Data mining analysis of human gut microbiota links Fusobacterium spp. with colorectal cancer onset

Abstract

Gut microbiota and their metabolites play a vital role in colon health and disease. Accumulating evidence suggests that the gut microbiota contributes to the risk of colorectal cancer (CRC). However, the role of a specific microbial community together with their metabolites contributing to the risk, initiation and progression of CRC is still unknown. Hence, we used a Bayesian Networks in combination with the IDA (Intervention calculus when the DAG is absent) to generate a graphical model that allows causal relationships to be inferred from observational data. Results from the analysis of publically available datasets showed that four species: Fusobacteium, Citrobacter, Microbacterium and Slaxkia have estimated non-null lower bounds of causal effects of CRC. These findings support the hypothesis that specific bacterial species (microbial markers) act in concert with locally modified microbiota to cause or influence CRC progression. Additional comprehensive studies are required to validate the potential use of F. nucleatum, Citrobacter as well as Slackia as microbial biomarkers in CRC for prevention, diagnosis, prognosis and/or therapeutics.

Keywords: Colorectal cancer; Fusobacterium spp; IDA method; bacteria; biomarker; microbiome.

Figure 1

Schematic flowchart showing the main steps of the IDA Method

Figure 2

Network model for the study of Marchesi et al. (2011). Numbers in the table correspond to regression coefficients.

Figure 3

Network structure for the study of Zeller et al. 2014. Numbers in the table correspond to regression coefficients.

Figure 4

Individual and shared distribution of orthologue proteins in the four microbial species