Loss of function genetic screens reveal MTGR1 as - Journal of ...
Journal of Neuroscience Methods 177 (2009) 322–333
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Journal of Neuroscience Methods
journal homepage: www.elsevier.com/locate/jneumeth
Loss of function genetic screens reveal MTGR1 as an intracellular
repressor of ␤1 integrin-dependent neurite outgrowth
Valeria S. Ossovskayaa,b,d,∗
, Gregory Dolganovc,e
, Allan I. Basbauma,b
Department of Anatomy, University of California San Francisco, San Francisco, CA 94158, USA
Department of Physiology, University of California San Francisco, San Francisco, CA 94158, USA
Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA
BiPar Sciences Inc., Brisbane, CA 94005, USA
Department of Infectious Diseases, School of Medicine, Stanford University, Stanford, CA 94305, USA
a r t i c l e i n f o
Received 15 March 2008
Received in revised form
13 September 2008
Accepted 15 October 2008
a b s t r a c t
Integrins are transmembrane receptors that promote neurite growth and guidance. To identify regulators
of integrin-dependent neurite outgrowth, here we used two loss of function genetic screens in SH-SY5Y
neuroblastoma 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 transcriptional
factor MTGR1 (myeloid translocation gene-related protein-1). Treatment of SH-SY5Y cells with MTGR1
siRNA enhanced neurite outgrowth and concurrently increased expression of GAP-43, a protein linked
to neurite outgrowth. Second, we transduced SH-SY5Y with a genome-wide GFP-labeled lentiviral siRNA
library, which expressed 40,000 independent siRNAs targeting 8500 human genes. From this screen we
isolated 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 novel
contributions of MTGR1 and GFI1 to the regulation of neurite outgrowth and identify novel repressors of
integrin-dependent neurite outgrowth.
Published by Elsevier B.V.
Despite signiﬁcant advances in our understanding of the
molecules that contribute to axonal growth, progress in overcom-
ing the failure of central nervous system axons to regenerate after
injury has been disappointing. Among the many factors that con-
tribute to the poor regeneration of injured CNS axons are: reduced
intrinsic growth capacity of the injured neurons, inability to over-
come inhibitory molecules in the region of the injury, and failure
to respond to growth promoting molecules in the region of the
injury. As axonal growth is not hindered during development, it is
reasonable to hypothesize that these properties are present in the
developing neuron, but are lost or suppressed in the adult (Spencer
and Filbin, 2004; He and Koprivica, 2004; Neumann et al., 2002).
Importantly, manipulations of the molecular machinery of the
damaged neuron in the adult can enhance growth, indicating that
these properties can be reinstated (Neumann and Woolf, 1999;
Neumann et al., 2002; Filbin, 2003). Indeed, in recent years several
∗ Corresponding author at: BiPar Sciences, 1000 Marina Blvd., Suite 550, Brisbane,
CA 94005, USA. Tel.: +1 650 635 6045; fax: +1 650 635 6057.
E-mail address: email@example.com (V.S. Ossovskaya).
small molecules and proteins that either promote or inhibit the
growth of neurites and axons have been identiﬁed. Among these
are guidance and signaling molecules (e.g. cAMP), secreted growth
promoting and inhibitory molecules, including neurotrophins,
netrins, slits, ephrins, semaphorins and myelin-associated proteins
(Tessier-Lavigne and Goodman, 2000, 1996; Schnorrer and Dickson,
2004; Nakamura et al., 1998; Arevalo and Chao, 2005; Neumann
and Woolf, 1999; Neumann et al., 2002).
With a view to providing a more extensive catalogue of the
molecular contribution to various complex processes, attention
has turned to genetic screens (Nijman et al., 2005; Paddison et
al., 2004). For example, several comprehensive screening meth-
ods to study regulators of neuronal function have been described
in drosophila, C. elegans and zebraﬁsh (Hivert et al., 2002; Hua et
al., 2005; Runko and Kaprielian, 2004; Shao et al., 2005). Here we
describe the results of two functional genetic screens for repressors
of neurite outgrowth. We generated and screened a genome-wide
retroviral GFP-genetic suppressor element (GSE) library and a large-
scale lentiviral siRNA library targeting 8500 genes. The screen
integrated a highly sensitive and comprehensive functional and
array-based analysis. Most of the targets that we identiﬁed fell
into ﬁve major categories: receptors, proteoglycans, kinases adap-
tor proteins and transcription factors. In this paper we report on
0165-0270/$ – see front matter. Published by Elsevier B.V.
V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333 323
the contribution of MTGR1 (myeloid translocation gene-related
protein-1) and GFI1 (growth factor independence-1), both of which
belong to the same ETO/MTG8 (myeloid translocation gene on
8q22) protein complex (Hock and Orkin, 2006; McGhee et al., 2003;
Amann et al., 2005). This complex is a transcriptional repressor
that regulates proliferation and differentiation of hematopoietic
and stem cells. We demonstrated that the MTGR1 and GFI1 neg-
atively regulate ␤1-integrin-dependent elongation of neurites in
human SH-SY5Y neuroblastoma cells.
2. Materials and methods
2.1. Cell culture
SH-SY5Y cells were obtained from the ATCC and maintained
in DMEM/F12 media (50:50; Gibco) supplemented with 1% non-
essential amino acids (Gibco), 15% heat-inactivated fetal calf serum,
FCS (HyClone), 100 g/mL penicillin and 100 g/mL streptomycin
at 37 ◦C, 5% CO2. To induce differentiation, cells were plated on
laminin-coated plates (Becton Dickinson Labware) and treated with
0–50 M trans-retinoic acid (RA) (Sigma) for 36–72 h. Phoenix cells
were obtained from the ATCC with permission of G. Nolan (Stan-
ford University). AmphoPackTM-293 packaging cells were obtained
from Clontech. Phoenix and AmphoPackTM-293 were maintained
in DMEM media (Gibco) supplemented with 10% heat-inactivated
fetal calf serum (HyClone), 100 g/mL penicillin and 100 g/mL
streptomycin at 37 ◦C, 5% CO2.
2.2. GSE library construction
A self-inactivating retroviral vector, pQCGFPL was constructed
using the pQCXIX vector (Clontech) in which the CMV-IRES cassette
was replaced with a CMV-EGFP-linker-adaptor cassette. The CMV-
EGFP cassette was derived from the pLEGFP-N1 retroviral vector
(Clontech). This adapter was used to insert the GSE library (Fig. 1A
SH-SY5Y cells were treated with 25 M trans-retinoic acid
(Sigma) for 0, 12, 24, 48 or 72 h. After incubation with RA, the
SH-SY5Y cells were collected and used to construct the library, as
previously described (Gudkov et al., 1994; Ossovskaya et al., 1996),
with modiﬁcations provided below. Brieﬂy, total mRNA was iso-
lated from 107 SH-SY5Y cells using the RNAqueous Kit (Ambion,
Austin, TX) in six independent reactions, according to the manufac-
turer’s instructions. mRNA quality was determined by microﬂuidic
analysis (Agilent® 2100 bioanalyzer with Caliper’s RNA LabChip®
Kit; Agilent). mRNA with a 28S–18S rRNA ratio of >1.2 was used for
poly(A)+ RNA puriﬁcation. Poly(A)+ RNA was puriﬁed from 2.0 mg
of total mRNA with two rounds of oligo(dT) selection using the
Poly(A)Purist Kit (Ambion, Austin, TX) according to the manu-
facturer’s instructions. The isolated poly(A)+ RNA with A260–A280
values in the range of 1.85–2.1 was used for cDNA synthesis. The
purity and integrity of the poly(A)+ RNA were veriﬁed by formalde-
hyde 2.5% agarose gel electrophoresis and capillary electrophoresis
using the Agilent® 2100 bioanalyzer.
PolyA + RNA was used for cDNA synthesis with the SMART
cDNA library protocol (Clontech) in six independent reactions,
according to the manufacturer’s instructions, with some modiﬁ-
cations. Brieﬂy, for each reaction 1.0 g of PolyA + RNA was mixed
with 1.0 L 10 M oligo(dT) (CDS primer), 1.0 L 10 M SMART II
Oligonucleotide, and deionized water for a total volume of 5.0 L.
The mixture was heated at 72 ◦C for 2 min, cooled on ice for
2 min and spun for 30 s. The reaction was followed by the addi-
tion of 2.0 L 5 reaction buffer (250 mM Tris–HCl, pH 8.3, 30 mM
MgCl2, and 375 mM KCl), 1.0 L 20 mM DTT, 1.0 L 10 mM dNTP
Fig. 1. Schematic illustration of the functional screen. (A) pQCGFPL retroviral vector
used as the transfer vector for library delivery into SH-SY5Y cells. LTR: long terminal
repeat; 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 in
the 3 LTR. (B) The vector pQCGFPL-GSE carries the GSE library and GFP for selection
of infected cells. PCR primers used for rescue of integrated provirus are illustrated
by arrows. (C) Schematic illustration of retroviral transduction of SH-SY5Y cells with
pQCGFPL-GSE library and the functional genetic screening strategy for inhibitors of
(10 mM each dATP, dCTP, dGTP, and dTTP; Amersham Pharmacia,
Piscataway, NJ, USA), 0.5 L of 100 U/L Power Script Reverse Tran-
criptase (Clontech) and 28 U/L Anti-RNase (Ambion, Austin, TX,
USA). The samples were incubated at 42 ◦C for 1 h followed by inac-
tivation of reverse transcriptase at 72 ◦C for 7 min. Next 40 L TE
buffer (10 mM Tris–HCl, pH 7.4, 1 mM EDTA) were added to each
sample, which were subsequently stored at −20 ◦C. To determine
the number of PCR cycles necessary for optimal ampliﬁcation of
cDNA, 1.0 L from each ﬁrst-strand cDNA reaction mixture was
combined with 10 L 10× advantage polymerase buffer (40 mM
Tricine–KOH, pH 9.2, 15 mM KOAc, 3.5 mM Mg(OAc)2), 1.0 L PCR
primer (5 -AAGCAGTGGTAACAACGCAGAGT-3 ), 2.0 L 10 mM dNTP
mix (10 mM dATP, 10 mM dCTP, 10 mM dGTP, and 10 mM dTTP), and
1.0 L Advantage cDNA Polymerase Mix (Clontech). Samples were
ampliﬁed using the following program: 1 cycle at 95 ◦C for 1 min,
then 15 cycles at 95 ◦C for 15 s, 65 ◦C for 30 s and 68 ◦C for 6 min.
After 15 cycles, 15 L of the reaction mixture were transferred
to a new 0.5-mL tube and subjected to three additional cycles;
the remaining 85 L of the PCR mixture were kept on ice. After
three additional cycles, 5.0 L of reaction mixture was aliquoted
for analysis by agarose gel, while the remaining 10 L of the reac-
tion mixture were subjected to another three cycles, for a total of 21
cycles. To determine the optimal number of cycles, 5.0 L of each
of the reaction mixture (i.e., 15-, 18-, and 21-cycle PCR products)
324 V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333
were analyzed on a 1.5% agarose gel in Tris–acetate EDTA (TAE)
buffer. Based on the results of the agarose gel analysis, samples
were subjected to additional cycles. Products of cDNA reactions
were puriﬁed using the NucleoTrap PCR Puriﬁcation Kit (Clontech)
and eluted in 50 L TE buffer. One microgram of PolyA + RNA yields
up to 10 g of puriﬁed cDNA. The synthesized cDNA was ana-
lyzed with 0.8%, 1.5% and 3% agarose gels in Tris–acetate EDTA
The size of synthesized cDNA ranged from 0.5 to 6 kb with
enrichment at 0.9–3 kb, which is typical for human brain RNA. Ten
micrograms of synthesized cDNA was digested with RsaI endonu-
clase, which recognizes the sequence 5 -GTAC-3 , creating cDNA
fragments with an average size of 100–250 bp. Ten micrograms of
synthesized cDNA in the second independent reaction was son-
icated and fractionated by Quick Spin Columns (Sephadex G-25,
Sephadex G-50; Roche). The 25–250 bp cDNA fragments from both
reactions were puriﬁed by electrophoresis and gel ﬁltration using
Sephadex G-25, G-50 and G-100 (Sigma). cDNA fragments with
an average size of 25–350 bp were ligated to attB1 and attB2
Gateway adapters, according to the Gateway protocol (Gibco, Invit-
rogen) and cloned into the pQCGFPL vector with the GATEWAY
Cloning System (Gibco, Invitrogen), according to the manufac-
turer’s instructions. The GSE library was ampliﬁed in TOP10 E. coli
cells on 50 independent 150-mm LB agar plates containing 0.1% glu-
cose. The complexity of the GSE library was 9.6 × 107 independent E.
coli clones. The library was puriﬁed with the QIAGEN Plasmid Maxi
Kit (QIAGEN) according to the manufacturer’s instructions and used
to transfect packaging cells (see Section 2.1).
2.2.1. Transduction of SH-SY5Y cells with the GSE library
The viral supernatant carrying the library was produced as
described previously (Martens et al., 2000; Ossovskaya et al.,
1996) with some modiﬁcations. Brieﬂy, AmphoPack packaging cells
(Clontech) were plated at 5 × 107 cells per 150 mm plate (Corning)
12 h prior to the transfection. After a 12 h incubation, the media was
changed and packaging cells were transfected with 30 g retro-
viral plasmid DNA per plate using the FuGENE 6 reagent (Roche
Applied Science), according to the manufacturer’s instructions. A
total of 5 × 108 AmphoPack packaging cells were transfected with
the GSE library. At 12 h after transfection, the media was replaced
with growth medium and cell cultures maintained at 37 ◦C in 5%
CO2 for 12–24 h, then at 32 ◦C in 6% CO2 for 24–36 h.
Sixty hours after transfection, the virus-containing supernatant
was collected from transfected packaging cells, ﬁltered through
0.45 m ﬁlters (Nalgene), supplied with 5 g/mL Polybrene (Sigma,
St. Louis, MO) and overlayed on SH-SY5Y target cells for 12 h.
(The SH-SY5Y cells had been plated for 12 h prior to retroviral
transduction, with a seeding density of 2500 cells/cm2.) A total of
5 × 108 SH-SY5Y cells were transduced with the GSE library. The
medium was changed 12 h after retroviral transduction and then
again 12 h later. Ninety-six hours after retroviral transduction, the
SH-SY5Y cells were detached with trypsin and plated on laminin-
coated plates (Becton Dickinson Labware) with a seeding density
of 2500 cells/cm2 and then treated with 25 M trans-retinoic acid
(Sigma) for 36 h to induce neurite outgrowth. Then the SH-SY5Y
cells were collected with No-Zyme solution (Sigma) and immunos-
tained with an anti-␤1 integrin antibody directly conjugated to APC
(Pharmingen) as described below. The ﬂuorescently labeled cells
were subsequently analyzed by ﬂow cytometry for GFP expression
and ␤1 integrin immunostaining.
2.3. Screening the human siRNA library
The human siRNA library contained about 43,000 siRNA tar-
geting 8500 human genes and was cloned into an FIV-based
pSIF1-H1 vector, as previously described (System Biosciences, SBI).
The pSIF1-H1 vector carried GFP, which was used as a reporter
for ﬂuorescence-activated cell sorting (FACS) analysis (Fig. 8A).
Brieﬂy, the siRNA library targeted and overlapped with the 8500
genes represented on the GeneChip® Human Genome Focus Array
The viral supernatant carrying the library was produced as
described previously (Zufferey et al., 1998). Brieﬂy, the siRNA
library was transfected into 293T packaging cells (ATCC) with the
pFIV-PACK packaging plasmid mix (Zufferey et al., 1998; System
Biosciences; Cellecta, Mountain View, CA). The virus-containing
supernatant was ﬁltered through 0.45 m ﬁlters (Nalgene), and
stored at −70 ◦C. Prior to infection of cells with library-carrying
virus, the viral supernatant was thawed for 5 min at 37 ◦C and
immediately used to infect 5 × 108 SH-SY5Y cells. (The SH-SY5Y
cells had been plated 12 h prior to viral transduction and were
distributed in 16 six-well plates, with a seeding density of
2 × 106 cells/well.) Three hundred microliters of supernatant and
polybrene, at 5.0 g/mL (Sigma, St. Louis, MO) ﬁnal concentra-
tion, were added to each well. The plates were spun in a swinging
bucket rotor centrifuge for 90 min at 1500 × g and 25 ◦C and then
incubated at 32 ◦C, 5% CO2. Ninety-six hours after viral trans-
duction, the SH-SY5Y cells were detached with trypsin, plated
on laminin-coated plates (Becton Dickinson Labware) at a seed-
ing density of 2500 cells/cm2 and then treated with 25 M RA
(Sigma) for 36 h to induce neurite outgrowth. Then the SH-SY5Y
cells were collected with No-Zyme solution (Sigma) and immunos-
tained with an anti-␤1 integrin antibody directly conjugated to
APC (Pharmingen) as described below, for subsequent analysis by
ﬂow cytometry for GFP expression and ␤1 integrin immunostain-
2.4. Flow cytometric (FACS) analysis and sorting
To detect ␤1 integrin in live cells, the cells were detached from
the plates with No-Zyme solution (Sigma), washed twice with cold
PBS and then stained with an anti-␤1 integrin antibody directly
conjugated to APC (Pharmigen). Brieﬂy, 5.0 L of APC-coupled anti-
␤1 integrin antibody, which recognizes an extracellular epitope of
␤1 integrin, was used to stain 1 × 106 cells. The SH-SY5Y cells were
incubated with antibody in growth media, with 3% heat-inactivated
FCS (HyClone), for 1 h on ice. Next the cells were washed three times
with PBS, resuspended in cold PBS, analyzed and sorted by FACS
(BD Biosciences). Data were analyzed with FACScan, CellQuest and
2.5. Rescue of integrated provirus and identiﬁcation of target
genes: GSE library
From each sorted population, 1–5 × 106 cells were spun
and resuspended in PBS to purify genomic DNA, accord-
ing to the manufacturer’s instructions (DNeasy Tissue Kit,
Qiagen). Isolated genomic DNA was used as a template
for PCR reactions. To isolate the integrated provirus from
genomic DNA we used PCR with forward primers designed
to EGFP: 5 -ACTCTCAAGGATCTTACCGCTGTTGAGATC-3 and 5 -
AGATCCAGTTCGATGTAAC CCACTCGTGCA-3 and a reverse primer
(5 -ACCCAGCTTTCTTGTACAAAGTGGT AGGTAGGTAGG-3 ), which
corresponds to the Gateway cloning adapter (GATEWAY Cloning
System, Gibco, Invitrogen). After the PCR reaction, the PCR products
were analyzed with 1.5% and 3% agarose gels in TAE buffer. Relevant
PCR fragments were cloned into the pCR2 vector (Invitrogen) and
then individual clones were isolated with the QIAGEN Plasmid Mini
Kit (QIAGEN) and then sequenced to identify GSE library clones.
V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333 325
2.5.1. Rescue of integrated provirus and identiﬁcation of the
target genes: siRNA library
Total mRNA and genomic DNA from sorted cells were isolated
with the Trizol reagent (Invitrogen) according to the manufacturer’s
instructions. Reverse transcription was performed according the
GeneNet protocol (System Biosciences). The isolation of integrated
provirus carrying siRNA was performed by PCR using TitaniumTM
Taq DNA polymerase (Clontech) as previously described (System
Biosciences, Cellecta, Mountain View). Next PCR products were
re-ampliﬁed with biotinylated primers, puriﬁed with QIAGEN’s
QIAquick PCR Puriﬁcation Kit (QIAGEN) and then analyzed with
the Affymetrix GeneChip® Human Genome Focus Array accord-
ing to the manufacturer’s instructions and with recommended
Affymetrix reagents at 45 ◦C, without DMSO for 16 h (Affymetrix,
System Biosciences, Cellecta, Mountain View, CA). Data analysis
was performed with GeneNet software (System Biosciences, Cel-
lecta, Mountain View, CA) and Pathway Studio (Ariadne Genomics,
2.6. siRNA transfection
SH-SY5Y cells were plated on 24-well laminin-coated plates
(Becton Dickinson) at a seeding density of 2500 cells/cm2 12 h
before transfection. The siRNA was synthesized commercially
(Dharmacon, Thermo Fisher Scientiﬁc). The following siRNA was
used as a control: 5 -UAGCGACUAAACACAUCAAUU-3 . Transfec-
tions with siRNA were performed as previously described (Reynolds
et al., 2004). Forty-eight hours after transfection the cells were
treated with either 0 or 25 M RA. Neurite outgrowth was quan-
tiﬁed at 36, 48 and 72 h after the RA treatment. To this end,
the cells were ﬁxed and stained with DAPI (Molecular probes)
and phalloidin-TRITC (Sigma) as previously described (Gallo and
Letourneau, 1998). Neurite length was measured as described
2.7. Gene transcriptional proﬁling by quantitative real-time
Total mRNA was isolated from FACS-sorted cells with the RNeasy
Kit as recommended by the manufacturer (Qiagen). Isolated mRNA
was analyzed with the Agilent 2100 bioanalyzer and the RNA
6000 Nano LabChip Kit (Agilent Technologies, Palo Alto, CA). Next,
20–40 ng of total mRNA was reverse transcribed into cDNA using
PowerScript (BD Biosciences, Palo Alto, CA) with random hexamers.
The resultant cDNA (30 L) was ampliﬁed by PCR with a mixture of
gene-speciﬁc primers (5.0 pM each) and Advantage 2 TaqDNA poly-
merase (BD Biosciences) to produce amplicons <250 bp. For details
see Dolganov et al. (2001).
Next the ampliﬁed cDNA was used to quantify individual
gene expression via quantitative real-time RT-PCR, using TaqMan
probes and primers, and with Universal Master Mix (Invitrogen)
as described previously (Woodruff et al., 2007). All assays were
performed with an ABI Prism 7900 Sequence Detection Systems
(Applied Biosystems). The real-time RT-PCR Ct values were con-
verted to relative gene copy numbers (Dolganov et al., 2001). For
controls and to normalize results we monitored expression of the
following genes: GAPDH, PPIA, EEF1A, RPL13A, UBIQUITIN B and
Gene-speciﬁc primers for real-time RT-PCR were designed
for each gene of interest using either Primer3 (http://jura.wi.
mit.edu/rozen/) or Primer Express software (PerkinElmer) based on
sequencing data from the NCBI database. Primers were purchased
from Biosearch Technologies (Novato, CA). For primer sequences,
see http://adgenomics.stanford.edu. Normalized gene expression
data were analyzed by t-test, so as to identify genes with statisti-
cally signiﬁcant changes in expression.
2.8. cDNA cloning
Human spinal cord mRNA was obtained from Clontech (Clon-
tech). The quality of the mRNA was analyzed by capillary
electrophoresis using the Agilent 2100 bioanalyzer and RNA 6000
Nano LabChip Kit (Agilent Technologies, Palo Alto, CA). cDNA syn-
thesis was performed with the SMART PCR cDNA Synthesis Kit and
Advantage 2 PCR Kit (BD Biosciences) according to the manufac-
turer’s instructions. cDNA was used for MTGR1 cDNA ampliﬁcation
by PCR with speciﬁc primers designed for the 5 and 3 ends of
MGTR1 and the Advantage 2 PCR Kit (BD Biosciences). Isolated
cDNA was re-ampliﬁed with primers containing Gateway attB
adapters, according to the Gateway protocol (Gibco, Invitrogen) and
cloned into the pQCGFPL vector with the GATEWAY Cloning System
(Gibco, Invitrogen) according to the manufacturer’s instructions.
The accuracy of the GFP-MTGR1 fusion and absence of mutations
in the pQCGFPL-MTGR1 construct were conﬁrmed by sequencing
and BLAST analysis (NCBI).
2.9. Immunoﬂuorescent analyses and image capture
EGFP expression in live cells was monitored and analyzed with a
Nikon TE200 inverted microscope equipped with an Orca ER cooled
charge-coupled device (CCD) camera (Hamamatsu, Middlesex, NJ).
Images were collected and analyzed with the Simple PCI software
(Compix). To analyze neurite outgrowth, the SH-SY5Y cells were
plated at a seeding density of 1000 cells/cm2 in growth media and
incubated 12–18 h at 37 ◦C, 5% CO2. To label neurites, cells were
ﬁxed with 4% paraformaldehyde in 100 mM PBS, pH 7.4 (15 min at
4 ◦C), and washed for 15 min with 1× PBS containing 0.1% saponin
and 1% FCS. The ﬁxed cells were washed with 3× PBS, permeabilized
(0.1% Triton X-100-PBS, pH 7.4; 15 min) and stained with 50 g/mL
phalloidin-TRITC in PBS containing 1% FCS for 2 h at 4 ◦C. Next
the cells were washed with 3× PBS followed by incubation with
10 g/mL 4 -6-diamidino-2-phenylindole, DAPI (Molecular Probes)
for 10 min, washed in 3× PBS and analyzed with a Nikon TE200
microscope (Nikon) or with the Cellomics ArrayScan VTI (Thermo
2.9.1. Manual image capture and analysis
The images of cells plated on six-well plates (Corning) were
captured manually with an inverted Nikon TE200 microscope and
an ORCA-ER CCD digital camera. From the digitized images we
measured neurite/process length with the Simple PCI software
(Compix). Brieﬂy, we ﬁrst manually captured random rectangu-
lar ﬁelds of cells. Next, the corners of the rectangular ﬁelds were
connected with digital diagonal lines, so as to deﬁne an unbiased
determination of the cells to be measured. We then measured
the length of neurites/processes from 100 cells whose processes
crossed the diagonals.
2.9.2. Automated image capture and analysis
For automated analysis, we captured the images of cells plated
on 96-well plates with a Celllomics ArrayScan® VTI, which includes
a high-resolution Zeiss optical system, a multiple bandpass emis-
sion ﬁlter with matched single band excitation ﬁlters (XF57 or
XF100, Omega Optical), CCD camera and an ArrayScan VTI HCS
Reader (Thermo Scientiﬁc Cellomics). The system provides simul-
taneous image capture of several ﬂuorophores in the same cell.
The Cellomics algorithm identiﬁes cells, evaluates the integrity of
a nucleus and automatically excludes dead cells from the analysis.
Dual 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 was
estimated 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; lower
histogram 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 retroviral
transduction 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 and
72%—transduced cells). The histograms (D) illustrate GFP-negative and GFP-positive SH-SY5Y cells. The upper histogram represents control cells; lower histogram represents
SH-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 (without
library). (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 transduced
with GSE-GFP library. All cells were labeled with ␤1 integrin antibody directly conjugated to allophycocyanin (APC; see Section 2). Rectangle deﬁnes the sorted population
V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333 327
well of the plate. From these images, neurite measurements were
calculated with an automated quantitative high content screen-
ing algorithm for neurite outgrowth (Thermo Scientiﬁc Cellomics)
according to the manufacturer’s instructions.
Bioinformatic analysis was performed using the NCBI and EMBL
databases. To gain insight into particular biological pathways we
used the PathwayStudio and PathwayExpert software packages
(Ariadne Genomics, Rockville, MD).
Fig. 1C illustrates the strategy that we followed in the ﬁrst screen.
We generated a library from SH-SY5Y cells, which is a sympathetic
nervous system-derived, clonal human neuroblastoma cell line. We
chose SH-SY5Y cells for several reasons. SH-SY5Y cells exhibit a dis-
tinct neuronal phenotype when grown on laminin and treated with
neurotrophic factors or retinoic acid (Pahlman et al., 1981; Kaplan et
al., 1993; Jalava et al., 1992, 1993; Jamsa et al., 2004). Differentiated
SH-SY5Y cells express a variety of neuronal markers, including GAP-
43, synaptotagmin-l and synaptobrevin (Kim et al., 2000; Goodall
et al., 1997). Most importantly, retinoic acid-stimulates the devel-
opment of neurite-like processes (Clagett-Dame et al., 2006), and
their growth can be readily monitored using surface marker expres-
sion. This greatly facilitates high throughput screening for genes
that regulate neurite outgrowth. Given these properties, SH-SY5Y
cells, although not equivalent to primary neurons, provide an excel-
lent surrogate with which to perform and validate the utility of this
high throughput screen.
3.1. Library construction
Fig. 1A and B illustrate the design of the retroviral vector that
we used for the library construction. We created and used a self-
inactivating retroviral vector because after retroviral integration of
the vector into the target cell genome, transcription is driven only
from the CMV promoter. This property is achieved through dele-
tion of the U3 region of the 3 LTR in the pQCGFPL vector, and is
an important feature that signiﬁcantly increases the ﬁdelity of the
system (Fig. 1A and B).
The library covered the entire SH-SY5Y genome and included
combinatorial random fragments of cDNA (25–350 nucleotides
long) in both the sense and antisense orientations. We designed 5
and 3 adapters for directional cloning and the 3 adapter included
stop codons in all three frames. Members of the library function as
either antisense mRNA molecules (if they were cloned in an anti-
sense orientation) or lead to the production of functional interfering
peptides (if the inserts were cloned in the sense orientation). An
important feature of the library is that each random library clone
is fused to GFP; this greatly facilitates subsequent recovery of func-
tional inserts during the FACS protocol (see below). The genetic
complexity of the library was 1 × 107 independent recombinant
3.2. Retroviral transduction
We chose a retroviral strategy for the following reasons. First,
retroviruses permit efﬁcient and accurate delivery of genes and
recombinant clones into target cells. Second, there is stable inte-
gration of the provirus into target genome, resulting in long-term
expression of the encoded genetic information, including the GFP.
Third, under optimal conditions, only one virion can be incorpo-
rated per cell (Kustikova et al., 2003; Miller, 2002). This greatly
facilitates high throughput recovery and subsequent identiﬁcation
of functional library clones, namely those that alter process out-
growth in SH-SY5Y cells.
We found that >99% of the packaging cells were transfected
with the library. This was established by visualization of GFP ﬂu-
orescence (Fig. 2A) and by FACS analysis (Fig. 2B). We obtained
about 55% efﬁciency in the delivery of the library into SH-SY5Y
cells (Fig. 2C and D) and we also observed a signiﬁcant functional
impact of the library. Thus, in cells infected with the control vector,
pQCGFPL (Fig. 2E), the GFP was uniformly distributed. By con-
trast, after transduction of the SH-SY5Y cells with the library, we
observed signiﬁcant phenotypic variability of the GFP expression
(Fig. 2F–K). In some cases, the GFP was exclusively cytoplasmic and
in the processes of the cells; in other examples the GFP had clearly
translocated to the nucleus (Fig. 2H). We also observed structural
changes, including cells with elongated processes (Jamsa et al.,
3.3. High throughput functional screening for increased
The next step was to identify a marker that we could use
to screen for genes that inﬂuence process length. Ideal markers
for screening should either be upregulated in the population of
cells with growing processes or should exclusively be expressed
on developing growth cones of cells that are differentiating. In a
preliminary analysis we monitored the expression of a variety of
markers of differentiated SH-SY5Y cells using real-time PCR. Based
on this analysis we turned our attention to the integrins, which
are the family of receptors through which extracellular matrix
molecules, including laminin, interact. Of particular importance to
the present approach is that there is increased ␤1 integrin expres-
sion on the growing neurites of embryonic retinal ganglion cells
(Neugebauer and Reichardt, 1991; Stone and Sakaguchi, 1996; Ivins
et al., 1998; Treubert and Brummendorf, 1998). ␤1 integrin is also
localized on the axons and growth cones of regenerating facial
nerve and the magnitude of ␤1 integrin immunoreactivity corre-
lates with axonal growth of dorsal root ganglia neurites (Arevalo
and Chao, 2005).
As illustrated in Fig. 3A–E, retinoic acid dose-dependently
induced a neuronal phenotype in SH-SY5Y cells and, consistent
with a previous report (Jenab and Inturrisi, 2002; Li et al., 2000),
we found that RA signiﬁcantly upregulated ␤1 integrin mRNA in
cells grown on laminin (Fig. 3F). Furthermore, using FACS analysis
to follow these changes in a high throughput fashion we found that
the level of ␤1 integrin protein in RA-treated SH-SY5Y cells was
also signiﬁcantly increased (Fig. 3G). For these studies we used an
antibody that recognizes an extracellular epitope of ␤1 integrin in
live non-permeabilized cells.
These results demonstrate that RA induction of processes in
SH-SY5Y cells occurs concomitantly with increased ␤1 integrin
expression on the surface of the cells and on their processes. Finally,
consistent with the conclusion that this increase indeed represents
neurite outgrowth, we also found an increase of the cytoplasmic
marker, GAP-43, a protein associated with neurite growth (Bomze
et al., 2001; Anderson et al., 1998; Skene, 1989; Fig. 3G).
of viable, GFP-positive cells that over-express ␤1 integrin, after transduction with the GSE library. This population corresponds to 1.42% of the GFP and ␤1 integrin—APC-
positive cells that were isolated by FACS (the ﬂuorescence intensity is a logarithmic readout of the magnitude of antibody binding). (For interpretation of the references to
color in this ﬁgure legend, the reader is referred to the web version of the article.)
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 were
plated 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 CCD
digital 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) Quantitative
real-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 separate
experiments (for abbreviations and the panel of genes analyzed see Supplementary Table 1). (G) FACS analysis of the immunostaining of live SH-SY5Y cells plated on laminin,
treated with 0 or 25 M RA for 72 h and stained with ␤1 integrin antibody. Cells were labeled with ␤1 integrin antibody directly conjugated to allophycocyanin (APC) or
isotype control antibody directly conjugated to APC. Data were collected by FACScan and analyzed with CellQuest and FlowJo softwares.
To conﬁrm that the magnitude of ␤1 integrin indeed correlates
with the extent of neurite outgrowth we next monitored neu-
rite outgrowth after downregulation of ␤1 integrin with siRNA.
Twenty-four hours after transfection of the ␤1 integrin siRNA, we
treated the cells with RA. ␤1 integrin siRNA signiﬁcantly reduced
␤1 integrin mRNA by about 50% (Fig. 4A), and most importantly,
this reduction correlated with a dramatic inhibition of neurite out-
growth (Fig. 4B) compared to the growth observed in the absence
of ␤1 integrin siRNA or in cells treated with control luciferase siRNA
Having established that increases in surface ␤1 integrin
immunoreactivity correlate with the RA-induced neuronal phe-
notype, we next developed a FACS protocol to rapidly sort cells
transduced with the library. Three sorting gates were used: (1) GFP,
which marks cells that were transduced with the library; (2) APC,
which marks cells immunostained with an APC-coupled anti-␤1
integrin antibody; (3) cell size, so as to exclude dead cells.
The control groups consisted of cells immunostained with iso-
type control antibody conjugated to APC or of cells transduced
with empty vector-GFP and immunostained with APC-coupled ␤1
integrin antibodies. From 108 library-transduced SH-SY5Y cells we
sorted the top 1.42% of ␤1 integrin expressors that were also GFP-
positive, were viable and did not overlap with the population of
cells infected with the control, empty-GFP vector (Fig. 2L).
3.4. Rescue of functional clones
Next we used speciﬁc primers to isolate the provirus from sorted
cells. The primers were designed to the backbone of the vector or
to GFP (Fig. 1B). All PCR products were individually sequenced to
identify candidate genes. We found that 80% of the isolated clones
had inserts in the antisense orientation; 20% of isolated clones were
sense-oriented and in frame with GFP. In our ﬁrst analysis, which
established the utility of this approach, we analyzed 30 clones
and recovered a variety of genes, including transcription factors,
scaffold proteins, channels and several genes for which a function
has yet to be identiﬁed. Below we describe some of these genes
and demonstrate their functional relevance to process/neurite out-
V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333 329
Fig. 4. Transfection of SH-SY5Y cells with ␤1 integrin siRNA. SH-SY5Y cells transfected with ␤1 integrin siRNA or a control siRNA. (A) Quantitative real-time RT-PCR-based
transcriptional proﬁling of SH-SY5Y cells 48 h after transfection with ␤1 integrin siRNA. Data, expressed as relative gene copy number, were normalized to the mRNA level
in cells transfected with control siRNA and were determined from the average of three independent experiments (see Supplementary Table 1). (B) Digital images of SH-SY5Y
cells transfected with ␤1 integrin siRNA or control siRNA and treated with 25 M RA for 60 h (scale bar equals 50 m).
3.5. siRNA inhibition of MTGR1 expression induces neurite
Our attention was directed at a clone that encodes the MTGR1
gene, which we chose to further characterize, for three reasons.
First, we isolated three independent, although not identical, clones
corresponding to the MTGR1 gene. Second, MTGR1 is a transcrip-
tional co-repressor that has been implicated in the regulation
of differentiation of hematopoetic cells (Kitabayashi et al., 1998;
Calabi and Cilli, 1998; Rossetti et al., 2004). Third, MTGR1 is a human
homologue of XETOR, which inhibits neurogenesis in Xenopus (Cao
et al., 2002).
Because the MTGR1 clones were isolated from the library in the
antisense orientation we concluded that the increase of ␤1 inte-
grin expression resulted from inhibition of MTGR1. To conﬁrm this
observation and to test the hypothesis that increased ␤1 integrin
expression is associated with increased process/neurite outgrowth,
we developed a secondary screen using siRNA to reduce MTGR1
mRNA expression in an in vitro analysis of neurite outgrowth in
Fig. 5A demonstrates that transfection of SH-SY5Y cells with
MTGR1 siRNAs reduced MTGR1 mRNA by greater than 80%. Consis-
tent with the FACS analysis we also found that inhibition of MTGR1
by siRNA concurrently induced a pronounced increase of ␤1 inte-
grin and GAP-43 mRNA (Fig. 5E). Finally, we found an increase of
epidermal growth factor (EGF) and ﬁbroblast growth factor-1 (FGF-
1) mRNA, both of which induce neurite outgrowth in SH-SY5Y cells
(Kornblum et al., 1990; Morrison et al., 1988), even in the absence of
RA (Fig. 5C and D). Importantly, we found no changes in the expres-
sion of a panel of other genes that were analyzed in SH-SY5Y cells
(Supplementary Table 1 and Section 2).
We also performed several additional controls. First, we tar-
geted SH-SY5Y cells with an siRNA designed to another clone that
was isolated during the primary screen, Sox4. Despite signiﬁcant
knockdown of Sox4 mRNA with Sox4 siRNA (Fig. 5A), we found no
change in the level of ␤1 integrin, GAP-43, EGF or FGF-1 mRNA (data
not shown). Finally, we used an siRNA directed against luciferase
and also found no changes in mRNA levels of these genes (Fig. 5C
and D). Most importantly, morphological analysis of SH-SY5Y cells
treated with MTGR1 siRNA demonstrated an increase in process
Fig. 5. Effect of MTGR1 siRNA on SH-SY5Y cells. Quantitative real-time PCR-based transcriptional proﬁling of MTGR1 and Sox4 (A), FGF-1 (C), EFG (D), ␤1 integrin and GAP-43
(E) 48 h after transfection with MTGR1, Sox4 or luciferase siRNA in SH-SY5Y cells. Values are normalized to mock transfected cells. (B) Quantiﬁcation of neurite outgrowth
from SH-SY5Y cells plated onto laminin and treated with 0 or 25 M RA for 72 h.
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-
SY5Y cells transduced with control pQCGFPL vector. (B) SH-SY5Y cells transduced
with retroviral vector pQCGFPL-MTGR1 containing MTGR1 full length cDNA isolated
from human spinal cord and fused to GFP. In (B, bottom), there is nuclear localization
of the MTGR1.
length (Fig. 5B). This was the case both for SH-SY5Y cells incubated
without RA (43% increase) or in the presence of RA (40% increase).
In fact, the length of processes in the presence of MTGR1 siRNA,
but without RA, was comparable to the length of processes in con-
trol, RA-treated cells. We found no effect of control siRNAs or Sox4
siRNA on process length (Fig. 5B).
3.6. Overexpression of MTGR1 inhibits neurite outgrowth
We next studied the effect of full length MTGR1 cDNA overex-
pression in SH-SY5Y cells. We isolated full length MTGR1cDNA from
adult human spinal cord by RT-PCR and cloned it as a GFP-fusion
into the retroviral vector pQCGFPL (Fig. 1A) to generate pQCGFP-
MTGR1. We then infected a naïve population of SH-SY5Y cells with
pQCGFP-MTGR1 and 72 h later isolated the GFP-positive cells by
In cells transduced with a control, empty GFP vector, there is
uniform distribution of the GFP ﬂuorescence (Fig. 6A). By contrast,
Fig. 6B illustrates that the GFP-MTGR1 protein is only found in the
nucleus of infected SH-SY5Y cells, which is consistent with the
reports that MTGR1 is member of the ETO family of nuclear repres-
sor proteins (Davis et al., 2003; Lindberg et al., 2003). When we
studied the consequence of overexpression of GFP-MTGR1 in RA-
stimulated SH-SY5Y cells, we observed a signiﬁcant inhibition of
process outgrowth (Fig. 7E–H) compared to cells transduced with
empty GFP vector (Fig. 7A–D). These results provide evidence that
human MTGR1 is indeed a repressor of process/neurite outgrowth
in the SH-SY5Y cells.
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)
and treated with or without RA for 72 h. (A and E) Phalloidin-TRITC staining; (B
and F) GFP; (C and G) overlay of phalloidin-TRITC and GFP; (D and H) overlay of
phalloidin-TRITC and DAPI (scale bar equals 50 m).
3.7. Expression proﬁle of MTGR1
Although Morohoshi et al. (2000) demonstrated that MTGR1 is
expressed at high levels in human bone marrow cells, hemopoi-
etic tissues and lymphoid organs, its presence in human neuronal
tissue was not reported. For this reason, in the present study we
analyzed expression of MTGR1 in human primary neuronal tissues.
We found high levels of MTGR1 mRNA in cerebellum, spinal cord,
motor cortex, hippocampus and substantia nigra (Supplementary
Fig. 1). These results suggest that our observations in SH-SY5Y cells
are of general relevance to neurite outgrowth in diverse regions of
the central nervous system.
3.8. Parallel and independent screening using a lentiviral siRNA
In a parallel and independent functional genetic screen we used
a GFP-labeled large-scale siRNA library that is expressed from an
FIV-based lentiviral vector pSIF1-H1 (Fig. 8A). The library contains
40,000 individual siRNA that target 8500 human genes (Section
2). We delivered this library to naive SH-SY5Y cells and, as in the
previous screen, we found that the library-induced diverse mor-
phological changes of the SH-SY5Y cells (Fig. 8C) compared to cells
expressing 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:
rev responsive element; cPPT: central polypurine tract; CMV: CMV promoter; GFP: green ﬂuorescent protein; WPRE: woodchuck hepatitis virus posttranscriptional regulatory
element. The siRNA library under the control of the H1 promoter was inserted into the 3 UTR of the pSIF lentiviral vector. (B) SH-SY5Y cells transduced with empty pSIF-GFP
control vector. (C) Neurite outgrowth induced in SH-SY5Y cell transduced with pSIF-siRNA library (scale bar equals 50 m).
We performed two independent screens of the lentiviral siRNA
library. To identify functional siRNA, we used a modiﬁcation of the
FACS approach described above and isolated an experimental and
a control population of cells. The experimental population showed
high upregulation of extracellular ␤1 integrin. The control popu-
lation showed levels of ␤1 integrin expression comparable to that
recorded in either vector-GFP transduced cells or in untreated cells.
To identify functional clones we isolated integrated provirus from
both populations of sorted cells, using primers designed to the
vector (Section 2). Instead of sequencing individual clones from
the sorted cells, we used a high throughput approach (Affymetrix
GeneChip® Human Genome Focus Array, Section 2) to identify siR-
NAs that induced the increased ␤1 integrin expression.
From the analysis of two independent screens of the lentivi-
ral siRNA library we identiﬁed 39 genes that appeared in both
screens. Among these genes were many that encode proteogly-
cans, kinases, receptors, adaptor proteins and transcription factors
(Supplementary Table 2). In several instances, the same gene was
uncovered by several independent siRNAs, among which are those
corresponding to protein tyrosine kinase HEK2, Rab GDI, neuro-
oncological ventral antigen 1 (NOVA1) and neurite outgrowth
Of particular interest and relevance to the results obtained in
the GSE screen, is that from the lentiviral screen we isolated an
siRNA that targets GFI1 and GF1B. A bioinformatic analysis (Path-
way Studio, Ariadne Genomics) revealed that GFI1 is a zinc ﬁnger
transcriptional repressor and a member of the MTG8(ETO)/MTGR1
protein complex (Hock and Orkin, 2006; McGhee et al., 2003).
GFI1B is 97% identical in the zinc ﬁnger domain and 95% identi-
cal in the SNAG domain to GFI1 (Garcon et al., 2005). Thus, using
two independent genome-wide functional genetic screens of genes
that regulate neurite outgrowth we uncovered the same protein
In this paper we describe a powerful, high throughput genetic
strategy that uses a functional genetic screen of two large-
scale libraries in human neuronal cells. The success of this
screening approach is illustrated by our discovery that the
MTG8(ETO)/MTGR1 protein complex is a signiﬁcant contributor to
the molecular mechanisms that underlie and regulate ␤1 integrin-
dependent neurite elongation/outgrowth in SH-SY5Y cells. These
novel primary and secondary screens establish a powerful system
for comprehensive identiﬁcation of genes that regulate neurite out-
A great advantage of the GSE library is that it is genome wide and
is syngenic for the targeted SH-SY5T cells. To complement this we
used a large-scale siRNA library that targeted 8500 human genes.
In both screens we delivered libraries by retroviral transduction
into SH-SY5Y cells. We used retroviral vectors, as under optimized
conditions the cells only take up a single virion during retrovi-
ral transduction (Kustikova et al., 2003). This made it possible to
follow the long-term phenotypic changes produced by individual
elements of the library, in individual cells, which also greatly sim-
pliﬁed subsequent identiﬁcation of functional clones.
We were searching for a relatively rare event. Thus, it was
essential to have a high throughput method of analysis. To this
end, we used multiparameter ﬂuorescence-activated cell sort-
ing to identify phenotypic changes induced by the libraries and
to select cells that signiﬁcantly manifest these changes. There
are several features of our approach that greatly facilitated FACS
332 V.S. Ossovskaya et al. / Journal of Neuroscience Methods 177 (2009) 322–333
analysis. Most importantly, we identiﬁed an antigen that could be
used to monitor library-induced phenotypic changes, namely ␤1
integrin. It is theoretically possible to monitor intracellular mark-
ers, but this generally requires ﬁxation and permeabilization of
cells, which complicates the subsequent identiﬁcation of functional
clones. Moreover, we found that monitoring intracellular markers
of neurite outgrowth in ﬁxed cells signiﬁcantly reduced the efﬁ-
ciency of the functional screen as it was more difﬁcult to recover
the functional provirus or clones of interest from the library.
Because the library carried GFP, the sorting could be restricted to
cells that incorporated the library. Taken together, we were able to
screen rapidly millions of cells and to identify functional clones. The
approach can be readily adapted to other cell types and phenotypic
To conﬁrm the functional relevance of candidate clones iso-
lated in the primary GSE screen, we used a secondary, cell-based
assay of neurite outgrowth. This functional screen involved siRNA
suppression of the expression of candidate genes isolated in the
primary screen. Importantly, we not only monitored the same end-
point as in the primary screen (namely ␤1 integrin expression)
but we also documented that upregulation of ␤1 integrin cor-
related with neurite outgrowth. In a further conﬁrmation of the
functional signiﬁcance of the candidate genes, we overexpressed
full-length cDNA corresponding to the candidate gene, and as pre-
dicted, observed inhibition of neurite outgrowth.
4.1. Leniviral siRNA screen and high throughput analysis
To conﬁrm the results from the GSE screen we performed two
additional independent functional screens of a large-scale lentivi-
ral library of 40,000 siRNAs that target 8500 characterized human
genes. From FACS analysis of cells sorted for ␤1 integrin upregu-
lation, we identiﬁed positive clones using a microarray approach.
Among isolated genes we found chondroitin-sulfate proteoglycan
(Versican), which has been previously described as an inhibitor of
CNS axon growth in vitro and in vivo (Schweigreiter et al., 2004).
Of particular interest, however, was our isolation of GFI1 and GFIB,
members of the MTGR1 protein complex (see below). This discov-
ery provided a very strong validation, not only of the utility of the
primary screen to identify genes that inﬂuence neurite outgrowth,
but also of the importance and value of the secondary, independent
screen. The two screening approaches clearly complemented each
4.2. MTGR1, GFI1 and neurite outgrowth
From these two independent genome-wide functional screens
we isolated myeloid-transforming gene-related protein 1 and
growth factor independence 1 and 1B. MTGR1 heterodimerizes
with the myeloid translocation gene on chromosome 8, MTG8,
also known as eight-twenty-one or ETO (Kitabayashi et al., 1998).
Gﬁ1 is a DNA binding transcriptional repressor that associates with
MTG8/ETO and MTGR1 (McGhee et al., 2003; Amann et al., 2005).
Thus, MTGR-1 and GFI1 belong to the same MTG8/ETO protein com-
plex and represent a family of nuclear repressor proteins (Hock and
Orkin, 2006; McGhee et al., 2003; Amann et al., 2005). Studies of
homologs of MTGR1 have provided evidence consistent with our
ﬁnding that inhibition of MTGR-1 promotes neurite outgrowth. For
example, and as noted above, Xenopus XETOR, a homolog of human
MTGR-1, is a transcriptional repressor that suppresses neurogene-
sis during embryogenesis (Cao et al., 2002; Logan et al., 2005). The
MTG8/ETO protein complex also blocks activity of G-CSF, which in
human neural stem cells stimulates neurogenesis through recip-
rocal interaction with VEGF and STAT activation (Ahn et al., 1998;
Jung et al., 2006). Taken together with our ﬁnding that inhibition of
MTGR1 also induces transcription of EGF and FGF-1, both of which
contribute to the regulation of neurite outgrowth and axon guid-
ance (Kornblum et al., 1990; Morrison et al., 1988; Arevalo and
Chao, 2005), these results indicate that the MTGR1/ETO/GFI1 pro-
tein complex function as nuclear repressors of pathways that can
regulate neurite outgrowth.
We thank Alex Chenchik and Michail Makhanov (System Bio-
sciences) for help with the lentiviral siRNA libraries, Valerie Vincent
for help with the Cellomics analysis and Ariadne Genomics for
help with bioinformatics. This work was supported by NIH grants
NS14627 and 48499 and an Opportunity Award from the Sandler
Program in Basic Sciences at UCSF.
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