4.3 Results
4.3.2 Gene prioritisation based on differential expression
Four algorithms were used to prioritise genes in the network based on genes that were differentially expressed, namely: Page rank with priors, Random walk with restart, Network propagation, and NetCombo. The prioritisation took into account both the strength of the differential expression (absolute log fold change for significantly differentially expressed genes), and the confidence score of the interaction. Spearman’s rank correlation was used to assess the correlation between each pair of measures. The measures were all strongly positively correlated with each other (see Table4.3). Network propagation and Random walk with restart were the highest correlated measures, while NetCombo and Page rank with priors were the least correlated measures.
Table 4.3Spearman’s rank correlation between scores of gene prioritisation algorithms.
Algorithm scores compared Spearman’sρ p-value
NetCombo vs. Random walk with restart 0.911 <0.001
NetCombo vs. Network Propagation 0.932 <0.001
NetCombo vs. Page rank with priors 0.904 <0.001
Network propagation vs. Random walk with restart 0.984 <0.001 Network propagation vs. Page rank with priors 0.930 <0.001 Random walk with restart vs. Page rank with priors 0.952 <0.001
The percentile rank of the 28 human proteins that functionally interacted with both an HIV-1
<0.001
<0.01
<0.05 Significance level key Protein LTB vs. HIV-TB LTB vs. PTB LTB vs. HIV
EIF2AK2 -1.11 0.21 -0.79
NAP1L1 0.59 -0.23 0.33
CDC42 -0.76 0.85 -0.34
PRKCQ 0.60 -0.67 -0.01
LCK 0.56 -0.77 -1.05
GAPDH -0.33 0.28 -0.05
CALM1 0.27 -0.38 0.04
FYN 0.41 -0.50 -0.18
CAV1 -0.75 0.14 -0.82
PRKCH 0.46 -0.67 -0.21
CTSD -0.41 0.37 0.06
EPRS 0.22 -0.22 -0.05
HNRNPR 0.25 -0.26 0.12
MSN 0.17 -0.12 0.03
YBX1 0.29 0.03 -0.03
RAC2 -0.11 0.02 -0.12
MAP3K5 -0.11 0.13 0.06
HSPD1 0.20 0.24 0.09
STAT3 -0.16 0.30 0.09
CBFB 0.16 -0.23 0.07
RAB7A -0.08 0.14 0.05
NFKB1 0.04 0.02 -0.01
HEXIM1 -0.06 0.04 -0.03
CD209 -0.47 0.95 -0.58
AKT2 -0.36 0.57 -0.68
HSP90B1 -0.05 0.07 -0.24
FN1 0.06 -0.13 0.25
ARF6 -0.01 0.03 -0.05
Figure 4.1Log fold change in gene expression levels of the bridge proteins during HIV-TB co-infection, HIV infection, and TB infection compared to latent TB infection.
This tabular diagram shows the log fold change in expression of the 28 bridge proteins during three disease states compare to latent TB infection (HIV-TB co-infection, HIV infection, and TB infection). For each column, latent TB infection (LTB) is the numerator, and the log is calculated as base 2. Cells are coloured by the significance level of the differential expression as indicated in the key. Proteins that were significantly differentially expressed (p<0.001) are in bold and proteins that were marginally significantly differentially expressed (p<0.05) are italicised. Proteins that were significantly or marginally significantly differentially expressed during all three disease states are indicated by an orange rectangle surrounding the cells.
and aMtbprotein (bridge proteins) was assessed for each algorithm. On average, the bridge proteins scored well above the upper quartile (83 percentile rank) across all four measures.
Only three bridge proteins did not score in the upper quartile for any measure (HEXIM1, CBFB, and MSN). CDC42, EIF2AK2, and CAV1 were the three top scoring bridge proteins, scoring above the 95thpercentile for all measures. The prioritisation scores for each of the 28 bridge proteins as well as their percentile rank for each algorithm are displayed in Table4.4 Table 4.4Prioritisation scores and ranking of the bridge proteins
Protein Page Rank Rank (Score)
Random Walk Rank (Score)
Network propagation Rank (Score)
NetCombo Rank (Score) CDC42 99.9 (0.078) 98.0 (4.16E-04) 95.5 (2.78E-04) 96.8 (0.357) EIF2AK2 95.0 (0.021) 97.6 (3.82E-04) 97.6 (3.72E-04) 98.1 (0.403) CAV1 99.3 (0.044) 97.1 (3.54E-04) 95.3 (2.72E-04) 96.0 (0.337) LCK 99.6 (0.051) 96.1 (3.13E-04) 93.0 (2.19E-04) 94.6 (0.315) FYN 99.9 (0.076) 97.3 (3.63E-04) 91.1 (1.87E-04) 93.0 (0.293) PRKCQ 97.7 (0.029) 92.5 (2.21E-04) 92.2 (2.03E-04) 93.7 (0.302) NAP1L1 95.1 (0.022) 92.5 (2.20E-04) 92.6 (2.11E-04) 94.4 (0.312) CALM1 99.7 (0.060) 94.3 (2.59E-04) 86.2 (1.31E-04) 89.3 (0.262) CTSD 94.8 (0.021) 93.0 (2.30E-04) 88.3 (1.51E-04) 89.8 (0.266) GAPDH 98.3 (0.032) 90.3 (1.85E-04) 86.9 (1.38E-04) 89.8 (0.266) STAT3 99.8 (0.067) 94.3 (2.59E-04) 81.6 (5.81E-05) 82.4 (0.219) NFKB1 99.6 (0.049) 87.6 (1.52E-04) 81.4 (5.06E-05) 84.9 (0.230) FN1 97.7 (0.029) 82.6 (1.00E-04) 81.1 (4.35E-05) 81.6 (0.217) PRKCH 75.6 (0.008) 87.4 (1.50E-04) 88.3 (1.51E-04) 87.9 (0.252) RAC2 97.8 (0.029) 80.3 (7.07E-05) 79.0 (2.94E-05) 73.3 (0.200) EPRS 90.2 (0.015) 78.6 (5.09E-05) 79.8 (3.22E-05) 79.4 (0.213) YBX1 96.5 (0.025) 78.7 (5.19E-05) 78.7 (2.88E-05) 73.7 (0.201) ARF6 97.0 (0.026) 80.6 (7.41E-05) 79.3 (3.02E-05) 69.9 (0.193) HSPD1 94.2 (0.020) 79.0 (5.41E-05) 79.0 (2.95E-05) 73.4 (0.200) AKT2 97.7 (0.029) 81.5 (8.83E-05) 79.2 (2.99E-05) 64.5 (0.185) HSP90B1 96.8 (0.026) 80.6 (7.43E-05) 78.7 (2.87E-05) 66.1 (0.188) MAP3K5 91.5 (0.017) 77.3 (4.20E-05) 76.7 (2.54E-05) 73.3 (0.200) HNRNPR 90.5 (0.016) 75.7 (3.51E-05) 72.0 (2.01E-05) 73.6 (0.201) RAB7A 85.7 (0.013) 76.6 (3.82E-05) 65.9 (1.62E-05) 66.2 (0.188) CD209 73.0 (0.008) 74.4 (3.10E-05) 76.0 (2.43E-05) 63.8 (0.184) MSN 72.9 (0.008) 65.7 (1.80E-05) 61.8 (1.44E-05) 58.9 (0.176) CBFB 51.8 (0.003) 51.6 (7.46E-06) 50.1 (9.26E-06) 55.2 (0.170) HEXIM1 48.2 (0.002) 46.0 (4.59E-06) 41.3 (5.86E-06) 45.4 (0.153)
The top ranking protein for Network propagation and NetCombo was IFI27 (Interferon alpha-inducible protein 27), and the top ranking protein for Page rank with priors and Random walk with restart was UBC (Polyubiquitin-C ). Neither of these proteins functionally interacted with an HIV-1 orMtbprotein in this network. Both were significantly differentially expressed during co-infection compared with latent TB infection. UBC seems to have been prioritised due to it being a hub protein in the network, as it is involved in over 4000
interactions in the PPIN. IFI27 seems to have been prioritised due to it having the largest change in gene expression during co-infection (10 times higher during co-infection vs. latent TB infection). The top ten ranked proteins for each of the four prioritisation algorithms along with their priority score is displayed in Table4.5.
Table 4.5Top ten ranking proteins across each of the four prioritisation algorithms Page Rank Protein
(Score)
Random Walk Protein (Score)
Network Propagation Protein (Score)
NetCombo Protein (Score)
UBC (1.000) UBC (6.06E-03) IFI27 (1.48E-03) IFI27 (1.000) TP53 (0.158) IFI27 (1.51E-03) OTOF (1.32E-03) C1QB (0.822) SRC (0.125) OTOF (1.32E-03) C1QB (1.20E-03) SERPING1 (0.822) AKT1 (0.112) C1QB (1.21E-03) SERPING1 (1.19E-03) OTOF (0.806) HSP90AA1 (0.109) SERPING1 (1.19E-03) CD177 (1.15E-03) CD177 (0.790) CDK1 (0.108) BATF2 (1.15E-03) BATF2 (1.15E-03) BATF2 (0.776) RPS27A (0.099) CD177 (1.14E-03) SEPT4 (1.06E-03) DEFA4 (0.775) UBA52 (0.088) ISG15 (1.13E-03) CEACAM8 (1.05E-03) RSAD2 (0.752) MYC (0.085) FCGR1A (1.06E-03) C1QC (1.05E-03) SEPT4 (0.749)
Of the 145 MHC proteins in the network, 125 were assessed for differential expression, of which 46 were shown to be significantly differentially expressed during co-infection. Analysis of the prioritisation scores of the MHC proteins showed that they had consistently higher prioritisation scores across the four measures; however, only NetCombo was marginally significantly higher (p=0.04) for MHC proteins than non-MHC proteins (see Table4.6). The expression values and prioritisation scores for all the MHC proteins is available as an appendix in Table7.7.
Table 4.6Wilcoxon rank-sum test comparing prioritisation measures for MHC and non-MHC proteins Prioritisation measure MHC protein (n=145)
median (IQR)
Non-MHC protein
(n=15 629) median (IQR) S p-value Page Rank with priors 0.006 (0.0007, 0.01) 0.003 (0.0008, 0.01) 1.88 0.06 Random Walk with restart 2.44e-05 (2.5e-06,
1.27e-04) 1.2e-05 (2.0e-06,
5.61e-05) 1.76 0.08
Network propagation 1.8e-05 (5.19e-06, 1.19e-04)
1.29e-05 (4.52e-06,
3.00e-05) 1.35 0.17
NetCombo 0.19 (0.15, 0.24) 0.18 (0.14, 0.21) 2.09 0.04