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Journal of Neuroscience Methods 177 (2009) 322–333

Contents lists available at ScienceDirect

Journal of Neuroscience Methods

journa l homepage: www.e lsev ier .com/ locate / jneumeth

oss of function genetic screens reveal MTGR1 as an intracellularepressor of �1 integrin-dependent neurite outgrowth

aleria S. Ossovskayaa,b,d,∗, Gregory Dolganovc,e, Allan I. Basbauma,b

Department of Anatomy, University of California San Francisco, San Francisco, CA 94158, USADepartment of Physiology, University of California San Francisco, San Francisco, CA 94158, USADepartment of Medicine, University of California San Francisco, San Francisco, CA 94158, USABiPar Sciences Inc., Brisbane, CA 94005, USADepartment of Infectious Diseases, School of Medicine, Stanford University, Stanford, CA 94305, USA

r t i c l e i n f o

rticle history:eceived 15 March 2008eceived in revised form3 September 2008ccepted 15 October 2008

a b s t r a c t

Integrins are transmembrane receptors that promote neurite growth and guidance. To identify regulatorsof integrin-dependent neurite outgrowth, here we used two loss of function genetic screens in SH-SY5Yneuroblastoma cells. First, we screened a genome-wide retroviral library of genetic suppressor elements(GSEs). Among the many genes identified in the GSE screen, we isolated the hematopoetic transcriptionalfactor MTGR1 (myeloid translocation gene-related protein-1). Treatment of SH-SY5Y cells with MTGR1

eywords:SEiRNAenetic screenseurite outgrowthTGR1

siRNA enhanced neurite outgrowth and concurrently increased expression of GAP-43, a protein linkedto neurite outgrowth. Second, we transduced SH-SY5Y with a genome-wide GFP-labeled lentiviral siRNAlibrary, which expressed 40,000 independent siRNAs targeting 8500 human genes. From this screen weisolated GFI1 (growth factor independence-1), which, like MTGR1, is a member of the myeloid transloca-tion gene on 8q22 (MTG8)/ETO protein complex of nuclear repressor proteins. These results reveal novelcontributions of MTGR1 and GFI1 to the regulation of neurite outgrowth and identify novel repressors of

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. Introduction

Despite significant advances in our understanding of theolecules that contribute to axonal growth, progress in overcom-

ng the failure of central nervous system axons to regenerate afternjury has been disappointing. Among the many factors that con-ribute to the poor regeneration of injured CNS axons are: reducedntrinsic growth capacity of the injured neurons, inability to over-ome inhibitory molecules in the region of the injury, and failureo respond to growth promoting molecules in the region of thenjury. As axonal growth is not hindered during development, it iseasonable to hypothesize that these properties are present in theeveloping neuron, but are lost or suppressed in the adult (Spencernd Filbin, 2004; He and Koprivica, 2004; Neumann et al., 2002).

Importantly, manipulations of the molecular machinery of theamaged neuron in the adult can enhance growth, indicating thathese properties can be reinstated (Neumann and Woolf, 1999;eumann et al., 2002; Filbin, 2003). Indeed, in recent years several

∗ Corresponding author at: BiPar Sciences, 1000 Marina Blvd., Suite 550, Brisbane,A 94005, USA. Tel.: +1 650 635 6045; fax: +1 650 635 6057.

E-mail address: vossovskaya@biparsciences.com (V.S. Ossovskaya).

adorsiait

165-0270/$ – see front matter. Published by Elsevier B.V.oi:10.1016/j.jneumeth.2008.10.031

growth.Published by Elsevier B.V.

mall molecules and proteins that either promote or inhibit therowth of neurites and axons have been identified. Among thesere guidance and signaling molecules (e.g. cAMP), secreted growthromoting and inhibitory molecules, including neurotrophins,etrins, slits, ephrins, semaphorins and myelin-associated proteinsTessier-Lavigne and Goodman, 2000, 1996; Schnorrer and Dickson,004; Nakamura et al., 1998; Arevalo and Chao, 2005; Neumannnd Woolf, 1999; Neumann et al., 2002).

With a view to providing a more extensive catalogue of theolecular contribution to various complex processes, attention

as turned to genetic screens (Nijman et al., 2005; Paddison etl., 2004). For example, several comprehensive screening meth-ds to study regulators of neuronal function have been describedn drosophila, C. elegans and zebrafish (Hivert et al., 2002; Hua etl., 2005; Runko and Kaprielian, 2004; Shao et al., 2005). Here weescribe the results of two functional genetic screens for repressorsf neurite outgrowth. We generated and screened a genome-wideetroviral GFP-genetic suppressor element (GSE) library and a large-

cale lentiviral siRNA library targeting 8500 genes. The screenntegrated a highly sensitive and comprehensive functional andrray-based analysis. Most of the targets that we identified fellnto five major categories: receptors, proteoglycans, kinases adap-or proteins and transcription factors. In this paper we report on

uroscience Methods 177 (2009) 322–333 323

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Fig. 1. Schematic illustration of the functional screen. (A) pQCGFPL retroviral vectorused as the transfer vector for library delivery into SH-SY5Y cells. LTR: long terminalrepeat; CMV: CMV promoter; EGFP: enhanced green fluorescent protein; L: linker.The self-inactivating feature of the vector is provided by a deletion of the U3 region inthe 3′LTR. (B) The vector pQCGFPL-GSE carries the GSE library and GFP for selectionof infected cells. PCR primers used for rescue of integrated provirus are illustratedbpn

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V.S. Ossovskaya et al. / Journal of Ne

he contribution of MTGR1 (myeloid translocation gene-relatedrotein-1) and GFI1 (growth factor independence-1), both of whichelong to the same ETO/MTG8 (myeloid translocation gene onq22) protein complex (Hock and Orkin, 2006; McGhee et al., 2003;mann et al., 2005). This complex is a transcriptional repressor

hat regulates proliferation and differentiation of hematopoieticnd stem cells. We demonstrated that the MTGR1 and GFI1 neg-tively regulate �1-integrin-dependent elongation of neurites inuman SH-SY5Y neuroblastoma cells.

. Materials and methods

.1. Cell culture

SH-SY5Y cells were obtained from the ATCC and maintainedn DMEM/F12 media (50:50; Gibco) supplemented with 1% non-ssential amino acids (Gibco), 15% heat-inactivated fetal calf serum,CS (HyClone), 100 �g/mL penicillin and 100 �g/mL streptomycint 37 ◦C, 5% CO2. To induce differentiation, cells were plated onaminin-coated plates (Becton Dickinson Labware) and treated with–50 �M trans-retinoic acid (RA) (Sigma) for 36–72 h. Phoenix cellsere obtained from the ATCC with permission of G. Nolan (Stan-

ord University). AmphoPackTM-293 packaging cells were obtainedrom Clontech. Phoenix and AmphoPackTM-293 were maintainedn DMEM media (Gibco) supplemented with 10% heat-inactivatedetal calf serum (HyClone), 100 �g/mL penicillin and 100 �g/mLtreptomycin at 37 ◦C, 5% CO2.

.2. GSE library construction

A self-inactivating retroviral vector, pQCGFPL was constructedsing the pQCXIX vector (Clontech) in which the CMV-IRES cassetteas replaced with a CMV-EGFP-linker-adaptor cassette. The CMV-

GFP cassette was derived from the pLEGFP-N1 retroviral vectorClontech). This adapter was used to insert the GSE library (Fig. 1And B).

SH-SY5Y cells were treated with 25 �M trans-retinoic acidSigma) for 0, 12, 24, 48 or 72 h. After incubation with RA, theH-SY5Y cells were collected and used to construct the library, asreviously described (Gudkov et al., 1994; Ossovskaya et al., 1996),ith modifications provided below. Briefly, total mRNA was iso-

ated from 107 SH-SY5Y cells using the RNAqueous Kit (Ambion,ustin, TX) in six independent reactions, according to the manufac-urer’s instructions. mRNA quality was determined by microfluidicnalysis (Agilent® 2100 bioanalyzer with Caliper’s RNA LabChip®

it; Agilent). mRNA with a 28S–18S rRNA ratio of >1.2 was used foroly(A)+ RNA purification. Poly(A)+ RNA was purified from 2.0 mgf total mRNA with two rounds of oligo(dT) selection using theoly(A)Purist Kit (Ambion, Austin, TX) according to the manu-acturer’s instructions. The isolated poly(A)+ RNA with A260–A280alues in the range of 1.85–2.1 was used for cDNA synthesis. Theurity and integrity of the poly(A)+ RNA were verified by formalde-yde 2.5% agarose gel electrophoresis and capillary electrophoresissing the Agilent® 2100 bioanalyzer.

PolyA + RNA was used for cDNA synthesis with the SMARTDNA library protocol (Clontech) in six independent reactions,ccording to the manufacturer’s instructions, with some modifi-ations. Briefly, for each reaction 1.0 �g of PolyA + RNA was mixedith 1.0 �L 10 �M oligo(dT) (CDS primer), 1.0 �L 10 �M SMART II

ligonucleotide, and deionized water for a total volume of 5.0 �L.he mixture was heated at 72 ◦C for 2 min, cooled on ice formin and spun for 30 s. The reaction was followed by the addi-

ion of 2.0 �L 5′ reaction buffer (250 mM Tris–HCl, pH 8.3, 30 mMgCl2, and 375 mM KCl), 1.0 �L 20 mM DTT, 1.0 �L 10 mM dNTP

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y arrows. (C) Schematic illustration of retroviral transduction of SH-SY5Y cells withQCGFPL-GSE library and the functional genetic screening strategy for inhibitors ofeurite outgrowth.

10 mM each dATP, dCTP, dGTP, and dTTP; Amersham Pharmacia,iscataway, NJ, USA), 0.5 �L of 100 U/�L Power Script Reverse Tran-riptase (Clontech) and 28 U/�L Anti-RNase (Ambion, Austin, TX,SA). The samples were incubated at 42 ◦C for 1 h followed by inac-

ivation of reverse transcriptase at 72 ◦C for 7 min. Next 40 �L TEuffer (10 mM Tris–HCl, pH 7.4, 1 mM EDTA) were added to eachample, which were subsequently stored at −20 ◦C. To determinehe number of PCR cycles necessary for optimal amplification ofDNA, 1.0 �L from each first-strand cDNA reaction mixture wasombined with 10 �L 10× advantage polymerase buffer (40 mMricine–KOH, pH 9.2, 15 mM KOAc, 3.5 mM Mg(OAc)2), 1.0 �L PCRrimer (5′-AAGCAGTGGTAACAACGCAGAGT-3′), 2.0 �L 10 mM dNTPix (10 mM dATP, 10 mM dCTP, 10 mM dGTP, and 10 mM dTTP), and

.0 �L Advantage cDNA Polymerase Mix (Clontech). Samples weremplified using the following program: 1 cycle at 95 ◦C for 1 min,hen 15 cycles at 95 ◦C for 15 s, 65 ◦C for 30 s and 68 ◦C for 6 min.fter 15 cycles, 15 �L of the reaction mixture were transferred

o a new 0.5-mL tube and subjected to three additional cycles;he remaining 85 �L of the PCR mixture were kept on ice. Afterhree additional cycles, 5.0 �L of reaction mixture was aliquoted

or analysis by agarose gel, while the remaining 10 �L of the reac-ion mixture were subjected to another three cycles, for a total of 21ycles. To determine the optimal number of cycles, 5.0 �L of eachf the reaction mixture (i.e., 15-, 18-, and 21-cycle PCR products)

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24 V.S. Ossovskaya et al. / Journal of Ne

ere analyzed on a 1.5% agarose gel in Tris–acetate EDTA (TAE)uffer. Based on the results of the agarose gel analysis, samplesere subjected to additional cycles. Products of cDNA reactionsere purified using the NucleoTrap PCR Purification Kit (Clontech)

nd eluted in 50 �L TE buffer. One microgram of PolyA + RNA yieldsp to 10 �g of purified cDNA. The synthesized cDNA was ana-

yzed with 0.8%, 1.5% and 3% agarose gels in Tris–acetate EDTAuffer.

The size of synthesized cDNA ranged from 0.5 to 6 kb withnrichment at 0.9–3 kb, which is typical for human brain RNA. Tenicrograms of synthesized cDNA was digested with RsaI endonu-

lase, which recognizes the sequence 5′-GTAC-3′, creating cDNAragments with an average size of 100–250 bp. Ten micrograms ofynthesized cDNA in the second independent reaction was son-cated and fractionated by Quick Spin Columns (Sephadex G-25,ephadex G-50; Roche). The 25–250 bp cDNA fragments from botheactions were purified by electrophoresis and gel filtration usingephadex G-25, G-50 and G-100 (Sigma). cDNA fragments withn average size of 25–350 bp were ligated to attB1 and attB2ateway adapters, according to the Gateway protocol (Gibco, Invit-

ogen) and cloned into the pQCGFPL vector with the GATEWAYloning System (Gibco, Invitrogen), according to the manufac-urer’s instructions. The GSE library was amplified in TOP10 E. coliells on 50 independent 150-mm LB agar plates containing 0.1% glu-ose. The complexity of the GSE library was 9.6 × 107 independent E.oli clones. The library was purified with the QIAGEN Plasmid Maxiit (QIAGEN) according to the manufacturer’s instructions and used

o transfect packaging cells (see Section 2.1).

.2.1. Transduction of SH-SY5Y cells with the GSE libraryThe viral supernatant carrying the library was produced as

escribed previously (Martens et al., 2000; Ossovskaya et al.,996) with some modifications. Briefly, AmphoPack packaging cellsClontech) were plated at 5 × 107 cells per 150 mm plate (Corning)2 h prior to the transfection. After a 12 h incubation, the media washanged and packaging cells were transfected with 30 �g retro-iral plasmid DNA per plate using the FuGENE 6 reagent (Rochepplied Science), according to the manufacturer’s instructions. A

otal of 5 × 108 AmphoPack packaging cells were transfected withhe GSE library. At 12 h after transfection, the media was replacedith growth medium and cell cultures maintained at 37 ◦C in 5%

O2 for 12–24 h, then at 32 ◦C in 6% CO2 for 24–36 h.Sixty hours after transfection, the virus-containing supernatant

as collected from transfected packaging cells, filtered through.45 �m filters (Nalgene), supplied with 5 �g/mL Polybrene (Sigma,t. Louis, MO) and overlayed on SH-SY5Y target cells for 12 h.The SH-SY5Y cells had been plated for 12 h prior to retroviralransduction, with a seeding density of 2500 cells/cm2.) A total of× 108 SH-SY5Y cells were transduced with the GSE library. Theedium was changed 12 h after retroviral transduction and then

gain 12 h later. Ninety-six hours after retroviral transduction, theH-SY5Y cells were detached with trypsin and plated on laminin-oated plates (Becton Dickinson Labware) with a seeding densityf 2500 cells/cm2 and then treated with 25 �M trans-retinoic acidSigma) for 36 h to induce neurite outgrowth. Then the SH-SY5Yells were collected with No-Zyme solution (Sigma) and immunos-ained with an anti-�1 integrin antibody directly conjugated to APCPharmingen) as described below. The fluorescently labeled cellsere subsequently analyzed by flow cytometry for GFP expression

nd �1 integrin immunostaining.

.3. Screening the human siRNA library

The human siRNA library contained about 43,000 siRNA tar-eting 8500 human genes and was cloned into an FIV-based

SwPtK

ence Methods 177 (2009) 322–333

SIF1-H1 vector, as previously described (System Biosciences, SBI).he pSIF1-H1 vector carried GFP, which was used as a reporteror fluorescence-activated cell sorting (FACS) analysis (Fig. 8A).riefly, the siRNA library targeted and overlapped with the 8500enes represented on the GeneChip® Human Genome Focus ArrayAffimetrix).

The viral supernatant carrying the library was produced asescribed previously (Zufferey et al., 1998). Briefly, the siRNA

ibrary was transfected into 293T packaging cells (ATCC) with theFIV-PACK packaging plasmid mix (Zufferey et al., 1998; Systemiosciences; Cellecta, Mountain View, CA). The virus-containingupernatant was filtered through 0.45 �m filters (Nalgene), andtored at −70 ◦C. Prior to infection of cells with library-carryingirus, the viral supernatant was thawed for 5 min at 37 ◦C andmmediately used to infect 5 × 108 SH-SY5Y cells. (The SH-SY5Yells had been plated 12 h prior to viral transduction and wereistributed in 16 six-well plates, with a seeding density of× 106 cells/well.) Three hundred microliters of supernatant andolybrene, at 5.0 �g/mL (Sigma, St. Louis, MO) final concentra-ion, were added to each well. The plates were spun in a swingingucket rotor centrifuge for 90 min at 1500 × g and 25 ◦C and then

ncubated at 32 ◦C, 5% CO2. Ninety-six hours after viral trans-uction, the SH-SY5Y cells were detached with trypsin, platedn laminin-coated plates (Becton Dickinson Labware) at a seed-ng density of 2500 cells/cm2 and then treated with 25 �M RASigma) for 36 h to induce neurite outgrowth. Then the SH-SY5Yells were collected with No-Zyme solution (Sigma) and immunos-ained with an anti-�1 integrin antibody directly conjugated toPC (Pharmingen) as described below, for subsequent analysis byow cytometry for GFP expression and �1 integrin immunostain-

ng.

.4. Flow cytometric (FACS) analysis and sorting

To detect �1 integrin in live cells, the cells were detached fromhe plates with No-Zyme solution (Sigma), washed twice with coldBS and then stained with an anti-�1 integrin antibody directlyonjugated to APC (Pharmigen). Briefly, 5.0 �L of APC-coupled anti-1 integrin antibody, which recognizes an extracellular epitope of1 integrin, was used to stain 1 × 106 cells. The SH-SY5Y cells were

ncubated with antibody in growth media, with 3% heat-inactivatedCS (HyClone), for 1 h on ice. Next the cells were washed three timesith PBS, resuspended in cold PBS, analyzed and sorted by FACS

BD Biosciences). Data were analyzed with FACScan, CellQuest andlowJo software.

.5. Rescue of integrated provirus and identification of targetenes: GSE library

From each sorted population, 1–5 × 106 cells were spunnd resuspended in PBS to purify genomic DNA, accord-ng to the manufacturer’s instructions (DNeasy Tissue Kit,iagen). Isolated genomic DNA was used as a template

or PCR reactions. To isolate the integrated provirus fromenomic DNA we used PCR with forward primers designedo EGFP: 5′-ACTCTCAAGGATCTTACCGCTGTTGAGATC-3′ and 5′-GATCCAGTTCGATGTAAC CCACTCGTGCA-3′ and a reverse primer5′-ACCCAGCTTTCTTGTACAAAGTGGT AGGTAGGTAGG-3′), which

ystem, Gibco, Invitrogen). After the PCR reaction, the PCR productsere analyzed with 1.5% and 3% agarose gels in TAE buffer. Relevant

CR fragments were cloned into the pCR2 vector (Invitrogen) andhen individual clones were isolated with the QIAGEN Plasmid Miniit (QIAGEN) and then sequenced to identify GSE library clones.

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.5.1. Rescue of integrated provirus and identification of thearget genes: siRNA library

Total mRNA and genomic DNA from sorted cells were isolatedith the Trizol reagent (Invitrogen) according to the manufacturer’s

nstructions. Reverse transcription was performed according theeneNet protocol (System Biosciences). The isolation of integratedrovirus carrying siRNA was performed by PCR using TitaniumTM

aq DNA polymerase (Clontech) as previously described (Systemiosciences, Cellecta, Mountain View). Next PCR products weree-amplified with biotinylated primers, purified with QIAGEN’sIAquick PCR Purification Kit (QIAGEN) and then analyzed with

he Affymetrix GeneChip® Human Genome Focus Array accord-ng to the manufacturer’s instructions and with recommendedffymetrix reagents at 45 ◦C, without DMSO for 16 h (Affymetrix,ystem Biosciences, Cellecta, Mountain View, CA). Data analysisas performed with GeneNet software (System Biosciences, Cel-

ecta, Mountain View, CA) and Pathway Studio (Ariadne Genomics,ockville, MD).

.6. siRNA transfection

SH-SY5Y cells were plated on 24-well laminin-coated platesBecton Dickinson) at a seeding density of 2500 cells/cm2 12 hefore transfection. The siRNA was synthesized commerciallyDharmacon, Thermo Fisher Scientific). The following siRNA wassed as a control: 5′-UAGCGACUAAACACAUCAAUU-3′. Transfec-ions with siRNA were performed as previously described (Reynoldst al., 2004). Forty-eight hours after transfection the cells werereated with either 0 or 25 �M RA. Neurite outgrowth was quan-ified at 36, 48 and 72 h after the RA treatment. To this end,he cells were fixed and stained with DAPI (Molecular probes)nd phalloidin-TRITC (Sigma) as previously described (Gallo andetourneau, 1998). Neurite length was measured as describedelow.

.7. Gene transcriptional profiling by quantitative real-timeT-PCR

Total mRNA was isolated from FACS-sorted cells with the RNeasyit as recommended by the manufacturer (Qiagen). Isolated mRNAas analyzed with the Agilent 2100 bioanalyzer and the RNA000 Nano LabChip Kit (Agilent Technologies, Palo Alto, CA). Next,0–40 ng of total mRNA was reverse transcribed into cDNA usingowerScript (BD Biosciences, Palo Alto, CA) with random hexamers.he resultant cDNA (30 �L) was amplified by PCR with a mixture ofene-specific primers (5.0 pM each) and Advantage 2 TaqDNA poly-erase (BD Biosciences) to produce amplicons <250 bp. For details

ee Dolganov et al. (2001).Next the amplified cDNA was used to quantify individual

ene expression via quantitative real-time RT-PCR, using TaqManrobes and primers, and with Universal Master Mix (Invitrogen)s described previously (Woodruff et al., 2007). All assays wereerformed with an ABI Prism 7900 Sequence Detection SystemsApplied Biosystems). The real-time RT-PCR Ct values were con-erted to relative gene copy numbers (Dolganov et al., 2001). Forontrols and to normalize results we monitored expression of theollowing genes: GAPDH, PPIA, EEF1A, RPL13A, UBIQUITIN B andBP.

Gene-specific primers for real-time RT-PCR were designed

or each gene of interest using either Primer3 (http://jura.wi.

it.edu/rozen/) or Primer Express software (PerkinElmer) based onequencing data from the NCBI database. Primers were purchasedrom Biosearch Technologies (Novato, CA). For primer sequences,ee http://adgenomics.stanford.edu. Normalized gene expression

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ence Methods 177 (2009) 322–333 325

ata were analyzed by t-test, so as to identify genes with statisti-ally significant changes in expression.

.8. cDNA cloning

Human spinal cord mRNA was obtained from Clontech (Clon-ech). The quality of the mRNA was analyzed by capillarylectrophoresis using the Agilent 2100 bioanalyzer and RNA 6000ano LabChip Kit (Agilent Technologies, Palo Alto, CA). cDNA syn-

hesis was performed with the SMART PCR cDNA Synthesis Kit anddvantage 2 PCR Kit (BD Biosciences) according to the manufac-

urer’s instructions. cDNA was used for MTGR1 cDNA amplificationy PCR with specific primers designed for the 5′ and 3′ ends ofGTR1 and the Advantage 2 PCR Kit (BD Biosciences). Isolated

DNA was re-amplified with primers containing Gateway attBdapters, according to the Gateway protocol (Gibco, Invitrogen) andloned into the pQCGFPL vector with the GATEWAY Cloning SystemGibco, Invitrogen) according to the manufacturer’s instructions.he accuracy of the GFP-MTGR1 fusion and absence of mutationsn the pQCGFPL-MTGR1 construct were confirmed by sequencingnd BLAST analysis (NCBI).

.9. Immunofluorescent analyses and image capture

EGFP expression in live cells was monitored and analyzed with aikon TE200 inverted microscope equipped with an Orca ER cooledharge-coupled device (CCD) camera (Hamamatsu, Middlesex, NJ).mages were collected and analyzed with the Simple PCI softwareCompix). To analyze neurite outgrowth, the SH-SY5Y cells werelated at a seeding density of 1000 cells/cm2 in growth media and

ncubated 12–18 h at 37 ◦C, 5% CO2. To label neurites, cells werexed with 4% paraformaldehyde in 100 mM PBS, pH 7.4 (15 min at◦C), and washed for 15 min with 1× PBS containing 0.1% saponinnd 1% FCS. The fixed cells were washed with 3× PBS, permeabilized0.1% Triton X-100-PBS, pH 7.4; 15 min) and stained with 50 �g/mLhalloidin-TRITC in PBS containing 1% FCS for 2 h at 4 ◦C. Nexthe cells were washed with 3× PBS followed by incubation with0 �g/mL 4′-6-diamidino-2-phenylindole, DAPI (Molecular Probes)or 10 min, washed in 3× PBS and analyzed with a Nikon TE200

icroscope (Nikon) or with the Cellomics ArrayScan VTI (Thermoisher Scientific).

.9.1. Manual image capture and analysisThe images of cells plated on six-well plates (Corning) were

aptured manually with an inverted Nikon TE200 microscope andn ORCA-ER CCD digital camera. From the digitized images weeasured neurite/process length with the Simple PCI software

Compix). Briefly, we first manually captured random rectangu-ar fields of cells. Next, the corners of the rectangular fields wereonnected with digital diagonal lines, so as to define an unbiasedetermination of the cells to be measured. We then measuredhe length of neurites/processes from 100 cells whose processesrossed the diagonals.

.9.2. Automated image capture and analysisFor automated analysis, we captured the images of cells plated

n 96-well plates with a Celllomics ArrayScan® VTI, which includeshigh-resolution Zeiss optical system, a multiple bandpass emis-

ion filter with matched single band excitation filters (XF57 orF100, Omega Optical), CCD camera and an ArrayScan VTI HCS

eader (Thermo Scientific Cellomics). The system provides simul-aneous image capture of several fluorophores in the same cell.he Cellomics algorithm identifies cells, evaluates the integrity ofnucleus and automatically excludes dead cells from the analysis.ual emission images were acquired from six discrete fields in each

326 V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333

Fig. 2. Retroviral transduction and delivery of pQCGFPL-GSE library into SH-SY5Y cells. (A and B) The magnitude of the delivery of GSE library into packaging cells wasestimated by fluorescence microscopic analysis of GFP expression (A) and by FACS (B). A total of 2 × 104 cells were analyzed by FACS. The oval (B) identifies the viable cells(90%—control cells and 90.4%—transfected cells). The histograms (B) illustrate GFP-negative and GFP-positive cells. The upper histogram represents control cells; lowerhistogram represents packaging cells transfected with GSE library (99.2%). (C and D) The magnitude of the delivery of GSE library into target SH-SY5Y cells by retroviraltransduction was estimated by fluorescence microscopic analysis of GFP expression (C) and by FACS (D). The oval gate (D) identifies the viable cells (71.7%—control cells and72%—transduced cells). The histograms (D) illustrate GFP-negative and GFP-positive SH-SY5Y cells. The upper histogram represents control cells; lower histogram representsSH-SY5Y cells transduced with the GSE library (50.3%). FSC-H: forward scatter; SSC-H: side scatter. (E) Image of SH-SY5Y cells transduced with vector control (withoutlibrary). (F–K) SH-SY5Y cells transduced with GSE library (scale bar equals 50 �m). (L) Red: SH-SY5Y cells transduced with control GFP vector. Blue: SH-SY5Y cells transducedwith GSE-GFP library. All cells were labeled with �1 integrin antibody directly conjugated to allophycocyanin (APC; see Section 2). Rectangle defines the sorted population

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ell of the plate. From these images, neurite measurements werealculated with an automated quantitative high content screen-ng algorithm for neurite outgrowth (Thermo Scientific Cellomics)ccording to the manufacturer’s instructions.

.9.3. BioinformaticsBioinformatic analysis was performed using the NCBI and EMBL

atabases. To gain insight into particular biological pathways wesed the PathwayStudio and PathwayExpert software packagesAriadne Genomics, Rockville, MD).

. Results

Fig. 1C illustrates the strategy that we followed in the first screen.e generated a library from SH-SY5Y cells, which is a sympathetic

ervous system-derived, clonal human neuroblastoma cell line. Wehose SH-SY5Y cells for several reasons. SH-SY5Y cells exhibit a dis-inct neuronal phenotype when grown on laminin and treated witheurotrophic factors or retinoic acid (Pahlman et al., 1981; Kaplan etl., 1993; Jalava et al., 1992, 1993; Jamsa et al., 2004). DifferentiatedH-SY5Y cells express a variety of neuronal markers, including GAP-3, synaptotagmin-l and synaptobrevin (Kim et al., 2000; Goodallt al., 1997). Most importantly, retinoic acid-stimulates the devel-pment of neurite-like processes (Clagett-Dame et al., 2006), andheir growth can be readily monitored using surface marker expres-ion. This greatly facilitates high throughput screening for geneshat regulate neurite outgrowth. Given these properties, SH-SY5Yells, although not equivalent to primary neurons, provide an excel-ent surrogate with which to perform and validate the utility of thisigh throughput screen.

.1. Library construction

Fig. 1A and B illustrate the design of the retroviral vector thate used for the library construction. We created and used a self-

nactivating retroviral vector because after retroviral integration ofhe vector into the target cell genome, transcription is driven onlyrom the CMV promoter. This property is achieved through dele-ion of the U3 region of the 3′LTR in the pQCGFPL vector, and isn important feature that significantly increases the fidelity of theystem (Fig. 1A and B).

The library covered the entire SH-SY5Y genome and includedombinatorial random fragments of cDNA (25–350 nucleotidesong) in both the sense and antisense orientations. We designed 5′

nd 3′ adapters for directional cloning and the 3′ adapter includedtop codons in all three frames. Members of the library function asither antisense mRNA molecules (if they were cloned in an anti-ense orientation) or lead to the production of functional interferingeptides (if the inserts were cloned in the sense orientation). An

mportant feature of the library is that each random library clones fused to GFP; this greatly facilitates subsequent recovery of func-ional inserts during the FACS protocol (see below). The geneticomplexity of the library was 1 × 107 independent recombinantlones.

.2. Retroviral transduction

We chose a retroviral strategy for the following reasons. First,etroviruses permit efficient and accurate delivery of genes andecombinant clones into target cells. Second, there is stable inte-

ecnme

f viable, GFP-positive cells that over-express �1 integrin, after transduction with the GSositive cells that were isolated by FACS (the fluorescence intensity is a logarithmic readolor in this figure legend, the reader is referred to the web version of the article.)

ence Methods 177 (2009) 322–333 327

ration of the provirus into target genome, resulting in long-termxpression of the encoded genetic information, including the GFP.hird, under optimal conditions, only one virion can be incorpo-ated per cell (Kustikova et al., 2003; Miller, 2002). This greatlyacilitates high throughput recovery and subsequent identificationf functional library clones, namely those that alter process out-rowth in SH-SY5Y cells.

We found that >99% of the packaging cells were transfectedith the library. This was established by visualization of GFP flu-

rescence (Fig. 2A) and by FACS analysis (Fig. 2B). We obtainedbout 55% efficiency in the delivery of the library into SH-SY5Yells (Fig. 2C and D) and we also observed a significant functionalmpact of the library. Thus, in cells infected with the control vector,QCGFPL (Fig. 2E), the GFP was uniformly distributed. By con-rast, after transduction of the SH-SY5Y cells with the library, webserved significant phenotypic variability of the GFP expressionFig. 2F–K). In some cases, the GFP was exclusively cytoplasmic andn the processes of the cells; in other examples the GFP had clearlyranslocated to the nucleus (Fig. 2H). We also observed structuralhanges, including cells with elongated processes (Jamsa et al.,004).

.3. High throughput functional screening for increasedrocess/neurite outgrowth

The next step was to identify a marker that we could useo screen for genes that influence process length. Ideal markersor screening should either be upregulated in the population ofells with growing processes or should exclusively be expressedn developing growth cones of cells that are differentiating. In areliminary analysis we monitored the expression of a variety ofarkers of differentiated SH-SY5Y cells using real-time PCR. Based

n this analysis we turned our attention to the integrins, whichre the family of receptors through which extracellular matrixolecules, including laminin, interact. Of particular importance to

he present approach is that there is increased �1 integrin expres-ion on the growing neurites of embryonic retinal ganglion cellsNeugebauer and Reichardt, 1991; Stone and Sakaguchi, 1996; Ivinst al., 1998; Treubert and Brummendorf, 1998). �1 integrin is alsoocalized on the axons and growth cones of regenerating facialerve and the magnitude of �1 integrin immunoreactivity corre-

ates with axonal growth of dorsal root ganglia neurites (Arevalond Chao, 2005).

As illustrated in Fig. 3A–E, retinoic acid dose-dependentlynduced a neuronal phenotype in SH-SY5Y cells and, consistent

ith a previous report (Jenab and Inturrisi, 2002; Li et al., 2000),e found that RA significantly upregulated �1 integrin mRNA in

ells grown on laminin (Fig. 3F). Furthermore, using FACS analysiso follow these changes in a high throughput fashion we found thathe level of �1 integrin protein in RA-treated SH-SY5Y cells waslso significantly increased (Fig. 3G). For these studies we used anntibody that recognizes an extracellular epitope of �1 integrin inive non-permeabilized cells.

These results demonstrate that RA induction of processes inH-SY5Y cells occurs concomitantly with increased �1 integrin

xpression on the surface of the cells and on their processes. Finally,onsistent with the conclusion that this increase indeed representseurite outgrowth, we also found an increase of the cytoplasmicarker, GAP-43, a protein associated with neurite growth (Bomze

t al., 2001; Anderson et al., 1998; Skene, 1989; Fig. 3G).

E library. This population corresponds to 1.42% of the GFP and �1 integrin—APC-out of the magnitude of antibody binding). (For interpretation of the references to

328 V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333

Fig. 3. Retinoic acid (RA) induces neurite outgrowth in SH-SY5Y cells. (A–E) SH-SY5Y cells differentiated and extended neurites after treatment with RA. SH-SY5Y cells wereplated onto laminin and 24 h after plating, the cells were treated with 0, 12.5, 25 or 50 �M RA for 72 h (scale bar equals 50 �m). Images were captured with an ORCA-ER CCDdigital camera and neurite length (see Section 2). (E) Average length of neurites of SH-SY5Y cells plated on laminin without RA or treated with 50 �M RA. (F) Quantitativereal-time RT-PCR-based transcriptional profiling of SH-SY5Y cells after treatment with RA (see Section 2). Results are means ± S.E.M. of pooled data from three separatee Tablet ere li n and

wrTt�tgo(

intwwi

tw

ispc

3

ctihsestablished the utility of this approach, we analyzed 30 clones

xperiments (for abbreviations and the panel of genes analyzed see Supplementaryreated with 0 or 25 �M RA for 72 h and stained with �1 integrin antibody. Cells wsotype control antibody directly conjugated to APC. Data were collected by FACSca

To confirm that the magnitude of �1 integrin indeed correlatesith the extent of neurite outgrowth we next monitored neu-

ite outgrowth after downregulation of �1 integrin with siRNA.wenty-four hours after transfection of the �1 integrin siRNA, wereated the cells with RA. �1 integrin siRNA significantly reduced1 integrin mRNA by about 50% (Fig. 4A), and most importantly,

his reduction correlated with a dramatic inhibition of neurite out-rowth (Fig. 4B) compared to the growth observed in the absencef �1 integrin siRNA or in cells treated with control luciferase siRNAFig. 4B).

Having established that increases in surface �1 integrinmmunoreactivity correlate with the RA-induced neuronal phe-otype, we next developed a FACS protocol to rapidly sort cellsransduced with the library. Three sorting gates were used: (1) GFP,hich marks cells that were transduced with the library; (2) APC,

hich marks cells immunostained with an APC-coupled anti-�1

ntegrin antibody; (3) cell size, so as to exclude dead cells.The control groups consisted of cells immunostained with iso-

ype control antibody conjugated to APC or of cells transducedith empty vector-GFP and immunostained with APC-coupled �1

ashag

1). (G) FACS analysis of the immunostaining of live SH-SY5Y cells plated on laminin,abeled with �1 integrin antibody directly conjugated to allophycocyanin (APC) oranalyzed with CellQuest and FlowJo softwares.

ntegrin antibodies. From 108 library-transduced SH-SY5Y cells weorted the top 1.42% of �1 integrin expressors that were also GFP-ositive, were viable and did not overlap with the population ofells infected with the control, empty-GFP vector (Fig. 2L).

.4. Rescue of functional clones

Next we used specific primers to isolate the provirus from sortedells. The primers were designed to the backbone of the vector oro GFP (Fig. 1B). All PCR products were individually sequenced todentify candidate genes. We found that 80% of the isolated clonesad inserts in the antisense orientation; 20% of isolated clones wereense-oriented and in frame with GFP. In our first analysis, which

nd recovered a variety of genes, including transcription factors,caffold proteins, channels and several genes for which a functionas yet to be identified. Below we describe some of these genesnd demonstrate their functional relevance to process/neurite out-rowth.

V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333 329

F ted wt RNA. Di ee indc A for 6

3o

gFctoChe

agoewmS

Mtbge1(Rs(

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ig. 4. Transfection of SH-SY5Y cells with �1 integrin siRNA. SH-SY5Y cells transfecranscriptional profiling of SH-SY5Y cells 48 h after transfection with �1 integrin sin cells transfected with control siRNA and were determined from the average of thrells transfected with �1 integrin siRNA or control siRNA and treated with 25 �M R

.5. siRNA inhibition of MTGR1 expression induces neuriteutgrowth

Our attention was directed at a clone that encodes the MTGR1ene, which we chose to further characterize, for three reasons.irst, we isolated three independent, although not identical, clonesorresponding to the MTGR1 gene. Second, MTGR1 is a transcrip-ional co-repressor that has been implicated in the regulationf differentiation of hematopoetic cells (Kitabayashi et al., 1998;alabi and Cilli, 1998; Rossetti et al., 2004). Third, MTGR1 is a humanomologue of XETOR, which inhibits neurogenesis in Xenopus (Caot al., 2002).

Because the MTGR1 clones were isolated from the library in thentisense orientation we concluded that the increase of �1 inte-rin expression resulted from inhibition of MTGR1. To confirm this

bservation and to test the hypothesis that increased �1 integrinxpression is associated with increased process/neurite outgrowth,e developed a secondary screen using siRNA to reduce MTGR1RNA expression in an in vitro analysis of neurite outgrowth in

H-SY5Y cells.

cnaat

ig. 5. Effect of MTGR1 siRNA on SH-SY5Y cells. Quantitative real-time PCR-based transcriE) 48 h after transfection with MTGR1, Sox4 or luciferase siRNA in SH-SY5Y cells. Valuesrom SH-SY5Y cells plated onto laminin and treated with 0 or 25 �M RA for 72 h.

ith �1 integrin siRNA or a control siRNA. (A) Quantitative real-time RT-PCR-basedata, expressed as relative gene copy number, were normalized to the mRNA level

ependent experiments (see Supplementary Table 1). (B) Digital images of SH-SY5Y0 h (scale bar equals 50 �m).

Fig. 5A demonstrates that transfection of SH-SY5Y cells withTGR1 siRNAs reduced MTGR1 mRNA by greater than 80%. Consis-

ent with the FACS analysis we also found that inhibition of MTGR1y siRNA concurrently induced a pronounced increase of �1 inte-rin and GAP-43 mRNA (Fig. 5E). Finally, we found an increase ofpidermal growth factor (EGF) and fibroblast growth factor-1 (FGF-) mRNA, both of which induce neurite outgrowth in SH-SY5Y cellsKornblum et al., 1990; Morrison et al., 1988), even in the absence ofA (Fig. 5C and D). Importantly, we found no changes in the expres-ion of a panel of other genes that were analyzed in SH-SY5Y cellsSupplementary Table 1 and Section 2).

We also performed several additional controls. First, we tar-eted SH-SY5Y cells with an siRNA designed to another clone thatas isolated during the primary screen, Sox4. Despite significant

nockdown of Sox4 mRNA with Sox4 siRNA (Fig. 5A), we found no

hange in the level of �1 integrin, GAP-43, EGF or FGF-1 mRNA (dataot shown). Finally, we used an siRNA directed against luciferasend also found no changes in mRNA levels of these genes (Fig. 5Cnd D). Most importantly, morphological analysis of SH-SY5Y cellsreated with MTGR1 siRNA demonstrated an increase in process

ptional profiling of MTGR1 and Sox4 (A), FGF-1 (C), EFG (D), �1 integrin and GAP-43are normalized to mock transfected cells. (B) Quantification of neurite outgrowth

330 V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333

Fig. 6. Overexpression of full length MTGR1 cDNA in SH-SY5Y cells. (A, top) SH-Swfo

lwIbts

3

paiMpF

uFnrssspehi

Fig. 7. Overexpression of MTGR1 cDNA inhibits neurite outgrowth in SH-SY5Y cells.SH-SY5Y cells transduced with GFP-vector control (A–D) or with GFP-MTGR1 (E–H)aap

3

eetaWmFat

3l

aF

Y5Y cells transduced with control pQCGFPL vector. (B) SH-SY5Y cells transducedith retroviral vector pQCGFPL-MTGR1 containing MTGR1 full length cDNA isolated

rom human spinal cord and fused to GFP. In (B, bottom), there is nuclear localizationf the MTGR1.

ength (Fig. 5B). This was the case both for SH-SY5Y cells incubatedithout RA (43% increase) or in the presence of RA (40% increase).

n fact, the length of processes in the presence of MTGR1 siRNA,ut without RA, was comparable to the length of processes in con-rol, RA-treated cells. We found no effect of control siRNAs or Sox4iRNA on process length (Fig. 5B).

.6. Overexpression of MTGR1 inhibits neurite outgrowth

We next studied the effect of full length MTGR1 cDNA overex-ression in SH-SY5Y cells. We isolated full length MTGR1cDNA fromdult human spinal cord by RT-PCR and cloned it as a GFP-fusionnto the retroviral vector pQCGFPL (Fig. 1A) to generate pQCGFP-

TGR1. We then infected a naïve population of SH-SY5Y cells withQCGFP-MTGR1 and 72 h later isolated the GFP-positive cells byACS.

In cells transduced with a control, empty GFP vector, there isniform distribution of the GFP fluorescence (Fig. 6A). By contrast,ig. 6B illustrates that the GFP-MTGR1 protein is only found in theucleus of infected SH-SY5Y cells, which is consistent with theeports that MTGR1 is member of the ETO family of nuclear repres-or proteins (Davis et al., 2003; Lindberg et al., 2003). When wetudied the consequence of overexpression of GFP-MTGR1 in RA-

timulated SH-SY5Y cells, we observed a significant inhibition ofrocess outgrowth (Fig. 7E–H) compared to cells transduced withmpty GFP vector (Fig. 7A–D). These results provide evidence thatuman MTGR1 is indeed a repressor of process/neurite outgrowth

n the SH-SY5Y cells.

42ppe

nd treated with or without RA for 72 h. (A and E) Phalloidin-TRITC staining; (Bnd F) GFP; (C and G) overlay of phalloidin-TRITC and GFP; (D and H) overlay ofhalloidin-TRITC and DAPI (scale bar equals 50 �m).

.7. Expression profile of MTGR1

Although Morohoshi et al. (2000) demonstrated that MTGR1 isxpressed at high levels in human bone marrow cells, hemopoi-tic tissues and lymphoid organs, its presence in human neuronalissue was not reported. For this reason, in the present study wenalyzed expression of MTGR1 in human primary neuronal tissues.e found high levels of MTGR1 mRNA in cerebellum, spinal cord,otor cortex, hippocampus and substantia nigra (Supplementary

ig. 1). These results suggest that our observations in SH-SY5Y cellsre of general relevance to neurite outgrowth in diverse regions ofhe central nervous system.

.8. Parallel and independent screening using a lentiviral siRNAibrary

In a parallel and independent functional genetic screen we usedGFP-labeled large-scale siRNA library that is expressed from an

IV-based lentiviral vector pSIF1-H1 (Fig. 8A). The library contains0,000 individual siRNA that target 8500 human genes (Section

). We delivered this library to naive SH-SY5Y cells and, as in therevious screen, we found that the library-induced diverse mor-hological changes of the SH-SY5Y cells (Fig. 8C) compared to cellsxpressing vector control (Fig. 8B).

V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333 331

Fig. 8. Lentiviral-based siRNA screening. (A) pSIF-H1 lentiviral vector used for siRNA library expression and delivery. LTR: long terminal repeat; gag: structural protein; RRE:r een fle he 3′Uc -siRN

lFahlrTbvtGN

rsc(ucoi

tswtpGct

tc

4

sssMtdnfg

iuIicrfep

ev responsive element; cPPT: central polypurine tract; CMV: CMV promoter; GFP: grlement. The siRNA library under the control of the H1 promoter was inserted into tontrol vector. (C) Neurite outgrowth induced in SH-SY5Y cell transduced with pSIF

We performed two independent screens of the lentiviral siRNAibrary. To identify functional siRNA, we used a modification of theACS approach described above and isolated an experimental andcontrol population of cells. The experimental population showedigh upregulation of extracellular �1 integrin. The control popu-

ation showed levels of �1 integrin expression comparable to thatecorded in either vector-GFP transduced cells or in untreated cells.o identify functional clones we isolated integrated provirus fromoth populations of sorted cells, using primers designed to theector (Section 2). Instead of sequencing individual clones fromhe sorted cells, we used a high throughput approach (AffymetrixeneChip® Human Genome Focus Array, Section 2) to identify siR-As that induced the increased �1 integrin expression.

From the analysis of two independent screens of the lentivi-al siRNA library we identified 39 genes that appeared in bothcreens. Among these genes were many that encode proteogly-ans, kinases, receptors, adaptor proteins and transcription factorsSupplementary Table 2). In several instances, the same gene wasncovered by several independent siRNAs, among which are thoseorresponding to protein tyrosine kinase HEK2, Rab GDI, neuro-ncological ventral antigen 1 (NOVA1) and neurite outgrowthnhibitor (NOGO).

Of particular interest and relevance to the results obtained inhe GSE screen, is that from the lentiviral screen we isolated aniRNA that targets GFI1 and GF1B. A bioinformatic analysis (Path-ay Studio, Ariadne Genomics) revealed that GFI1 is a zinc finger

ranscriptional repressor and a member of the MTG8(ETO)/MTGR1rotein complex (Hock and Orkin, 2006; McGhee et al., 2003).FI1B is 97% identical in the zinc finger domain and 95% identi-al in the SNAG domain to GFI1 (Garcon et al., 2005). Thus, usingwo independent genome-wide functional genetic screens of genes

eeita

uorescent protein; WPRE: woodchuck hepatitis virus posttranscriptional regulatoryTR of the pSIF lentiviral vector. (B) SH-SY5Y cells transduced with empty pSIF-GFP

A library (scale bar equals 50 �m).

hat regulate neurite outgrowth we uncovered the same proteinomplex.

. Discussion

In this paper we describe a powerful, high throughput genetictrategy that uses a functional genetic screen of two large-cale libraries in human neuronal cells. The success of thiscreening approach is illustrated by our discovery that theTG8(ETO)/MTGR1 protein complex is a significant contributor to

he molecular mechanisms that underlie and regulate �1 integrin-ependent neurite elongation/outgrowth in SH-SY5Y cells. Theseovel primary and secondary screens establish a powerful system

or comprehensive identification of genes that regulate neurite out-rowth.

A great advantage of the GSE library is that it is genome wide ands syngenic for the targeted SH-SY5T cells. To complement this wesed a large-scale siRNA library that targeted 8500 human genes.

n both screens we delivered libraries by retroviral transductionnto SH-SY5Y cells. We used retroviral vectors, as under optimizedonditions the cells only take up a single virion during retrovi-al transduction (Kustikova et al., 2003). This made it possible toollow the long-term phenotypic changes produced by individuallements of the library, in individual cells, which also greatly sim-lified subsequent identification of functional clones.

We were searching for a relatively rare event. Thus, it was

ssential to have a high throughput method of analysis. To thisnd, we used multiparameter fluorescence-activated cell sort-ng to identify phenotypic changes induced by the libraries ando select cells that significantly manifest these changes. Therere several features of our approach that greatly facilitated FACS

3 urosci

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4

wgwaGMTpOhfieMsMhrJ

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32 V.S. Ossovskaya et al. / Journal of Ne

nalysis. Most importantly, we identified an antigen that could besed to monitor library-induced phenotypic changes, namely �1

ntegrin. It is theoretically possible to monitor intracellular mark-rs, but this generally requires fixation and permeabilization ofells, which complicates the subsequent identification of functionallones. Moreover, we found that monitoring intracellular markersf neurite outgrowth in fixed cells significantly reduced the effi-iency of the functional screen as it was more difficult to recoverhe functional provirus or clones of interest from the library.

Because the library carried GFP, the sorting could be restricted toells that incorporated the library. Taken together, we were able tocreen rapidly millions of cells and to identify functional clones. Thepproach can be readily adapted to other cell types and phenotypichanges.

To confirm the functional relevance of candidate clones iso-ated in the primary GSE screen, we used a secondary, cell-basedssay of neurite outgrowth. This functional screen involved siRNAuppression of the expression of candidate genes isolated in therimary screen. Importantly, we not only monitored the same end-oint as in the primary screen (namely �1 integrin expression)ut we also documented that upregulation of �1 integrin cor-elated with neurite outgrowth. In a further confirmation of theunctional significance of the candidate genes, we overexpressedull-length cDNA corresponding to the candidate gene, and as pre-icted, observed inhibition of neurite outgrowth.

.1. Leniviral siRNA screen and high throughput analysis

To confirm the results from the GSE screen we performed twodditional independent functional screens of a large-scale lentivi-al library of 40,000 siRNAs that target 8500 characterized humanenes. From FACS analysis of cells sorted for �1 integrin upregu-ation, we identified positive clones using a microarray approach.mong isolated genes we found chondroitin-sulfate proteoglycan

Versican), which has been previously described as an inhibitor ofNS axon growth in vitro and in vivo (Schweigreiter et al., 2004).f particular interest, however, was our isolation of GFI1 and GFIB,embers of the MTGR1 protein complex (see below). This discov-

ry provided a very strong validation, not only of the utility of therimary screen to identify genes that influence neurite outgrowth,ut also of the importance and value of the secondary, independentcreen. The two screening approaches clearly complemented eachther.

.2. MTGR1, GFI1 and neurite outgrowth

From these two independent genome-wide functional screense isolated myeloid-transforming gene-related protein 1 and

rowth factor independence 1 and 1B. MTGR1 heterodimerizesith the myeloid translocation gene on chromosome 8, MTG8,

lso known as eight-twenty-one or ETO (Kitabayashi et al., 1998).fi1 is a DNA binding transcriptional repressor that associates withTG8/ETO and MTGR1 (McGhee et al., 2003; Amann et al., 2005).

hus, MTGR-1 and GFI1 belong to the same MTG8/ETO protein com-lex and represent a family of nuclear repressor proteins (Hock andrkin, 2006; McGhee et al., 2003; Amann et al., 2005). Studies ofomologs of MTGR1 have provided evidence consistent with ournding that inhibition of MTGR-1 promotes neurite outgrowth. Forxample, and as noted above, Xenopus XETOR, a homolog of humanTGR-1, is a transcriptional repressor that suppresses neurogene-

is during embryogenesis (Cao et al., 2002; Logan et al., 2005). TheTG8/ETO protein complex also blocks activity of G-CSF, which in

uman neural stem cells stimulates neurogenesis through recip-ocal interaction with VEGF and STAT activation (Ahn et al., 1998;ung et al., 2006). Taken together with our finding that inhibition of

I

J

ence Methods 177 (2009) 322–333

TGR1 also induces transcription of EGF and FGF-1, both of whichontribute to the regulation of neurite outgrowth and axon guid-nce (Kornblum et al., 1990; Morrison et al., 1988; Arevalo andhao, 2005), these results indicate that the MTGR1/ETO/GFI1 pro-ein complex function as nuclear repressors of pathways that canegulate neurite outgrowth.

cknowledgments

We thank Alex Chenchik and Michail Makhanov (System Bio-ciences) for help with the lentiviral siRNA libraries, Valerie Vincentor help with the Cellomics analysis and Ariadne Genomics forelp with bioinformatics. This work was supported by NIH grantsS14627 and 48499 and an Opportunity Award from the Sandlerrogram in Basic Sciences at UCSF.

ppendix A. Supplementary data

Supplementary data associated with this article can be found,n the online version, at doi:10.1016/j.jneumeth.2008.10.031.

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