A sperm-specific proteome-scale metabolic network model identifies non-glycolytic genes for energy deficiency in asthenozoospermia

Figures & data

Figure 1. Model reconstruction procedure and findings. We first collected the sperm-specific proteomic data from databases and literature. Then, after converting the protein data to the corresponding gene data, we used them for reconstructing the sperm-specific metabolic network model. Finally, we used the reconstructed model for analyzing energy metabolism in healthy sperm and in asthenozoospermia. After that, under single knockout analysis, our model predicted several genes that may play a role in asthenozoospermia.

Figure 2. From the total of 29 predicted essential gene sets, 18 gene sets (62%) were previously reported in the literature to be linked to ATP production, and thus, to asthenozoospermia. To the best of our knowledge, the other 11 gene sets (38%) have not previously reported to be linked to asthenozoospermia. The accompanying table shows a list of these genes.

Figure 3. The four reaction categories which show flux decrease or increase in the knockout model based on FVA [Hadi and Marashi 2014]. X-axis represents total reactions possible flux ranges. The solid color lines represent the flux of reaction in normal sperm cell model, (ranges from c to d). The dashed arrows indicate the flux of reaction in knockout model (ranges from a to b). If this means a high confidence decrease, however if it means a high confidence increase. If , it will result in a decrease, while if it will result in an increase.

Table 1. Novel genes predicted by the SpermNet model to play a role in asthenozoospermia.

Entrez Gene ID	Abbreviated name	Gene full name
2592	GALT	Galactose-1-phosphate uridylyltransferase
55577	NAGK	N-acetyl glucosamine kinase
5238	PGM3	Phosphoglucomutase 3
2650	GCNT1	Glucosaminyl (N-acetyl) transferase 1
51727	CMPK	Cytidine monophosphate kinase
9583	ENTPD4	Ectonucleoside triphosphate diphosphohydrolase 4
2720	GLB1	Galactosidase beta 1
5476	CTSA	Cathepsin A
11046	SLC35D2	Solute carrier family 35, member D2
7355	SLC35A2	Solute carrier family 35 (UDP-galactose transporter), member A2
4668	NAGA	N-acetylgalactosaminidase

Table 2. List of genes that are known to be linked to asthenozoospermia but have not been predicted to influence ATP production by the SpermNet model.

Entrez ID	Gene symbol	Gene name	Reference
2821	GPI	Glucose 6-phosphate isomerase	Amaral et al. 2014
5162	PDHB	Pyruvate dehydrogenase beta	Amaral et al. 2014
1891	ECH1	Enoyl-CoA Hydratase 1	Martínez-Heredia et al. 2008
2597	GAPDH	Glyceraldehyde-3-Phosphate Dehydrogenase	Shen et al. 2013
5232	PGK2	Phosphoglycerate kinase 2	Shen et al. 2013
4538	MT-ND4	Mitochondrially encoded NADH dehydrogenase 4	Pereira et al. 2008
4540	MT-ND5	Mitochondrially encoded NADH dehydrogenase 5	Dada et al. 2011
1080	CFTR	Cystic fibrosis transmembrane conductance regulator	Slezak et al. 2007
116369	SLC26A8	Solute carrier family 26 (anion exchanger), member 8	Dirami et al. 2013

Figure 4. Enriched pathways based on inactivated or activated genes in gene knockout simulations. (A) Enriched pathways based on 307 inactivated genes as a result of deleting asthenozoospermia-implicated metabolic genes not predicted by SpermNet. (B) Enriched pathways based on 287 activated genes as a result of deleting asthenozoospermia-implicated metabolic genes not predicted by SpermNet.

Hadi, M. and Marashi, S.-A. (2014) Reconstruction of a generic metabolic network model of cancer cells. Mol BioSystems 10: 3014–3021.

 PubMed Web of Science ®Google Scholar

Amaral, A., Paiva, C., Attardo Parrinello, C., Estanyol, J.M., Ballescà, J.L., Ramalho-Santos, J., et al. (2014) Identification of proteins involved in human sperm motility using high-throughput differential proteomics. J Proteome Res 13: 5670–5684.

 PubMed Web of Science ®Google Scholar

Martínez-Heredia, J., de Mateo, S., Vidal-Taboada, J.M., Ballescà, J.L. and Oliva, R. (2008) Identification of proteomic differences in asthenozoospermic sperm samples. Human Reprod 23: 783–791.

 PubMed Web of Science ®Google Scholar

Shen, S., Wang, J., Liang, J. and He, D. (2013) Comparative proteomic study between human normal motility sperm and idiopathic asthenozoospermia. World J Urol 31: 1395–1401.

 PubMed Web of Science ®Google Scholar

Pereira, L., Gonçalves, J. and Bandelt, H. J. (2008) Mutation C11994T in the mitochondrial ND4 gene is not a cause of low sperm motility in Portugal. Fertil Steril 89: 738–741.

 PubMed Web of Science ®Google Scholar

Dada, R., Mahfouz, R. Z., Kumar, R., Venkatesh, S., Shamsi, M. B., Agarwal, A., et al. (2011) A comprehensive work up for an asthenozoospermic man with repeated intracytoplasmic sperm injection (ICSI) failure. Andrologia 43: 368–372.

 PubMed Web of Science ®Google Scholar

Dirami, T., Rode, B., Jollivet, M., Da Silva, N., Escalier, D., Gaitch, N., et al. (2013) Missense mutations in SLC26A8, encoding a sperm-specific activator of CFTR, are associated with human asthenozoospermia. Am J Human Genet 92: 760–766.

 PubMed Web of Science ®Google Scholar