Disruption of murine Tcte3-3 induces tissue specific apoptosis via co-expression of Anxa5 and Pebp1

Computational Biology and Chemistry 53 (2014) 214–225

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Computational Biology and Chemistry journal homepage: www.elsevier.com/locate/compbiolchem

Disruption of murine Tcte3-3 induces tissue specific apoptosis via co-expression of Anxa5 and Pebp1 Zahida Parveen a , Zohra Bibi a , Nousheen Bibi a , Juergen Neesen b , Sajid Rashid a, * a b

National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan Institute of Medical Genetics, Medical University of Vienna, Austria

A R T I C L E I N F O

A B S T R A C T

Article history: Received 26 May 2014 Received in revised form 12 October 2014 Accepted 21 October 2014 Available online 24 October 2014

Programmed cell death or apoptosis plays a vital physiological role in the development and homeostasis. Any discrepancy in apoptosis may trigger testicular and neurodegenerative diseases, ischemic damage, autoimmune disorders and many types of cancer. Tcte3 (T-complex testis expressed 3) is an accessory component of axonemal and cytoplasmic dynein which expresses predominantly in meiotic and postmeiotic germ cells. It plays an essential role during spermatogenesis; however, to explore its diverse and complex functioning in male germ cell apoptosis, requires further prosecution. Here, 2D-gel electrophoresis, mass spectrometry and qRT–PCR analyses were performed to elucidate the differential expression of genes, in both wild-type and homozygous Tcte3-3 mice. We observed an increased expression of Tcte3 in homozygotes as compared to wild-type testes. Perpetually, an increased expression of Anxa5 and Pebp1, while a lower expression of Rsph1 was detected in Tcte3-3
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mice. We propose that over-expression of Pebp1 and Anxa5 in Tcte3-3
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testes might be due to increased apoptosis. To evaluate this possibility, testes specific microarray data set extracted from NCBI gene ontology omnibus (GEO) was used to cluster the possible co-expression partners of Tcte3. Further functional coherence of compiled candidate genes was monitored computationally by studying the common TFBS overlapped at the regulatory regions. Differential expression of Tcte3-3 and its involvement in apoptosis may provide a basis for the investigation of transcriptional specificities of other Tcte3 paralogs (Tcte3-1 and Tcte3-2). A complete understanding of controlling factors which have implications in regulating tissue-specific Tcte3 expression would provide additional insights into the gene control events. The collective knowledge may prove useful for the development of novel therapeutic regimen and would open new avenues in defining selective roles of Tcte3 in germ cell development. ã 2014 Elsevier Ltd. All rights reserved.

Keywords: Apoptosis Tcte3 Spermatogenesis qRT–PCR 2D-gel electrophrosis Transcription factors binding sites (TFBS)

1. Introduction The coordinated balance and tight regulation among cell proliferation, differentiation and apoptosis is critical to control various biological events. The process of programmed cell death or apoptosis plays a critical physiological role in development and homeostasis (Steller, 1995; Jacobson et al., 1997). Apoptosis is considered as a vital component of various processes including spermatogenesis, neurogenesis, normal cell turnover, proper development and functioning of the immune system, hormone-dependent atrophy, embryonic development and chemical-induced cell death (Oppenheim, 1991; de Rooij and Grootegoed, 1998). Any alteration or inappropriate apoptosis (either too little or too much) may lead to the onset of a number

* Corresponding author. Tel.: +92 90644107 E-mail address: [email protected] (S. Rashid). http://dx.doi.org/10.1016/j.compbiolchem.2014.10.005 1476-9271/ ã 2014 Elsevier Ltd. All rights reserved.

of abnormalities including testicular diseases (de Rooij and Grootegoed, 1998), neurodegenerative diseases, ischemic damage, autoimmune disorders and many types of cancer. Although many of the key apoptotic proteins have been identified, the complete understanding of molecular mechanisms and signaling pathways that control cell cycle arrest and apoptosis need to be explored which contemplate designing therapeutic strategy to modulate the apoptotic effecter machinery (Strasser et al., 2000; Levy and Holzbaur, 2006). Recently, it has been reported that dyneins have both direct and indirect roles in male germ cell apoptosis which results in male infertility phenotype (Rashid et al., 2010). Dynein is a large multi-subunit protein complex that powers minus end-directed movement along microtubules. It consists of two heavy chains of 530 kD (Paschal et al., 1987; Holzbaur and Vallee, 1994), that constitute the motors themselves. It also contains a number of noncatalytic subunits, conspicuously two intermediate chains of 74 kD, four light intermediate chains of 55 kD and a number of less

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(0.75 mm thickness). SDS-PAGE was run for 1.5 h at 12.5 mA/gel. The gel was stained with Roti Blue stain according to the specified protocol (Roth) and placed between the two sheets of cellophane. The gel spots were detected by PD-Quest Software (Bio-Rad), scanned and labeled.

characterized light chains such as LC8, Tctex1 or Rp3 and Tcte3 (Rappold et al., 1992; King et al., 1998; Hirokawa et al., 2010). Dyneins are classified into two functional categories: axonemal and cytoplasmic (Paschal et al., 1987; Pazour et al., 1999; Sakakibara et al., 1999). Axonemal dyneins are responsible for the movement of cilia and flagella, while cytoplasmic form of dynein serves many cellular functions, including regulation of mitotic checkpoint (Howell et al., 2001), organization of the Golgi apparatus (Vaughan, 2005), minus-end-directed transport of vesicles including endosomes and lysosomes. They also carry out retrograde axonal transport in neurons (Vallee et al., 2004) and implicate in the clearance of protein aggregates (Ravikumar et al., 2005). Tcte3 is a component of outer dynein arm complex, initially characterized in Chlamydomonas as a homolog of LC2 (light chain 2) (Patel-King et al., 1997). Although Tcte3 is predominantly expressed in testis, its expression had also been monitored in several other tissues lacking cilia or flagella (DiBella et al., 2001; Neesen et al., 2002). Previously, we reported that at least three copies of Tcte3 exist in mouse genome and subsequent inactivation of Tcte3-3 copy results in sperm motility defects thereby resulting in partial male infertility phenotype (Rashid et al., 2010). Evidently, Tcte3-3
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testis exhibited an increased rate of apoptosis in spermiogenesis. It is however unclear why loss of Tcte3-3 results in apoptosis of male germ cells. Here, in an effort to identify the possible role of Tcte3 in sperm development, we employed a set of experimental and in-silico based approaches. Our findings elucidated several co-expressed partners of Tcte3 including Anxa5 and Pebp1, whose functional coherence may help in better understanding of apoptotic induction.

Gel pieces corresponding to the indicated spots were isolated and added into 50 ml of H2O. Individual samples were destained by adding 50 ml of 50:50 Acetonitrile (ACN) and H2O followed by incubation for 15 min. The solution was pulled off and added fresh ACN until the stain was completely removed. Later on, 100 ml of 100 mM ammonium bicarbonate was added into the samples and equilibrated through 20 min incubation. The samples were treated with 100 ml ACN followed by another 15 min incubation. The solution was completely removed and samples were dried by speed-vac. Samples were subjected to trypsin digestion by adding digestion buffer (5 ml of 1 M CaCl2, 25 ml of 1 M ambic and 12.5 ml of trypsin) and incubating them on ice for 45 min. The digestion buffer was replaced by 50 ml buffer without trypsin with an overnight incubation at 37  C. The supernatant was transferred into new tubes followed by addition of 40 ml tri-floric acid (TFA). The tubes were incubated in the sonicating water bath for 20 min. Peptides resulting from the digest were twice extracted from the gel pieces with TFA and a gradient of ACN. The samples were dried and analyzed by Q-TOF (UMG, Goettingen). The acquired MS/MS spectra were used to search the non redundant database (http://www.ncbi.nlm.nih.gov) using the SEQUEST program (Eng et al., 2008).

2. Materials and methods

2.5. Real time PCR

2.1. Sample preparation

Roche light cycler 480 SYBR green real time kit was used to conduct quantitative PCR using 4 ml of SYBR green I mastermix, 3.5 ml of water, 0.5 ml of 0.25 mg cDNA and 1 ml of each 10 mM reverse and forward primer (Table 1) total 10 ml reaction mix. Amplification conditions for Light Cycler 480 multi well 384 well plates were used according to standard protocol (Roche Applied Science).

Tcte3-3
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mice (Rashid et al., 2010) were obtained from Institute of Human Genetics, Goettingen, Germany and kept at the animal facility of NCB, Quaid-i-Azam University (www.qau.edu. pk). Tcte3-3 gene was originally disrupted in mixed genetic (129/SvJ/C57BL/6J) background by homologous recombination. Later on, 20 adult male mice were sacrificed by CO2 overdose as approved by the Animal Care and Use Committee of the University of Goettingen, Germany. Testicular and brain tissues were dissected from wild-type and Tcte3-3 homozygous animals and immediately stored in the liquid nitrogen until use. Tissues were thawed, incubated in Lysis buffer (9 M urea, 4% CHAPS, 1% DTT, 10 mM PMSF) and homogenized by sonicating the samples on ice (Vibra Cell sonicator) five times for 5 s. Then resulting lysates were clarified by centrifugation and soluble portion was transferred into new tubes.

2.4. Protein identification

2.6. Microarray data mining Apoptosis related experiments from NCBI gene expression omnibus (GEO) database were shortlisted for testis and brain using stringent filters like specie, tissues and GO processes. Shortlisted testes data set having the accession numbers GDS2923 was retrieved. One experiment from each of control and treated group was randomly selected and employed in the current study. 2.7. Expression based data processing through networking

2.2. Acetone precipitation Acetone was added into the sample tubes followed by overnight incubation at
20  C. Later on, samples were centrifuged at 14,000 rpm for 20 min. The resulting pellet was dried in air and dissolved in 200 ml lysis buffer (9 M urea, 4% CHAPS). The concentration was measured by Bio-Rad assay as described by the manufacturer (Bradford, 1976). 2.3. 2D-PAGE analyses 200 mg of total protein in a volume of 50 ml was used for each 2D-gel experiment. Isoelectric focusing was carried out by using 2.0% ampholines (pH 3.5–10) and 9 M urea for 8000 V–1.30 h. The second dimension was run on a 10% Tris-Glycin acrylamide gel

Cytoscape tool version 2.8.3 (Shannon et al., 2003) was used for assembling the tissue specific networks for testes data. In order to get rid of genes with low information content, gene clusters were developed using expression value (Eq. (1)) and divided into three Table 1 List of the primers used for the amplification of Tcte3, Anxa5 and Pebp1 along with two internal controls Gapdh and beta-actin. Gene name

Forward primer (50 –30 )

Reverse primer (50 –30 )

Tcte3 Anxa5 Pebp1 Gapdh Beta-actin

ACCGGCCAAACGCATCAATC CTCAGGCATTGTTCCAGGCT TGTTGTACTCTGATAGCCCG GGTGAAGGTCGGTGTGAACG CCACAGCTGAGAGGGAAATC

TTTTGCCAGGGCACTTTTCC TAGACTTCACGACAGCCAGG GTCTCCACCTTGAACTTGCC CTCGCTCCTGGAAGATGGTG ACCGCTCGTTGCCAATAGTG

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3. Results

groups (up-regulated, down-regulated and non-significant). DExpvalue ¼ TTExpvalue
CTExpvalue

(1)

where DExpvalue = difference in expression value, TTExpvalue = treated test value of gene expression and CTExpvalue = control test value of gene expression. Negative value indicates down-regulated, positive value represents up-regulated, while zero indicates non-significant genes. Single nodes and small components of the network were removed and the largest component was considered as a new network. Duplicated edges and self-loops were removed by using the network analyzer (Assenov et al., 2008). Green, red and blue color labels were used to represent up-regulated, down-regulated and non-significantly expressed gene clusters. Overall, modified cluster of testes data sets were composed of 9892 nodes. 2.8. Gene ontology annotation For further analyses, biological processes were selected with associated level of significance (0.01) by applying hyper-geometric test (Eq. (2)) and mouse genome was used as a reference.

 K N
K k n
k
 PðX ¼ kÞ ¼ (2) N n where “N” is the mouse genome, “K” is the number of genes present in biological processes in mouse genome, “n” is the total number of genes present in the network, “k” is the number of genes present in biological processes in network. Next, gene ontology (GO) analysis was carried out for each group of pro-apoptotic testes data set (up-regulated, downregulated) using Cytoscape plugin BiNGO (Maere et al., 2005). Microtubule and apoptosis related biological processes were shortlisted based on the significant P-value < 0.05. To find specific and common genes involved in regulation of both processes, advance merging and three consecutive intersections were carried out for data set. Initial two intersections were executed between apoptosis and microtubule related clusters of pro-apoptotic data, while final intersection was performed by using above two results in order to isolate common candidates involved in both apoptosis and microtubule related biological processes.

2.9. Mapping of transcription factor binding sites Transcription factor binding site (TFBSs) analyses of Tcte3 and its putative interacting partners were carried out by Match tool (Kel et al., 2003) which is based on TRANSFAC database. Subsequently, clustering and sub networking (Eqs. (3) and (4)) of TFBSs was performed. SubNet

impTF

SubNet

T

TFup
reg ð\ÞTFdown
reg ð\ÞTFTcte3;Anxa5;Pebp1

Testes

Cluster

ð\ÞSubNet

impTF

(3)

(4)

T where :" " is intersection, TF is transcription factor related to specific gene of interest, SubNetimpTF is subnet of functionally important TFs, is symbol of “implies that”, ClusterTestes is microarray data of testes.

3.1. Increased amount of Tcte3 modulates the expression patterns of Rsph1, Pebp1 and Anxa5 in testis In mouse, three Tcte3 paralogs were identified through BLAT search using ENSEMBL genome browser (www.ensembl.org) designated as Tcte3-1 [ID: ENSMUSG00000079710], Tcte3-2 [ID: ENSMUSG00000036648] and Tcte3-3 [ID: ENSMUSG00000079707], respectively. These three gene copies were localized at the minus strand of mouse chromosome 17 at 15101153–15115621, 15132803–15147148 and 15164115–15178523, respectively. Further comparison of Tcte3 transcripts through BLAST2 (www.ncbi.nlm.nih.gov) revealed minor differences at sequence level. In Tcte3-3 cDNA sequence, addition of seven nucleotides (GGCGGAG) at 50 -UTR differentiates it from the other two copies; while, a single substitution of C into G is present in Tcte3-1. Multiple sequence alignment (MSA) was performed by ClustalW (www.ebi.ac.uk/tools/msa/clustalw2) with default parameters and refined by JalView tool (www.jalview. org) (Fig. S1). Supplementry material related to this article found, in the online version, at http://dx.doi.org/10.1016/j.compbiolchem.2014.10.005. Previously, we reported that Tcte3-3 deficient mice bear defects in male fertility due to reduced sperm motility and a higher rate of apoptosis during spermatogenesis (Rashid et al., 2010). These mice were genotyped by real time PCR due to closer similarity in Tcte3 homologs. Next, we performed restriction mapping analyses and compared the fragment lengths. We observed that the length of Xba1–Spe1 deletion in Tcte3-1 was 7909 bp; however, in case of Tcte3-2 and Tcte3-3, Xba1–Spe1 fragments (containing exon 2) were 7690 bp and 7601 bp, respectively. To differentiate between the Tcte3-2 and Tcte3-3, 3.8 kb Xba1 fragment encompassing exon 1 was cut by BamH1 restriction enzyme. The fragments of 2388 bp and 2395 bp lengths clearly distinguished the Tcte3-2 and Tcte3-3 genes (Fig. S2). Taken together, it is evident through restriction mapping that homologous recombination occurred in Tcte3-3 (Rashid et al., 2010). Supplementry material related to this article found, in the online version, at http://dx.doi.org/10.1016/j.compbiolchem.2014.10.005. 3.2. Identification of putative co-expressed partners of Tcte3 by 2D-gel electrophoresis Comparative 2D-gel electrophoresis was performed to search the differentially expressed partners of Tcte3. Testes of Tcte3-3+/+ and Tcte3-3
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mice were excised and subjected to protein isolation. Individual protein samples were analyzed by 2D-gel electrophoresis using image analyses tool. The differentially expressed protein spots (Fig. 1, marked by rectangles A–F) were cut out and identified by mass spectrometry. A total of 30 spots were tested in both Tcte3-3+/+and Tcte3-3
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testes and selected for detailed analyses. In some spots, multiple proteins were present. Thus, these spots could not be unequivocally determined for differentially expressed proteins. However, most significant differences were observed in three differentially expressed proteins including Rsph1, Pebp1 and Anxa5. Our data indicated up-regulation of Rsph1, while both Pebp1 and Anxa5 exhibited reduced expression in wild-type testis as compared to Tcte3-3
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(Fig. 1A–C). 3.3. mRNA expression analysis In order to validate the expression patterns of Pebp1, Rsph1 and Anxa5 at RNA level, total RNA samples were isolated from the testes

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Fig. 1. Two dimensional gels containing the protein samples isolated from Tcte3-3+/+ and Tcte3-3
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testes. The samples were stained by Roti Blue stain. A total of 30 spots were tested and three differentially expressed proteins (Rsph1,Pebp1 and Anxa5) in both Tcte3-3+/+ and Tcte3-3
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testes were picked for detailed analyses. Rsph1 (A) was upregulated, while both Pebp1 (B) and Anxa5 (C) proteins had shown reduced expression in Tcte3-3+/+ testes as compared to Tcte3-3
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testes.

tissues of 3x wild-type and Tcte3-3 deficient mice of adult age. Real time PCR (qRT–PCR) facilitated the differential expression of Tcte3, Pebp1, Rsph1 and Anxa5 in Tcte3-3
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mice were compared to wildtype with glyceraldehyde-3-phosphate dehydrogenase (Gapdh) and beta-actin as a control. Experiment was repeated thrice and fold change was calculated by comparing gene expression of wildtype vs. Tcte3-3
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mice. We observed an overall decrease in the expression level of Tcte3, Pebp1 and Anxa5 in Tcte3-3
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testes as compared to normal tissue (Fig. 2). Notably, significant measurable change in the expression pattern of Rsph1 was not detected. However, a unique synergy in the expression pattern of apoptotic marker (Anxa5) together with Tcte3 compelled us to explore the detailed role of Tcte3 in apoptosis-related biological processes.

threshold. Next, hyper geometric test (Eq. (2)) was applied and gene ontology (GO) analyses were carried out to ensure the biological relevance of co-expression network. Two biological processes (microtubular and apoptotic) with an associated level of significance (<0.01) were selected. Later on, advanced merging and three subsequent intersections were performed. By these analyses, we identified a number of common co-regulated genes whose

[(Fig._2)TD$IG]

3.4. Co-expression network analyses The overall schema followed for the network construction to identify the putative relationships among Tcte3, Anxa5 and Pebp1 in apoptotic context is demonstrated in Fig. 3. Microarray data related to apoptotic induction in mouse testes were gathered from NCBI (GEO). In total, 9892 genes (Fig. 3 red box) were selected from proapoptotic testes data set for further analyses. Based on the gene expression values (Eq. (1)), co-expression networks of upregulated (green), down-regulated (red) and non-significantly regulated (blue) genes (Fig. 4) were constructed, where each node represents individual gene and two genes are connected by an edge if their expression similarity level is above a pre-selected

Fig. 2. Real time-PCR analyses of Tcte3, Anxa5 and Pebp1 in testis of 3x wild-type and Tcte3-3
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mice. Graphical representation of real time PCR of 3x adult wild-type and Tcte3-3
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mice testes samples. Expression values were normalized with two internal control glyceraldehyde-3-phosphate dehydrogenase (Gapdh) and betaactin. Fold change of Tcte3, Anxa5 and Pebp1 was plotted and error bars show reliability between experimental replicate.

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Fig. 3. Schematic representation of data mining and analyses based on GO (gene ontology) and TFBSs (transcription factors binding sites) analyses. Data mining (steps 1–3): (1) NCBI gene expression omnibus was explored for the retrieval of valuable data; (2) data search was restricted by stringent filters like specie, tissues and biological processes; (3) relevant experiment was selected for pro-apoptotic data set from testes (red spots) of mouse (red rectangles). Respective experiments were indicated at the top right corner of rectangle. Data processing: steps are enclosed in blue rectangles (steps 4–7); (4) a pair of samples (control and treated) from each experiment was randomly selected; (5) networks were built from the data on the basis of expression value differences. Genes represented by red box are pro-apoptotic testes data set; (6) network was divided into three major clusters: up-regulated, down-regulated and non-significantly differential genes clusters represented by green, red and blue colors, respectively; (7) genes studied in the current work (Tcte3, Anxa5, and Pebp1) were indentified in individual clusters. Data analyses: (green rectangle with green shade). BiNGO analyses (steps 8–11), TFBS related analyses (steps 12–15); (8) BiNGO analyses was carried out on up-regulated and down-regulated clusters; (9) significant gene ontology (GO) with respect to biological processes was obtained; (10) on the basis of significant p-value, genes involved in apoptosis and microtubule related biological processes were selected and their clustering was performed; (11) advance merging was applied to get functionally important genes; (12) sequences of genes were retrieved from ensembl genome browser (http://www.ensembl.org) and submitted to TRANSFAC database; (13) with respect to each gene, TFs were retrieved and networks were developed; (14) sub networking was applied to obtain the valuable data; (15) shortlisted TFs were re-checked with initial up-regulated and down-regulated microarray data sets. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

expression might be co-modulated with Tcte3 and Anxa5 (Fig. 5). Transcription factor binding site (TFBSs) analyses were carried out using TRANSFAC Match tool (Kel et al., 2003) to understand regulation of Tcte3, Anxa5, Pebp1 and other shortlisted co-expressed partners in both up and down-regulated data sets. Afterwards, clustering and sub network analyses were performed (Eqs. (3) and (4)). The TF clusters inferred from TRANSFAC were linked to microarray data sets via shared data (Fig. 6BII), red outlined square (testes data). Overall, our consensus of collective data analysis depicted a common transcriptional regulation of Tcte3 and its putative interacting partners. 3.5. Clustering of co-regulated genes based on their expression values Integration of biological knowledge (microarray gene expression data) into clustering is a powerful tool to elucidate co-regulatory relationships of genes (Qin, 2006). It has been

commonly observed that genes which are involved in similar biological processes or perform similar functions are likely to be co-expressed. Hence clustering the gene expression profiles provides a means for gene function prediction (Wu et al., 2002; Xiao and Pan, 2005). Aim of the present study was to investigate the possible relationships among Tcte3 and its co-expressed partners: Anxa5 and Pebp1 in the induction of male germ cell apoptosis. During spermatogenesis, Anxa5 binds to PS specifically in a calcium-dependent manner and results in more TUNEL positive spermatogenic cells upon over expression (Maeda et al., 2002). It has been reported that phosphatidylethanolamine (PE)/ phosphatidylserine (PS) level is monitored by the Anxa5 in apoptotic cells (Vermes et al., 1995) and expression of Anxa5 is restricted only to Leydig cells, endothelial cells and spermatocytes (Yao and Kawaminami, 2008). Pebp1 or RKIP1 is a sperm surface protein which acts as a decapacitating factor (Nixon et al., 2006) or decapacitation factor receptor (Gibbons et al., 2005). Significant amount of Pebp1 mRNA expression has been observed in testis

[(Fig._4)TD$IG]

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Fig. 4. Overall representation of testes data set. (A) Represent clustering of apoptotic microarray testes data with up-regulated (green), down-regulated (red) and nonsignificantly expressed genes (blue). Three subsequent sub network clusters with non-significant genes are represented by (B) (blue color), up-regulated cluster is shown by (C) (blue and green shade), while down-regulated group of genes is indicated by (D) (blue and red). Genes of interest (Tcte3, Anxa5 and Pebp1) are represented by green circles in respective data sets. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

during spermatogenesis, particularly from late pachytene spermatocytes (Hickox et al., 2002). Pebp1 plays a vital role in regulating testicular apoptotic events by modulating ERK and NF-kB pathways (Yeung et al., 2001; Rasoulpour and Boekelheide, 2005, 2007). Here clustering of microarray data set (Fig. 4A) was performed comprising 9892 genes. In order to identify significantly differentially expressed genes, based on gene expression value (Eq. (1)) sub network clustering of pro-apoptotic testis data set was carried out where 19, 4786 and 5092 genes were clustered together in non-significantly regulated group (blue color, Fig. 4B), upregulated (green and blue shade, Fig. 4C) and down-regulated (blue and red color, Fig. 4D). In these clusters, we marked genes of interest (Tcte3, Anxa5 and Pebp1) (Fig. 4) and found that all three genes were located in same gene clusters which is consistent with our experimental results as Tcte3, Anxa5 and Pebp1 harbored similar expressions in Tcte3-3
/
testis compared to wild-type. 3.6. GO analyses To gain a deep insight whether selected significant clusters are biologically meaningful, we evaluated and computed their enrichments in biochemical pathways (i.e, number of genes present in biological processes in a specific network compared to the overall number of genes present in biological processes in mouse genome). By performing GO analyses (Table S1), clusters specific to apoptosis and microtubule related biological processes were shortlisted with significant scores (Tables 2 and 3) and subjected to further analyses. Supplementry material related to this article found, in the online version, at http://dx.doi.org/10.1016/j.compbiolchem.2014.10.005.

3.7. Isolation of modules correlated with microtubule and apoptosis related biological processes Hyper geometric test was applied (Eq. (2)) and two biological processes (apoptosis and microtubule) with associated level of significance (<0.01) were shortlisted. Tables 2 and 3 enlisted the up and down-regulated genes, involved in apoptosis and microtubule related biological processes along with their corresponding E-values in testis. The significant biological processes were plotted indicating up and down-regulated genes (represented by different shades of red and green colors) (Fig. 5A). We correlated both processes on the basis of similar expression patterns. Subsequently, advance merging followed by three intersections is carried out to isolate the common putative candidates that were involved in both biological processes in testis (Fig. 5). In total, 372 genes were detected to play specific roles in apoptosis in up-regulated group (green circle). Anxa5 was also located in the up-regulated data set which is a clear notion that it has important function in testicular apoptosis (Fig. 5BI). In the up-regulated group of microtubule related processes, 57 genes (green circle) were identified (Fig. 5BII). We investigated the presence of Tcte3 in this group having a central role in microtubule related processes (Fig. 5BII). However, CryAB, Mapt (Fasulo et al., 2000), (Steigerwald et al., 2005), Brca1 (Shao et al., 1996) and Tpx2 (Chang et al., 2012) were common genes for both processes which are involved in regulating the induction of cell death, inhibition of mitosis, cell cycle control and/or induction of cellular differentiation ((Fig. 5B), purple circle). Next, downregulated data set of testis, associated with apoptosis and microtubule related biological processes were intersected (Fig. 5C). We observed that among down-regulated genes, 626 and 80 genes were specific to testis apoptosis and microtubule

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Fig. 5. GO analysis of microarray data set. (A) Graphical overview of the biological processes related to microtubule and apoptosis with respective p-values. Pro-apoptotic testis data is indicated by green, red and blue shaded peaks. Green shade represents up-regulated genes and red shades designate down-regulated genes. (B) Green circle indicate up-regulated genes involved in apoptosis (BI) and microtubule (BII) related processes for data set. (C) Intersection of networks for down-regulated set of genes using pro-apoptotic data implicated in apoptosis (CI) and microtubule (CII) related biological processes (red circle). Rectangles demonstrate respective biological processes, red circle shows up-regulated (5BI and 5BII), green circle illustrates down-regulated (5(CI) and 5(CII)) apoptotic and microtubule testis data, respectively, while circle in purple indicates intersection of the data extracted from both biological processes. Genes labeled within purple circles are common genes between two biological processes. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

processes, respectively (Fig. 5CI and CII). Finally, intersection of shared genes (purple shade) among testis specific apoptosis and microtubular processes (626 and 80 genes) resulted in short-listing of nine genes, namely Htt Birc5 (Altieri, 2001; Li,

2003), Ptk2 (Garces et al., 2006; Ezratty et al., 2005), Dynll1 (Puthalakath et al., 1999), Ube2b, Mlh1, Mapk8 (Wada and Penninger, 2004), Prkcz and Cenpf (Fig. 5C, purple circle) that were involved in exhibiting common functionalities. It can be

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[(Fig._6)TD$IG]

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Fig. 6. Illustration of TFBSs analyses for Tcte3-3 and its coexpressed partners. (A) Nodes represent genes and TFs. Link indicates binding of TFs with genes. Common TF networks of shared up-regulated (light sea green squares) and down-regulated genes (hot pink squares) performing microtubule or apoptosis related biological processes and genes under investigation (Tcte3, Anxa5 and Pebp1) (yellow squares) are represented by squares in respective cluster (AI, AII and AIII). Circular nodes indicated by pink color are TFs of all genes in one cluster, while functionally important TFs are shown by purple shade octagon. (BI) Sub-network shows shortlisted common TFs shared among up-regulated, down-regulated and genes under study (blue rectangle). (BII) Sub-network represented by red rectangle is obtained through overlapping of TF data with pro-apoptotic testes microarray data set. Common TFs are indicated by purple octagons, while green and red octagons show up-regulated and down-regulated TFs in testes microarray data sets, respectively. (C) Graphical representation of genomic region of mouse chromosome 17 encompassing Tcte3-3 gene. TFBSs are indicated by circles of respective colors along with their positions on Tcte3-3. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

speculated that these differentially expressed genes may play significant roles in both apoptotic and microtubule-based processes, specifically regulated by similar TFs. 3.8. TFBS study for Tcte3 co-expressed genes Co-expression of genes shares certain regulatory mechanisms and transcriptional factors (TFs) (Yu et al., 2003). Detection of gene specific common transcription factor binding sites (TFBSs) is a powerful tool to elucidate their biological relevance (Werner, 2001). To gain deep insight into the functional coherence of coexpressed genes, we performed comparative TFBS analyses of Tcte3, Anxa5 and Pebp1 (Table S2) in comparison to the candidate hits shortlisted by GO analyses. These included five genes from the up-regulated data set namely Tpx2 (Xenopus kinesin-like protein 2), Mapt (microtubule associated protein tau), Brca1 (breast cancer

1, early onset), Apc (adenomatous polyposis coli) and CryAB (alphacrystallin B chain) (Fig. 5B, purple circle) and nine genes Htt (huntingtin), Birc5 (baculoviral IAP repeat containing 5), Ptk2 (protein tyrosine kinase 2), Dynll1 (dynein light chain 1, cytoplasmic), Cenpf (centromere protein F), Mapk8 (mitogenactivated protein kinase 8), Prkcz (protein kinase C, zeta), Mlh1 (human mutL homolog 1) and Ube2b (ubiquitin-conjugating enzyme E2B) from the down-regulated data set (Fig. 5C, purple circle). Initially, TFBSs for the selected genes were mapped using TRANSFAC Match tool (Kel et al., 2003) (Table S2), followed by their clustering. Subsequent union of individual clusters resulted in 214, 197 and 149 common TFs which were involved in the regulation of up-regulated, down-regulated and targeted genes (Tcte3, Anxa5 and Pebp1), respectively. The genes under investigation were represented by light sea green, pink and yellow shaded squares (Fig. 6AI–III). Through these analyses E2F, TBP, Myb SP1,

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Table 2 List of biological processes related to apoptosis with significant p-value (<0.01) scores obtained via GO analysis carried out on up and down-regulated set of gene data in testis. ID

Description

Down-regulated genes (Testis)

Up-regulated genes (Testis)

Testis

6916 6915 6921 42771

Anti-apoptosis Apoptosis Cellular component disassembly involved in apoptosis DNA damage response, signal transduction by p53 class mediator resulting in induction of apoptosis DNA damage response, signal transduction resulting in induction of apoptosis Induction of apoptosis Induction of apoptosis by extracellular signals Induction of apoptosis by intracellular signals Induction of apoptosis via death domain receptors Lymphocyte apoptosis Negative regulation of apoptosis Negative regulation of lymphocyte apoptosis Negative regulation of neuron apoptosis Negative regulation of T cell apoptosis Positive regulation of anti-apoptosis Positive regulation of apoptosis Positive regulation of neuron apoptosis Regulation of anti-apoptosis Regulation of apoptosis Regulation of B cell apoptosis Regulation of lymphocyte apoptosis Regulation of muscle cell apoptosis Regulation of myeloid cell apoptosis Regulation of neuron apoptosis Regulation of T cell apoptosis

1.42E–10 2.82E–25 Null Null

1.41E–06 6.80E–28 4.63E–03 Null

1.84E–23 3.98E–70 1.02E–05 2.23E–03

3.28E–03 8.41E–12 Null 2.14E–04 Null Null 3.86E–24 Null 2.57E–05 Null Null 1.75E–18 Null Null 3.18E–40 4.20E–03 2.19E–04 Null Null 1.92E–08 Null

7.07E–03 2.00E–13 2.03E–03 3.06E–03 Null 1.37E–03 6.15E–23 Null 1.06E–06 Null 1.62E–05 8.60E–28 4.29E–05 6.75E–07 4.14E–50 Null Null Null 1.43E–02 2.53E–11 Null

5.39E–07 1.01E–33 3.03E–07 6.43E–09 2.52E–03 2.23E–03 1.06E–63 4.36E–03 1.95E–15 2.52E–03 1.99E–07 1.07E–63 1.50E–06 2.21E–09 0.00E + 00 1.68E–03 1.85E–05 7.29E–03 1.32E–04 1.74E–25 4.36E–03

8630 6917 8624 8629 8625 70227 43066 70229 43524 70233 45768 43065 43525 45767 42981 2902 70228 10660 33032 43523 70232

P300, CREB, AP1, AP2 and c-Myc/Max (highlighted by violet octagons) are common TFs known to contribute in apoptosis related processes. Supplementry material related to this article found, in the online version, at http://dx.doi.org/10.1016/j.compbiolchem.2014.10.005. Afterwards, sub-network was extracted having functionally important TFs present in the above three clusters and overlapped with testes microarray data set to collect meaningful data. The subnetworking (Eq. (3)) was carried out to gain deep insight whether TFs indicated by violet octagons were shared among all selected genes. Interestingly, these TFs were found to be shared by majority of genes under analyses (Fig. 6BI). Further intersections of this subnetwork with pro-apoptotic (Eq. (4)) microarray dataset of testes were also performed to identify the tissue specific gene regulation by TFs. This analysis revealed several common TFs which were highlighted in green and red boxes, representing both up and down-regulated TFs, respectively in testis microarray data set (Fig. 6BII). Among them, CREB (CREB3l1 and CREB2f), E2F3, E2F5 and E2F6 were up-regulated; while Myb TBP, c-Myc/Max SP1 and CREB (CREB and CREB3) were down-regulated in testes

data (represented by green and red circles) (Fig. 6(BII)). Based on these analyses, the TFs namely E2F, TBP, Myb SP1, P300, CREB, AP1, AP2 and c-Myc/Max might be involved in the regulation of Tcte3 expression. The basic roles of E2F and Myb in cell cycle progression, differentiation and apoptosis are well documented (Dimova and Dyson, 2005; Sala, 2005; Slansky and Farnham, 1996; Oh and Reddy, 1999). Specifically, regulatory roles of these TFs are explicit to male meiosis (Bolcun-Filas et al., 2011; Holmberg et al., 1998; Toscani et al., 1997). Moreover, it is well-documented that p300/ CBP participates in a broad range of cellular processes by binding with various other TFs like CREB, YY1, c-fos, c-jun, c-Myb and certain members of steroid hormone receptor family. p300/CBP (CREB-binding protein) dependent processes include cellular differentiation, signal transduction, cell cycle regulation and stress (Eckner et al., 1996; Visel et al., 2009). Next, TFBSs on Tcte3-3 gene copy were mapped, as indicated in Fig. 6C. To evaluate whether above-selected TFs orchestrate Tcte3 expression in terms of tissue specificities, we analyzed ChIP-seq data for all three gene copies of murine Tcte3 (Http://genome.ucsc. edu/ENCODE/) (Rosenbloom et al., 2012). We observed a considerable number of quantitative changes of HAT p300, c-Myc TBP,

Table 3 List of biological processes related to microtubule with significant p-value (<0.01) scores obtained via GO analysis carried out on up and down-regulated set of gene data in testis. ID

Description

Down-regulated gene (Testis)

Up-regulated gene (Testis)

Testis

7017 10970 31114 31023 32886 226 7018 70507 31111 31113 47496 7026 1578 31110

Microtubule-based process Microtubule-based transport Regulation of microtubule depolymerization Microtubule organizing center organization Regulation of microtubule-based process Microtubule cytoskeleton organization Microtubule-based movement Regulation of microtubule cytoskeleton organization Negative regulation of microtubule polymerization or depolymerization Regulation of microtubule polymerization Vesicle transport along microtubule Negative regulation of microtubule depolymerization Microtubule bundle formation Regulation of microtubule polymerization or depolymerization

1.46E–12 4.04E–04 Null Null 7.73E–04 7.36E–11 8.33E–05 4.93E–04 Null Null Null Null 1.80E–03 1.04E–03

3.68E–04 Null 2.22E–03 Null 1.85E–03 Null 1.47E–03 1.55E–03 1.75E–03 Null Null 2.22E–03 Null 4.26E–03

5.79E–24 8.53E–05 1.94E–03 Null 1.13E–08 2.19E–18 1.61E–09 6.28E–07 5.09E–04 Null Null 1.94E–03 1.24E–03 3.49E–05

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E2F4 and c-Myb binding sites at the regulatory regions of Tcte3 paralogs (Fig. S3). This indicates a clear notion that co-expression of genes is correlated with an underlying transcriptional regulatory entity and might be controlling Tcte3 tissue specific expression and associated functions. Supplementry material related to this article found, in the online version, at http://dx.doi.org/10.1016/j.compbiolchem.2014.10.005. 4. Discussion Among dynein light chains including LC8 (DYNLL, Tctex1/RP3 (DYNLT) and Rbl (DYNLRB), Tcte3 has been initially characterized as a testicular protein which plays a unique role in the axonemal assembly (Pazour et al., 1999). However, subsequent expression of Tcte3 in tissues lacking cilia or flagella (DiBella et al., 2001; Neesen et al., 2002) demonstrated additional roles of this protein. Previously, we reported that Tcte3-3 mutant mice exhibit defects in spermatogenesis due to apoptosis of male germ cells (Rashid et al., 2010). Here, we screened whole testicular proteome of Tcte3-3 wild-type and mutant mice to study the differentially expressed proteins. Through qRT–PCR analysis, we detected lower expression levels of Tcte3, Anxa5 and Pebp1 in the testes of homozygous mice as compared to wild-type. However, 2D gel electrophoresis showed induction of all three genes at protein level; which compelled us to investigate their tissue-specific roles by integrating computational approaches. Possibly, these genes exhibit differences in mRNA and protein levels as half lives of proteins may vary (48 h) compared to mRNA degradation rate which is 2–7 h in mammals (Vogel and Marcotte, 2012). Similarly, translation rate is much faster than mRNA synthesis (Mata et al., 2005; Nie et al., 2006). Thus, gene expression changes at mRNA and protein level are very common observation due to poor correlation between transcriptional and translational level. During male germ cell development, Tcte3 role has been characterized in the elongated spermatids, suggesting a dramatic role of Tcte3 in spermatid differentiation. Moreover, a restricted expression of Pebp1 has been observed in the elongated spermatids (Hickox et al., 2002). In apoptotic cells, phospholipid proteins including phosphatidylserine (PS) and phosphatidyletanolamine (PE) translocate at the outer membrane (Maeda et al., 2002), where phagocytic sertoli cells detect the externalized PS/PE for binding to the apoptotic cells and clear them (Vermes et al., 1995). At this stage, another principal component Anxa5 binds to the PS/PE to regulate the phagocytic event. Moreover, a higher rate of apoptosis is tightly correlated with Anxa5 abundance (Maeda et al., 2002). Through the co-expression behavior of Tcte3, Pebp1 and Anxa5, it is plausible to interpret a model and evaluate their exact involvements in apoptosis. Despite substantial experimental progress, determination of essential co-expression patterns of genes in similar processes remains elusive and a demanding task. To this end, we elucidated a mechanistically diverse set of co-expressed genes sharing common attributes in apoptosis and microtubule associated functions through screening of microarray-based data set which was derived from mouse testis, pretreated with histone deacetylase inhibitor trichostatin A (TSA). TSA serves as an effective inhibitor against anti-apoptotic Bcl2 protein and up-regulates the pro-apoptotic Bax in human lung cells (Martin et al., 1995; Choi, 2005). A subcutaneous injection of TSA into mice results in a severe reduction of spermatids and pachytene spermatocytes, indicating its prominent role in apoptotic induction of meiotic cells (Fenic et al., 2004). Moreover, it has been reported that in various cell lines, TSA affects a variety of biological processes, including induction of cell cycle arrest, differentiation, inhibition of cell proliferation and apoptosis (Liu et al., 2000; Herold et al.,

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2002; Touma et al., 2005). The rationale behind using this particular data set was based on the phenotypic correlations between TSA injected and Tcte3-3 disrupted mice testis. Moreover, at transcriptome level, we observed a similar expression profile for Tcte3, Anxa5 and Pebp1 in our study. Which prompted us to use TSA treated microarray data set. It is important to mention that by using this data set; we aimed to elucidate the genes involved in apoptosis cluster together with our genes of interest and corresponding transcription factor binding sites (TFBS) of common TFs. Subsequently, we compared these TFs to that of lying at Tcte3 promoters. Through integration of descriptive and predictive applications, testicular microarray data were intersected simultaneously in context of apoptosis and microtubule associated functions to unravel common targets. Several known hits including Tpx2 (Xenopus kinesin-like protein 2), Mapt (microtubule associated protein tau), Brca1 (breast cancer 1, early onset), Apc (adenomatous polyposis coli) and CryAB (alpha-crystallin B chain) were found to be up-regulated in data and observed in modulating the apoptotic process (Fasulo et al., 2000; Shao et al., 1996; Chis et al., 2012; Moss et al., 2009; Dikovskaya et al., 2007). Quite interestingly, Tcte3 and Anxa5 were detected in intersection data set. Similarly, in downregulated testis microarray data, co-regulated hits having both apoptotic and microtubule based functions, includes Htt (huntingtin), Birc5 (baculoviral IAP repeat containing 5), Ptk2 (protein tyrosine kinase 2), Dynll1 (dynein light chain 1, cytoplasmic), Cenpf (centromere protein F), Mapk8 (mitogen-activated protein kinase 8), Prkcz (protein kinase C, zeta), Mlh1 (human mutL homolog 1) and Ube2b (ubiquitin-conjugating enzyme E2B). Subsequent merging and intersections of TFBSs clusters of mentioned hits, resulted in the isolation of tissue-specific TFs including E2F, TBP, Myb SP1, p300, CREB, AP1, AP2 and c-Myc/Max. Through ChIP-seq data analysis, we observed quantitative differences of these TFs at the regulatory regions of Tcte3 paralogs, indicating a coordinated basal expression pattern of target genes due to selective binding of these TFs. It is well established fact that both p300 and CREB-binding protein (CBP) act as chromatin regulators within genes or proximal promoters (Visel et al., 2009; Heintzman et al., 2007) by interacting with distinct TFs. For example, CBP acts as transcription repressor by binding to AP-1 and SRF binding sites, while p300 activates transcription by binding to AP-2, E2F and SP-1 binding sites (Ramos et al., 2010). Moreover, p300, CBP and RNA polymerase II are known to interact with each other to modulate transcriptional regulation of antisense transcripts (Katayama et al., 2005; Cho et al., 1998). Based on these observations, it could be speculated that p300 and CBP might be the causative agents of tissue specific transcriptional abundance of Tcte3. Generally, phosphorylation of cAMP-response element binding protein (CREB) activates a cascade of events and recruits CBP to a larger transcriptional complex (Sassone-Corsi, 2002). A compelling amount of data established that TFs linked to the CREB/cAMP-response element modulator (CREM) act as transcriptional activators of post-meiotic genes specifically in testis (Kimmins et al., 2004). This notion could be further supported by the fact that a novel member of CREB family, Atce1 (CREB3L4; cAMP-responsive element binding protein-like gene) has been identified in mouse testis as interacting partner of Tcte3 (Stelzer and Don, 2002) which acts as an activator of late haploid phase of spermatogenesis. These findings suggest that the mechanisms employed in the regulation of apoptosis are tightly associated with Tcte3 expression. Taken together, our data would contribute to a better understanding of testes-specific transcriptional control of genes involved in apoptosis by addressing the cooperative influence of diverse regulatory partners, pivotal in unraveling the mechanisms leading to tissue-wise regulation of biological processes.

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Conflict of interest The authors declared no conflict of interest.

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