Information theoretic approach to complex biological network reconstruction: application to cytokine release in RAW 264.7 macrophages

Farhangmehr, Farzaneh; Maurya, Mano Ram; Tartakovsky, Daniel M; Subramaniam, Shankar

doi:10.1186/1752-0509-8-77

Table 1 Significant components of phosphoprotein-cytokine signaling network

From: Information theoretic approach to complex biological network reconstruction: application to cytokine release in RAW 264.7 macrophages

Interactions		MI	PCR	Lit.	Comment	Interactions		MI	PCR	Lit.	Comment
G-CSF	NF-κB	✓	✓	✓[44]		IL-6	RSK	✓	✘	✓[45]	- IL-6 has the lowest R ²-value. This may be due to avoiding the linearity assumption in computing the mutual information.
(Pro-inflammatory)	JNK lg	✓	✓	✓[46]		(Anti-inflammatory and pro-inflammatory)	JNK lg	✓	✓	✓[47]
	JNK sh	✓	✓	✓[46]			JNK sh	✓	✓	✓[47]
	P38	✓	✓	✘			P38	✓	✘	✓[48]
	PKCμ2	✓	✘	✓[49]			PKCμ2	✓	✘	✓[50]
	ERK1	✓	✘	✓[51]			NF-κB	✓	✓	✓[52]
	ERK2	✓	✘	✓[51]			ERK1	✓	✘	✓[45]
	RSK	✓	✘	✓[53]			ERK2	✓	✘	✓[45]
	Finding: Our model confirms the regulatory effect of P38, which has been suggested by the PCR minimal model [34].						cAMP	✓	✓	✓[54]
TNFα	RSK	✓	✘	✘	- TNFα has the largest network. This study identifies the regulatory effect of 12 phosphoproteins on TNFα.	IL-10	JNK lg	✓	✓	✘
(Pro-inflammatory)	AKT	✓	✓	✓[55]		(Anti-inflammatory)	P38	✓	✘	✓[56]
	P38	✓	✓	✓[57]
	RPS6	✓	✘	✓[58]
	GSK3A	✓	✘	✓[59]	- TNFα yields the highest coefficient of determination R ² = 0.62
	GSK3B	✘	✘	✓[59]
	PKCμ2	✓	✘	✓[60]			ERK1	✓	✘	✓[61]
	cAMP	✓	✓	✓[62]			ERK2	✓	✘	✓[61]
	NF-κB	✓	✓	✓[58]			JNK sh	✓	✓	✘
	JNK lg	✓	✓	✓[63]			NF-κB	✓	✓	✓[64]
	JNK sh	✓	✓	✓[63]			PKCμ2	✓	✘	✓[65]
	ERK2	✓	✘	✓[66]			RSK	✓	✘	✓[67]
	ERK1	✓	✘	✓[66]			Finding: Our study confirms the regulatory effects of JNK sh/ lg on IL-10.
	Finding: Our study suggests the novel regulatory effect of RSK on TNFα.
MIP-1α	P38	✓	✓	✓[57]	- This study doesn’t confirm the regulatory effects of STAT1α/β/3 on MIP-1α suggested by one study [68]. The PCR minimal model [34] identifies the impact of STAT1α on MIP-1a.	RANTES	STAT3	✓	✘	✓[69]	- Unlike the PCR minimal model [34], this study successfully captures the regulatory impacts of STAT1α/3/5 on RANTES.
(Anti-inflammatory)	NF-κB	✓	✓	✓[70]		(Anti-inflammatory)	STAT5	✓	✘	✓[71]
	cAMP	✓	✓	✓[72]			STAT1α	✓	✓	✓[73]
	RSK	✓	✘	✓[74]			NF-κB	✓	✓	✓[75]
	JNK lg	✓	✓	✓[76]			P38	✓	✘	✓[77]
	JNK sh	✓	✓	✓[76]			PKCμ2	✓	✘	✓[78]
	AKT	✓	✘	✓[79]			JNK sh	✓	✓	✓[75]
	ERK1	✓	✘	✓[74]			JNK lg	✓	✓	✓[75]
	ERK2	✓	✘	✓[74]			RSK	✓	✘	✓[80]
	STAT1α	✘	✓	✓[68]			ERK2	✓	✘	✓[80]
	STAT1β	✘	✘	✓[68]			ERK1	✓	✘	✓[80]
	STAT3	✘	✘	✓[68]		IL-1α	ERK2	✓	✘	✓[81]
						(Pro-inflammatory)	ERK1	✓	✘	✓[81]
							RSK	✓	✘	✓[82]
							P38	✓	✘	✓[83]
							JNK lg	✓	✓	✓[84]
							JNK sh	✓	✓	✓[84]
							NF-κB	✓	✓	✓[85]

A comparison of phosphoprotein-cytokine regulatory connections identified by information theoretic approach (‘MI’), PCR (‘PCR’) and the literature knowledge (‘Lit.’). Identified interactions are shown by ✓ and cells marked by ✘ indicate missed interactions by a method.

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ISSN: 1752-0509

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