Stem Cells International

Stem Cells International / 2016 / Article
Special Issue

Factors Regulating Stem Cell Biology in Development and Disease

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Research Article | Open Access

Volume 2016 |Article ID 9695827 | 13 pages | https://doi.org/10.1155/2016/9695827

Comparative Microarray Analysis of Proliferating and Differentiating Murine ENS Progenitor Cells

Academic Editor: Kodandaramireddy Nalapareddy
Received15 May 2015
Accepted12 Jul 2015
Published30 Nov 2015

Abstract

Postnatal neural progenitor cells of the enteric nervous system are a potential source for future cell replacement therapies of developmental dysplasia like Hirschsprung’s disease. However, little is known about the molecular mechanisms driving the homeostasis and differentiation of this cell pool. In this work, we conducted Affymetrix GeneChip experiments to identify differences in gene regulation between proliferation and early differentiation of enteric neural progenitors from neonatal mice. We detected a total of 1333 regulated genes that were linked to different groups of cellular mechanisms involved in cell cycle, apoptosis, neural proliferation, and differentiation. As expected, we found an augmented inhibition in the gene expression of cell cycle progression as well as an enhanced mRNA expression of neuronal and glial differentiation markers. We further found a marked inactivation of the canonical Wnt pathway after the induction of cellular differentiation. Taken together, these data demonstrate the various molecular mechanisms taking place during the proliferation and early differentiation of enteric neural progenitor cells.

1. Introduction

The enteric nervous system (ENS) is a largely autonomous and highly complex neuronal network found in the gastrointestinal tract. Its two major plexuses are integrated into the layered anatomy of the gut wall and, together with central modulating influences, exert control over gastrointestinal motility, secretion, ion-homeostasis, and immunological mechanisms [1]. In order to achieve this variety of functions, the ENS is composed of a multitude of different neuronal and glial cell types and closely interacts with smooth muscle cells and myogenic pacemaker cells called interstitial cells of Cajal. Furthermore, a population of neural stem or progenitor cells in the ENS has been identified in rodents [2, 3] and humans that retain their proliferative capacity throughout adult life even into old age [4, 5]. It is therefore not surprising that the correct functioning of the ENS as well as the regulation on enteric neural progenitor cells is subjected to the influence of a myriad of transmitters, neurotrophic and growth factors, signalling molecules, and extracellular matrix components, which are not exclusively expressed by neural cell types [6]. Likewise, the control of the development of the ENS is equally complex and mutations in its genetic program can lead to fatal dysplasia like Hirschsprung’s disease (HCSR) [7, 8].

HSCR is hallmarked by an aganglionic distal bowel leading to life-threatening disturbances in intestinal motility. Today’s therapeutic gold standard, the surgical resection of the affected gut segments, is nevertheless associated with problematic long-term outcomes with regard to continence [9]. In order to improve the therapeutic success, the use of autologous enteric neural stem cells was proposed [10]. This concept relies on the in vitro expansion of enteric neural stem cells derived from small biopsy materials. However, we are just beginning to understand the molecular mechanisms that underlie neural stem cell biology and how this knowledge can be used for optimizing in vitro culture conditions [11, 12].

Genome-wide gene-expression analyses are a useful tool to examine the genetic programs and cellular interactions and have been widely used to identify potential markers or signalling mechanisms especially in CNS neurospheres or cancer tissues. Further, gene-expression assays have also helped to unravel genetic prepositions associated with HSCR [13, 14], though little effort has so far been put into characterizing the genetic profile of enteric neural stem cells in vitro [15].

Here, we used an Affymetrix microarray analysis to evaluate the genetic expression profile of proliferating murine enteric neural stem cells and its changes during the early differentiation in vitro.

2. Materials and Methods

2.1. Cell Culturing

Cell culturing was conducted as described previously [15]. The handling of animals was in accordance to the institutional guidelines of the University of Tuebingen, which conform to the international guidelines.

Neonatal (P0) C57BL/6 mice without regard to sex were decapitated and the whole gut was removed. After removal of adherent mesentery the longitudinal and circular muscle layers containing myenteric plexus could be stripped as a whole from the small intestine. Tissue was chopped and incubated in collagenase type XI (750 U/mL; Sigma-Aldrich, Taufkirchen, Germany) and dispase II (250 μg/mL; Roche Diagnostics, Mannheim, Germany) dissolved in Hanks’ balanced salt solution with Ca2+/Mg2+ (HBSS; PAA, Pasching, Austria) for 30 min at 37°C. During enzymatic dissociation the tissue was carefully triturated every 10 min with a fire polished 1 mL pipette tip. Prior to the first trituration step, cell suspension was treated with 0.05% (w/v) DNAse I (Sigma-Aldrich). After 30 min, tissue dissociation was stopped by adding fetal calf serum (FCS; PAA) to a final concentration of 10% (v/v) to the medium. Undigested larger tissue pieces were removed with a 40 μm cell strainer (BD Biosciences, Franklin Lakes, NJ, USA). Residual enzymes were removed during two washing steps in HBSS at 200 g. After dissociation, cells were resuspended in proliferation culture medium (Dulbecco’s modified Eagle’s medium with Ham’s F12 medium (DMEM/F12; 1 : 1; PAA)) containing N2 supplement (1 : 100; Invitrogen, Darmstadt, Germany), penicillin (100 U/mL; PAA), streptomycin (100 μg/mL; PAA), L-glutamine (2 mM; PAA), epidermal growth factor (EGF; 20 ng/mL; Sigma-Aldrich), and fibroblast growth factor (FGF; 20 ng/mL; Sigma-Aldrich). Cells were seeded into 6-well plates (BD Biosciences) in a concentration of 2.5 × 104 cells/cm2. Only once before seeding, the medium was supplemented with B27 (1 : 50; Invitrogen). EGF and FGF were added daily and culture medium was exchanged every 3 days. All cultivation steps were conducted in a humidified incubator at 37°C and 5% CO2. An overview of the following cell culture protocol is shown in Figure 1. During proliferation phase of the culture, cells formed spheroid-like bodies termed enterospheres. After 5 days of proliferation, free-floating enterospheres were picked and transferred to petri dishes (Ø 60 mm; Greiner Bio One, Frickenhausen, Germany) in 5 mL fresh proliferation medium and proliferation was continued for further 4 days.

Single free-floating enterospheres (50 enterospheres/dish) were picked again, washed 3 times in Tris buffer, and transferred into new petri dishes containing either proliferation medium or differentiation medium. Differentiation medium consists of DMEM/F12 containing N2 supplement (1 : 100), penicillin (100 U/mL), streptomycin (100 μg/mL), L-glutamine (2 mM), and ascorbic acid-2-phosphate (200 μM; Sigma-Aldrich).

Enterospheres were proliferated or differentiated for 2 more days, thereby forming the two experimental groups “proliferation” and “differentiation.” The difference in expression between those two groups (differentiation versus proliferation) was successively compared by microarray analysis as described below.

2.2. Affymetrix Microarray Analysis

Affymetrix microarray analysis was conducted similar to previously published data in three independent experiments, each with cell cultures prepared from 2 pups from the same litter [15]. In each experiment, free-floating enterospheres were picked as described above in order to diminish the fraction of adhesive fibroblasts and smooth muscle cells.

Total RNA of enterospheres of both groups was extracted using the RNeasy Micro Kit (Qiagen). RNA quality was evaluated on Agilent 2100 Bioanalyzer with RNA integrity numbers (RIN) of the samples in this study being in the range from 8 to 10. RIN numbers higher than 8 are considered optimal for downstream application [16].

Double-stranded cDNA was synthesized from 100 ng of total RNA, subsequently linearly amplified, and biotinylated using the GeneChip WT cDNA Synthesis and Amplification Kit (Affymetrix, Santa Clara, CA, USA) according to the manufacturer’s instructions. 15 μg of labeled and fragmented cDNA was hybridized to GeneChip Mouse Gene 1.0 ST arrays (Affymetrix). After hybridization, the arrays were stained and washed in a Fluidics Station 450 (Affymetrix) with the recommended washing procedure. Biotinylated cDNA bound to target molecules was detected with streptavidin-coupled phycoerythrin, biotinylated anti-streptavidin IgG antibodies and again streptavidin-coupled phycoerythrin according to the protocol. Arrays were scanned using the GCS3000 GeneChip Scanner (Affymetrix) and AGCC 3.0 software. Scanned images were subjected to visual inspection to check for hybridization artifacts and proper grid alignment and analyzed with Expression Console 1.0 (Affymetrix) to generate report files for quality control.

Normalization of raw data was performed by the Partek Software 6.6, applying an RMA (Robust Multichip Average) algorithm. Significance was calculated using a -test without multiple testing correction (Partek), selecting all transcripts with a minimum change in expression level of 1.5-fold together with a value less than 0.05.

3. Results

In this study, we investigated the changes of the genetic expression profile that occur during the transition from proliferating to differentiating enteric neural progenitor cells in vitro. Therefore, we generated enterospheres by 9 day in vitro cultures, which then could be picked and either proliferated or differentiated for two more days (Figure 1). mRNA was subsequently extracted and gene expression of these two groups was analysed by Affymetrix microarray analysis.

Analysis of mRNA expression was performed on a GeneChip Mouse Gene 1.0 ST array that determines the expression profile of 28.853 genes. Each gene was interrogated by a median of 27 probes that are spread along the full gene.

In total, the gene chip detected 1454 transcripts to be at least 1.5-fold differentially expressed between proliferating and differentiating enterospheres. 1333 of these transcripts code for already identified proteins. 541 genes were found to be upregulated and 792 genes were found to be downregulated in comparison to proliferating enterospheres (see Supplementary Table of the Supplementary Material available online at http://dx.doi.org/10.1155/2016/9695827).

We used the ingenuity pathway analysis software (IPA) and data mining with the science literature search engine http://www.ncbi.nlm.nih.gov/pubmed/ to divide the genes into different groups according to their function during cellular development. The largest functional group contained 171 genes related to cell cycle and apoptosis (Table 1, Supplementary Table ). Here, we identified especially different cyclin proteins and cell division cycle proteins that were mainly downregulated. Further, we found several genes that are linked to neural development as well as genes regulating neural stem cell proliferation and differentiation. Furthermore, we also detected neuronal and glial differentiation markers and numerous genes involved in synapse formation (Table 2). It is noteworthy that we also identified a group of genes that are known to be involved in the differentiation of smooth muscle cells (Table 3) as well as in extracellular matrix components (Table 4). Additionally, we found regulated genes related to canonical Wnt signalling indicating a deactivation of this pathway during ENS progenitor cell differentiation (Figure 2, Table 5).


GeneEncoded proteinFold changeCell cycle

AURKAAurora kinase A−2.712STOP
AURKBAurora kinase B−4.146STOP
CCNA2Cyclin A2−4.652STOP
CCNB1Cyclin B1−5.752 
−5.820 
−5.857
STOP
CCNB2Cyclin B2−3.392STOP
CCND1Cyclin D1−2.476STOP
CCND3Cyclin D3−1.539STOP
CCNE1Cyclin E1−1.777STOP
CCNE2Cyclin E2−2.847STOP
CCNFCyclin F−3.211STOP
CDC6Cell division cycle 6−1.936STOP
CDC20Cell division cycle 20−3.113STOP
CDC25BCell division cycle 25B−1.636STOP
CDC25CCell division cycle 25C−2.414STOP
CDC45Cell division cycle 45−1.769STOP
CDCA2Cell division cycle associated 2−3.461STOP
CDCA3Cell division cycle associated 3−3.003STOP
CDCA5Cell division cycle associated 5−3.053STOP
CDCA7LCell division cycle associated 7-like−4.123STOP
CDCA8Cell division cycle associated 8−3.467STOP
CDK1Cyclin-dependent kinase 1−3.227STOP
CDK15Cyclin-dependent kinase 151.618GO
CDK19Cyclin-dependent kinase 191.619GO
CDK5R1Cyclin-dependent kinase 5, regulatory subunit 1 (p35)1.597
CENPACentromere protein A−1.895STOP
CENPECentromere protein E, 312 kDa−4.140STOP
CENPFCentromere protein F, 350/400 kDa−3.927STOP
CENPICentromere protein I−2.899STOP
CENPKCentromere protein K−2.813STOP
CENPLCentromere protein L−1.864STOP
CENPMCentromere protein M−3.407STOP
CENPNCentromere protein N−2.465STOP
CENPUCentromere protein U−1.624STOP
SKA1Spindle and kinetochore associated complex subunit 1−1.532STOP
SKA2Spindle and kinetochore associated complex subunit 2−1.582STOP
SKA3Spindle and kinetochore associated complex subunit 3−3.490STOP
SKP2S-phase kinase-associated protein 2, E3 ubiquitin protein ligase−1.845STOP
SPC25SPC25, NDC80 kinetochore complex component−4.148STOP


GeneEncoded proteinFold change

Neural stem cells
ABCG2ATP-binding cassette, subfamily G (WHITE), member 2 (junior blood group)−1.526
ASPMasp (abnormal spindle) homolog, microcephaly associated (Drosophila)−4.911
CDT1Chromatin licensing and DNA replication factor 1−1.528
EGFL7EGF-like-domain, multiple 73.132
EPHA2EPH receptor A2−1.529
ETV4ets variant 4−1.934
ETV5ets variant 5−2.844
−2.651
FABP7Fatty acid binding protein 7, brain−2.095

Neural differentiation
ATOH8Atonal homolog 8 (Drosophila)1.932
AXLAXL receptor tyrosine kinase2.015
CRIM1Cysteine-rich transmembrane BMP regulator 1 (chordin-like)1.999
CRLF1Cytokine receptor-like factor 12.382
DAB1Dab, reelin signal transducer, homolog 1 (Drosophila)−2.297
ELK3ELK3, ETS-domain protein (SRF accessory protein 2)−1.613
ESCO2Establishment of sister chromatid cohesion N-acetyltransferase 2−4.767
GAP43Growth associated protein 431.613
GLDNGliomedin5.809
HMOX1Heme oxygenase (decycling) 11.884
KLF9Kruppel-like factor 91.592
Lmo3LIM domain only 31.542
MAP6Microtubule-associated protein 61.874
MYRFMyelin regulatory factor2.527
NEUROD4Neuronal differentiation 42.036
OLIG1Oligodendrocyte transcription factor 12.660
PvrPoliovirus receptor1.768
RGS4Regulator of G-protein signaling 41.955
S1PR1Sphingosine-1-phosphate receptor 15.073
SOCS2Suppressor of cytokine signaling 22.052
2.335
WIPF1WAS/WASL interacting protein family, member 11.587

Neural differentiation markers
CALB2Calbindin 21.616
CNP2′,3′-Cyclic nucleotide 3′-phosphodiesterase1.732
GFAPGlial fibrillary acidic protein2.239
MBPMyelin basic protein1.768
MturnMaturin, neural progenitor differentiation regulator homolog (Xenopus)1.853
OMGOligodendrocyte myelin glycoprotein−1.822
OPALINOligodendrocytic myelin paranodal and inner loop protein39.246
PLP1Proteolipid protein 11.630
S100BS100 calcium binding protein B−1.675
TUBB2ATubulin, beta 2A class IIa1.608
TUBB2BTubulin, beta 2B class IIb1.535
TUBB3Tubulin, beta 3 class III1.976

Synapse and neurotransmitters
ABAT4-Aminobutyrate aminotransferase−1.512
ADRA1DAdrenoceptor alpha 1D1.803
ADRA2AAdrenoceptor alpha 2A2.900
ADRA2BAdrenoceptor alpha 2B−2.093
CHRM2Cholinergic receptor, muscarinic 21.635
CHRM3Cholinergic receptor, muscarinic 3−1.715
CHRNA7Cholinergic receptor, nicotinic, alpha 7 (neuronal)1.772
COMTCatechol-O-methyltransferase1.515
DDCDOPA decarboxylase (aromatic L-amino acid decarboxylase)1.711
DNM3Dynamin 32.643
EPHA5EPH receptor A52.076
GRIA3Glutamate receptor, ionotropic, AMPA 3−1.528
GRIA4Glutamate receptor, ionotropic, AMPA 4−1.997
GRIK2Glutamate receptor, ionotropic, kainate 2−1.565
GRM5Glutamate receptor, metabotropic 5−1.600
HTR1B5-Hydroxytryptamine (serotonin) receptor 1B, G-protein-coupled−2.377
HTR2B5-Hydroxytryptamine (serotonin) receptor 2B, G-protein-coupled2.205
LRRTM2Leucine-rich repeat transmembrane neuronal 23.665
LRRTM3Leucine-rich repeat transmembrane neuronal 32.210
NTMNeurotrimin1.820
PENKProenkephalin3.478
PRR7Proline rich 7 (synaptic)1.788
SLC10A4Solute carrier family 10, member 41.824
1.867
SLITRK2SLIT and NTRK-like family, member 2−2.414
SLITRK6SLIT and NTRK-like family, member 61.672
STON2Stonin 24.054
STXBP3Syntaxin-binding protein 31.730
Stxbp3bSyntaxin-binding protein 3B1.637
SV2CSynaptic vesicle glycoprotein 2C1.929
SYT6Synaptotagmin VI2.571

Neurite outgrowth
ATF3Activating transcription factor 32.579
DOK4Docking protein 44.937
FEZ2Fasciculation and elongation protein zeta 2 (zygin II)1.547
NAV2Neuron navigator 21.647
NRCAMNeuronal cell adhesion molecule2.496
PLXNB3Plexin B31.739
RGMARepulsive guidance molecule family member a1.552
RNF165Ring finger protein 165−1.548
ROBO2Roundabout, axon guidance receptor, homolog 2 (Drosophila)−2.211
SEMA3BSema domain, immunoglobulin domain (Ig), short basic domain, secreted (semaphorin) 3B3.692
SEMA3ESema domain, immunoglobulin domain (Ig), short basic domain, secreted (semaphorin) 3E2.877
SEMA4FSema domain, immunoglobulin domain (Ig), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 4F4.891
SEMA6ASema domain, transmembrane domain (TM), and cytoplasmic domain (semaphorin) 6A−1.707
SRGAP1SLIT-ROBO Rho GTPase activating protein 11.524
UNC5Bunc-5 homolog B (C. elegans)−1.927

Growth factors
ARTNArtemin2.423
FGF2Fibroblast growth factor 2 (basic)2.264
FGF5Fibroblast growth factor 57.704
GDF10Growth differentiation factor 10−2.361
GDF11Growth differentiation factor 111.604
GDNFGlial cell derived neurotrophic factor4.325
GFRA3GDNF family receptor alpha 31.707
METMET protooncogene, receptor tyrosine kinase6.680
NGFRNerve growth factor receptor1.728
NTRK3Neurotrophic tyrosine kinase, receptor, type 3−1.575
SNX16Sorting nexin 161.641
SPHK1Sphingosine kinase 11.704
SPRY1Sprouty homolog 1, antagonist of FGF signaling (Drosophila)−1.647


GeneEncoded proteinFold change

Smooth muscle cells
ACTA2Actin, alpha 2, smooth muscle, aorta1.693
ACTG2Actin, gamma 2, smooth muscle, enteric2.336
ACTN1Actinin, alpha 1−1.724
AEBP1AE binding protein 12.702
AFAP1Actin filament associated protein 11.638
ARID5BAT-rich interactive domain 5B (MRF1-like)1.521
Cald1Caldesmon 1−1.535
CNN1Calponin 1, basic, smooth muscle1.652
ENGEndoglin−1.552
ENPP1Ectonucleotide pyrophosphatase/phosphodiesterase 1−1.522
ENPP2Ectonucleotide pyrophosphatase/phosphodiesterase 22.959
ENTPD1Ectonucleoside triphosphate diphosphohydrolase 11.636
FOSL2FOS-like antigen 22.566
GAMTGuanidinoacetate N-methyltransferase1.725
MYO1EMyosin IE1.569
MYO5AMyosin VA (heavy chain 12, myoxin)1.680
MYO7BMyosin VIIB1.710
MYO18AMyosin XVIIIA1.994
MYPNMyopalladin1.570
NEBNebulin1.569
NeblNebulette2.378
NUP210Nucleoporin 210 kDa−1.838
RBM24RNA binding motif protein 241.548
SMTNSmoothelin−1.778
SSPNSarcospan1.603
TAGLNTransgelin2.706

ICC
GUCY1A3Guanylate cyclase 1, soluble, alpha 3−1.876
GUCY1B3Guanylate cyclase 1, soluble, beta 3−2.008
KITv-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog−1.798
KITLGKIT ligand−1.541


GeneEncoded proteinFold change

CHSY3Chondroitin sulfate synthase 3−1.645
COL6A5Collagen, type VI, alpha 51.527
COL12A1Collagen, type XII, alpha 1−1.973
COL14A1Collagen, type XIV, alpha 16.135
COL16A1Collagen, type XVI, alpha 11.666
COL18A1Collagen, type XVIII, alpha 11.595
COL27A1Collagen, type XXVII, alpha 11.522
COLGALT2Collagen beta(1-O)galactosyltransferase 2−1.564
CSPG4Chondroitin sulfate proteoglycan 4−2.952
CSPG5Chondroitin sulfate proteoglycan 5 (neuroglycan C)−1.585
CYR61Cysteine-rich, angiogenic inducer, 611.748
ECM1Extracellular matrix protein 12.580
HSPG2Heparan sulfate proteoglycan 21.923
ITGA1Integrin, alpha 1−1.665
ITGA4Integrin, alpha 4 (antigen CD49D, alpha 4 subunit of VLA-4 receptor)−2.324
ITGA7Integrin, alpha 74.203
ITGA8Integrin, alpha 8−2.262
ITGA11Integrin, alpha 111.762
ITGB3Integrin, beta 3 (platelet glycoprotein IIIa, antigen CD61)−5.342
ITGB4Integrin, beta 41.567
KRT80Keratin 802.833
LAMA4Laminin, alpha 4−1.537
LAMA5Laminin, alpha 51.684
LOXLysyl oxidase3.250
LOXL4Lysyl oxidase-like 42.427
2.417
MATN2Matrilin 22.570
MMP2Matrix metallopeptidase 2 (gelatinase A, 72 kDa gelatinase, 72 kDa type IV collagenase)1.668
MMP9Matrix metallopeptidase 9 (gelatinase B, 92 kDa gelatinase, 92 kDa type IV collagenase)−5.557
MMP15Matrix metallopeptidase 15 (membrane-inserted)−2.017
MMP16Matrix metallopeptidase 16 (membrane-inserted)−1.634
MMP17Matrix metallopeptidase 17 (membrane-inserted)1.612
MMP19Matrix metallopeptidase 193.236
MMP28Matrix metallopeptidase 281.956
NDST3N-deacetylase/N-sulfotransferase (heparan glucosaminyl) 3−5.557
P4HA1Prolyl 4-hydroxylase, alpha polypeptide I−1.958
PLOD3Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 32.250
UGDHUDP-glucose 6-dehydrogenase1.529


GeneEncoded proteinFold change

Wnt signaling cascade
FZD7Frizzled class receptor 7−2.271
LEF1Lymphoid enhancer-binding factor 1−2.680
LRP5Low density lipoprotein receptor-related protein 5−1.571
LRRK2Leucine-rich repeat kinase 21.677
TCF19Transcription factor 19−2.217
F7L1Transcription factor 7-like 1 (T-cell specific, HMG-box)−1.762
WNT5AWingless-type MMTV integration site family, member 5A−2.325
WNT7BWingless-type MMTV integration site family, member 7B2.942

Target gene
ARL4CADP-ribosylation factor-like 4C2.179
AXIN2Axin 21.744
CCND1Cyclin D1−2.476
CSRNP1Cysteine-serine-rich nuclear protein 11.822
RACGAP1Rac GTPase activating protein 1−3.201
SPRY2Sprouty homolog 2 (Drosophila) −1.771
SPRY4Sprouty homolog 4 (Drosophila)−2.771
WISP1WNT1 inducible signaling pathway protein 12.489

Wnt antagonists/inhibitors
APOEApolipoprotein E1.704
DKK2Dickkopf WNT signaling pathway inhibitor 21.731
EDIL3EGF-like repeats and discoidin I-like domains 32.258
FRZBFrizzled-related protein1.938
HIC1Hypermethylated in cancer 1−1.731
JADE1Jade family PHD finger 1−1.656
LRP4Low density lipoprotein receptor-related protein 41.979
NARFNuclear prelamin A recognition factor−1.699
NEDD4LNeural precursor cell expressed, developmentally downregulated 4-like, E3 ubiquitin protein ligase1.588
NKD1Naked cuticle homolog 1 (Drosophila)3.220
NOTUMNotum pectinacetylesterase homolog (Drosophila)2.631
NOVNephroblastoma overexpressed2.050
PRICKLE1Prickle homolog 1 (Drosophila)1.536
TLE3Transducin-like enhancer of split 31.714
TRIB2Tribbles pseudokinase 2−1.637

Wnt activators
DAAM2Dishevelled associated activator of morphogenesis 2−1.993
PSRC1Proline/serine-rich coiled-coil 1−2.235
TNIKTRAF2 and NCK interacting kinase1.677
TRAF4TNF receptor-associated factor 4−1.673

4. Discussion

The proliferation and differentiation of enteric neural progenitor cells during embryonic and postnatal development are controlled by a complex interplay of various intrinsic and extrinsic factors. Their exact timing is crucial for proper migration and proliferation of neural crest cells and for their differentiation into the various neural cell types that compose the complex neural structures of the ENS. Although research in recent years extended our understanding of ENS development and its pathologies [13], there are still many genes and processes unknown. Particularly, factors regulating neural progenitor proliferation and differentiation in the developing and postnatal gut as well as cellular and molecular interaction systems remain largely elusive. Here, we used in vitro cultures of enteric neural progenitor cells derived from murine tunica muscularis to scan for molecular programs and signalling pathways acting on cell proliferation and early differentiation.

Our experiment aimed to elucidate gene regulations in enterospheres that occur while ENS progenitor cells leave their proliferative state and begin to differentiate into more defined and specific cell types. The results of the Affymetrix gene expression analysis showed the up- and downregulation of overall 1333 known genes that code for already identified proteins. 171 of these genes could be linked to cell proliferation (Table 1, Supplementary Table ). Amongst them we detected genes coding for proteins related to the kinetochore complex (like NSL1 [17], NUF2 [18], SKA1-3 [19], and ZWILCH [20]), cyclin proteins [21], cyclin-dependent kinases (CDK) [22], and several types of centromere proteins. The regulation of 145 of these genes strongly indicates a slowdown of cell cycle progression as it was intended by the experimental deprivation of growth factor supplementation by the end of the proliferation phase (see Section 3). Interestingly, betacellulin (BTC) was upregulated nearly 6-fold although it was reported to promote cellular proliferation in the neural stem cell niche [23]. Nonetheless, the vast majority of genes including all regulated cyclins, cell division cycle proteins, and kinetochore proteins were found to be downregulated.

We also checked the regulated genes for apoptosis markers to see whether the stop in proliferation was related to cell death (Supplementary Table ). Since only 3 of 12 apoptotic genes were regulated in the direction that indicates apoptosis, it is unlikely that apoptosis played a leading role in the interruption of proliferation. Still, the effect and regulation of apoptosis during enteric sphere cultures are an important cornerstone of understanding enteric neural progenitors in culture and in vivo and require further investigation. Together, on a broad basis, this dataset provides strong evidence that this cell culture design is applicable to decreasing the proliferative rate of enteric neural progenitor cells without inducing cell death or apoptosis in an appreciable quantity.

To further evaluate the proliferative conditions of cell types present in enterospheres, we focused on different cell specific markers of neural progenitors as well as neurons, glial, or smooth muscle cells. We consider this complex cellular composition of the enterospheres an advantage compared to more purified neural crest derived neurospheres as we are able to capture complex interactions and secretion mechanisms between cell types that might also play an important role in vivo. Interestingly, we found 8 genes involved in adult central or embryonic neural stem cells homeostasis (Table 2). The majority of genes like EPHA2 [24] are regulated in a way that suggests that neural stem cells exit the proliferative cell cycle to enter differentiation programs. This idea was supported by the upregulation of numerous genes that drive neuronal and glial differentiation like NEUROD4 [25] or OLIG1 [26]. In this context, we identified several upregulated genes involved in proper myelination. As enteric and central glia cells are known to temporally express myelin-related proteins during development, it is conceivable that this regulation is part of the early glial differentiation program [27]. Moreover, also typical markers of differentiated neurons (class III beta-tubulin, CALB2 [28]) and enteric glia (GFAP [29]) were found to be upregulated. Intriguingly, S100B, a common glia cell marker, was downregulated contrasting the rest of our data. Again, this might be due to the complex differentiation program of enteric glia, in which S100B plays a role at later stages.

Furthermore, the establishment of neuronal cell communication was strongly regulated. Here, we found an increased expression of genes related to synaptogenesis (LRRTM2 and 3 [30], neurotrimin [31]) and to SNARE or vesicle protein function (STXBP3, SV2C [32], and SYT6 [33]). We also identified a number of genes involved in transmitter metabolism (COMT, DDC) as well as neurotransmitter receptor like 5-HT, glutamate, and adrenergic receptors. However, the regulation of those genes was highly variable shedding light on the intricacy of synapse formation in the developing enteric nervous system. This complexity is carried on by genes related to axon sprouting and guidance like semaphorins [34] or RGMa [35].

Additionally, we found that regulated genes directly involved in the differentiation of muscle cells and/or enteric pacemaker cells called interstitial cells of Cajal (Table 3). Particularly interesting is the upregulation of a number of genes known to drive smooth muscle differentiation like ARID5B [36], FOSL2 [36] and genes that are expressed in differentiated smooth muscle cells in the intestine like AFAP1 [37], ENPP2 [38], and CNN1 [39] as well as various myosin and actin isoforms. These data confirm the fact that cultured spheroids are composed of different cell types present in the intestinal tunica muscularis and further indicate that deprivation of growth factors induces differentiation of smooth muscle cells resembling molecular processes in the developing gut. In fact, we among others were previously able to confirm the presence of smooth muscle cells derived from enterosphere culture by BrdU-immunolabeling costudies [4]. However, it is noteworthy that a few genes related to muscular differentiation (endoglin [40], smoothelin [41], NUP210 [42], caldesmon 1 [43], and ACTN1 [44]) were downregulated contrasting the expression pattern observed in the majority of regulated genes. This hints to complex regulatory mechanisms controlling the myogenic differentiation program in which these genes are not required at all or in a different temporal sequence not mapped by our experimental design. It is further remarkable that five markers expressed in interstitial cells of Cajal (ICC) including KIT [45] were downregulated.

Moreover, the regulation of 43 extracellular matrix proteins like collagens, integrins, proteoglycans, and matrix metallopeptidases points to a reconstruction of extracellular environment that has been discussed to influence neural stem cell behaviour [46] (Table 4). Taken together, these results illustrate the ongoing genetic programs during early differentiation of enterospheres.

Within the dataset, it was of special interest to find particularly many regulated genes related to the canonical Wnt pathway (Table 5). The involvement of canonical Wnt signalling has frequently been shown in the regulation of various stem cell niches, like intestinal epithelium or CNS derived neural stem cells. However, these studies exhibited different and partly contradicting outcomes, which strongly hint to the variable functions of canonical Wnt signals in different tissues during embryonic and postnatal development. In previous work, we found regulation of several Wnt-related genes in the context of thyroid hormone dependent differentiation of enteric neural progenitor cells indicating a potential role of the canonical Wnt pathway activation during the proliferation of this progenitor cell pool [15]. Canonical Wnt signalling has frequently been reviewed in the literature—just recently by Ring et al. [47]. In brief, secreted Wnt proteins bind to frizzled receptors (FZD) complexed with low density lipoprotein receptor-related protein 5/6 (LRP5/6) coreceptors. Thereafter, the scaffolding protein disheveled (DVL) is recruited to FZD and inhibits the β-catenin destruction complex (AXIN2, APC, and GSK-3β). Therefore, β-catenin accumulates in the cytoplasm and translocates to the nucleus where it binds to TCF/LEF transcription factors to initiate Wnt target gene expression. Interestingly, our current data strongly indicate that the canonical Wnt pathway is switched off during the first two days of enteric progenitor differentiation on several levels of the signalling cascade (Figure 2). On the one hand we identified a downregulation of activating parts of the signalling cascade itself like the receptor proteins FZD7 and LRP5 or the transcription factors TCF19, TCF7L1, and LEF1. On the other hand, inactivating elements of the pathway like parts of the β-catenin destruction complex AXIN2 and LRRK2 [48] were upregulated. We also found numerous modulators of the signalling cascade. It is of interest that the majority of those genes are reported to inhibit the signalling process extracellularly or on receptor level (Notum [49], FRZB [50], DKK2 [51], and LRP4 [52]), in the cytoplasm (NEDD4L [53], NKD1 [54], PRICKLE1 [55], NOV [56], and APOE [57]), or in the nucleus (TLE3 [58], EDIL3 [59]). Furthermore, we identified target genes of the canonical Wnt pathway that were either upregulated (e.g., AXIN2 that exerts a negative feedback on the pathway) or downregulated like the cell cycle progression genes CCND1 and SPRY4 [60]. We also found a lower expression of SPRY2 [61], a Wnt target gene and known inhibitor of GDNF signalling [62], in the differentiation group. Together with a strong upregulation of GDNF itself by 4.325-fold, this might drive enteric progenitor cells into neural differentiation [12].

Taken together, it is conceivable that canonical Wnt signalling plays a role in the maintenance of the enteric progenitor pool during proliferation and is switched off at the beginning of differentiation conditions. Indeed, our previous gene expression analyses [15] as well as recently published cell culture experiments [63] and yet unpublished in vitro analyses strongly support this hypothesis.

5. Conclusion

This study focused on the changes in gene expression of enteric neural progenitor cells occurring within the first two days of transition from a proliferative state to differentiation in vitro. Using microarray analysis, we found a marked inhibition of cell cycle progression in general as well as strong evidence for neural stem cells differentiation into enteric neurons and glia cells. These findings were substantiated by the upregulation of genes related to synapse formation and neural connectivity. Most interesting, we found that this transition from enteric neural progenitor proliferation to differentiation was accompanied by a considerable inactivation of the canonical Wnt signalling pathway. This, together with previous work, strongly indicates that canonical Wnt activation is one of the driving mechanisms of enteric neural progenitor proliferation and thus might play a role in the homeostasis of this cell pool in vivo and in vitro.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Authors’ Contribution

Peter Helmut Neckel and Roland Mohr contributed equally to this work.

Acknowledgments

The project was supported by a grant from the German Federal Ministry for Education and Research (01GN0967). The authors would like to thank Andrea Wizenmann, Andreas Mack, and Sven Poths for their helpful advice.

Supplementary Materials

The supplementary material contains tables with additional information about the gene expression analysis.

  1. Supplementary Material

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