title: Inferring the effective TOR-dependent network: a computational study in yeast.
abstract: BACKGROUND
  Calorie restriction (CR) is one of the most conserved non-genetic interventions that extends healthspan in evolutionarily distant species, ranging from yeast to mammals. The target of rapamycin (TOR) has been shown to play a key role in mediating healthspan extension in response to CR by integrating different signals that monitor nutrient-availability and orchestrating various components of cellular machinery in response. Both genetic and pharmacological interventions that inhibit the TOR pathway exhibit a similar phenotype, which is not further amplified by CR.
  
  
  RESULTS
  In this paper, we present the first comprehensive, computationally derived map of TOR downstream effectors, with the objective of discovering key lifespan mediators, their crosstalk, and high-level organization. We adopt a systematic approach for tracing information flow from the TOR complex and use it to identify relevant signaling elements. By constructing a high-level functional map of TOR downstream effectors, we show that our approach is not only capable of recapturing previously known pathways, but also suggests potential targets for future studies.Information flow scores provide an aggregate ranking of relevance of proteins with respect to the TOR signaling pathway. These rankings must be normalized for degree bias, appropriately interpreted, and mapped to associated roles in pathways. We propose a novel statistical framework for integrating information flow scores, the set of differentially expressed genes in response to rapamycin treatment, and the transcriptional regulatory network. We use this framework to identify the most relevant transcription factors in mediating the observed transcriptional response, and to construct the effective response network of the TOR pathway. This network is hypothesized to mediate life-span extension in response to TOR inhibition.
  
  
  CONCLUSIONS
  Our approach, unlike experimental methods, is not limited to specific aspects of cellular response. Rather, it predicts transcriptional changes and post-translational modifications in response to TOR inhibition. The constructed effective response network greatly enhances understanding of the mechanisms underlying the aging process and helps in identifying new targets for further investigation of anti-aging regimes. It also allows us to identify potential network biomarkers for diagnosis and prognosis of age-related pathologies.
authors.affiliation: Department of Computer Science, Purdue University, West Lafayette, Indiana, USA. mohammadi@purdue.edu.
authors.forename: Shahin
authors.initials: S
authors.lastname: Mohammadi
authors.forename: Shankar
authors.initials: S
authors.lastname: Subramaniam
authors.forename: Ananth
authors.initials: A
authors.lastname: Grama
mesh_terms: D063990:Gene Ontology; D053263:Gene Regulatory Networks / Q000187:drug effects; D005800:Genes, Fungal / Q000235:genetics; D011499:Protein Processing, Post-Translational / Q000187:drug effects; D017346:Protein Serine-Threonine Kinases / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000187:drug effects / Q000235:genetics* / Q000378:metabolism* / Q000502:physiology; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism*; D020123:Sirolimus / Q000494:pharmacology; D049490:Systems Biology; D014157:Transcription Factors / Q000378:metabolism; D059467:Transcriptome / Q000187:drug effects
chemical_list: D029701:Saccharomyces cerevisiae Proteins; D014157:Transcription Factors; D017346:Protein Serine-Threonine Kinases; C500749:target of rapamycin protein, S cerevisiae; D020123:Sirolimus