Integrated Co-expression Analysis of Host–Parasite Transcriptomes Reveals Mechanisms of Host Modulation in an Ant–Cestode System

How parasites interact with their hosts at the molecular level is a central question in parasitology, yet identifying host pathways directly targeted by parasites is challenging because infections often have broad effects on host physiology. This difficulty is particularly pronounced in non-model systems, such as the interaction between the parasitic tapeworm Anomotaenia brevis and its intermediate host, the ant Temnothorax nylanderi, in which infection induces strong phenotypic changes. Here, we integrated host and parasite transcriptomes through a combined weighted gene co-expression network analysis (WGCNA) to identify candidate genes and gene networks involved in this interaction. We detected strong negative correlations between parasite and host gene expression, whereas within-species associations were largely positive. Candidate parasite genes were associated with host molecular pathways relevant to infection and host phenotype. The gene networks and expression correlations identified were consistent with those described in model parasite–host systems, supporting the robustness of our approach. Besides, our analysis provided initial functional insights into previously unannotated parasite proteins that may act as effectors of host manipulation. Expression of these parasite genes was correlated with host genes involved in oxidative stress resistance, metabolism, muscle function, immunity, and cuticular sclerotization. These associations suggest that the parasite may modulate multiple host pathways to facilitate infection and transmission. Overall, our findings advance our understanding of molecular mechanisms underlying parasite interference and highlight the value of integrating host and parasite transcriptomic data. More generally, our combined WGCNA framework provides a useful tool for uncovering transcriptional interactions in complex host–parasite systems.

Files and variables

File: link_wgcna.R
Description: R-script for the analysis of the transcriptome data

File: merged_ant_cestode_gcm.csv
Description: Gene count matrix of parasite and host transcriptomes combined, each column is a sample name, each row is a gene, if the gene name starts with a "g", it is a parasite gene, when it starts with an "M" it is a host gene.

Code/software
Software needed is R, R packages used are: WGCNA, ggplot2, dplyr, topGO, clusterProfiler, pathview, data.table, stringr, RColorBrewer, tidyverse, forcats

Access information
Data was derived from the following source:
10.5061/dryad.8cz8w9h3b
Additional data can also be found on this link