title: Systems biology of the autophagy-lysosomal pathway.
abstract: The mechanisms of the control and activity of the autophagy-lysosomal protein degradation machinery are emerging as an important theme for neurodevelopment and neurodegeneration. However, the underlying regulatory and functional networks of known genes controlling autophagy and lysosomal function and their role in disease are relatively unexplored. We performed a systems biology-based integrative computational analysis to study the interactions between molecular components and to develop models for regulation and function of genes involved in autophagy and lysosomal function. Specifically, we analyzed transcriptional and microRNA-based post-transcriptional regulation of these genes and performed functional enrichment analyses to understand their involvement in nervous system-related diseases and phenotypes. Transcriptional regulatory network analysis showed that binding sites for transcription factors, SREBP1, USF, AP-1 and NFE2, are common among autophagy and lysosomal genes. MicroRNA enrichment analysis revealed miR-130, 98, 124, 204 and 142 as the putative post-transcriptional regulators of the autophagy-lysosomal pathway genes. Pathway enrichment analyses revealed that the mTOR and insulin signaling pathways are important in the regulation of genes involved in autophagy. In addition, we found that glycosaminoglycan and glycosphingolipid pathways also make a major contribution to lysosomal gene regulation. The analysis confirmed the known contribution of the autophagy-lysosomal genes to Alzheimer and Parkinson diseases and also revealed potential involvement in tuberous sclerosis, neuronal ceroidlipofuscinoses, sepsis and lung, liver and prostatic neoplasms. To further probe the impact of autophagy-lysosomal gene deficits on neurologically-linked phenotypes, we also mined the mouse knockout phenotype data for the autophagylysosomal genes and found them to be highly predictive of nervous system dysfunction. Overall this study demonstrates the utility of systems biology-based approaches for understanding the autophagy-lysosomal pathways and gaining additional insights into the potential impact of defects in these complex biological processes.
authors.affiliation: Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
authors.forename: Anil G
authors.initials: AG
authors.lastname: Jegga
authors.forename: Lonnie
authors.initials: L
authors.lastname: Schneider
authors.forename: Xiaosen
authors.initials: X
authors.lastname: Ouyang
authors.forename: Jianhua
authors.initials: J
authors.lastname: Zhang
mesh_terms: D000818:Animals; D001343:Autophagy / Q000235:genetics* / Q000502:physiology; D016000:Cluster Analysis; D019295:Computational Biology; D004843:Epistasis, Genetic / Q000502:physiology; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks / Q000502:physiology; D006801:Humans; D008247:Lysosomes / Q000235:genetics* / Q000378:metabolism* / Q000502:physiology; D008297:Male; D008322:Mammals / Q000235:genetics / Q000378:metabolism / Q000502:physiology; D051379:Mice; D046228:Microarray Analysis; D059748:Proteolysis; D015398:Signal Transduction / Q000235:genetics; D049490:Systems Biology / Q000379:methods; D014158:Transcription, Genetic