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Inferring the effective TOR-dependent network: a computational study in yeast.

Mohammadi S, Subramaniam S, Grama A - BMC Syst Biol (2013)

Bottom Line: These rankings must be normalized for degree bias, appropriately interpreted, and mapped to associated roles in pathways.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.It also allows us to identify potential network biomarkers for diagnosis and prognosis of age-related pathologies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, Purdue University, West Lafayette, Indiana, USA. mohammadi@purdue.edu.

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.

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Enrichment analysis of the ERN. Static word cloud for the enriched BP terms in the effective response network (ERN).
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Figure 8: Enrichment analysis of the ERN. Static word cloud for the enriched BP terms in the effective response network (ERN).

Mentions: In order to better understand the functional roles of the predicted targets, we use FIDEA [76] to identify enriched GO terms under the biological process (BP) branch. Figure 8 illustrates the static word cloud of the enriched terms, as generated by FIDEA, the complete list of which is available for download as Additional file 7. Unlike the enrichment map of TORC1, which spans a variety of different functions, targets in the effective response network (ERN) are almost exclusively involved in ribosome biogenesis and the cellular translation process. Ribosome biogenesis is one of the most energy-consuming tasks in the cell that is directly linked to the rate of translation and is required for cell growth [77]. Calorie restriction, or alternatively inhibiting TORC1 by Rapamycin treatment, is known to coordinately regulate this process via a complex set of pathways involving transcription factors Ifh1, Sfp1, Fhl1, and Rap1[77]. Interestingly, all four of these transcription factors are identified by our method among the top 6 TFs with the highest relevance scores (together with Gcn3 and Met4). The effective response network provides a refined view of how yeast cells re-wire various aspects of ribosome biogenesis in order to modulate cell growth. This network can be used to gain a detailed understanding of the regulatory mechanisms that are responsible for TOR-dependent transcriptional changes in yeast.


Inferring the effective TOR-dependent network: a computational study in yeast.

Mohammadi S, Subramaniam S, Grama A - BMC Syst Biol (2013)

Enrichment analysis of the ERN. Static word cloud for the enriched BP terms in the effective response network (ERN).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4016608&req=5

Figure 8: Enrichment analysis of the ERN. Static word cloud for the enriched BP terms in the effective response network (ERN).
Mentions: In order to better understand the functional roles of the predicted targets, we use FIDEA [76] to identify enriched GO terms under the biological process (BP) branch. Figure 8 illustrates the static word cloud of the enriched terms, as generated by FIDEA, the complete list of which is available for download as Additional file 7. Unlike the enrichment map of TORC1, which spans a variety of different functions, targets in the effective response network (ERN) are almost exclusively involved in ribosome biogenesis and the cellular translation process. Ribosome biogenesis is one of the most energy-consuming tasks in the cell that is directly linked to the rate of translation and is required for cell growth [77]. Calorie restriction, or alternatively inhibiting TORC1 by Rapamycin treatment, is known to coordinately regulate this process via a complex set of pathways involving transcription factors Ifh1, Sfp1, Fhl1, and Rap1[77]. Interestingly, all four of these transcription factors are identified by our method among the top 6 TFs with the highest relevance scores (together with Gcn3 and Met4). The effective response network provides a refined view of how yeast cells re-wire various aspects of ribosome biogenesis in order to modulate cell growth. This network can be used to gain a detailed understanding of the regulatory mechanisms that are responsible for TOR-dependent transcriptional changes in yeast.

Bottom Line: These rankings must be normalized for degree bias, appropriately interpreted, and mapped to associated roles in pathways.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.It also allows us to identify potential network biomarkers for diagnosis and prognosis of age-related pathologies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, Purdue University, West Lafayette, Indiana, USA. mohammadi@purdue.edu.

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.

Show MeSH
Related in: MedlinePlus