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. 2017 Nov 30;12(11):e0188897.
doi: 10.1371/journal.pone.0188897. eCollection 2017.

A Bayesian view of murine seminal cytokine networks

Michelle L Johnson  1 , Tathagata Dasgupta  2   3 , Nadia Gopichandran  4 , Sarah L Field  4 , Nicolas M Orsi  1
Affiliations

A Bayesian view of murine seminal cytokine networks

Michelle L Johnson et al. PLoS One. .

Abstract

It has long been established that active agents in seminal fluid are key to initiating and coordinating mating-induced immunomodulation. This is in part governed by the actions of a network of cytokine interactions which, to date, remain largely undefined, and whose interspecific evolutionary conservation is unknown. This study applied Bayesian methods to illustrate the interrelationships between seminal profiles of interleukin (IL)-1alpha, IL-1beta, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12 (p70), IL-13, IL-17, eotaxin, granulocyte-colony stimulating factor (G-CSF), granulocyte macrophage-colony stimulating factor (GM-CSF), interferon (IFN)-gamma, keratinocyte-derived chemokine (KC), monocyte chemoattractant protein (MCP-1), macrophage inflammatory protein (MIP-1) alpha, MIP-1beta, regulated on activation normal T cell expressed and secreted (RANTES), tumour necrosis factor (TNF)-alpha, leptin, inducible protein (IP)-10 and vascular endothelial growth factor (VEGF) in a rat model. IL-2, IL-9, IL-12 (p70), IL-13, IL-18, eotaxin, IFN-gamma, IP-10, KC, leptin, MCP-1, MIP-1alpha and TNF-alpha were significantly higher in serum, whilst IL-1beta, IL-5, IL-6, IL-10, IL-17, G-CSF and GM-CSF were significantly higher in seminal fluid. When compared to mouse profiles, only G-CSF was present at significantly higher levels in the seminal fluid in both species. Bayesian modelling highlighted key shared features across mouse and rat networks, namely TNF-alpha as the terminal node in both serum and seminal plasma, and MCP-1 as a central coordinator of seminal cytokine networks through the intermediary of KC and RANTES. These findings reveal a marked interspecific conservation of seminal cytokine networks.

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Conflict of interest statement

Competing Interests: These authors have no competing interests.

Figures

Fig 1
Fig 1. Bayesian network depicting cytokine interrelationships in rat seminal fluid.
The nodes are colour-coded according to the conditional probability of corresponding mediator relative concentrations being high (green), low (red) or medium (white) concentration given the state(s) of their parent nodes. Relative to the white colour, the normalised concentration (low or high) determines the intensity of the node colour. Grey-coloured confidence level edges (causal connecting arrows between nodes) represent a confidence level of 80%; red edges are below this level, based upon the confidence analysis of the Bayesian result.
Fig 2
Fig 2. Bayesian network depicting cytokine interrelationships in rat serum.
(See Fig 1 legend for details regarding colour-coding).
Fig 3
Fig 3. Bayesian network depicting cytokine interrelationships in rat seminal fluid, with nodes not common with the mouse network removed.
(See Fig 1 legend for details regarding colour-coding).
Fig 4
Fig 4. Bayesian network depicting cytokine interrelationships in rat serum, with nodes not common with the mouse network removed.
(See Fig 1 legend for details regarding colour-coding).
Fig 5
Fig 5. Bayesian network depicting cytokine interrelationships in mouse seminal fluid.
(See Fig 1 legend for details regarding colour-coding).
Fig 6
Fig 6. Bayesian network depicting cytokine interrelationships in mouse serum.
(See Fig 1 legend for details regarding colour-coding).
Fig 7
Fig 7. Bayesian network depicting cytokine interrelationships in mouse seminal fluid, with nodes not common with the rat network removed.
(See Fig 1 legend for details regarding colour-coding).
Fig 8
Fig 8. Bayesian network depicting cytokine interrelationships in mouse seminal fluid, with nodes not common with the rat network removed.
(See Fig 1 legend for details regarding colour-coding).
See this image and copyright information in PMC

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