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RESEARC H ARTIC L E Open Access
MicroRNAs coordinately regulate protein
complexes
Steffen Sass
1†
, Sabine Dietmann
1,2†
, Ulrike Burk
3†
, Simone Brabletz
3†
, Dominik Lutter
1
, Andreas Kowarsch
1
,
Klaus F Mayer
1
, Thomas Brabletz
3
, Andreas Ruepp
1
, Fabian Theis
1*
and Yu Wang
1,4*
Abstract
Background: In animals, microRNAs (miRNAs) regulate the protein synthesis of their target messenger RNAs
(mRNAs) by either translational repression or deadenylation. miRNAs are frequently found to be co-expressed in
different tissues and cell types, while some form polycistronic clusters on genomes. Interactions between targets of
co-expressed miRNAs (including miRNA clusters) have not yet been systematically investigated.
Results: Here we integrated information from predicted and experimentally verified miRNA targets to characterize
protein complex networks regulated by human miRNAs. We found striking evidence that individual miRNAs or co-
expressed miRNAs frequently target several components of protein complexes. We experimentally verified that the
miR-141-200c cluster targets different components of the CtBP/ZEB complex, suggesting a potential orchestrated
regulation in epithelial to mesenchymal transition.
Conclusions: Our findings indicate a coordinate posttranscriptional regulation of protein complexes by miRNAs.
These provide a sound basis for designing experiments to study miRNA function at a systems level.
Background
Hundreds of microRNA (miRNA) genes have been iden-
tified in mammalian genomes [1]. Each miRNA may
repress the translation of, and/or destabilize numerous
messenger RNAs (mRNAs). Moreover, miRNA genes
are frequently organized into genomic clusters [2-4],
which are transcribed from a common promoter as
polycistronic primary transcripts, and whose coordinate
functional roles remain to be investigated [5]. Recent
large-scale, quantitative proteomics studies have demon-
strated that some miRNAs probably participate in fine-
tuning the production of their targets, both at the mes-
senger RNA and the protein level [6,7]. However, the
overall effect of miRNAs on many of their target pro-
teins is often intriguingly modest. It remains unclear
how these marginal effects can convey the necessary
regulatory information for proper cellular activities [8].
We applied a network-based strategy to systematically
map coordinate regulatory interactions of single and co-
expressed (including clustered) miRNAs. Previous works
[9-12] have demonstrated that the targets of single miR-
NAs are more connected in the protein-protein interac-
tion network than expected by chance. The use of
protein-protein interaction (PPI) data provides only a
rough overall picture of miRNA target interactions. It is
not easy to evaluate the regulatory effects of miRNAs
on such large-scaled PPI networks. Instead, as the basic
functional units of the cellular machinery, experimen-
tally verified protein complexes are natural subsets of
PPI networks for investigating miRNA target interac-
tions. Several components of protein complexes may be
regulated simultaneously by a single miRNA or by sev-
eral co-expressed miRNAs. Thus, although the regula-
tion of protein synthesis is marginal for some of the
miRNA targets, a cumulative effect for substantial phe-
notypic consequence may be achieved for those targets,
which are members of the same protein complexes.
To test this hypothesis, we developed a robust compu-
tational framework to select protein complexes, of which
several distinct components are simultaneously regu-
lated by either single miRNAs or co-expressed miRNAs.
* Correspondence: fabian.theis@helmholtz-muenchen.de; yu.
wang@helmholtz-muenchen.de
†Contributed equally
1
MIPS, Institute for Bioinformatics and System Biology, Helmholtz Center
Munich, German Research Center for Environmental Health, Ingolstädter
Landstraße 1, D-85764 Neuherberg, Germany
Full list of author information is available at the end of the article
Sass et al.BMC Systems Biology 2011, 5:136
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© 2011 Sass et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution L icense (http://creati vecommons.org/licenses/by/2.0), which perm its unrestricted use, di stribution, and reproduction in
any medium, provided the original work is properly cited.
We applied the framework to characterize the protein
complex networks, which consist of 722 experimentally
verified protein complexes and protein-protein interac-
tions. These protein complex networks are regulated by
677 miRNAs and 154 known miRNA clusters in
humans. We find that our framework has several advan-
tages over previous analyses of miRNA targets and their
interactions. First, high-confidence miRNA target pre-
dictions allowed us to characterize the overall functional
spectrum of miRNA-regulated protein complexes. Sec-
ond, we demonstrated that miRNAs, which target the
same protein complexes, are frequently co-expressed.
Finally, we experimentally verified that the miR141-200c
cluster simultaneously targets several protein compo-
nents of the CtBP/ZEB complex, implying an efficient
regulation of a protein complex by a cluster of miRNAs.
Methods
miRNA targets and target interaction networks
Recent studies showed a high reliability of miRNA tar-
gets predicted by TargetScan [7]. Therefore we selected
the targets for all human miRNAs listed in the TargetS-
can database. We obtained a set of 677 miRNAs and
18,880 unique target proteins. The resulting miRNA-
protein network contained 224,316 interactions. To pre-
dict miRNA targets based on PAR-CLIP data, the cross-
link-centered regions (CCRs) from combined AGO-
PAR-CLIP libraries [13] were used. Target site predic-
tion for all CCRs was done with the program RNAhy-
brid [14] with the default parameters. From the
resulting list we filtered all predictions with a p-value
below 0.02 and an energy score below the 25% quantlile.
This resulted in a final miRNA- mRNA list of 50,160
predicted interactions.
Association of protein complexes with miRNA target sets
- test for statistical significance
We used the Fisher’s exact test for assigning the sig-
nificance of the association with protein complexes
for each miRNA target set. The hypergeometric P-
value is given as the probability under which we
could expect at least N
c
miRNA targets by chance in
a protein complex, if we randomly select N
t
(total
number of miRNA targets) proteins out of the total
set of proteins N consisting of all miRNA targets N
T
and all proteins in complexes N
C
.P-valueswerecor-
rected for multiple testing of 677 miRNAs using the
Holm-Bonferroni correction method. We assigned
the association of complexes and miRNA clusters by
using the union of targets from all miRNAs within
one cluster. Here, we tested for significant overlaps
of these unified sets between the components of a
complex in the same way as for single miRNA target
sets.
Enrichment of biological processes
In order to test for significantenrichmentofbiological
functions based on Gene Ontology (GO) [15] and
KEGG [16] pathways within the set of targets in protein
complexes, the R package GOstats [17] was used. A set
of targeted components of 722 targeted protein com-
plexes was extracted and compared to a set of proteins
which consisted of all components of these complexes.
Comparison of fold change distributions
We used fold change measurements after over-expres-
sion of selected miRNAs from recent proteomics studies
[6,7]. We selected for every of these miRNAs the protein
complexes consisting of at least one of its targets. A set
of components of these protein complexes was built.
Within this set, we compared the fold changes of com-
ponents that are targets of the specific miRNA with the
fold changes of the non-target components. This was
done by performing a one sided Kolmogorov-Smirnov
test for each of the miRNAs that were investigated in
the proteomics studies.
Cell culture
PANC-1 cells were purchased from ATCC (Manassas,
VA, USA). PANC-1 stable clones for miR-141 or miR-
200c were obtained with sequence verified pRetroSuper-
miRNA plasmids. Cell lines were cultivated under stan-
dard conditions in DMEM + 10% fetal bovine serum +
2μg/ml puromycin. For transient knock down PANC-1
were transfected with siRNA targeting ZEB1 (r(aga uga
uga aug cga guc g)d(TT)), CtBP2 (1: r(cuuuggauucagc-
gucaua)d(TT), 2: r(cuuuguaacugauucugga)d(TT)) or
GFP (r(gcu acc ugu ucc aug gcc a)d(TT). All transfec-
tions and reporter assays were performed as described
previously [18].
Specific assay for miRNA modulation
RNA from cultured cells was extracted using the mir-
Vana™miRNA Isolation Kit (Ambion, Austin, TX,
USA). mRNA expression values were measured in tripli-
cate using the Roche LightCycler 480 and normalized to
b-actin expression as a housekeeping control. Expression
values were calculated according to ref.[19].
Immunoblots
were performed using modified standard protocols. In
brief, whole cell extracts were made of the cells in Tri-
ple Lysis Buffer [50 mM Tris-HCl pH8, 150 mM NaCl,
0,02% (w/v) NaN
3
,0,5%(w/v)NaDeoxycholate,0,1%
SDS, 1% (v/v) NP40]. Extracts (10 μg/lane) were sepa-
rated on a 10% SDS-polyacrylamide gel, blotted onto a
PVDF membrane, and incubated with the indicated pri-
mary antibodies diluted in blocking buffer (5% nonfat
dry milk) over night at 4°C. After washing and
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incubation with peroxidase-coupled species-specific sec-
ondary antibodies, the signal was developed using
SuperSignal West PICO Chemiluminescent Substrate
(Perbio Science, Bonn, Germany) according to manufac-
turer’sprotocol.CtBP2, CDYL, RCOR3, b-actin and
ZEB1 were immunodetected with the following primary
antibodies: anti-CtBP2 mouse monoclonal antibody
(1:8.000, BD Transduction Laboratories™,Franklin
Lakes, NJ, USA), anti-CDYL rabbit polyclonal antibody
(1:500,Abcam,Cambridge,UK),anti-RCOR3 rabbit
polyclonal antibody (1:1000Abcam, Cambridge, UK)
anti-b-actin mouse monoclonal antibody (1:5.000,
Sigma-Aldrich Chemie GmbH, Munich, Germany). The
anti-ZEB1 rabbit polyclonal antibody (1:20.000) was a
gift of D.S. Darling, University of Louisville, Louisville,
KY, USA.
Results
In order to identify protein complexes of which several
distinct components are coordinately regulated by miR-
NAs, we assembled a miRNA-protein target network for
677 human miRNAs and 18,880 targets which are listed
in the TargetScan http://www.targetscan.org database.
The targets were mapped to a non-redundant set of
2,177 experimentally verified protein complexes from
the CORUM database [20]. We compiled the protein
complexes, which are more significantly associated with
the target sets of miRNAs than expected for random
target lists based on Fisher’s exact test (see Methods).
The analysis resulted in 722 miRNA-regulated protein
complexes (P-value < 0.05; Fisher’s exact test with Bon-
ferroni correction for multiple testing), which contained
at least two targets of an individual miRNA. The entire
list of miRNA-regulated protein complexes can be
found in Additional file 1, Table S1 online. Furthermore,
140 protein complexes were significantly regulated by
miRNA clusters (P-value < 0.05, Fisher’s exact test with
Bonferroni correction for multiple testing). The list of
protein complexes regulated by clusters of miRNA can
be found in Additional file 2, Table S2. The highest
ranked complexes are listed in Table 1 and Table 2.
Functional spectrum of miRNA-regulated protein
complexes
We next analyzed the spectrum of functions covered by
our set of miRNA-regulated protein complexes. We
identified the biological processes (Gene ontology cate-
gories [15]) and pathways representing the molecular
interactions and reaction networks (KEGG [16]), which
are enriched within the total set of 810 miRNA-targeted
components of the protein complexes (Additional file 3,
Table S3 and Additional file 4, Table S4 online). In all,
as shown in Figure 1a, the miRNA-regulated protein
complexes are mainly involved in regulation of RNA
metabolic process, regulation of transcription and chro-
matin modification. Conversely, house-keeping func-
tions, such as translational elongation and ATP
synthesis coupled electron transport are underrepre-
sented. The results confirm earlier investigations [21]
showing that miRNAs less frequently target genes
involved in essential cellular processes. Interestingly,
there is an overrepresentation of genes involved in the
G1 phase of mitotic cell cycle, while genes that are
involved in the S phase and the M/G1 transition of
mitotic cell cycle are underrepresented. Experimental
evidence has already been reported for the regulation of
signal transduction in several metazoan species [22-26]
and the cell cycle [27,28] by miRNAs. The regulation of
the cell cycle by miRNAs is further supported by strong
correlations of miRNA over-expression with different
types of cancer [29].
These observations correspond with the overrepresenta-
tion of targeted genes contained in pathways from
KEGG (see Figure 1b). A highoverrepresentationof
genes could be observed in “Pathways in cancer”.Also
many signaling pathways are overrepresented, namely
Wnt signaling, TGF-beta signaling, Insulin signaling,
Notch signaling, ErbB signaling, MAPK signaling, T and
B cell receptor signaling and Chemokine signaling.
Genes involved in house-keeping functions were under-
represented also in KEGG pathways, namely RNA poly-
merase, RNA transport, Proteasome, Oxidative
phosphorylation and Ribosome.
Table 1 Top ranking single miRNAs targeting protein complexes
Complex Description miRNA P-value
corum_3028 TGF-beta receptor II-TGF-beta receptor I-TGF-beta3 complex hsa-miR-665 2.00326E-05
corum_1810 ITGA4-PXN-GIT1 complex hsa-miR-199a-5p 3.26913E-05
corum_4 ACTR-p300-PCAF complex hsa-miR-338-5p 3.65869E-05
corum_642 CtBP complex hsa-miR-129-5p 4.60618E-05
corum_642 CtBP complex hsa-miR-548f 5.10388E-05
corum_3754 CREBBP-SMAD3-SMAD4 pentameric complex hsa-miR-1284 7.21639E-05
corum_3753 CREBBP-SMAD2-SMAD4 pentameric complex hsa-miR-1264 8.26908E-05
corum_2377 ITGA2b-ITGB3-CD47-SRC complex hsa-miR-149 8.78087E-05
corum_2760 SMAD3-SMAD4-FOXO3 complex hsa-miR-1284 9.18449E-05
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Validating predicted miRNA targets in protein complexes
Two recent proteomics studies measured the changes
in synthesis of proteins in response to miRNA over-
expression or knockdown on a genome-wide scale for
selected miRNAs [6,7]. We incorporated the data of
these studies in order to validate our predictions. To
determine the impact of protein downregulation by
miRNAs, which have targets in protein complexes, the
level of downregulation of targeted components and
non-targeted components was compared. We consid-
ered both significantly and insignificantly regulated
complexes, since the amount of significantly regulated
complexes for the examined miRNAs in the proteo-
mics study is too low to provide statistical significance.
The negative fold changes of the targeted components
were significantly higher than the negative fold changes
of the non-targeted components (see Table 3 and Fig-
ure 2) for every analyzed miRNA. For example, our
data showed that the LARC (LCR-associated remodel-
ling) complex [30] has two (out of 19) components,
which are computationally predicted targets of let-7.
These two components, namely DPF2 (Zinc finger pro-
tein ubi-d4) and SMARCC1 (SWI/SNF-related matrix-
associated actin-dependent regulator of chromatin
Table 2 Top ranking miRNA clusters targeting protein complexes
Complex Description Cluster P-value
corum_3028 TGF-beta receptor II-TGF-beta receptor I-TGF-beta3 complex hsa-miR-493-665 0.00079949
corum_3753 CREBBP-SMAD2-SMAD4 pentameric complex hsa-miR-1912-1264 0.00095073
corum_3059 ITGA11-ITGB1-COL1A1 complex hsa-miR-29a-29b 0.00101944
corum_3059 ITGA11-ITGB1-COL1A1 complex hsa-miR-29c-29b 0.00101944
corum_1080 P-TEFb.2 complex hsa-miR-224-452 0.00168046
corum_3054 MAD1-mSin3A-HDAC2 complex hsa-miR-1912-1264 0.00316828
corum_3054 MAD1-mSin3A-HDAC2 complex hsa-miR-510-514 0.00316828
corum_422 Beta-dystroglycan-caveolin-3 complex hsa-miR-3671-101 0.00330472
corum_2436 ITGAV-ITGB1 complex hsa-miR-513c-513b 0.00333788
Figure 1 Functional analysis and validation of miRNA-regulated protein complexes. Functional analysis: Enrichment of Gene Ontology
(GO) terms and KEGG pathways in the target subunits of protein complexes. The size of the bars for each term indicates the negative logarithm
of the P-value. Only meaningful and non-redundant terms were selected for illustration. See Additional file 3 &4, Table S3&S4 for a complete and
detailed list of significant terms.
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subfamily C member 1) were modestly down-regulated
(fold changes of -0.38, and -0.2, respectively), when
let-7b was over-expressed in HeLa cells [7]. LARC
binds to the DNase hypersensitive 2 site in the human
b-globin locus control region(LCR)andtransactivates
b-like globin genes [30]. By simultaneously down-regu-
lating two components of the LARC complex, let-7b
might contribute to the overall transcriptional repres-
sion of the human b-globin locus.
PAR-CLIP (Photoactivatable-Ribonucleoside-Enhanced
Crosslinking and Immuno-precipitation) is a powerful
tool to detect segments of RNA bound by RNA-binding
proteins (RBPs) and ribonucleoprotein complexes
(RNPs). We corroborated the miRNA target sites identi-
fied by PAR-CLIP [13] with the proteomics data [6,7].
55% of the proteins with miRNA targets sites predicted
based on PAR-CLIP data were moderately down-regu-
lated (log2-fold change < -0.1). 413 protein complexes
contained miRNA target sites in at least two subunits
(Additional file 5, Table S5 online). Interestingly, of the
5,185 unique proteins with miRNA target sites identified
based on PAR-CLIP data, 607 (12%) are members of pro-
tein complexes (with at least two distinct targets of one
miRNA in the same protein complex). For comparison,
the manually curated collection of human protein com-
plexes in the CORUM database covers 2,780 unique pro-
teins (2% of UniProt proteins). This implies miRNA
targets identified from PAR-CLIP data are more likely to
be in a protein complex from the CORUM database
(12%) as compared to proteins in general (2%). While
miRNAs frequently target multiple genes with isolated
functions, these independent data, though only by a sim-
ple estimate, suggest that there is also a significant pro-
portion of miRNA targets, which are distinct members of
protein complexes (hypergeometic P-value 1.23e-11).
Table 3 Significance of miRNA target downregulation
miRNA P-value
hsa-let-7b 1,5E-05
hsa-miR-1 5,1E-12
hsa-miR-155 5,3E-04
hsa-miR-16 1,8E-08
hsa-miR-30b 1,6E-03
The P-value was calculated by a one-sided Kolmogorov-Smirnov test. It was
used to compare the fold change distributions of complex components that
are miRNA targets and non-target ones.
Figure 2 Validation of targeted complex components. Fold change distributions of targeted and non-targeted proteins in complexes for
each investigated miRNA. The (*) indicates high significance in the Kolmogorov-Smirnov test.
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Protein complexes and miRNA expression
We next tested whether miRNAs, which target different
components of the same protein complex, are more
likely to be co-expressed. The average expression corre-
lation (Co-expression as calculated by Pearson correla-
tion coefficients, hereafter termed PC values) of
miRNAs was examined based on pairwise correlation
calculations of miRNA expression profiles obtained for
26 different organ systems and cell types [31]. To test
for statistical significance, we combined all pairwise PC
values obtained from the sets of miRNAs which signifi-
cantly target the same complex. These PC values were
then compared to all other pairwise PC values that were
present in the data set from [31]. We performed a one-
sidedKolmogorov-Smirnov(KS)testforthetwoPC
value distributions and obtained a significantly (P-value
6.106e-24) higher co-expression within the sets of miR-
NAs that target the same complex. Since we are inter-
ested in coexpression of miRNAs that are not in one
transcription unit, we also testedforincreasedcorrela-
tion only for miRNAs of different transcription units.
Onlyafew(3.3%)ofthecorrelatedmiRNAswereactu-
ally contained in one transcription unit. Therefore, the
result remains highly significant (P-value 2.11e-18).
Another bias of our results might occur due to fact that
all miRNAs from one family must target the same com-
plex since they target the same set of mRNA. We com-
pared only miRNAs within one complex that belong to
different families. The KS test resulted in a P-value of
0.0058. Taken together, our statistical test indicates that
miRNAs targeting different components of a protein
complex are significantly co-expressed. The average
Pearson correlations of miRNAs that simultaneously tar-
get a specific complex can be found in Additional file 6,
Table S6 online1).
Protein complex networks co-ordinately regulated by
clusters of miRNAs
We systematically characterized the protein complex
networks, which are simultaneously regulated by clus-
tered miRNAs in 154 transcription units gained from
miRBase [1]. The interconnectivity of the target sets of
the miRNA gene clusters was first assessed as follows:
the number of protein-protein interactions between the
target sets of each pair of miRNAs in the cluster was
counted, and these values were compared to 1,000 ran-
domly sampled sets of miRNAs. To avoid miRNA target
prediction bias arising from redundant prediction of
clustered miRNA family members, only targets of one
family member were counted within each cluster. The
statistical analysis revealed 35 clusters, whose targets are
significantly interconnected in the protein-protein inter-
action network (P-value < 0.05, permutation test, 1,000
samples, Table 1). Comparing the observed number of
interactions (Figure 3b) with the corresponding distribu-
tions of randomly sampled sets of miRNAs provides a
strong indication that a significant fraction of miRNAs
in clusters might co-ordinately regulate targets (P-Value
< 0.02, Wilcoxon signed rank test, Additional file 7,
Table S7 online). In order to support this finding, we
also applied Fisher’s exact test to test if the global num-
ber of target interactions from miRNA clusters is higher
than expected by chance. This test resulted in a P-value
< 2e-16.
CtBP/ZEB complex regulated by the miR-141-200c cluster
The network perspective provides fascinating insights of
gene regulation by miRNA gene clusters, whose target
sets have not yet been analyzed at a systems-level. To
explore this in detail we examined the protein com-
plexes predicted to be co-ordinately regulated by the
Figure 3 Statistical evidence of coordinate regulation by miRNAs.a, Pearson correlation distributions of miRNAs that target the same
complex (red line) is plotted against the distribution of all observed Pearson correlation values (black dotted line). Also the distributions of
excluded Pearson correlations of miRNAs from the same family (blue) and the same cluster (green) are plotted. b, Boxplot for direct interactions
of proteins targeted by NmiRNAs within a cluster as compared to a null model of Nrandomly sampled miRNAs, respectively.
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miR-141-200c cluster. The miR-141 and miR-200c genes
are located on chromosome 12p 13.31, separated by a
338bp spacer sequence; miR-141 and miR-200c belong
to the miR-200 family. The seed region of miR-141 dif-
fers to that of miR-200c by one nucleotide at position 4
of the miRNA; therefore, miR-141 and miR-200c have,
based on the “seed”rule, different computationally pre-
dicted targets. Nevertheless, we found that the targets of
the miR-141-200c cluster are significantly intercon-
nected (P-value < 0.02, Table 4).
Very recent reports have shown that the miR-200
family regulates epithelial to mesenchymal transition
(EMT) by targeting the transcriptional repressor zinc-
finger E-box binding homebox 1 (ZEB1)andZEB2
[4,32-35]. During EMT, the miR-141-200c cluster and
the tumor invasion suppressor gene E-cadherin are
downregulated by ZEB1/2 [35]. ZEB1 and ZEB2 repress
transcription through interaction with corepressor CtBP
(C-terminal binding protein) [36]. Interestingly, several
essential components of the CtBP/ZEB complex, namely
ZEB1/2, CtBP2, RCOR3 (REST corepressor 3) and
CDYL (Chromodomain Y-like protein), are predicted
targets of the miR-141-200c cluster. CtBP2 has one
miR-141 target site and one miR-200c target site, while
ZEB1 and CDYL have two miR-200c target sites.
RCOR3 has one miR-141 target site. The CtBP/ZEB
complex mediates the transcriptional repression of its
target genes by binding to their promotors and altering
the histone modification [37].
We showed that overexpression of miR-141 and miR-
200c led to reduced expression of CtBP2 and ZEB1 in
human pancreatic carcinoma (PANC-1) cells (Figure 4a).
Luciferase reporter assay showed reduced activity of the
CtBP2 and ZEB1 3’UTR-luciferase reporters with
increased levels of miR-141 and miR-200c (Additional file
8, Figure S1 online). These results are also confirmed on
protein level by immunoblots (Figure 4b). In order to rule
out the possibility that the stability of ZEB1 and CtBP2 are
dependent on each other, we separately knocked down
ZEB1 and CtBP2 by siRNAs in PANC-1 cells and observed
no change in protein levels of the respective complex part-
ner (Figure 4c). Although the expression of CDYL and
RCOR3 is less obviously affected by overexpression of
miR-141 and miR-200c in PANC-1 cells as compared to
CtBP2 and ZEB1 (data not shown), we observed a downre-
gulation of CDYL and RCOR3 on the protein level, when
miR-141 or miR-200c were transiently transfected in
PANC-1 cells (Figure 4d), suggesting that CDYL and
RCOR3 are also targets of the miR141-200c cluster.
Together, these experiments demonstrate, for the first
time, that CtBP2, CDYL and RCOR3 can be regulated by
miR141-200c cluster post-transcriptionally. As the func-
tional consequence of miRNA overexpression, the expres-
sion of E-cadherin mRNA is greatly upregulated (Figure
4a), indicating that the repression activity of CtBP/ZEB
complex is compromised. The interaction between the
miR-141-200c cluster and multiple components of the
CtBP/ZEB complex suggests a coordinated regulation of
Table 4 Top ranking miRNA clusters with interconnected
target sets
miRNA cluster
15,
* # targ Ppis [#| P-value] Ppis [miR-miR]
[# |P-value]
hsa-miR-3671-101 116 94 0.1294 94 0
hsa-let-7a-7b 120 48 0.1748 48 0
hsa-miR-1912-1264 49 24 0.3224 24 0
hsa-miR-214-199a 69 22 0.3222 22 0
hsa-miR-296-298 52 24 0.3324 24 0
hsa-miR-105-767 58 18 0.3418 18 0
hsa-miR-34b-34c 43 22 0.3522 22 0
hsa-miR-3677-940 55 18 0.3618 18 0
hsa-miR-1914-647 38 20 0.3720 20 0
hsa-miR-599-875 23 6 0.536 6 0
hsa-miR-16-15a 172 172 0.12172 172 0
hsa-miR-15b-16 172 172 0.15172 172 0
hsa-miR-181c-181d 160 142 0.21142 142 0
hsa-miR-195-497 172 172 0.15172 172 0
hsa-miR-181a-181b 160 142 0.19142 142 0
hsa-miR-181b-181a 160 142 0.18142 142 0.01
hsa-miR-30e-30c 183 144 0.2144 144 0.01
hsa-miR-513c-513b 125 142 0.21142 142 0.01
hsa-miR-23b-24 305 584 0.02234 234 0.01
hsa-miR-363-106a 341 550 0.29823 823 0.01
hsa-miR-200c-141 246 392 0.02112 112 0.01
hsa-miR-30b-30d 183 144 0.2144 144 0.01
hsa-miR-519a-1283 298 702 0.02258 258 0.01
hsa-miR-24-23a 305 584 0.03234 234 0.02
hsa-miR-522-1283 323 864 0.02377 377 0.02
hsa-miR-25-106b 233 236 0.22224 224 0.02
hsa-miR-301b-130b 123 86 0.3486 86 0.03
hsa-miR-182-183 218 288 0.15196 196 0.03
hsa-miR-17-92a 341 550 0.28607 607 0.03
hsa-miR-133a-1 189 262 0.0574 74 0.03
hsa-miR-545-374a 180 212 0.0862 62 0.04
hsa-miR-206-133b 189 262 0.0774 74 0.04
hsa-miR-29a-29b 126 64 0.3864 64 0.05
hsa-miR-513a-508 242 256 0.0559 59 0.05
hsa-miR-513a-507 242 256 0.0559 59 0.05
*miRNA cluster is termed in the following way: miR-first_miRNA-last_miRNA.For
instance, miR-17-92a cluster is consisted of six miRNAs, miR-17 is the fir st
miRNA in the cluster and miR-92a is the last miRNA in the cluster.
Interconnectivity of the target sets was evaluated as: (1) Number of interactions
in the union target set and (2) Number of interactions between target sets of all
distinct miRNA pairs in a cluster (ppis [miR-miR]). The P-values were estimated by
comparing the observed value with 1,000 randomly sampled target sets of equal
size. The results for all clusters are shown in Additional file 7, Table S7 online.
Sass et al.BMC Systems Biology 2011, 5:136
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the repression activity for the CtBP/ZEB complex. Intrigu-
ingly, the miR-141-200c cluster also targets b-catenin,
which is a shared component of cell adhesion and Wnt
signalling [38]. b-catenin is found in the plasma mem-
brane, where it promotes cell adhesion by binding to E-
cadherin, in the cytoplasm, where it is easily phosphory-
lated and degraded in the absence of a Wnt signal, and in
the nucleus, where it binds to TCF transcription factors
and induces the transcription of Wnt target genes. Most
protein-interacting motifs of b-catenin overlap in such a
way that its interactions with each of its protein partners
are mutually exclusive [38]. Since the miR-141-200c clus-
ter and E-cadherin are both downregulated during EMT,
it is tempting to speculate that more b-catenin would be
made available for participating in transactivating down-
stream genes, which may contribute to the progress of
cancer [4].
Discussion
MicroRNAs and their functions have been a fascinating
research topic in recent years [8,39,40]. In animals,
miRNA-guided regulations of gene expression are likely
to involve hundreds of miRNAs and their targets.
Genetic studies have successfully elucidated some
miRNA activities, termed genetic switches, which have
intrinsic phenotypic consequences [8,40]. miRNA activ-
ities can be classified based on whether their major
effect is conveyed through one, a few or many targets
(from tens to hundreds). All genetic switches discovered
so far belong to the former class (a few targets). It is
unclear how the latter class, termed target battery [8],
which might be subtly regulated on the protein level
[6,7], contributes to proper phenotypes.
In this study, we completed a comprehensive analysis
of human protein complexes, which might be co-ordi-
nately regulated by miRNAs. When this paper was
under review, Tsang et al. [12] predicted human micro-
RNA functions by miRBridge to assess the statistical
enrichment of microRNA-targeting signatures in anno-
tated gene sets, including our CORUM protein com-
plexes [20]. These protein complexes can be considered
as examples of “target battery”[8]. Our statistical
Figure 4 Protein complexes regulated by the miR-141-200c cluster.a, Real-time reverse transcription-PCR of CtBP2 and ZEB1 after
transfection of the indicated miRNAs in undifferentiated cancer cells (PANC-1). The expression levels of E-cadherin (of which the transcription is
repressed by CtBP/ZEB complex) are included as positive controls. b, Confirmation of the regulation of CtBP2 and ZEB1 by miR-141 and miR-200c
on protein levels by immunoblots. c, ZEB1 and CtBP2 knock down by siRNAs, no change in protein levels of the respective complex partner is
oberserved. e, Downregulation of CDYL and RCOR3 on protein level when miR-141 or miR-200c was transiently transfected.
Sass et al.BMC Systems Biology 2011, 5:136
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Page 8 of 11
analysis suggests that, by simultaneously targeting sev-
eral components of protein complexes, a single miRNA
or co-expressed miRNAs may have cumulative effects.
To demonstrate this, we experimentally verified that the
miR141-200c cluster interacts with four different com-
ponents of the CtBP/ZEB complex. Interestingly,
although Tsang et al. used their own miRNA target pre-
dition, which is different from TargetScan prediction,
their protein complex result also included the interac-
tion of the miR200 family and CtBP complex [12] which
includes miR-200c. This supports our finding that the
miR141-200c cluster also interacts with the CtBP com-
plex. The functional analysis of the miRNA-regulated
protein complexes revealed a clear bias towards tran-
scriptional regulation, signal transduction, cell cycle and
chromatin regulation, for which confirmation has been
reported only by individual experimental studies of
selected miRNAs. Our approach provides improved can-
didate miRNA target lists to the experimentalist, as
demonstrated by a benchmark against large-scale, quan-
titative proteomics data.
Some ancient miRNA genes are deeply conserved in
the kingdom Animalia [37,38] or in the kingdom Plantae
[41] while during the evolution, novel miRNA genes
were constantly created, fixed or lost [42-45]. Interest-
ingly, the genomic organization of some miRNA clusters
were well preserved for millions of years, implying a
functional incentive to keep such configurations [5,46].
The evolution of homogeneous miRNA clusters can be
easily explained by the classical gene duplication theory
[47]. The regulatory effect of such clusters might merely
be an increase of dosage. The evolution of hetergeneous
miRNA clusters is more complicated. Two different
miRNAs can be located near each other by various
genomic events, such as recombination, transposon
insertion, etc. Or large number hairpin repeats might
evolve into miRNAs of different families. For example,
the largest human miRNA cluster miR-379-656 [46]
consists of different miRNA families, which evolved by
tandem duplication of an ancient hairpin sequence.
Once a newly formed miRNA cluster proves to provide
a functional advantage, which might be co-ordinate reg-
ulation of protein complexes, the genomic organization
of such a cluster could be fixed by evolution [43].
In eukaryotic cells, RNA operons, mostly sequence-
specific RNA binding proteins, may co-ordinately regu-
late functionally related mRNAs to aid the formation of
macromolecular protein complexes [48]. In such a sce-
nario, mRNAs of different components of a protein
complex are brought together by associating with speci-
fic RNA operons. The localization of these mRNAs
might also facilitate the simultaneous interaction of
miRNAs and their corresponding target mRNAs. Inter-
estingly, RNA operons bind to motifs, which are
sometimes located in the 3’UTRs of mRNAs. Thus, the
competition or cooperation between miRNA binding
and RNA operon binding might be a research topic
worth pursuing.
Conclusion
The results presented here can be used as a starting
point for experimentalists to systematically evaluate
miRNAs and targets interactions at a systems level. The
concept that coexpressed small RNAs may synergisti-
cally target protein complexes for a more efficient regu-
lation is of course not limited to animal miRNAs.
Additional material
Additional file 1: Supplementary Table S1, complexes that are
significantly targeted by single miRNAs (P-value < 0.05, Fisher’s
exact test)
Additional file 2: Supplementary Table S2, complexes that are
significantly targeted by clusters of miRNAs (P-value < 0.05, Fisher’s
exact test)
Additional file 3: Supplementary Table S3, over- and
underrepresentation of Gene Ontology terms in complex members
that are targeted by miRNAs
Additional file 4: Supplementary Table S4, over- and
underrepresentation of KEGG pathways in complex members that
are targeted by miRNAs
Additional file 5: Supplementary Table S5, miRNA target sites
inferred by PAR-CLIP in experimentally verified protein complexes
Additional file 6: Supplementary Table S6, average Pearson
correlation of miRNAs that simultaneously target a specific complex
Additional file 7: Supplementary Table S7, target interconnectivity
of miRNA clusters
Additional file 8: Supplementary Figure S1, reduced activity of the
CtBP2 and ZEB1 3’UTR-luciferase reporters with increased levels of
miR-141 and miR-200c
Acknowledgements
SS, DL, AK and FT are supported by the Initiative and Networking Fund of
the Helmholtz Association within the Helmholtz Alliance on Systems Biology
(project CoReNe). The authors thank Peter Brodersen and Hans-Werner
Mewes for their critical reading of the manuscript and Ivan Kondofersky for
his statistical support.
Author details
1
MIPS, Institute for Bioinformatics and System Biology, Helmholtz Center
Munich, German Research Center for Environmental Health, Ingolstädter
Landstraße 1, D-85764 Neuherberg, Germany.
2
Wellcome Trust Center for
Stem Cell Research, University of Cambridge, Tennis Court Road, Cambridge
CB2 1QN, UK.
3
Department of Visceral Surgery, Universitätsklinikum Freiburg,
Hugstetter Strasse 55, D-79106, Freiburg, Germany.
4
Center for Life and Food
Sciences Weihenstephan, Technicial University Munich, Emil-Ramann-Str. 4,
D-85354 Freising, Germany.
Authors’contributions
SS and SD designed the statistical analyses, interpreted the results. UB, SSB,
YW and TB designed miR141-200c related experiments. UB and SSB
performed experiments. UB, SSB, YW and TB interpreted the results. DL, AK,
KFM, and AR contributed to data analysis. YW conceived the idea. YW and
FT coordinated the study, interpreted the results. SS, SD and YW wrote the
manuscript. All authors have read and approved the manuscript.
Sass et al.BMC Systems Biology 2011, 5:136
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Page 9 of 11
Received: 14 February 2011 Accepted: 25 August 2011
Published: 25 August 2011
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doi:10.1186/1752-0509-5-136
Cite this article as: Sass et al.: MicroRNAs coordinately regulate protein
complexes. BMC Systems Biology 2011 5:136.
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