Abstract
Developmental defects in motile cilia, arising from genetic
abnormalities in one or more ciliary genes, can lead to a common
ciliopathy known as primary ciliary dyskinesia (PCD). Functional
studies in model organisms undertaken to understand PCD or cilia
biogenesis have identified 100s of genes regulated by Foxj1, the master
regulator of motile ciliogenesis. However, limited systems based
studies have been performed to elucidate proteins or network/s crucial
to the motile ciliary interactome, although this approach holds promise
for identification of multiple cilia-associated genes, which, in turn,
could be utilized for screening and early diagnosis of the disease.
Here, based on the assumption that FOXJ1-mediated regulatory and
signaling networks are representative of the motile cilia interactome,
we have constructed and analyzed the gene regulatory and
protein–protein interaction network (PPIN) mediated by FOXJ1. The
predicted FOXJ1 regulatory network comprises of 424 directly and 148
indirectly regulated genes. Additionally, based on gene ontology
analysis, we have associated 17 directly and 6 indirectly regulated
genes with possible ciliary roles. Topological and perturbation
analyses of the PPIN (6927 proteins, 40,608 interactions) identified
121 proteins expressed in ciliated cells, which interact with multiple
proteins encoded by FoxJ1 induced genes (FIG) as important interacting
proteins (IIP). However, it is plausible that IIP transcriptionally
regulated by FOXJ1 and/or differentially expressed in PCD are likely to
have crucial roles in motile cilia. We have found 20 de-regulated
topologically important effector proteins in the FOXJ1 regulatory
network, among which some (PLSCR1, SSX2IP, ACTN2, CDC42, HSP90AA1,
PIAS4) have previously reported ciliary roles. Furthermore, based on
pathway enrichment of these proteins and their primary interactors, we
have rationalized their possible roles in the ciliary interactome. For
instance, 5 among these novel proteins that are involved in cilia
associated signaling pathways (like Notch, Wnt, Hedgehog, Toll-like
receptor etc.) could be ‘topologically important signaling proteins.’
Therefore, based on this FOXJ1 network study we have predicted
important effectors in the motile cilia interactome, which are possibly
associated with ciliary biology and/or function and are likely to
further our understanding of the pathophysiology in ciliopathies like
PCD.
Keywords: FOXJ1, motile cilia, primary ciliary dyskinesia, ciliopathy,
transcriptional network, protein–protein interaction, network analysis
Introduction
Cilia, microtubule based hair-like organelles, are primarily composed
of a structural core, the axoneme, in addition to the basal body,
transition zone, ciliary membrane and the ciliary tip ([27]Fliegauf et
al., 2007). Macromolecular synthesis and assembly of all of these
ciliary structures is a complex and co-ordinately regulated process
that involves intraflagellar transport (except cytosolic ciliogenesis),
membrane trafficking and selective import of ciliary proteins through
the transition zone ([28]Ishikawa and Marshall, 2011). Based on their
axonemal organization, 9+2 microtubular architecture with dynein arms
or 9+0 without dynein, cilia can be either motile or non-motile,
respectively. Both of these kinds of cilia have diverse tissue specific
roles in different physiological and developmental processes like
cellular motility, fluid clearance, sensory reception, and signaling
([29]Bisgrove and Yost, 2006; [30]Fliegauf et al., 2007). Given their
complexity, mutation(s) or defect(s) in one or more proteins involved
in the structural organization of cilia or regulation of their assembly
can result in abnormalities in the formation or function of these
organelles ([31]Horani et al., 2016). These defects in cilia formation
or function result in disrupted development of body pattern or
physiology of multiple organ systems ([32]Bisgrove and Yost, 2006;
[33]Ishikawa and Marshall, 2011) leading to a range of disorders
collectively referred to as ‘ciliopathies.’ In particular, this
spectrum of disorders could be associated with immotile/primary cilia
like polycystic kidney diseases, nephronophthisis, Bardet-Biedl
syndrome etc. or with motile cilia like primary ciliary dyskinesia
(PCD) ([34]Bisgrove and Yost, 2006).
PCD, the most prevalent of ciliopathies, is a genetically heterogeneous
disorder, clinically associated with chronic respiratory infections,
bronchiectasis, infertility and in certain cases, hydrocephalus or
laterality defects ([35]Zariwala et al., 2011). However, PCD exhibits
variability in clinical phenotype, and further, mutations in all
disease causing genes may not be exhibited as defects in ciliary
ultrastructure. Thus, a genetic screening test for PCD causing genes
could be helpful for disease diagnosis ([36]Zariwala et al., 2011). In
this respect, the genetic basis of PCD, which is usually inherited as
an autosomal recessive trait, has been studied with the help of
conventional family based, genome-wide linkage studies, candidate gene
testing, homozygosity mapping as well as genome and exome sequencing
studies to identify causative mutations ([37]Zariwala et al., 2011;
[38]Horani et al., 2016). In addition, while identification of PCD
causing genes with conventional studies (family based or genome-wide
linkage analysis) has been challenging due to locus heterogeneity,
nevertheless, different sequencing approaches have identified multiple
disease causing genes in families of PCD patients during the last
decade ([39]Zariwala et al., 2011; [40]Horani et al., 2016). At
present, the OMIM database lists about 35 disease causing genes with
mutations associated with PCD ([41]McKusick, 1998; [42]Amberger et al.,
2015).
However, such disease causing variants identified with the help of
sequencing could be family specific ([43]Horani et al., 2016), and
moreover, such approaches may only be useful to study certain cases
that have been successfully diagnosed. Thus, other complementary
approaches in model organisms, which explore cilia biogenesis to
identify genes or proteins important in cilia formation or function,
have also been undertaken (for example, [44]May-Simera et al., 2016;
[45]Rao et al., 2016; [46]Terré et al., 2016). In addition, some large
scale studies have identified thousands of proteins in the ciliary
proteome that co-ordinately interact to form these organelles
([47]Ishikawa et al., 2012; [48]Boldt et al., 2016), and such cascades
of interactions are regulated by transcription factors like GemC1,
McIdas, E2f4, E2f5, Myb, Rfx1, Rfx2, Rfx3, Rfx4, and FoxJ1 ([49]Choksi
et al., 2014b; [50]Arbi et al., 2016; [51]Danielian et al., 2016;
[52]Vladar and Mitchell, 2016). Further, while Rfx factors regulate
both motile and immotile cilia genes, FoxJ1 specifically regulates
motile cilia biogenesis, and appears to be its master regulator
([53]Choksi et al., 2014b). This is because FoxJ1 regulates a set of
genes known as FoxJ1 induced genes (FIG), which together are sufficient
for motile cilia development and function ([54]Stubbs et al., 2008;
[55]Yu et al., 2008; [56]Choksi et al., 2014a).
In this study, our primary objective lay in studying the motile cilia
interactome to identify possible essential proteins and their probable
functions in this interactome. In this respect, we have studied two
components of the motile cilia interactome, a probable transcriptional
network and a probable signaling network. The transcriptional network
in the motile cilia interactome that we have considered here is the
FOXJ1 regulatory network. For this purpose, we have predicted the
regulatory network of the motile cilia master regulator, FOXJ1 and
annotated the network genes based on information from different ciliary
reference databases. Based on this analysis, however, we found that
while ∼83% of the regulatory network genes are expressed in multiple
motile ciliated tissues, only ∼24% of them are presently annotated.
Further, the annotated network genes mainly comprised of ciliary
structural component proteins or motility associated proteins. As
mentioned above, it has been established in previous studies that FoxJ1
over-expression is sufficient to drive the motile ciliogenic program
and generate functional ectopic motile cilia ([57]Stubbs et al., 2008;
[58]Yu et al., 2008; [59]Choksi et al., 2014a). It is possible that the
FIG encoded protein (FIGp) participate in motile cilia assembly or
function in a co-ordinated manner in association with other proteins
(signaling) of the ciliary milieu. In this context, we next sought to
study the representative motile cilia interactome comprised of the
regulatory network proteins and their protein–protein interaction
network (PPIN) with different graph theory metrics. This analysis was
performed in order to identify the key connector proteins (regulatory
network proteins) that relay the information onto the signaling
component/s during motile cilia biogenesis. Further, the topological
analysis has been complemented with a functional analysis to determine
whether these proteins could indeed be essential for ciliogenesis or
ciliary function. Traditionally, such essential proteins have been
identified with the help of gene misexpression, targeted gene knock-out
or knock-down studies in experimental model systems ([60]Stubbs et al.,
2008; [61]Yu et al., 2008; [62]Choksi et al., 2014a; [63]May-Simera et
al., 2016; [64]Terré et al., 2016). By contrast, in this study we have
utilized an in silico knock-out strategy, and determined the effects on
the motile cilia interactome by deriving whether the effective change
in a centrality measure as a result of the knock-out varied
significantly. Moreover, in order to ascertain the relevance of these
predicted essential proteins to ciliary biology, we have utilized
literature-based evidences to determine whether some of the proteins
have previously identified involvements in ciliary biology. Finally, to
determine the likely functions of these proteins, we have utilized the
concept of ‘guilt by association’ (which states that two proteins that
are known to interact with one another, may usually participate in the
same or similar cellular functions; [65]Oliver, 2000; [66]Schwikowski
et al., 2000), and determined the enriched pathways or processes among
the proteins of interest.
Thus, studying the PPIN associated with the FOXJ1 regulatory network
might help us in elucidating the topologically important effector
proteins that lie at the interface of the FOXJ1 regulatory network and
the associated protein interaction network. These proteins might form a
crucial link between the FOXJ1 regulatory and cilia
biogenesis-associated signaling components in the motile cilium, and
mediate some of the functions of FOXJ1 and its regulatory network.
Importantly, such proteins identified in this manner could be crucial
for ciliary development or maintenance of ciliary function, and one
could screen for defects in this repertoire of proteins to determine
possible causal or etiological genes for PCD.
Materials and Methods
Collating an Information Resource Regarding Cilia Biogenesis
Genes experimentally probed and identified to be involved in
ciliogenesis or ciliary function were collected from different studies
and databases like the SysCilia gold standard database ([67]van Dam et
al., 2013), Reactome pathway database [R-HSA-5617833] ([68]Croft et
al., 2014; [69]Fabregat et al., 2018), FIG study ([70]Choksi et al.,
2014a), cilliary proteome related studies ([71]Gupta et al., 2015;
[72]Boldt et al., 2016) and OMIM database ([73]McKusick, 1998;
[74]Amberger et al., 2015). This resource has been subsequently
utilized to summarize the previously identified involvement(s) of the
FOXJ1 transcriptional network genes. It has also been utilized as a
preliminary validation resource to ascertain whether certain genes
predicted to be involved in ciliogenesis or ciliary function by our
computational approach are actually involved in the process.
Cilia Associated Expression Analysis
In order to prepare a set of disease (PCD) associated genes, we have
considered a dataset available from a previous study that explored the
expression profile of bronchial tissue of PCD patients ([75]Geremek et
al., 2014). Differentially expressed genes were determined with the
help of limma ([76]Ritchie et al., 2015) R package in Gene Expression
Omnibus (GEO) series dataset ([77]GSE25186) ([78]Edgar et al., 2002;
[79]Barrett et al., 2013; [80]Geremek et al., 2014). Genes having fold
change ≥ 2 and p-value ≤ 0.05 were considered as differentially
expressed and possibly associated with PCD based on the considered PCD
case study. Databases or datasets [e.g., [81]Choksi et al. (2014a)
expression study, CilDB ([82]Arnaiz et al., 2009; [83]Arnaiz et al.,
2014), PCD expression analysis case study ([84]Geremek et al., 2014)
and Human Protein Atlas ([85]Uhlen et al., 2010; [86]Uhlén et al.,
2015; [87]Thul et al., 2017)] providing evidence for RNA or protein
expression abundance in ciliary cells were taken into consideration for
‘cilia associated expression analysis.’ For this, if genes had
expression information in the ‘cilia associated expression analysis,’
they were considered to have possible associations with ciliary
biology.
Constructing the FOXJ1 Regulatory Network
Transcription factor binding sites may generally be predicted by
scanning a position weight matrix (PWM) against DNA using a pattern
matching algorithm ([88]Bulyk, 2004). Genes which are likely to be
regulated transcriptionally by FOXJ1 were predicted with the help of
Rsat ([89]Turatsinze et al., 2008). An initial set of genes (FIG) to be
studied was prepared based on their induction upon FoxJ1
over-expression in the zebrafish ([90]Choksi et al., 2014a). With the
help of the Ensembl Compara database we could determine that these FIG
have high confidence orthologs in humans (Homo sapiens) and mice (Mus
musculus) ([91]Herrero et al., 2016). Further, for prediction of
transcription factor binding motifs, pre-requisites include a PWM for
the transcription factor and a background matrix representative of
general base frequencies around the transcription start site (TSS) of
genes. It is possible that orthologous transcription factors from human
and mouse may share similar binding specificities ([92]Jolma et al.,
2013). Thus, a PWM for FoxJ1 (mouse) [PB0016.1] was collected from
footprintDB database ([93]Sebastian and Contreras-Moreira, 2014) since
PWM for human FOXJ1 is unavailable. It was observed that these proteins
are 92.6% identical, and moreover, the DNA binding domains are 100%
identical ([94]Supplementary Figure 1A), which further suggested that
these proteins may share similar binding specificities. Further, a
background model (Markov order), representative of ±6 kb of random Homo
sapiens genes, was prepared. These were then utilized to scan ±6 kb of
the FIG for the presence of FOXJ1 binding motif ([95]Medina-Rivera et
al., 2015). Predicted binding sites having p-value ≤ 1e^−04 were
considered to be genes directly regulated by FOXJ1. Further, a logoplot
([96]R Core Team, 2016) representative of the binding specificity of
FOXJ1 (human) was prepared from the multiple sequence alignment of the
predicted FOXJ1 binding sites among human orthologs of FIG.
Determining Ciliary Functional Associations of FOXJ1 Regulatory Network Genes
Based on Gene Ontology (GO) Analysis
Based on the CCR dataset we could ascertain the ciliary roles of some
of the FOXJ1 regulatoy network genes. However, we further performed GO
analysis and GO enrichment analysis in order to assign probable
functional relevance to the remaining genes. GO analysis was performed
using DAVID web server ([97]Huang da et al., 2009b), and with the help
of FGNet ([98]Aibar et al., 2015), certain GO based enriched clusters
among the genes were determined. Functions of genes belonging to
clusters having p-value ≤ 1e^−02, cluster enrichment score ≥ 2, fold
enrichment ≥ 4 could be predicted based on this analysis.
Constructing the FOXJ1 Associated Ciliary Interactome
In order to prepare a PPIN representative of proteins and connections
important for cilia structure or function in relation to FOXJ1
activation, we considered the FIGp as seed proteins. In particular, a
PPIN is comprised of proteins as nodes, and two proteins are connected
by an edge if they are known to be interacting. Thus, a PPIN was
constructed around these seed proteins by obtaining high confidence
experimentally reported interactions between these proteins and other
proteins from SysCilia ([99]van Dam et al., 2013), Bioplex
([100]Huttlin et al., 2015), STRING ([101]Szklarczyk et al., 2015), and
BioGrid ([102]Stark et al., 2006; [103]Chatr-aryamontri et al., 2017)
databases. In this way, a network of primary interactors of FIGp was
constructed, and the largest connected component of this network was
extracted (FIG-sub-network). We then analyzed the degree distribution
of the FIG-sub-network to determine whether the constructed network was
a scale free network wherein the degree distribution follows a power
law. The degree (k: number of proteins each protein is connected to) of
each protein in the network was computed and a power law [P(k)∼ k^−α
where α is the degree exponent] was fitted to the resulting
distribution. A Kolmogorov–Smirnov test (which computes a p-value for
the estimated power-law fit to the data) was used to determine the
goodness of fit of the degree distributions to the power law (at 0.1
level of significance) ([104]Clauset et al., 2009; [105]R Core Team,
2016).
Identifying Topologically Important or Essential Proteins in the
Representative Motile Cilia Interactome (FIG-sub-network)
Once we had a PPIN representative of motile cilia interactome in hand,
we analyzed the FIG-sub-network based on a computationally faster
implementation of a previously proposed methodology ([106]Bhattacharyya
and Chakrabarti, 2015). With the help of this analysis we have
identified topologically important proteins in this network. For this
purpose, we have considered different graph theory metrics like degree,
shortest path and centrality to determine important interacting
proteins (IIP) (combination of hub, bottleneck, central, local network
perturbing, and global network perturbing proteins) in our
FIG-sub-network as outlined below.
Node Perturbation Analysis of the FIG-sub-network
Previously, it has been found that removal of hub proteins has a
significant effect on the topology of the PPIN, while they are
extremely resilient toward the removal of random nodes ([107]Barabási
and Oltvai, 2004). Based on this observation, we have previously
devised a centrality measure which tries to capture the change in the
topology of the network on in silico node removal to identify
topologically important proteins in a protein interaction network
([108]Bhattacharyya and Chakrabarti, 2015). Thus, with the objective of
identifying topologically important proteins, a node perturbation
analysis of the global network and local sub-graphs in the
FIG-sub-network was performed. The local sub-graphs comprised of
proteins having degree higher than 2, and their 2nd level interactors
and the local network centrality measures of the nodes before and after
node removal in the local sub-graph were compared. It was assumed that
higher the difference in the scores (LNCS), higher is the perturbation
ability, and thus, proteins important for maintaining the integrity of
the local sub-network determined in this manner were termed as local
network perturbing proteins (LNPP). Similarly, global network
perturbation was performed by removing a single node at a time and
studying its effect on the global network centrality score (GNCS)
before and after the perturbation. Proteins identified as crucial for
maintaining the global sub-network integrity, based on the difference
in the GNCS scores before and after perturbation, were termed as global
network perturbing proteins (GNPP).
[MATH: CS=∑C(betweeness)+C(closeness)+C(clustering
coeficient)CCS=∑1nCSLNCS=1/N<
mstyle
displaystyle="true">∑1NCCS :MATH]
where n is the number of first degree interactors, CS is the combined
score, CCS is the cumulative centrality score, LNCS is the local
network centrality score and N is the number of nodes in local sub
graph. The LNCS scores were normalized into z-score and nodes having
z-score ≥1 were considered as LNPP.
[MATH: GNCS=1/N<
mstyle
displaystyle="true">∑1NCCS
:MATH]
where GNCS is the global network centrality score and N is the number
of nodes in the global network. The GNCS scores were normalized into
z-score and nodes having z-score ≥ 0.5 were considered as GNPP.
Identification of Hub and Bottleneck Proteins
Analyses of different biological PPINs have identified that hub and
bottleneck proteins, which are determined by graph theory calculations
that measure inherent properties of scale free networks, could indeed
be essential proteins ([109]Barabási and Oltvai, 2004; [110]Albert,
2005; [111]Yu et al., 2007). For calculating hubs, the node degrees
were normalized into z-scores and the fraction of degree population
having z-score ≥2 was considered as having significantly higher degree
than the rest of the population, and protein nodes having degree 57 or
higher were considered as hub proteins. Additionally, bottleneck
proteins which have a high betweenness centrality value (multiple
“shortest paths” passing through them) could be key connector proteins
([112]Yu et al., 2007). Herein, proteins having betweenness centrality
indices higher than two standard deviations from the mean of the
betweenness centrality distribution were considered as bottleneck
proteins.
Centrality Analysis of the FIG-sub-network
Compactness of a network and capability of relaying information can be
further assessed with the help of another graph theory based concept,
for instance, centrality ([113]Pavlopoulos et al., 2011). It is
possible to identify proteins which could be of biological significance
with the help of centrality analysis, since previous reports have
suggested that the removal of central proteins by gene deletion may
lead to lethal phenotypic consequences ([114]Jeong et al., 2001). Thus
herein, we have considered a range of centrality indices to identify
central proteins with possible biological significance in our
FIG-sub-network. Centrality indices like closeness, load, eigen
centrality and clustering coefficient were evaluated and combined to
derive an average centrality parameter (combined score, CS) for each
node. The CS and the cumulative centrality score (CCS) were computed as
shown below:
[MATH: CS=∑C(load)+C(closeness)+C(eigen vector)+C(clustering
coeficient)CCS=∑1nCS :MATH]
where n is the number of first degree interactors, CS is the combined
score and CCS is the cumulative centrality score. The CCS scores were
normalized into z-score and nodes having z-score ≥ 2 were considered as
central proteins.
IIP in the FIG-sub-network
Based on the assumption that proteins identified as topologically
important in two or more categories (hub, bottleneck, central, local
network perturbing, and global network perturbing) could be essential
proteins in the FIG-sub-network, we have categorized them as IIP. Only
proteins with expression information support in ciliated cells based on
‘cilia associated expression analysis’ were retained as IIP.
Additionally, any overlap between the IIP and the CCR dataset may be
suggestive of their functional relevance in the ciliary milieu.
Moreover, in order to ascertain the probable functional role(s) of
these IIP in association with FIGp, we have estimated the enriched
pathways among interacting FIGp, IIP and their direct interactors with
the help of an R package ([115]Yu and He, 2016).
Identifying Important Effector Proteins by Comparing FOXJ1 Associated
Transcriptional and PPINs
IIP which could be associated with ciliogenesis or PCD based on their
differential expression status upon ectopic FoxJ1 expression in
zebrafish or in PCD were identified as important effectors in FOXJ1
regulatory network. Further, these topologically important effector
proteins are likely to be involved in a range of cellular pathways
particularly signaling pathways. Pathway enrichment analysis with
p-value cut off of 1e^−06 was performed in ReactomePA ([116]Yu and He,
2016) considering the effectors and their primary interactors. Proteins
participating in enriched ‘cilia associated signaling pathways’ were
predicted to have possible ciliary association. In this analysis, we
have considered ‘cilia associated signaling pathways’ such as cell
cycle ([117]Quarmby and Parker, 2005; [118]Izawa et al., 2015),
TGF-beta ([119]Clement et al., 2013), FGF ([120]Neugebauer et al.,
2009), RHO GTPase ([121]Kim et al., 2015), Hedgehog, PDGF, WNT
([122]Goetz and Anderson, 2010), TLR signaling ([123]Baek et al., 2017)
and vesicle mediated transport ([124]Nachury et al., 2010), since all
of these are known to have an association with cilia. The pathway
enrichment analysis was complemented with GO mapping in DAVID
([125]Huang da et al., 2009b). Proteins associated with GO categories
associated with cilia biology like cilium morphogenesis, cell cycle
([126]Quarmby and Parker, 2005; [127]Izawa et al., 2015), actin
organization (cytoskeleton organization, actin filament organization),
protein ubiquitination, centrosome cycle, protein folding (heat shock
proteins) and establishment or maintenance of cell polarity
([128]Stephens and Lemieux, 1999; [129]Pan et al., 2007; [130]Nachury
et al., 2010; [131]Bettencourt-Dias et al., 2011; [132]Jones et al.,
2012; [133]Prodromou et al., 2012; [134]Kasahara et al., 2014;
[135]May-Simera et al., 2016; [136]Shearer and Saunders, 2016;
[137]Kohli et al., 2017) were predicted to have possible ciliary
association.
Determining the Relevance of the Predicted IIP in the Ciliary Interactome to
Ciliary Biology
Literature based evidences of the involvements of the IIP in ciliary
biology or gene expression based association of the IIP with PCD were
considered as preliminary supportive evidences toward the relevance of
the computational predictions to ciliary biology. In order to determine
the significance of the finding that some of the IIP were found to be
differentially expressed in PCD patients, we have performed a
randomization analysis. In each trial, a 121 proteins were randomly
selected from the set of proteins in FIG-sub-network and matched to the
set of differentially expressed PCD proteins in our network. Based on
the number of matches obtained in a 1000 trials, a z-test was performed
to determine whether the association between the IIP and PCD expression
status that we had observed was significant. Additionally, a few of the
IIP proteins have previously reported ciliary roles in literature. A
similar randomization analysis was performed considering matches with
the CCR and the significance of this association was also determined.
Results
FOXJ1 Regulatory Network Governing Motile Cilia Biogenesis and Function
Functional genomics studies have identified the FoxJ1 protein as the
master regulator of motile ciliogenesis, and it is crucial for ciliary
axoneme assembly, basal body docking and ciliary motility ([138]Stubbs
et al., 2008; [139]Yu et al., 2008; [140]Choksi et al., 2014a).
Over-expression of FoxJ1 in model systems such as the zebrafish and
Xenopus appears to be necessary and sufficient for the development of
motile cilia ([141]Stubbs et al., 2008; [142]Yu et al., 2008).
Therefore, determining the predicted regulatory network of FOXJ1, might
in turn, help us to better understand ciliogenesis and ciliopathies
associated with abnormal ciliary differentiation and function in
humans. In order to study the regulatory network that is essential in
motile cilia development, we have predicted the genes that are likely
to be transcriptionally regulated, directly or indirectly, by FOXJ1 and
associated them with known or probable ciliary roles. Based on the
presence of FOXJ1 cis-regulatory sites in upstream/downstream region of
transcription start sites of FIG ([143]Choksi et al., 2014a), we could
identify that a large fraction of the FIG (424/572) are directly
regulated by FOXJ1 ([144]Supplementary Figure 1B and [145]Supplementary
Table 1). It is likely that the other 148 induced genes either contain
FOXJ1 binding sites in distant enhancers or are indirectly regulated by
FOXJ1 via other transcription factors directly activated by FOXJ1.
Further, the FOXJ1 protein appears to have a binding preference toward
the consensus sequence NNN[GA]TAAACAAANNNN ([146]Supplementary Figure
1C). Additionally, functional annotations for these genes were
retrieved from the CCR, and the identified known ciliary associations
for genes directly and indirectly regulated by FOXJ1 were classified
into functional cohorts (Assigned Ciliary Role) manually
([147]Supplementary Table 2).
Additional Ciliary Association for FOXJ1 Regulatory Network Genes Based on GO
Analysis
Functional enrichment analysis of proteins associating with one another
under a particular context may provide an idea regarding the probable
collective activities and the most likely functions that these proteins
may have in this context. At the outset, GO mapping elucidated 20
transcription factors (associated with DNA binding or transcription
factor ontology class) among the FIGp ([148]Supplementary Table 2).
Further, predicted ciliary associations were determined based on GO
enrichment analysis ([149]Supplementary Table 3). In the GO mapped
data, we found groups of genes having similar functions (co-associated
genes) ([150]Huang da et al., 2009a,[151]b) belonging to multiple GO
annotation categories, and such co-associated genes from different
annotation clusters were grouped and categorized into common ‘GO based
Ciliary Association(s)’ ([152]Supplementary Table 3).
In this manner, we were able to assign possible ciliary roles to 102
(directly) and 35 (indirectly) regulated genes based on the CCR dataset
([153]Supplementary Table 2), and 17 (directly) and 6 (indirectly)
regulated genes with the help of the GO analysis ([154]Table 1). Based
on the CCR dataset based annotation, we could assign ciliary
associations such as participating in ‘ciliary structural assembly or
motility’ for most of the directly (82) and indirectly (26) regulated
FOXJ1 target genes ([155]Figure 1 and [156]Supplementary Figure 2).
Briefly, this analysis elucidated that FOXJ1 primarily influences
‘ciliary structural assembly or motility’ by regulating three classes
of proteins. These classes include ‘proteins that act as structural
constituents of cilia’ (axoneme assembly, IFT complex, centrosome
component, basal body associated), ‘proteins that regulate the
structural assembly of cilia’ (cilia assembly, ciliogenesis) and
‘proteins that have a role in ciliary function’ (like ciliary transport
or motility) ([157]Figure 1, [158]Supplementary Figure 2, and
[159]Supplementary Table 2). A fraction of directly regulated (24.06%)
and indirectly regulated (23.65%) FIG shared an overlap with the CCR
dataset, and as such many FIG could not be associated with ciliary
roles in this manner ([160]Supplementary Table 2). Thus, having studied
the FOXJ1 transcriptional network, it became apparent that the majority
of genes that have been identified or extensively characterized are
structural components of cilia. However, based on ‘cilia associated
expression analysis,’ 84.67% of directly and 81.76% of indirectly
regulated genes were found to be expressed in multiple motile ciliated
tissues and some are differentially expressed in PCD
([161]Supplementary Figures 3A–C and [162]Supplementary Table 2).
Further, it has been established that signaling pathways like Notch,
Fgf and Wnt ([163]Neugebauer et al., 2009; [164]Lopes et al., 2010;
[165]Caron et al., 2012) are known to be involved in motile cilia
biology. In this context, we were interested in studying the regulatory
network proteins in a broader context including the associated
protein–protein interactions, in order to identify the key connector
proteins (regulatory network proteins) that relay the information onto
the signaling component within the cell. Additionally, it is possible
that disruptions in some of these network interactions or genes causing
PCD may alter the motile cilia interactome, in turn leading to
ciliopathies. Therefore, we were interested in studying the probable
signaling network/s acting concurrently or in response to FOXJ1
activation involved in this process. In order to achieve this, we have
subsequently analyzed the PPIN associated with FOXJ1 and its induced
proteins, and studied the probable role(s) of the identified essential
or effector proteins in the network.
Table 1.
Novel predicted functions of FOXJ1 regulated genes based on gene
ontology analysis.
S. No FOXJ1 Target Gene ^1Effect ^2Assigned Ciliary Role
1 RABGAP1L Direct Cilia associated by localization
2 DNAH8 Direct Ciliary structure/motility
3 TPPP3 Direct Ciliary structure/motility
4 NME9 Direct Ciliary structure/motility
5 DNAH17 Direct Ciliary structure/motility
6 TPGS1 Direct Ciliary structure/motility
7 EML5 Direct Ciliary structure/motility
8 SYBU Direct Ciliary structure/motility
9 HSBP1 Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
10 MYCBP Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
11 ATXN1 Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
12 BARHL2 Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
13 LMX1A Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
14 MEOX2 Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
15 PAX8 Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
16 RXRB Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
17 ZBTB22 Direct Regulates genes involved in ciliary assembly/motility
(Transcription factor)
18 TUBA3D Indirect Ciliary structure/motility
19 NR1H2 Indirect Regulates genes involved in ciliary assembly/motility
(Transcription factor)
20 FOSB Indirect Regulates genes involved in ciliary assembly/motility
(Transcription factor)
21 ATF5 Indirect Regulates genes involved in ciliary assembly/motility
(Transcription factor)
22 CHD4 Indirect Regulates genes involved in ciliary assembly/motility
(Transcription factor)
23 ELF3 Indirect Regulates genes involved in ciliary assembly/motility
(Transcription factor)
[166]Open in a new tab
^1Effect: Direct/Indirect depending on whether the gene is directly or
indirectly regulated by FOXJ1. ^2Assigned Ciliary Role: Predicted
ciliary role based on gene ontology analysis.
FIGURE 1.
[167]FIGURE 1
[168]Open in a new tab
Directly regulated genes in the predicted FOXJ1 gene regulatory network
and possible ciliary processes mediated by them. FOXJ1 directly
regulates genes that are involved in ciliary structure assembly and
motility, as depicted here. Known ciliary associations were derived
from the collated ciliary resource. Additionally, the probable roles of
some genes predicted based on gene ontology analysis have also been
included here. The genes and edges are color coded to indicate the
processes the genes regulate or are involved in (genes associated with
more than one process are not colored).
Essential or Important Interacting Proteins in Representative Motile Cilia
Network
Identification of IIP in the FOXJ1 regulatory network or possible
essential proteins in the motile cilia protein interactome may be
achieved with extensive computational analysis of the PPIN likely to be
associated with the FIGp. Scale free biological networks that follow a
power law exhibit certain characteristic topological properties, which
may be studied with different graph theory based metrics in pursuance
of inferences regarding the PPIN ([169]Barabási and Oltvai, 2004;
[170]Yook et al., 2004; [171]Yu et al., 2007). Therefore, with the help
of high confidence physical interaction data from different
protein-protein interaction databases including cilia specific
datasets, a re-constructed PPIN (FIG-sub-network) was prepared. The
FIG-sub-network comprised of 6493 primary interactors of FIGp (434) and
their first level interactors participating in 40,608 interactions
([172]Figure 2A). Networks conforming to the power law must have
p-value higher than 0.1 ([173]Clauset et al., 2009), and the p-value of
the estimated fit of the degree distribution to the power law
determined herein was found to be 0.71. Thus, it was concluded that the
re-constructed network was a scale free network ([174]Figure 2B).
FIGURE 2.
[175]FIGURE 2
[176]Open in a new tab
PPIN analysis of primary interaction network of FIG-sub-network
proteins. (A) The scale free network comprising of largest connected
component of primary interaction network of FIGp considered for the IIP
analysis is shown here. (B) The degree distribution plot and the
p-value for goodness of fit of the power law to the degree distribution
as determined by the Kolmogorov-Smirnov test is represented here. (C)
The number of proteins identified in each category (hub, bottleneck,
central, local network perturbing and global network perturbing
protein) considered during IIP analysis are indicated in the Venn
diagram. (D) The number of proteins that could be associated with cilia
based on ‘cilia associated expression analysis’ that were considered as
IIP is shown here. Abbreviations: FIG, FoxJ1 induced genes; FIGp, FIG
encoded protein; IIP, Important interacting proteins; PPIN,
protein-protein interaction network.
Network Analysis of Representative Motile Cilia Interactome (Primary
Interaction Network of FIGp)
Topologically important proteins in a scale free PPIN like hub,
bottleneck and central proteins, may be identified with the help of
different graph theory based measures, and such proteins could be
essential for the network integrity or function ([177]Barabási and
Oltvai, 2004; [178]Yu et al., 2007; [179]Pavlopoulos et al., 2011). In
this respect, in silico node deletion that resulted in significant
changes in network topology were studied as a measure of centrality,
and 85 local network perturbing and 13 global network perturbing
proteins were identified ([180]Figure 2C). The overlap among these
network perturbing proteins and other topologically important proteins
[hub (243), bottleneck (86), and central (166)] was studied, and
proteins identified as important in two or more metrics, were
identified as IIP (122) ([181]Figure 2C and [182]Supplementary Table
4). Genes may be associated with cilia based on their expression, and
such expression-based evidences from multiple studies might further
strengthen our assumption that IIP possibly interact with FIGp in the
ciliary interactome. We have taken into consideration expression
information at the mRNA or protein levels in multiple motile ciliated
tissues or differential expression (mRNA) information from studies
exploring cilia biogenesis or ciliopathies as indicated in the ‘cilia
associated expression analysis’ ([183]Figure 2D). Further, the
distribution pattern of the 121 cilia expressed IIP in multiple motile
ciliated tissues elucidated that 114 among them were expressed in all
ciliated tissues considered here ([184]Supplementary Figure 3D and
[185]Supplementary Table 4). Moreover, among these proteins, 6 were
found to be associated with PCD based on the differential expression
analysis ([186]Supplementary Figure 3E) [the randomization analysis
indicated that this observation is significant at 10% level of
significance]. Further, the observation that 33 IIP had established
roles in ciliogenesis and/or cilia function suggested that the
identified IIP could indeed have essential roles in motile cilia or PCD
pathogenesis ([187]Supplementary Table 4) [based on the randomization
analysis this observation is significant at 1% level of significance].
IIP and Their Probable Essential Roles in Motile Cilia Interactome
Among the thousands of interacting proteins in the motile cilia
interactome, 121 crucial interacting proteins were identified in the
representative motile cilia interactome (primary interaction network of
FIGp). These IIP form an inter-connected module in the ciliary
interactome including 2060 interactions among FIGp (246), IIP (120) and
their primary interactors (1666 motile cilia expressed proteins)
([188]Figure 3A). Such IIP that have extensive interactions with FIGp
could possibly be involved in the coordinated assembly of functional
motile cilia in association with FIGp. Such interacting proteins namely
FIGp and IIP, based on the concept of ‘guilt by association’
([189]Oliver, 2000; [190]Schwikowski et al., 2000), may participate in
the same or similar cellular pathways, possibly involved in
ciliogenesis. In order to further determine the cellular pathways that
the IIP might participate in together with FIGp, we have performed
Reactome pathway enrichment analysis among the IIP and FIGp that were
found to be interacting. Pathways such as signal transduction,
developmental biology, cell cycle, generic transcription pathway,
immune system etc. were found to be significantly enriched among these
proteins ([191]Figure 3B and [192]Supplementary Table 5). This suggests
that in addition to acting as structural components of the ciliary
organelle, FIGp, in association with IIP, may participate in different
signaling pathways, cell cycle and developmental biology associated
processes or regulate transcription of other genes during motile cilia
development.
FIGURE 3.
[193]FIGURE 3
[194]Open in a new tab
Inter-relationship among IIP and FOXJ1 regulatory network proteins or
FIGp. (A) The IIP (120) and their primary interactors form an
inter-connected module with FIGp (246) within the motile cilia
interactome as depicted here. (B) Cellular pathways that the
inter-connected FOXJ1 regulatory network proteins and IIP (enriched
pathways with p-value lower than 1e^−05) are likely to be involved in
are shown. Abbreviations: F.C., Fold change; FIG, FoxJ1 induced genes;
FIGp, FIG encoded protein; IIP, Important interacting proteins; PCD,
Primary ciliary dyskinesia.
Important Effector Proteins in the FOXJ1 Regulatory Network Possibly Involved
in Ciliary Biology
As outlined above, by extensively analyzing the probable motile cilia
interactome, we have determined topologically important proteins in the
network. Further, we could identify a module comprised of 246 FIGp and
topologically important proteins that are mainly signaling proteins.
While such IIP may be essential in the ciliary milieu and possibly
functionally relevant, another pertinent question is which proteins in
the FOXJ1 regulatory network might act as essential modulators that
relay the information onto the signaling component. To address this
question, firstly we have considered whether genes that are induced
upon FoxJ1 over-expression have been identified as IIP. In this
respect, we have found that in particular 16 IIP in the regulatory
network interact with multiple other FIG (26), IIP (68) and other
expression associated ciliary interactome proteins (1255) ([195]Figure
3A). These FIGp that share extensive interactions with topologically
important proteins in the motile cilia interactome are possibly key
mediators acting downstream of FOXJ1 activation that in turn
participate in ciliogenesis or maintenance of ciliary function.
Moreover, genes may be associated with ciliogenesis or PCD based on
their differential expression in respiratory epithelial cells of
patients with PCD. Interestingly, an additional set of 4 IIP that were
found to be differentially expressed in a PCD case study also had
associations with multiple FIGp ([196]Figure 3A). Thus, such IIP found
to be directly involved in the FOXJ1 regulatory network have been
classified as important interacting protein effector (IIP-effector) in
the FOXJ1 regulatory network. In addition, IIP that have possible
associations with PCD and the FOXJ1 regulatory network (via
intermediate FIGp), have also been classified as IIP-effector in the
FOXJ1 regulatory network ([197]Table 2). While some of these effector
proteins (HSP90AA1, CDC42, ACTN2, SSX2IP, PLSCR1, PIAS4) have
previously documented roles in ciliogenesis ([198]Choi et al., 2013;
[199]Choksi et al., 2014a; [200]Croft et al., 2014; [201]Klinger et
al., 2014; [202]Ramachandran et al., 2015; [203]Kohli et al., 2017;
[204]Fabregat et al., 2018), we report here a set of 14 novel proteins
that may act as crucial mediators in the FOXJ1 regulatory network
([205]Table 2).
Table 2.
IIP-effector proteins in FOXJ1 regulatory network.
IIP-effector Category Gene Name ^1IIP category ^2GO association
(Ciliary) ^3Comment
IIP directly regulated by FOXJ1 ATXN1 HUB and BP and CP
EEF1A1 HUB and BP and CP Associated with BBSome proteins ([206]Figure
4), could be involved in cargo trafficking to cilia
FKBP5 HUB & BP Protein folding (GO) [GO:0006457∼protein folding]
PIAS4 HUB and CP PIAS4 regulates SUMOylation of Glis2/NPHP7, which is a
transcriptional regulator mutated in type 7 nephronophthisis
([207]Ramachandran et al., 2015)
PLSCR1 HUB and BP Cilia phenotype defects occur upon knockdown
([208]Choksi et al., 2014a)
SOCS3 HUB and CP
SSX2IP HUB and CP Cilium morphogenesis (GO) [GO:0042384∼cilium
assembly, GO:0060271∼ cilium morphogenesis, GO:0035735∼intraciliary
transport involved in cilium morphogenesis SSX2IP targets Cep290 to the
ciliary transition zone. Cep290 takes a central role in gating proteins
to the ciliary compartment ([209]Klinger et al., 2014)
STOM HUB and BP and CP
SYNCRIP HUB and BP
MEOX2 HUB and BP and CP
NLGN3 HUB and BP
FAM19A3 HUB and BP
IIP indirectly regulated by FOXJ1 APOE HUB and CP Cytoskeleton
organization (GO)[GO:0007010∼ cytoskeleton organization]
DLG4 HUB and BP Establishment or maintenance of epithelial cell
apical/basal polarity (GO) [GO:0045197]
FOXJ1 directly regulated IIP showing differential expression (mRNA) in
PCD ACTN2 CP and GNPP Actin filament organization (GO)[GO:0051695∼actin
filament uncapping, GO:0005884∼actin filament], Cytoskeleton
organization (GO) [GO:0005856∼cytoskeleton] RhoA dependent actin
remodeling for establishment of an apical web-like structure of actin
for basal body docking and axoneme growth ([210]Kohli et al., 2017)
CASP8 HUB and BP and CP
IIP showing differential expression (mRNA) in PCD BTRC HUB and BP and
CP Protein ubiquitination (GO)[GO:0000209∼protein polyubiquitination,
GO:0006511∼ubiquitin-dependent protein catabolic process,
GO:0043161∼proteasome-mediated ubiquitin-dependent protein catabolic
process], Cell cycle (GO)[GO:0051726∼regulation of cell cycle]
HSP90AA1 HUB and BP and CP Protein folding (GO)[GO:0006457∼protein
folding] Participates in cilium assembly according to Reactome database
([211]Croft et al., 2014; [212]Fabregat et al., 2018)
TERF1 HUB and CP
CDC42 HUB & CP Establishment or maintenance of cell polarity
(GO)[GO:0007163∼establishment or maintenance of cell polarity], Small
GTPase mediated signal transduction (GO) [GO:0007264∼small GTPase
mediated signal transduction], Cytoskeleton organization
(GO)[GO:0030036∼actin cytoskeleton organization], Actin filament
organization (GO) [GO:0051017∼actin filament bundle assembly] Cdc42
docks vesicles carrying ciliary proteins and localizes the exocyst to
primary cilia. CDC42 deficiency results in deranged ciliogenesis and
polycystic kidney disease ([213]Choi et al., 2013).
[214]Open in a new tab
The identified IIP-effector proteins that figure at the interface of
the FOXJ1 regulatory network and the associated PPIN are listed here.
The possible roles of some of these IIP-effectors and their primary
interactors in cilia are also outlined. ^1IIP category: Different graph
theory metric categories (e.g., hubs: HUB, central proteins: CP,
bottleneck proteins: BP and global network perturbing proteins: GNPP)
that have identified the protein as topologically important. ^2GO
association (Ciliary): Predicted GO association of IIP-effector.
^3Comment: Reports whether this protein has been previously associated
with cilia assembly or function.
Previously, we have determined that the regulatory network proteins
forming a part of the inter-connected module interact primarily with
signaling proteins in motile ciliated cells ([215]Figure 3B).
Therefore, in order to determine which cellular pathways/processes
these IIP-effectors might be participating in within the ciliary
interactome, we have again utilized the concept of ‘guilt by
association.’ GO mapping suggested the involvement of DLG4 and CDC42 in
maintenance of cell polarity (establishment or maintenance of
epithelial cell apical/basal polarity [GO: 0045197], establishment or
maintenance of cell polarity [GO: 0007163], respectively) ([216]Table 2
and [217]Figure 4). Moreover, the pathway enrichment analysis revealed
the probable existence of a number of ‘cilia associated signaling
pathways’ among IIP-effectors and their primary interactors. Further,
based on this analysis, we could identify topologically important
signaling proteins in the FOXJ1 regulatory network which are
essentially IIP-effectors that were found to be related to or had
involvement in some ‘cilia associated signaling pathways.’ In this
respect, FOXJ1 effector proteins SYNCRIP and BTRC participate in
pathways that regulate motile cilium development like cell cycle, Fgfr,
Wnt and Notch signaling ([218]Supplementary Table 6 and [219]Figure 4).
CASP8, SOCS3, BTRC, PIAS4 (IIP-effector) and their primary interactors
might participate in pathways implicated in primary cilium development
and function like TGF-beta, Hedgehog and Toll-like receptor signaling
([220]Supplementary Table 6 and [221]Figure 4). Thus, it appears that
these pathways could also be important in motile cilia development
and/or function. Importantly, different FOXJ1 regulatory network genes
either code for topologically important signaling proteins (CASP8,
SOCS3, SYNCRIP) or form extensive cross-talk with topologically
important signaling proteins (BTRC, HSP90AA1, CDC42). Further, these
‘protein-pathway’ associations have not previously been studied in the
context of ciliogenesis which may be analyzed in further studies.
FIGURE 4.
[222]FIGURE 4
[223]Open in a new tab
IIP-effectors in FOXJ1 regulatory network and their probable ciliary
associations. Probable cilia associated pathways or processes that the
IIP-effectors and their network interactors may participate in were
determined with the help of pathway enrichment and GO analysis and such
possible ciliary role(s) of each IIP-effector is depicted. The edge
color denotes the ciliary process(es) or pathway(s) the gene/protein
is/are associated with. Fold changes in genes differentially expressed
in Choksi et al. expression study ([224]Choksi et al., 2014a) or PCD
case study ([225]Geremek et al., 2014) are mapped onto the protein
nodes.
Discussion
Here, extensive computational analysis of the FOXJ1 regulatory network
and the PPIN associated with it were undertaken to identify essential
proteins in the motile cilia interactome and key effector proteins in
the FOXJ1 regulatory network that possibly mediate the functional
role(s) of FOXJ1. With the help of GO and enrichment analysis of FOXJ1
regulatory network genes, we could identify additional transcription
factors and other proteins associated with ciliary structure or
motility among FIGp. For instance, directly regulated transcription
factors MYCBP and HSBP1 have predicted ciliary associations based on GO
analysis, and additional literature studies also indicated that it is
likely that MYCBP and HSBP1 may also play a role in ciliogenesis. This
is because MYCBP is known to regulate Hedgehog signaling ([226]Lin et
al., 2014) and also interacts with A-kinase anchoring proteins
([227]Rao et al., 2016) that are involved in regulating dynein-driven
motility, and HSBP1 may be involved in Wnt signaling pathway
([228]Eroglu et al., 2014). Similarly, indirectly regulated genes, ATF5
and CHD4 that participate in maintaining centrosome integrity
([229]Sillibourne et al., 2007; [230]Madarampalli et al., 2015), could
also have additional ciliary roles as transcription factors in cilia
[defects in centrosome structure or function may lead to ciliopathies;
[231]Bettencourt-Dias et al., 2011)]. We observed that the annotated
transcriptionally regulated proteins (∼24% of FIGp) mainly comprised of
ciliary structural component proteins, mutations in which may be
associated with ciliary ultrastructure defects occurring in PCD.
However, the other FIGp could also be involved in regulating the
assembly or function of cilia in association with other proteins
expressed in ciliating cells. In order to identify possible essential
proteins for motile cilia development or function, we have studied the
PPIN associated with FOXJ1 regulatory network proteins with the
assumption that it represents the motile cilia interactome. A number of
IIP (121) were identified with the help of an in silico node deletion
analysis and standard graph theory measures computed based on degree,
shortest path and centrality. Furthermore, 33 IIP had previously
reported ciliary roles, and it is likely that such topologically
important proteins participating in multiple signaling pathways, cell
cycle, generic transcription, developmental biology etc. may act as
essential proteins in cilia development or function.
Interestingly, 120 IIP along with 246 FIGp form an inter-connected
module in the ciliary interactome. Moreover, genes may be associated
with a condition based on their differential expression under a
diseased state. Thus, differentially expressed genes occurring in PCD
patients may be considered as genes associated with motile cilia
biogenesis or function. Similarly, genes that are differentially
expressed in in vitro model systems wherein motile ciliogenesis is
perturbed could also be associated with motile cilia biogenesis or
function. We have mapped such associations based on expression analysis
([232]Edgar et al., 2002; [233]Choksi et al., 2014a; [234]Geremek et
al., 2014) onto our predicted motile cilia interactome. These
associated genes (proteins) figure at the interface of the FOXJ1
regulatory network and the associated protein interaction network, and
we have classified such IIP as important effector proteins in the FOXJ1
regulatory network. 16 FOXJ1 regulated IIP-effectors share extensive
connections with the FOXJ1 regulatory network proteins and some cilia
specific PPIN proteins. Subsequently, we have tried to establish the
most likely roles of these IIP-effectors in ciliary biology based on
the assumption that interacting proteins may share similar cellular
functions (‘guilt by association’). Pathway enrichment analysis
elucidated that some of these IIP-effectors act as signaling proteins.
The IIP-effectors and its interacting partners in the interaction
module are particularly involved in Wnt, Notch, Fgfr, Hedgehog,
Tgf-beta and Toll-like receptor signaling pathways downstream of FOXJ1
activation. This is in accordance with previous reports wherein Notch,
Wnt and Fgf signaling pathways have been shown to regulate processes
like left-right patterning, cilia length or number in motile cilia
bearing cells ([235]Neugebauer et al., 2009; [236]Lopes et al., 2010;
[237]Caron et al., 2012). It is likely that the ‘topologically
important signaling proteins’ form a crucial link between the FOXJ1
regulatory and cilia biogenesis associated signaling components in the
motile cilium. In particular, BTRC and CASP8 (PCD associated
IIP-effector), along with their primary interactors in the ciliary
interactome, are possibly involved in mediating Toll-like receptor
signaling. Moreover, PCD patients generally are susceptible to
recurrent respiratory infections ([238]Alanin et al., 2015) which have
been attributed to impaired mucociliary clearance due to cilia motility
defects. However, these patients may additionally have impaired TLR
signaling that mediate innate immune responses ([239]Kawasaki and
Kawai, 2014) or innate immune response pathways due to defects in PCD
associated IIP-effectors or their interactome. Other IIP and FIGp also
have possible involvement in innate immune responses and Toll-like
receptor signaling cascades. Further, IIP-effectors like EEF1A1 and
DLG4 were found to be related to well-known processes involved in
ciliary biology like maintenance of cell polarity and intra-flagellar
transport. EEF1A1 (directly regulated IIP-effector), a small GTPase
protein, is likely to be involved in intra-flagellar transport because
of its interactions with multiple BBSome component proteins and it has
also been reported as an intra-flagellar transport cargo protein
([240]Engel et al., 2012). Likewise, the indirectly regulated
IIP-effector DLG4 may be involved in establishing or maintaining
apico-basal polarity of cells during ciliogenesis (as predicted by our
GO mapping). Therefore, based on cilia associated expression analysis,
literature studies, GO and pathway analysis we could rationalize the
involvement of the identified topologically important effector proteins
in cilia biogenesis or function. Additional experimental studies will
help establish their causal link to PCD.
Conclusion
In conclusion, by analyzing the FOXJ1 associated motile cilia
interactome comprised of predicted PPIN of the FOXJ1 regulatory network
proteins, we have identified topologically important effector proteins
in the motile cilia interactome and FOXJ1 regulatory network. Moreover,
we have rationalized their possible roles in ciliary biology with the
help of GO and enrichment analysis. We propose that defects in the
function(s) of such essential genes may be associated with impaired
ciliary development or function, and this list of genes will be useful
for screening and diagnosis of novel PCD associated mutations in the
future.
Data Availability
Expression analysis datasets are available in a publicly accessible
repository. [241]Choksi et al. (2014a) dataset utilized in this study
can be found at Array Express
([242]https://www.ebi.ac.uk/arrayexpress/) under accession number
[243]E-MTAB-2815 and the PCD case study dataset can be accessed at GEO
([244]https://www.ncbi.nlm.nih.gov/geo/) under accession number
[245]GSE25186
. The raw data [collated ciliary resource (prepared from ciliary
reference databases and other literature studies)] supporting the
conclusions of this manuscript will be made available by the authors,
without undue reservation, to any qualified researcher. All other
relevant data generated/analyzed for this study are included in the
manuscript and the [246]Supplementary Files.
Author Contributions
SC, SR, and IM formulated the study design. IM performed the
experiments. SC, IM, and SR analyzed and interpreted the results. IM,
SR, and SC prepared the manuscript. All authors read and approved the
final version of the manuscript.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a
potential conflict of interest.
Acknowledgments