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A derived network-based interferon-related signature of human macrophages responding to Mycobacterium tuberculosis.

Wu K, Fang H, Lyu LD, Lowrie DB, Wong KW, Fan XY - Biomed Res Int (2014)

Bottom Line: TMtb-iNet retained the enrichment of binding sites of interferon-related transcription factors and contained relatively more interferon-related interacting genes when compared to THP1r2Mtb-induced signature.Correlation on dataset from patients with AIDS or malaria was stronger for TMtb-iNet, indicating an involvement of TMtb-iNet in these chronic human infections.Collectively, the significance of this work is twofold: (1) we disseminate a hub-based approach in generating a biologically meaningful and clinically useful signature; (2) using this approach we introduce a new network-based signature and demonstrate its promising applications in understanding host responses to infections.

View Article: PubMed Central - PubMed

Affiliation: Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Road, Shanghai 201508, China ; Key Laboratory of Medical Molecular Virology of MOE/MOH, Shanghai Medical College, Fudan University, 138 Yixueyuan Road, Shanghai 200032, China ; State Key Laboratory of Medical Genomics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 197 Ruijin Road II, Shanghai 200025, China.

ABSTRACT
Network analysis of transcriptional signature typically relies on direct interaction between two highly expressed genes. However, this approach misses indirect and biological relevant interactions through a third factor (hub). Here we determine whether a hub-based network analysis can select an improved signature subset that correlates with a biological change in a stronger manner than the original signature. We have previously reported an interferon-related transcriptional signature (THP1r2Mtb-induced) from Mycobacterium tuberculosis (M. tb)-infected THP-1 human macrophage. We selected hub-connected THP1r2Mtb-induced genes into the refined network signature TMtb-iNet and grouped the excluded genes into the excluded signature TMtb-iEx. TMtb-iNet retained the enrichment of binding sites of interferon-related transcription factors and contained relatively more interferon-related interacting genes when compared to THP1r2Mtb-induced signature. TMtb-iNet correlated as strongly as THP1r2Mtb-induced signature on a public transcriptional dataset of patients with pulmonary tuberculosis (PTB). TMtb-iNet correlated more strongly in CD4(+) and CD8(+) T cells from PTB patients than THP1r2Mtb-induced signature and TMtb-iEx. When TMtb-iNet was applied to data during clinical therapy of tuberculosis, it resulted in the most pronounced response and the weakest correlation. Correlation on dataset from patients with AIDS or malaria was stronger for TMtb-iNet, indicating an involvement of TMtb-iNet in these chronic human infections. Collectively, the significance of this work is twofold: (1) we disseminate a hub-based approach in generating a biologically meaningful and clinically useful signature; (2) using this approach we introduce a new network-based signature and demonstrate its promising applications in understanding host responses to infections.

No MeSH data available.


Related in: MedlinePlus

Plot of NES values of THP1r2Mtb-induced signature, TMtb-iNet, and TMtb-iEx from human macrophages against array data from human blood. NES values from GSEA with THP1r2Mtb-induced signature, TMtb-iNet, or TMtb-iEx against array data preranked against cognate healthy controls (HC) are plotted. Detailed explanations of the shortened descriptive phrases can be found in the footnotes of the relevant tables: Tables 1–3 for “PTB” group; Tables 5 and 6 for “HIV” group; Table 7 for “malaria” group; Table 8 for “HCV” group; Table 9 for “other 1” group; and Table 10 for “other 2” group.
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fig8: Plot of NES values of THP1r2Mtb-induced signature, TMtb-iNet, and TMtb-iEx from human macrophages against array data from human blood. NES values from GSEA with THP1r2Mtb-induced signature, TMtb-iNet, or TMtb-iEx against array data preranked against cognate healthy controls (HC) are plotted. Detailed explanations of the shortened descriptive phrases can be found in the footnotes of the relevant tables: Tables 1–3 for “PTB” group; Tables 5 and 6 for “HIV” group; Table 7 for “malaria” group; Table 8 for “HCV” group; Table 9 for “other 1” group; and Table 10 for “other 2” group.

Mentions: We have previously indicated the high positive correlation of THP1r2Mtb-induced signature with a public transcriptional dataset on PTB patients [6]. We therefore examined whether the network-based signature of TMtb-iNet still inherited the significant degree of positive correlation with PTB patients. As shown in Table 1 (also in Figure 8), like THP1r2Mtb-induced signature, TMtb-iNet showed similar positive correlation with PTB more than with LTB and healthy controls (e.g., for the training set, PTB versus HC showed NES = 3.23 in THP1r2Mtb-induced signature, and NES = 3.30 in TMtb-iNet). This was the case for any of the three datasets (i.e., London patient-based training set, London patient-based test set, and Cape Town patient-based validation set). In comparison, the correlation of TMtb-iEx to PTB was lower (e.g., PTB versus HC showed NES = 2.66 in the training set). Our analysis indicated that the network-based signature of TMtb-iNet, but not the excluded signature of TMtb-iEx, was overall as expression-active as THP1r2Mtb-induced signature in the whole blood of PTB patients.


A derived network-based interferon-related signature of human macrophages responding to Mycobacterium tuberculosis.

Wu K, Fang H, Lyu LD, Lowrie DB, Wong KW, Fan XY - Biomed Res Int (2014)

Plot of NES values of THP1r2Mtb-induced signature, TMtb-iNet, and TMtb-iEx from human macrophages against array data from human blood. NES values from GSEA with THP1r2Mtb-induced signature, TMtb-iNet, or TMtb-iEx against array data preranked against cognate healthy controls (HC) are plotted. Detailed explanations of the shortened descriptive phrases can be found in the footnotes of the relevant tables: Tables 1–3 for “PTB” group; Tables 5 and 6 for “HIV” group; Table 7 for “malaria” group; Table 8 for “HCV” group; Table 9 for “other 1” group; and Table 10 for “other 2” group.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4209755&req=5

fig8: Plot of NES values of THP1r2Mtb-induced signature, TMtb-iNet, and TMtb-iEx from human macrophages against array data from human blood. NES values from GSEA with THP1r2Mtb-induced signature, TMtb-iNet, or TMtb-iEx against array data preranked against cognate healthy controls (HC) are plotted. Detailed explanations of the shortened descriptive phrases can be found in the footnotes of the relevant tables: Tables 1–3 for “PTB” group; Tables 5 and 6 for “HIV” group; Table 7 for “malaria” group; Table 8 for “HCV” group; Table 9 for “other 1” group; and Table 10 for “other 2” group.
Mentions: We have previously indicated the high positive correlation of THP1r2Mtb-induced signature with a public transcriptional dataset on PTB patients [6]. We therefore examined whether the network-based signature of TMtb-iNet still inherited the significant degree of positive correlation with PTB patients. As shown in Table 1 (also in Figure 8), like THP1r2Mtb-induced signature, TMtb-iNet showed similar positive correlation with PTB more than with LTB and healthy controls (e.g., for the training set, PTB versus HC showed NES = 3.23 in THP1r2Mtb-induced signature, and NES = 3.30 in TMtb-iNet). This was the case for any of the three datasets (i.e., London patient-based training set, London patient-based test set, and Cape Town patient-based validation set). In comparison, the correlation of TMtb-iEx to PTB was lower (e.g., PTB versus HC showed NES = 2.66 in the training set). Our analysis indicated that the network-based signature of TMtb-iNet, but not the excluded signature of TMtb-iEx, was overall as expression-active as THP1r2Mtb-induced signature in the whole blood of PTB patients.

Bottom Line: TMtb-iNet retained the enrichment of binding sites of interferon-related transcription factors and contained relatively more interferon-related interacting genes when compared to THP1r2Mtb-induced signature.Correlation on dataset from patients with AIDS or malaria was stronger for TMtb-iNet, indicating an involvement of TMtb-iNet in these chronic human infections.Collectively, the significance of this work is twofold: (1) we disseminate a hub-based approach in generating a biologically meaningful and clinically useful signature; (2) using this approach we introduce a new network-based signature and demonstrate its promising applications in understanding host responses to infections.

View Article: PubMed Central - PubMed

Affiliation: Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Road, Shanghai 201508, China ; Key Laboratory of Medical Molecular Virology of MOE/MOH, Shanghai Medical College, Fudan University, 138 Yixueyuan Road, Shanghai 200032, China ; State Key Laboratory of Medical Genomics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 197 Ruijin Road II, Shanghai 200025, China.

ABSTRACT
Network analysis of transcriptional signature typically relies on direct interaction between two highly expressed genes. However, this approach misses indirect and biological relevant interactions through a third factor (hub). Here we determine whether a hub-based network analysis can select an improved signature subset that correlates with a biological change in a stronger manner than the original signature. We have previously reported an interferon-related transcriptional signature (THP1r2Mtb-induced) from Mycobacterium tuberculosis (M. tb)-infected THP-1 human macrophage. We selected hub-connected THP1r2Mtb-induced genes into the refined network signature TMtb-iNet and grouped the excluded genes into the excluded signature TMtb-iEx. TMtb-iNet retained the enrichment of binding sites of interferon-related transcription factors and contained relatively more interferon-related interacting genes when compared to THP1r2Mtb-induced signature. TMtb-iNet correlated as strongly as THP1r2Mtb-induced signature on a public transcriptional dataset of patients with pulmonary tuberculosis (PTB). TMtb-iNet correlated more strongly in CD4(+) and CD8(+) T cells from PTB patients than THP1r2Mtb-induced signature and TMtb-iEx. When TMtb-iNet was applied to data during clinical therapy of tuberculosis, it resulted in the most pronounced response and the weakest correlation. Correlation on dataset from patients with AIDS or malaria was stronger for TMtb-iNet, indicating an involvement of TMtb-iNet in these chronic human infections. Collectively, the significance of this work is twofold: (1) we disseminate a hub-based approach in generating a biologically meaningful and clinically useful signature; (2) using this approach we introduce a new network-based signature and demonstrate its promising applications in understanding host responses to infections.

No MeSH data available.


Related in: MedlinePlus