A P P L I C AT I O N N O T E

SMARTvector
shRNA Lentiviralplatform:
Elucidating therole of factors
important inneurite outgrowth.

Introduction
Normal sensory, motor and cognitive functions rely heavily on
the ability of neurons to develop the intricate neurite architecturethat supports a complex signaling network. Abnormalities ofneuronal cell development and differentiation are implicatedin many diseases including Alzheimer’s, Parkinson’s and otherneurological disorders. Neuronal pathologies may also result
from stroke, hypoxia, severe blood loss or physical trauma.
Clinically, the prognosis for affected individuals can be poor
because the recovery and regeneration of damaged or diseased
neurons is poorly understood. Therefore, an important aim ofmany researchers is to elucidate the molecular mechanisms that
direct neuronal development, differentiation and regeneration.
This application note describes how the combination ofstate‑of‑the art Dharmacon™ SMARTvector™ shRNA lentiviraland high content analysis technologies provides multiple layers

Authors
Allison St. Amand
Debbie Nickisher
Annaleen Vermeulen
Queta Smith
Revvity, Inc.

of important cellular data. These promise to provide a wealthof information about neuronal cell biology and pave the way fordeveloping effective strategies for clinically relevant treatments.
Researchers often rely on in vitro cell culture as model systems
for identifying potential therapeutic targets. For example,
neuroblastomas are common pediatric solid tumors arisingfrom the neuroectoderm and are characterized by their ability
to undergo spontaneous regression to mature differentiatedneurons. This tumor type responds positively to treatments that
rely on inducers of differentiation such as retinoic acid (RA) and
its derivatives1. To better understand the interplay of factors
involved in differentiation and to identify novel therapeutic targets,researchers employ cell lines such as SH-SY5Y that are derived
from human neuroblastomas1-2. While SH-SY5Y cells represent a

SMARTvector shRNA Lentiviral platform: Elucidating the role of factors important in neurite outgrowth.

valuable model system for the discovery of novel chemical

In this application note, we describe how the SMARTvector

inducers or inhibitors of neuronal differentiation, application

shRNA lentiviral platform can be used to achieve targetedof RNAi-based gene knockdown has been hindered by (1) the

knockdown in SH-SY5Y cells in order to investigate the roleinefficient delivery of silencing constructs using traditionalof genes involved in neuronal differentiation. In addition,

lipid-mediated transfection methods, (2) the need for robust,

we demonstrate the utility of a high content screening

sustained silencing (up to 9 days), and (3) the lack of methods

approach which enables the detailed analysis of a neurite

to analyze cellular phenotypes in a mixed population

outgrowth phenotype in a cell line that exhibits at least twoof epithelial and neuronal cells (see “Measuring Neurite

morphologically distinct fates: a neuroblast-like phenotype

Outgrowth” on next page.

and an epithelial-like phenotype.

Measuring neurite outgrowth
Neurons assemble into functional networks bydeveloping axons and dendrites, together known as
neurites. Growth cones at the terminal processes
are the sites where a neurite elongates and splits
to create branchpoints. Neurite outgrowth was thenquantified in neuronal cells and sub-populations
were specifically categorized.
After cells are fixed and stained cells can bescanned and analyzed. Figure 2A shows aschematic representation of a neurite-bearing cell
indicating parameters that the Neuronal Profiling
BioApplication Software is able to measure.
The algorithm identifies key structures of theneuronal cell (nucleus, cell body and neurites) andmeasures multiple morphological parameters ofthese structures such as intensity, area, length andnumber. Average neurite count is the number ofneurites identified in a field divided by the numberof valid neuronal cell bodies. Average neurite lengthis calculated by taking the total measured lengthsof all the neurites in a field and dividing it by the
total neurite count. Branchpoint average countis determined by dividing the total branchpoint
count by the number of neurites in the field. Finally,
the branchpoint’s average distance from the cell
Figure 1: Experimental Workflow of SH-SY5Y Transductions.

body can be computed. Together, these parameters
can be used to assess the extent of neurite
outgrowth in treated and untreated cell populations.

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SMARTvector shRNA Lentiviral platform: Elucidating the role of factors important in neurite outgrowth.

Materials and methods

A

Experimental setup
The transduction conditions including optimal cell density
and multiplicity of infection (MOI) for SH-SY5Y cells were
determined previously (SMARTvector application note).
Transduction was performed at a high cell density inthe presence of Polybrene [American Bioanalytical,(Cat #AB01643)]. SH-SY5Y cells (120,000 cells per well in a
24-well plate) were transduced with different gene‑specific
SMARTvector shRNA lentiviral constructs at a MOI of 40

B

according to the general transduction protocol (SMARTvector
technical manual). Two days following transduction, cells
were split and plated at 2,500 cells per well in a 96-well cell
culture plate. Cells were allowed to recover from transduction
and adhere overnight. Culture medium was then changed tocomplete growth medium with or without All-Trans Retinoic
Acid (ATRA; 10 µM). Cells were cultured for an additionalsix days with medium changes every two to three days.
Cells were then harvested and prepared for mRNA analysis(QuantiGene™ branched DNA (bDNA), Panomics™, Freemont,
CA), cell viability assay (Thermo Scientific™ alamarBlue™)and immunocytochemistry. A schematic of the experimental
workflow is shown in Figure 1.
Genes targeted
SMARTvector shRNA Lentiviral Particles targeting human
RHOA (Accession #NM_001664), RAC1 (NM_006908),
SRC (NM_005417) and CSK (NM_004383) were used forsilencing experiments. SMARTvector Non-targeting Control(NTC) Particles (Dharmacon, Cat #S-005000-01) were usedas negative controls.

Figure 2: Measurements of Neurite Outgrowth in SH-SY5Y Cells
A. Schematic representation of a neuron and features that aremeasured by the algorithm. B. Composite image of the SH-SY5Y
cell line stained with Cellomics Neurite Outgrowth HCS Reagent Kit.
Blue indicates nuclei stained with Hoechst 33342. Green represents
neuronal bodies (bright green) and epithelial-like cells (faint green)with different intensities. C. Raw image with algorithmic overlays
from the Cellomics Neuronal Profiling BioApplication indicating
the epithelial cells (red demarcations) that were filtered from theanalysis based on their cell body average intensity. Blue and light
blue demarcations indicate selected neuronal nuclei and cell bodies.
Cyan, pink and green demarcations represent neurites and yellow
demarcations indicate branchpoints.

Gene knockdown and cell viability
The level of target mRNA knockdown was assessedusing the bDNA assay specific for the targets of interestat three and nine days post-transduction. Cell viability
was determined using the alamarBlue assay according to
manufacturer’s instructions.

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SMARTvector shRNA Lentiviral platform: Elucidating the role of factors important in neurite outgrowth.

High content analysis of neurite outgrowthA

After fixing with 3.7% formaldehyde in phosphate bufferedsaline (PBS), the cells were stained using antibodies
provided in the Cellomics Neurite Outgrowth HCS Reagent
Kit (Cat #K07-0001-1). Images were acquired on the
Cellomics ArrayScan VTI HCS Reader and analyzed with
the Cellomics Neuronal Profiling BioApplication. The mixed
population of neuronal and epithelial-like cell types was
distinguished with the gating technique provided by the
Neuronal Profiling BioApplication. While both the neuronaland epithelial cells are detectable with a primary neuralspecific antibody supplied in the kit, the fluorescenceBintensity is generally much stronger in the neuronal cells(Figure 2B). Epithelial-like cells were removed from analysis
by demarcation of the cell body based on the lower cellbody average intensities (Figure 2C). Four replicate wells
for each target and condition were analyzed. Six fields ineach well were measured (> 100 cells/field). Parameters
used in this analysis included: Mean Neurite Count.
Mean Neurite Average Length, Mean Branchpoint AverageCount and Mean Branchpoint Average Distance from the
Cell Body (see side Bar “Measuring Neurite Outgrowth,”
Figure 2). These measurements were collected for each of
the four replicates. The averages and standard deviations
were calculated for each target and condition. All data
was normalized to cells tranduced with the SMARTvector
Non-targeting Control Particles.

Results
ATRA induces neurite outgrowth in SH-SY5Y cells
The addition of ATRA to SH-SY5Y cells induces neurite
outgrowth in a dose dependent manner. It was determined

Figure 3: All-Trans Retinoic Acid Induces Neurite Outgrowthin SH-SY5Y Cells. SH-SY5Y cells were treated with increasing
concentrations of ATRA or DMSO. Cells were cultured withmedium changes every two or three days for seven days and thenfixed and stained. A. The Average Neurite Length and Branchpoint
Average Count were each determined by the Neuronal Profiling
Bioapplication. Values were normalized to DMSO-treated controls(gray bars). B. Representative micrograph of cells treated withDMSO or ATRA. Cells were stained with Neurite Outgrowth HitKit(green) and Hoechst 33342 (blue).
Table 1: Target Gene Knockdown and Viability of SH-SY5Y Cells
Transduced with SMART-vector shRNA Lentiviral Constructs.
Cells were transduced with SMARTvector constructs at an
MOI of 40, split after two days, maintained in culture medium
without selection and then harvested at three days and nine days
post‑transduction. The Thermo Scientific™ alamarBlue™ assay
was used to assess viability and normalized to the SMARTvector
NTC. mRNA levels were determined by the Panomics bDNA assay
and normalized to a house-keeping gene (GAPDH) and to the
SMARTvector Non-targeting Control.

that culturing the cells in ATRA for five to six days was

Target gene knockdown % Viability

the optimal time point for developing significant neurite

72 hours

216 hours

216 hours

SMART vector SRC

65%

51%

86%

SMART vector RAC1

96%

86%

80%

SMART vector CSK

75%

70%

111%

SMART vector RHOA

76%

64%

127%

outgrowth (data not shown). Both the average neurite
length and branchpoint count increased with the additionof 1 µM and 10 µM ATRA, respectively, compared tountreated and DMSO-treated cells (Figure 3). Addition of
ATRA at concentrations greater than 10 µM was not
optimal and resulted in an apparent decrease in neurite
outgrowth, possibly due to increased cell death (data notshown). ATRA was added at a 10 µM concentration for all
subsequent experiments.

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4SMARTvector shRNA Lentiviral platform: Elucidating the role of factors important in neurite outgrowth.

Sustained silencing of specific gene targets
SH-SY5Y cells were transduced with SMARTvector shRNAto an underestimation of knockdown after nine days.

Lentiviral Particles targeting RAC1, RHOA, SRC or CSK,

Depleting RAC1 and SRC mRNA had a negative effect on theas well as a NTC construct. Knockdown of mRNA was

growth rate of the cells: 80% and 86% viability comparedassessed at three and nine days post-transduction. All

to the cells transduced with the SMARTvector Non-targeting

genes were sufficiently silenced at both three days and nine

Control. In contrast, depleting RHOA and CSK mRNA

days (Table 1) with the slightly better knockdown at theresulted in a positive effect on growth rates: 111% and 127%

earlier time point (three days). Since cells were cultured incompared to the cells transduced with the SMARTvector

the absence of puromycin, untransduced cells may have

Non-targeting Control (Table 1, Figure 4).

had a growth advantage over transduced cells thus leading

A

B

Figure 4: Neurite Outgrowth Nine Days Post-Transduction. A. Neurite outgrowth parameters were measured with the Cellomics™ Neuronal
Profiling BioApplication (Mean Neurite Count, Mean Neurite Average Length, Mean Branchpoint Average Count and Mean Branchpoint Average
Distance from the Cell Body) in untreated SH-SY5Y cells. Data for targeted genes (SRC, RAC1, CSK and RHOA) was normalized to SMARTvector
NTC treated under similar conditions. B. Representative micrographs of SH-SY5Y cells transduced with SMARTvector constructs. Cells were
stained with Neurite Outgrowth HitKit (red) and Hoechst 33342 (blue).

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5SMARTvector shRNA Lentiviral platform: Elucidating the role of factors important in neurite outgrowth.

Targeted gene knockdown results in differences in neurite
outgrowth and response to retinoic acidSH-SY5Y cells transduced with target knockdown constructs
were cultured with or without ATRA for six days. Nine days
post-transduction, cells were fixed and stained according to
the Cellomics Neurite Outgrowth HCS Reagent Kit protocol.
Plates were then scanned on the Cellomics ArrayScan VTI using
the Neuronal Profiling BioApplication. Results from untreatedand ATRA-treated transduced cells are shown in Figure 4
and 5, respectively. Representative micrographs illustrating
the phenotypes of SH-SY5Y cells transduced with different
target-specific SMARTvector shRNA Lentiviral Particles andsubsequently treated with ATRA or untreated are also shown.
In the absence of an ATRA signal, depletion of RHOA
expression in SH-SY5Y cells led to neurite outgrowthphenotypes that had ~ 2.5-fold longer neurites witha ~ 4-fold increase in branchpoints compared to the
SMARTvector Non-targeting Control-transduced cells(Figure 4). Knockdown of RHOA in ATRA-treated cells did notlead to a significant increase in neurite outgrowth (Figure 5).
In contrast, silencing RAC1 expression in untreated cells
resulted in fewer neurites and any associated branching
was blocked. Furthermore, depletion of RAC1 strongly
inhibited ATRA-induced neurite outgrowth so that branching
was diminished ~ 10-fold, while neurite count and length
was decreased ~ 2-fold compared to the SMARTvector
NTC (Figure 5). Depletion of SRC also significantly inhibitedneurite outgrowth induced by ATRA. However, knockdown of
SRC and CSK expression in untreated cells had little to noeffect on neurite formation. CSK silencing had no effect onneuronal differentiation in ATRA-treated cells.

Conclusion
One of the aims of neurobiology is to identify those factorsthat promote differentiation and inhibit proliferation to apply
as possible therapeutics for treatment of neuronal disease,brain injury and cancers. To achieve this goal requires abetter understanding of complexities involved in neuronaldifferentiation. A critical challenge for the use of in vitro
neuronal model systems is that the relevant cell types tend to
be refractory to standard RNAi delivery methods. In addition,
the neuronal phenotypes under investigation require potent
and sustained target gene knockdown in order to observe
the morphological consequences. SMARTvector shRNA
Lentiviral Particles successfully address both challenges bypermitting sustained and extended knockdown in difficult-totransfect cell types, like SH-SY5Y, which have historically been
inaccessible to RNAi approaches.
The work described here demonstrates the application of
the SMARTvector shRNA lentiviral platform to investigate thespecific roles of individual genes in neuronal differentiaton.
Neurite outgrowth represents a key indicator of neuronaldifferentiation and requires synchronized changes between
the actin cytoskeleton and the microtubule network.
These changes are regulated by signaling pathways triggeredby neurotrophins such as nerve growth factor (NGF),
brain derived neurotrophic factor (BDNF), and retinoic acid(RA)3. Retinoic acid, a metabolic derivative of vitamin A,
is important to both development and differentiation of thenervous system. RA-induced signaling (Figure 6) is initiatedby binding to members of the nuclear hormone receptor
families (such as RAR and RXR)4. The RA-RAR complexes
are capable of binding to RA responsive elements (RARE)
in the promoter regions of target genes and independently
activating the Ras/PI3K/Rac1 pathway which results incytoskeletal reorganization1-2.

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SMARTvector shRNA Lentiviral platform: Elucidating the role of factors important in neurite outgrowth.

A

B

Figure 5: Neurite Outgrowth in Cells Treated with ATRA for Nine Days Post-Transduction. A. In ATRA-treated cells (10 µM), neurite outgrowthparameters measured with Cellomics Neuronal Profiling BioApplication (Mean Neurite Count, Mean Neurite Average Length, Mean Branchpoint
Average Count and Mean Branchpoint Average Distance from the Cell Body) are shown for gene targets SRC, RAC1, CSK and RHOA. Data
was normalized to SMARTvector Non-targeting Control treated under similar conditions. B. Representative micrographs of SH-SY5Y cells
transduced with SMARTvector constructs. Cells were stained with Neurite Outgrowth HitKit (red) and Hoechst 33342 (blue).

Rho-GTPases are able to modulate both the cytoskeleton
and transcriptional activation of target genes5. For example,
Rac1 activity leads to actin depolymerization andlamellipodia outgrowth essential for neuritogenesis.
In addition to cytoskeletal reorganization, interaction ofRac1 with Map3k1 activates the Mapk pathway leading totranscription of neuronal genes. In contrast, RhoA activity
results in stress fiber formation and focal adhesions
that hinder neuritogenesis. Long-term knockdown of
RHOA and RAC1 in SH-SY5Y cells with the SMARTvector
shRNA Lentiviral Particles resulted in measurable andquantifiable effects on neurite outgrowth. Silencing of
RHOA enhanced neurite outgrowth, while depletion
Figure 6: Retinoic Acid Signaling Pathway

of RAC1 inhibited the ability of the cells to generate
and maintain neurites even in the presence of ATRA.

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SMARTvector shRNA Lentiviral platform: Elucidating the role of factors important in neurite outgrowth.

These results are consistent with recent reports that show
similar effects with overexpression of dominant negative
versions of Rac 1 and RhoA whereas constitutively active

References
1. G. Lopez-Carballo, L. Moreno, Activation of themutants expressed in other cell types demonstrated

Phosphatidylinositol 3- Kinase/Akt Signaling Pathway by

opposing effects .

Retinoic Acid Is Required for Neural Differentiation of

6-7

The RA-RAR complex also interacts with Src, a non‑receptor
tyrosine kinase, to initiate downstream signaling forneuritogenesis4. Chemical inhibitors of Src block

SH-SY5Y Human Neuroblastoma Cells. J. Biol. Chem.
277(28), 25297-25304 (2002).
2. P. LoPresti, W. Poluha, Neuronal differentiation triggered

neurite outgrowth suggesting a key role for this gene inby blocking cell proliferation. Cell Growth Differ. 3(9),neuritogenesis. As expected, when SRC expression was

627‑635 (1992).

silenced in SH-SY5Y cells transduced with SMARTvector
SRC shRNA Particles, ATRA-induced neurite outgrowth
was blocked although to a lesser extent than with RAC1
silencing. The activity of SRC is regulated by CSK (C-terminal
Src Kinase) which phosphorylates and inhibits SRC. CSK
overexpression has been shown to block activation of SRC,
thus inhibiting RA-induced neurite outgrowth4. In this study,
we demonstrated that while expression of CSK can inhibit
neurite outgrowth, silencing of CSK expression has no
significant effect on promoting neuritogenesis indicating a
non-essential role for this member of the pathway.

3. P.L. So, P.K. Yip, Interactions between retinoic acid, nerve
growth factor and sonic hedgehog signalling pathways inneurite outgrowth. Dev. Biol. 298(1), 167-75 (2006).
4. N. Dey, P.K. De, CSK Controls Retinoic Acid Receptor (RAR)
Signaling: a RAR-c-SRC Signaling Axis Is Required for
Neuritogenic Differentiation. Mol. Cell. Biol. 27(11),4179‑4197 (2007).
5. I. de Curtis, Functions of Rac GTPases during neuronaldevelopment. Dev. Neurosci. 30(1-3), 47-58 (2008).
6. E.-E. Govek, S.E. Newey, The role of the Rho GTPases inneuronal development. Genes & Dev. 19(1), 1-49 (2005).

Summary
Potent and long-term knockdown of genes known to be
involved in regulation of neurite outgrowth (RAC1, RHOA,SRC, CSK) was successfully achieved in the difficult-

7. A. Hajdo-Milasinovic, S.I.J. Ellenbroek, Rac1 and Rac3 have
opposing functions in cell adhesion and differentiation ofneuronal cells. J. Cell Sci. 120(4), 555-566 (2007).

to-transfect SH-SY5Y cell line using the SMARTvector
shRNA lentiviral technology. The Neuronal Profiling
BioApplication software and Cellomics™ ArrayScan™
VTI HCS Reader further enabled detailed analysis that
distinguished the phenotypes of neuroblast-like cells fromthe epithelial cells in a mixed population characteristicof SH-SY5Y cells. Moreover, our silencing experiments
resulted in data consistent with the expected activities
of genes known to be important to neurite outgrowth,
further supporting the power of combining these biologicaland detection technologies.

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