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. 2023 May 28;24(11):9415.
doi: 10.3390/ijms24119415.

Network Analysis of Biomarkers Associated with Occupational Exposure to Benzene and Malathion

Marcus Vinicius C Santos  1 , Arthur S Feltrin  2 , Isabele C Costa-Amaral  1 , Liliane R Teixeira  1 , Jamila A Perini  3 , David C Martins Jr  2 , Ariane L Larentis  1
Affiliations

Network Analysis of Biomarkers Associated with Occupational Exposure to Benzene and Malathion

Marcus Vinicius C Santos et al. Int J Mol Sci. .

Abstract

Complex diseases are associated with the effects of multiple genes, proteins, and biological pathways. In this context, the tools of Network Medicine are compatible as a platform to systematically explore not only the molecular complexity of a specific disease but may also lead to the identification of disease modules and pathways. Such an approach enables us to gain a better understanding of how environmental chemical exposures affect the function of human cells, providing better perceptions about the mechanisms involved and helping to monitor/prevent exposure and disease to chemicals such as benzene and malathion. We selected differentially expressed genes for exposure to benzene and malathion. The construction of interaction networks was carried out using GeneMANIA and STRING. Topological properties were calculated using MCODE, BiNGO, and CentiScaPe, and a Benzene network composed of 114 genes and 2415 interactions was obtained. After topological analysis, five networks were identified. In these subnets, the most interconnected nodes were identified as: IL-8, KLF6, KLF4, JUN, SERTAD1, and MT1H. In the Malathion network, composed of 67 proteins and 134 interactions, HRAS and STAT3 were the most interconnected nodes. Path analysis, combined with various types of high-throughput data, reflects biological processes more clearly and comprehensively than analyses involving the evaluation of individual genes. We emphasize the central roles played by several important hub genes obtained by exposure to benzene and malathion.

Keywords: benzene; malathion; network medicine; occupational health.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Main stages of the experimental project.
Figure 2
Figure 2
Benzene biological interaction network. (A) Interaction network generated using GeneMania with 114 genes comprising 2415 interactions; (B) co-expression interactions; (C) physical interactions; (D) pathways; (E) predicted; (F) co-localizaton; (G) genetic interactions; and (H) shared protein domains.
Figure 3
Figure 3
Overview of the five clusters obtained from the benzene gene-gene network using the MCODE software. Interaction network generated using GeneMANIA with 114 nodes (8 nodes expanded from a 96-gene list) and 2415 edges. All nodes are interconnected in a unique connected component, but 38 nodes do not belong to any cluster: Cluster 1: score = 27.667; Cluster 2: score = 10.4; Cluster 3: score = 6.933; Cluster 4: score = 3.333; and Cluster 5: score = 3.25. Nodes may represent biological elements, while the edges describe the nature of their relationships (co-expression; physical; pathways; predicted; co-localizaton; Genetic interactions; and shared protein domains).
Figure 4
Figure 4
Most relevant nodes (in yellow) for the subnetworks predicted by the MCODE analysis in the benzene gene-gene network. Centrality is calculated by node degree, betweenness, and eigenvector. Cluster 1, IL8 was identified as the bottle-neck node; Cluster 2, KLF4, KLF6, and JUN were identified as the bottleneck nodes; Cluster 3, SERTAD1 and MT1H were identified as bottleneck nodes and Clusters 5 DEPDC1 and ARHGAP19 were identified as bottleneck nodes.
Figure 5
Figure 5
Most relevant nodes (in yellow) for Malathion PPI network analysis in STRING. Centrality is calculated by node degree, betweenness, and eigenvector. Interaction network generated using STRING with 67 nodes (10 nodes expanded from a 57-gene list) and 134 edges. Fifty nodes are interconnected in the main connected component, while 17 nodes are isolated.
Figure 6
Figure 6
Benzene Biological Process Overrepresentation Analysis (BiNGO).
Figure 7
Figure 7
Malathion Biological Process Overrepresentation Analysis (BiNGO).
See this image and copyright information in PMC

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