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Prediction and Characterisation of the System Effects of Aristolochic Acid: A Novel Joint Network Analysis towards Therapeutic and Toxicological Mechanisms.

Nie W, Lv Y, Yan L, Chen X, Lv H - Sci Rep (2015)

Bottom Line: However, the molecular mechanisms of AA systems effects remain poorly understood.Here, we employed a joint network analysis that combines network pharmacology, a protein-protein interaction (PPI) database, biological processes analysis and functional annotation analysis to explore system effects.Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA.

View Article: PubMed Central - PubMed

Affiliation: Chongqing University Innovative Drug Research Centre, School of Chemistry and Chemical Engineering, Chongqing 401331, P.R. China.

ABSTRACT
Aristolochic acid (AA) is the major active component of medicinal plants from the Aristolochiaceae family of flowering plants widely utilized for medicinal purposes. However, the molecular mechanisms of AA systems effects remain poorly understood. Here, we employed a joint network analysis that combines network pharmacology, a protein-protein interaction (PPI) database, biological processes analysis and functional annotation analysis to explore system effects. Firstly, we selected 15 protein targets (14 genes) in the PubChem database as the potential target genes and used PPI knowledge to incorporate these genes into an AA-specific gene network that contains 129 genes. Secondly, we performed biological processes analysis for these AA-related targets using ClueGO, some of new targeted genes were randomly selected and experimentally verified by employing the Quantitative Real-Time PCR assay for targeting the systems effects of AA in HK-2 cells with observed dependency of concentration. Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA. At last, we built an AA target pathway network of significant pathways to predict the system effects. Taken together, this joint network analysis revealed that the systematic regulatory effects of AA on multidimensional pathways involving both therapeutic action and toxicity.

No MeSH data available.


Related in: MedlinePlus

AAI treatment regulated the gene expressions in a variety of manners in HK-2 cells.AAI-0: HK-2 cells without AAI treatment; AAI-1: HK-2 cells were treated with AAI (10 mM); AAI-2: HK-2 cells were treated with AAI (50 mM); AAI-3: HK-2 cells were treated with AAI (100 mM). Compared to AAS-0 (control group), it was considered as statistical difference while P value is less than 0.05 (*), and it was considered as significantly statistical difference when P value is less than 0.01 (**).
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f4: AAI treatment regulated the gene expressions in a variety of manners in HK-2 cells.AAI-0: HK-2 cells without AAI treatment; AAI-1: HK-2 cells were treated with AAI (10 mM); AAI-2: HK-2 cells were treated with AAI (50 mM); AAI-3: HK-2 cells were treated with AAI (100 mM). Compared to AAS-0 (control group), it was considered as statistical difference while P value is less than 0.05 (*), and it was considered as significantly statistical difference when P value is less than 0.01 (**).

Mentions: To validate the predictive efficiency of the adopted joint network approach to the non-evident genes, we further treated the HK-2 cells with AAI in a variety of concentrations as 10 mM, 50 mM and 100 mM, respectively, then Quantitative Real-Time PCR assay was employed for the determination of relative expressional levels of 13 identified genes without direct evidence to link to the systems effects of AA against HK-2 cells, they are C11ORF17, IL1RAP, JUN, CYP19A1, IL4, IL23, ESR1, AR, IL1R1, ESRRA, CDKN1A, CDK5 and ILI8 (see Table 2). The results demonstrated that the normal expressional levels of the selected genes were significantly perturbed by AAI treatment in HK-2 cells, but not the IL1R1, CDK5 genes (see Figs 3 and 4). C11ORF17 and IL1RAP were down-regulated considerably when HK-2 cells exposed to AAI, however JUN, CYP19A1, IL4, HIL23A and ESR1 were observably upregulated by AAI. Interestingly those gene expressions were perturbed by AAI treatment rendered a remarkable dependent of concentration (Fig. 3). Contrast to the linear modulation of those identified genes by AAI intervention, the others including AR, ESRRA, CDKN1A and ILI8 were perturbed markedly by AAI treatment as well, while the expressional changes were not characterized as the noticeable dependent of concentration (Fig. 4). Take altogether, most of those selected genes were modulated significantly by AAI treatment that is consistent with our predictive results by the joint network approach as an experimental evidence confirmed and validated that this adopted network biology approach was feasible and confident, it holds the capacity to efficiently discovery and identify the candidate genes implicated in the defined biological events such as drug toxicity, drug effects or even disease development, which might provide novel insights into those biological events by integrating with relevantly experimental verification.


Prediction and Characterisation of the System Effects of Aristolochic Acid: A Novel Joint Network Analysis towards Therapeutic and Toxicological Mechanisms.

Nie W, Lv Y, Yan L, Chen X, Lv H - Sci Rep (2015)

AAI treatment regulated the gene expressions in a variety of manners in HK-2 cells.AAI-0: HK-2 cells without AAI treatment; AAI-1: HK-2 cells were treated with AAI (10 mM); AAI-2: HK-2 cells were treated with AAI (50 mM); AAI-3: HK-2 cells were treated with AAI (100 mM). Compared to AAS-0 (control group), it was considered as statistical difference while P value is less than 0.05 (*), and it was considered as significantly statistical difference when P value is less than 0.01 (**).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664954&req=5

f4: AAI treatment regulated the gene expressions in a variety of manners in HK-2 cells.AAI-0: HK-2 cells without AAI treatment; AAI-1: HK-2 cells were treated with AAI (10 mM); AAI-2: HK-2 cells were treated with AAI (50 mM); AAI-3: HK-2 cells were treated with AAI (100 mM). Compared to AAS-0 (control group), it was considered as statistical difference while P value is less than 0.05 (*), and it was considered as significantly statistical difference when P value is less than 0.01 (**).
Mentions: To validate the predictive efficiency of the adopted joint network approach to the non-evident genes, we further treated the HK-2 cells with AAI in a variety of concentrations as 10 mM, 50 mM and 100 mM, respectively, then Quantitative Real-Time PCR assay was employed for the determination of relative expressional levels of 13 identified genes without direct evidence to link to the systems effects of AA against HK-2 cells, they are C11ORF17, IL1RAP, JUN, CYP19A1, IL4, IL23, ESR1, AR, IL1R1, ESRRA, CDKN1A, CDK5 and ILI8 (see Table 2). The results demonstrated that the normal expressional levels of the selected genes were significantly perturbed by AAI treatment in HK-2 cells, but not the IL1R1, CDK5 genes (see Figs 3 and 4). C11ORF17 and IL1RAP were down-regulated considerably when HK-2 cells exposed to AAI, however JUN, CYP19A1, IL4, HIL23A and ESR1 were observably upregulated by AAI. Interestingly those gene expressions were perturbed by AAI treatment rendered a remarkable dependent of concentration (Fig. 3). Contrast to the linear modulation of those identified genes by AAI intervention, the others including AR, ESRRA, CDKN1A and ILI8 were perturbed markedly by AAI treatment as well, while the expressional changes were not characterized as the noticeable dependent of concentration (Fig. 4). Take altogether, most of those selected genes were modulated significantly by AAI treatment that is consistent with our predictive results by the joint network approach as an experimental evidence confirmed and validated that this adopted network biology approach was feasible and confident, it holds the capacity to efficiently discovery and identify the candidate genes implicated in the defined biological events such as drug toxicity, drug effects or even disease development, which might provide novel insights into those biological events by integrating with relevantly experimental verification.

Bottom Line: However, the molecular mechanisms of AA systems effects remain poorly understood.Here, we employed a joint network analysis that combines network pharmacology, a protein-protein interaction (PPI) database, biological processes analysis and functional annotation analysis to explore system effects.Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA.

View Article: PubMed Central - PubMed

Affiliation: Chongqing University Innovative Drug Research Centre, School of Chemistry and Chemical Engineering, Chongqing 401331, P.R. China.

ABSTRACT
Aristolochic acid (AA) is the major active component of medicinal plants from the Aristolochiaceae family of flowering plants widely utilized for medicinal purposes. However, the molecular mechanisms of AA systems effects remain poorly understood. Here, we employed a joint network analysis that combines network pharmacology, a protein-protein interaction (PPI) database, biological processes analysis and functional annotation analysis to explore system effects. Firstly, we selected 15 protein targets (14 genes) in the PubChem database as the potential target genes and used PPI knowledge to incorporate these genes into an AA-specific gene network that contains 129 genes. Secondly, we performed biological processes analysis for these AA-related targets using ClueGO, some of new targeted genes were randomly selected and experimentally verified by employing the Quantitative Real-Time PCR assay for targeting the systems effects of AA in HK-2 cells with observed dependency of concentration. Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA. At last, we built an AA target pathway network of significant pathways to predict the system effects. Taken together, this joint network analysis revealed that the systematic regulatory effects of AA on multidimensional pathways involving both therapeutic action and toxicity.

No MeSH data available.


Related in: MedlinePlus