Kruppel-like factor), GATA-1, a-Globin, b-Globin and c-Globin genes was evaluated by RT-PCR to ensure differentiation of HSCs to EPCs. RT-PCR was performed with 2 9 PCR Master Mix (Thermo Scientific, USA). Electrophoresis of PCR products was performed in 2 % agarose gel. HPRT1 (Hypoxanthine Phosphoribosyl Transferase 1) gene was as an endogenous control. The primers used were: GATA-1 (forward 50 -AGACGACCACCACGACAC-30 , reverse 50 CCAGATGCCTTGCGGTTTC-30 ), EKLF (forward 50 CGCCTTGCCCTCCATC AG-30 , reverse 50 -CCCTCTC ATCGTCCTCTTCC-30 ), a-Globin (forward 50 -TGACCTC CAAATACCGTTAAGC-30 , reverse 50 -CCGCCCACTCA GACTTTATTC-30 ), b-Globin (forward 50 - CTCACCTGG ACAACCTCAAG-30 , reverse 50 - AGCCACCACTTTCTG ATAGG-30 ), c-Globin (forward 50 -GTCCTCTGCCTCTG CCATC-30 , reverse 50 -CGGTCACCAGCACATTTCC-30 ), HPRT 1 (forward 50 -CCTGGCGTCGTGATTAGTG-30 , reverse 50 -TCAGTCCTGTCCATAATTAGTCC-30 ). qRT-PCR was performed to check down-regulation of Dicer and Drosha after transfection. The cDNA were subjected to qRT-PCR using SYBR Premix Ex Taq II

177

(Takara, Japan). GAPDH mRNA in each sample was quantified as an endogenous control. The relative expression levels of genes were calculated using the 2DDCt method. The primers used were: hDCR1 (Dicer1) (forward 50 -TGATGAAGAAGAGACCAGTGTTC-30 , reverse 50 GTGTGGAATCTGAGGTATGGG-30 ), Drosha (formerly RNASEN) (forward 50 -GGGCGAGGTGAGAGGCATC30 , reverse 50 -CCGATAAACCGTAACTCCTTCCAG-30 ), GAPDH (forward 50 -TAAGACCCCTGGACCACC-30 , reverse 50 -GGTTGAGCACAGGGT ACTTTATTG-30 ). Bioinformatics analysis MicroRNA prediction was done by the online microRNA prediction tools of RNA22 computational medicine center (https://cm.jefferson.edu/rna22/Interactive/) and the Segal lab of computational biology (http://genie.weizmann.ac.il/ pubs/mir07/mir07_prediction.html). Energy threshold was set to -16 kcal/mol in two microRNA prediction Data Bases. Statistical analysis All measurements were done in triplicate. Statistical analyses were performed by SPSS V 16.0 analytical Software. Data means were compared using one-way ANOVAs. Statistical significance was defined at P \ 0.05.

Results Differentiation to erythroid progenitors The purity of CD34? cells obtained from UCB was evaluated by flow cytometry. The percentage of CD34? Cells was nearly 85 % after immunomagnetic separation. To verify differentiation to erythroid progenitors after 10 day of in vitro culture, RT-PCR for EKLF, GATA-1, AlphaGlobin, Beta-Globin and Gama-Globin genes was performed (Fig. 1). The CD36 erythroid differentiation marker was present in around 83 % of cells, as evaluated by flow cytometry (Fig. 2).

Evaluation of efficacy of nucleofection and transfection by GFP vector To investigate the role of microRNAs in permissiveness of EPCs to parvovirus infection, cells were nucleofected with Dicer KO vector, psicoR human Drosha shRNAs to inhibit microRNA biogenesis. Nucleofection efficiency was evaluated by flow cytometry. 79 % of EPCs were nucleofected by GFP vector after 48 h post nucleofection.

123

178

Mol Biol Rep (2016) 43:175–181

Fig. 1 Gel electrophoresis of PCR products shows differentiation of CD34 ? HSCs to erythroid progenitors

Similarly, transfection was carried out in non-permissive HEK-293 and MCF-7 cell lines. Transfection efficiency was evaluated by flow cytometry. More than 82 % of cells were transfected by GFP vector after 48 h post transfection. Moreover, qRT-PCR was performed for Dicer and Drosha in order to ensure that shRNAs work specifically. The mean relative expression levels of Dicer down-regulated to 0.49 and Drosha to 0.55 in EPCs and cell lines in comparison to control group.

vector), luciferase activity in HEK-293 (P = 0.0075) and MCF-7 (P = 0.0022) cell lines significantly were increased after transfection of shRNAs whereas in EPCs, luciferase activity results were not significant (P = 0.1348) (Fig. 3).

Dual luciferase reporter assay

Bioinformatics results

To evaluate the ability of microRNAs binding to the 30 UTR of VP mRNAs, we first synthesized a reporter plasmid bearing a 0.3 kb fragment of PVB19 genome (bases 4952–5287) downstream of luciferase and co-transfected it with shRNAs or negative control into HEK-293, MCF7 and EPC cells. Compared with empty vector (psiCHECKTM -2

By bioinformatics analysis, using the online microRNA prediction tools of the Segal lab of computational biology (Table 1) and RNA22 computational medicine center (Table 2), we found that some human microRNAs were potentially able to bind to the regulatory 30 UTR of VP mRNAs, explaining the observed experimental results.

Fig. 3 Bar graph shows luciferase activity of groups after cotransfection with shRNAs

Fig. 2 The majority of differentiated cells shows CD36 antigen in their surface

123

Mol Biol Rep (2016) 43:175–181

179

Discussion

Table 1 MicroRNA prediction Results with Segal lab microRNA hsa-miR-8072

Position 67

dG duplex -18.45

hsa-miR-8072

285

-25.8

hsa-miR-8072

282

-24

hsa-miR-8072

278

-17.9

92

-22.2

hsa-miR-6728-5p hsa-miR-5698

68

-23.1

hsa-miR-5698

69

-22.7

hsa-miR-6511b-5p

76

-19.8

hsa-miR-5698

71

-18.5

hsa-miR-5698 hsa-miR-6511b-5p hsa-miR-6511b-5p

72

-17.5

60 287

-16.8 -18.4

hsa-miR-4767

41

-22.42

hsa-miR-4792

41

-17.52

hsa-miR-4767

286

-22.8

hsa-miR-4792

279

-16.4

hsa-miR-4751

297

-18.7

Table 2 MicroRNA prediction Results with RNA22

miR name

Position

The in vivo tropism of PVB19 for erythroid progenitor cells in bone marrow is paralleled in vitro by the limited range of cells susceptible to infection. In fact, PVB19 proliferation is mainly limited to EPCs. Hence, CD36? Cells derived from ex vivo CD34? HSCs can be used as a suitable cell model system to study regulation of PVB19 replication [2, 14]. Different reasons such as limited expression of special receptors and co-receptors for entrance of PVB19 into cells and also internal factors are considered to explain the marked tropism of PVB19 to EPCs [15, 16]. Epo stimulation is necessary not only for EPCs proliferation and differentiation, but is also directly involved to promote viral replication. Luo et al. [18] reported that PVB19 infection induces phosphorylation of all the upstream kinases in response to DNA damage [17]. Inhibition of kinase phosphorylation showed ATR-Chk1 signaling has a critical role in PVB19 proliferation [18]. Moreover, different studies showed that hypoxia facilitate PVB19

dG (Kcal/mol)

miR name

Position

dG (Kcal/mol)

hsa-miR-3064-5p

9

-18.50

hsa-miR-6776-5p

41

-23.80

hsa-miR-3064-5p

40

-16.40

hsa-miR-6795-5p

1

-16.10

hsa-miR-3141

2

-28.30

hsa-miR-6793-5p

3

-17.90

hsa-miR-3155a

3

-16.30

hsa-miR-6799-5p

39

-16.60

hsa-miR-3155b

6

-16.30

hsa-miR-6779-5p

42

-23.80

hsa-miR-3178

2

-20.00

hsa-miR-6803-5p

1

-22.20

hsa-miR-3934-3p

5

-16.90

hsa-miR-6805-5p

1

-19.40

hsa-miR-3945

1

-17.60

hsa-miR-6846-5p

1

-25.20

hsa-miR-4253

4

-20.30

hsa-miR-6862-5p

1

-22.40

hsa-miR-432-5p hsa-miR-4505

8 10

-20.40 -19.80

hsa-miR-6862-5p hsa-miR-6870-5p

1 1

-22.40 -19.10

hsa-miR-4483

42

-16.10

hsa-miR-6887-5p

1

-18.50

hsa-miR-4665-5p

3

-20.30

hsa-miR-6875-5p

3

-16.60

hsa-miR-4687-3p

2

-21.40

hsa-miR-7150

9

-21.10

hsa-miR-4689

3

-28.40

hsa-miR-8075

2

-18.30

hsa-miR-4673

5

-20.10

hsa-miR-8073

8

-20.10

hsa-miR-4710

6

-28.10

hsa-miR-6127

3

-23.90

hsa-miR-4701-3p

8

-23.70

hsa-miR-615-5p

3

-17.70

hsa-miR-4701-3p

40

-22.20

hsa-miR-6133

4

-19.10

4

-25.10

hsa-miR-6126

5

-16.00

hsa-miR-4758-5p

39

-19.30

hsa-miR-6727-5p

2

-23.20

hsa-miR-502-5p

11

-17.20

hsa-miR-659-3p

5

-18.70

hsa-miR-5194

2

-17.20

hsa-miR-6736-5p

7

-29.10

hsa-miR-6090

2

-18.60

hsa-miR-6745

41

-16.60

hsa-miR-4734

123

180

Mol Biol Rep (2016) 43:175–181

infection [14, 19]. Chen et al. displayed MAPK1 (Mitogenactivated protein kinase 1) and ERK (extracellular-signalregulated kinase) but not HIF-1 (Hypoxia-inducible factor 1) are involved in this process [19]. One of the important regulatory mechanisms of gene expression is miRNAs [19]. Recently, studies showed their role in some interactions between host and viruses. miRNAs change immune response against viral infection [20]. In some viruses, cellular miRNAs help to promote viral infection and sometimes limit their proliferation [20–22]. In 1997, Coralie Pallier et al., showed that 30 UTR of VP1 and VP2 mRNAs repress synthesis of capsid proteins in non-permissive cells [23]. As we know, miRNAs mostly adhere to 30 UTR of their target mRNAs and exert their inhibitory effect on translation of mRNAs [24]. With regard to mentioned information, we assumed miRNAs may play roles in PVB19 pathogenesis. Berillo et al. [4] showed that this inhibition might be due to specific microRNAs (miRNAs) present in non-permissive cells but not in permissive EPCs. To confirm the hypothesis, we evaluated the effect of miRNAs on VP expression. So if miRNAs are involved in permissiveness to PVB19 infection in EPCs, shRNAs for Dicer and Drosha may switch non-permissive cells to permissive cells. To evaluate the effect of miRNAs on VP expression, luciferase assay was performed. No significant difference was shown in luciferase activity of EPCs after co-transfection with shRNAs, while it was very significant in non-permissive cells. These results showed that miRNAs may be involved in inhibition of VP expression in non-permissive cells but not in permissive cells. To define which human miRNA regulates VP expression in non-permissive cells, miRNA prediction was performed by using online microRNA prediction tools. Analysis of predicted miRNAs showed that some human miRNAs were able to bind to 30 UTR of VP mRNAs. Berillo et al. [4] found 64 miRNAs which were able to bind to VP mRNA theoretically, while we found 53 miRNAs. The difference between our results might be due to difference in online microRNA prediction software and VP sequence. Although we could not find some common miRNAs in two databases, these results suggest that human miRNAs may have critical roles in PVB19 pathogenesis. In future experimental studies, understanding miRNAs pathways can help us to choose some of them which probably are not found in EPCs. Acknowledgments The present work supported by Stem Cell Technology Research Center, Tehran, Iran. Compliance with ethical standards Conflict of interest

123

All authors declare no conflict of interest.

References 1. Gallinella G (2013) Parvovirus B19 achievements and challenges. ISRN Virol 2013:1–33 2. Wong S, Zhi N, Filippone C, Keyvanfar K, Kajigaya S, Brown KE, Young NS (2008) Ex vivo-generated CD36 ? erythroid progenitors are highly permissive to human parvovirus B19 replication. J Virol 82(5):2470–2476 3. Bonvicini F, Filippone C, Delbarba S, Manaresi E, Zerbini M, Musiani M, Gallinella G (2006) Parvovirus B19 genome as a single, two-state replicative and transcriptional unit. Virology 347:447–454 4. Berillo O, Khailenko V, Ivashchenko A, Perlmuter-Shoshany L, Bolshoy A (2012) miRNA and tropism of human parvovirus B19. Comput Biol Chem 40:1–6 5. Guan W, Cheng F, Yoto Y, Kleiboeker S, Wong S, Zhi N, Pintel DJ, Qiu J (2008) Block to the production of full-length B19 virus transcripts by internal polyadenylation is overcome by replication of the viral genome. J Virol 82(20):9951–9963 6. Winter K, von Kietzell K, Heilbronn R, Pozzuto T, Fechner H, Weger S (2012) Roles of E4orf6 and VA I RNA in adenovirusmediated stimulation of human parvovirus B19 DNA replication and structural gene expression. J Virol 86(9):5099–5109 7. Tewary SK, Zhao H, Deng X, Qiu J, Tang L (2014) The human parvovirus B19 non-structural protein 1 N-terminal domain specifically binds to the origin of replication in the viral DNA. Virology 449:297–303 8. Pallier C, Greco A, Le Junter J, Saib A, Vassias I, Morinet F (1997) The 30 untranslated region of the B19 parvovirus capsid protein mRNAs inhibits its own mRNA translation in nonpermissive cells. J Virol 71(12):9482–9489 9. Bonvicini F, Mirasoli M, Manaresi E, Bua G, Calabria D, Roda A, Gallinella G (2013) Single-cell chemiluminescence imaging of parvovirus B19 life cycle. Virus Res 178:517–521 10. Huang Y, Shen XJ, Zou Q, Wang SP, Tang SM, Zhang GZ (2011) Biological functions of microRNAs: a review. J Physiol Biochem 67(1):129–139 11. Siomi H, Siomi MC (2010) Posttranscriptional regulation of microRNA biogenesis in animals. Mol Cell 38(3):323–332 12. Yeung ML, Benkirane M, Jeang K-T (2007) Small non-coding RNAs, mammalian cells, and viruses: regulatory interactions? Retrovirology 4(1):74 13. J-z Sun (2013) Wang J, Yuan D, Wang S, Li Z, Yi B, Mao Y, Hou Q, Liu W. Cellular microRNA miR-181b inhibits replication of mink enteritis virus by repression of non-structural protein 1 translation. PLoS One 8(12):e81515 14. Pillet S, Fichelson S, Morinet F (2008) Human B19 erythrovirus in vitro replication: what’s new? J Virol 82(17):8951–8953 15. Wolfisberg R, Ruprecht N, Kempf C, Ros C (2013) Impaired genome encapsidation restricts the in vitro propagation of human parvovirus B19. J Virol Methods 193(1):215–225 16. Pozzuto T, von Kietzell K, Bock T, Schmidt-Lucke C, Poller W, Zobel T, Lassner D, Zeichhardt H, Weger S, Fechner H (2011) Transactivation of human parvovirus B19 gene expression in endothelial cells by adenoviral helper functions. Virology 411(1):50–64 17. Chen AY, Guan W, Lou S, Liu Z, Kleiboeker S, Qiu J (2010) Role of erythropoietin receptor signaling in parvovirus B19 replication in human erythroid progenitor cells. J Virol 84:12385–12396 18. Luo Y, Lou S, Deng X, Liu Z, Li Y, Kleiboeker S, Qiu J (2011) Parvovirus B19 infection of human primary erythroid progenitor cells triggers ATR-Chk1 signaling, which promotes B19 virus replication. J Virol 85(16):8046–8055

Mol Biol Rep (2016) 43:175–181 19. Chen AY, Kleiboeker S, Qiu J (2011) Productive parvovirus B19 infection of primary human erythroid progenitor cells at hypoxia is regulated by STAT5A and MEK signaling but not HIFa. PLoS Pathog 7(6):e1002088 20. Filipowicz W, Bhattacharyya SN, Sonenberg N (2008) Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet 9(2):102–114 21. Zhang Y, Li Y-k (2013) MicroRNAs in the regulation of immune response against infections. J Zhejiang Univ Sci B 14(1):1–7

181 22. Huang J, Wang F, Argyris E, Chen K, Liang Z, Tian H, Huang W, Squires K, Verlinghieri G, Zhang H (2007) Cellular microRNAs contribute to HIV-1 latency in resting primary CD4 ? T lymphocytes. Nat Med 13(10):1241–1247 23. Chiang K, Rice AP (2012) MicroRNA-mediated restriction of HIV-1 in resting CD4 ? T cells and monocytes. Viruses 4(9):1390–1409 24. Bartel DP (2009) MicroRNAs: target recognition and regulatory functions. Cell 136(2):215–233

123